We present a new global model (LithoRef18) of the Earth's lithosphere and upper mantle obtained through joint inversion of multiple geophysical data sets and prior seismic, thermal and petrological information. The model includes estimates of crustal thickness and density, lithospheric thickness, depth-dependent density of the lithospheric mantle, lithospheric geotherms, and average density of the sublithospheric mantle down to 410 km depth. Our results for lithospheric thickness and sublithospheric density structure agree well with recent seismic tomography models. Comparisons with regional studies indicate improvements over previous global crustal models. Given the similarity with tomography models, LithoRef18 can be readily
This document discusses integrating lithostatic compression into velocity models for seismic depth imaging in complex geological settings. It proposes parameterizing the compression effect with a scaling function to create more geologically consistent velocity models. Testing on land seismic datasets from thrust belts showed that representing compression with a multiplicative scalar separated this effect successfully, allowing focus on defining lithological velocities and structures. This improves model consistency and efficiency.
This document discusses various geodetic remote sensing methods for estimating glacial mass balance, including altimetry, photogrammetry, and interferometric synthetic aperture radar (InSAR). It focuses on applications using the Geoscience Laser Altimeter System (GLAS) on ICESat, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and compares the advantages and limitations of different techniques. Satellite and airborne altimetry have proven most successful for monitoring elevation changes over time to estimate mass balance, though challenges remain regarding spatial and temporal resolution of data.
Ninety percent of major earthquakes of the world directly indicating the sources of subduction and collision zones with shallow, intermediate, and deep focus earthquakes. The state of Sabah not indicating a high seismic risk zone and not directly associated with the Ring of fire. Nevertheless, it is positive towards seismic risk as the state experienced more than 65 earthquakes. However, no attention of researchers on comparative analysis of PGA map recorded in literature. Therefore, this study conducted; 1) to analyze the earthquake hazard and active tectonics of Sabah using PGA map derived from three methods and; 2) to understand the intersection of faults that can create isoseismic elongation. More than 90% of earthquakes are shallow and focused at a hypo-central distance of (0 ~ 100) km as resulted from this research. Therefore, Sabah had been experienced a highest magnitude of ~6.3, which can create the maximum PGA values of ~ (0.075, 0.06 and 0.08) based on three different attenuation equations proposed in this study. These earthquakes can produce a maximum intensity of (MMI~7) that is derived from the resulted PGA values. The study on active tectonics explains about the major 12 active faults and their intersection relationship. Therefore, this whole study has been conducted based on three attenuation relation to find out the best method for preparing the PGA map and the stereo net plotting using an integrated GIS technique.
Geophysics is the study of the Earth, including its composition and structure, tectonic plates, earthquakes, and natural hazards. A geophysicist conducts seismic surveys using energy sources and geophones to collect and interpret data on subsurface structures. They use computer technology to process and visualize seismic data to find oil, gas, water, and other resources. Geophysics students gain experience through field trips and field schools. Geophysicists and technologists are employed by the petroleum industry, engineering companies, mining companies, universities, and governments.
This document reviews different height systems and vertical datums in the Australian context. It discusses two classes of height systems - geometrical systems that ignore gravity, and physical systems related to gravity. Ellipsoidal heights are an example of a geometrical system, using straight line distances from a reference ellipsoid. Physical systems use curved paths along equipotential surfaces defined by gravity. Australia uses the normal-orthometric height system embedded in the Australian Height Datum (AHD). The AHD was established using spirit leveling observations fixed to tide gauge measurements of mean sea level. Problems with the AHD and differences from the national geoid model are noted.
Deprem Verilerinin H/V Oranının Mevsimsel Değişimi Ali Osman Öncel
H/V oranının zaman içinde değişimi konusu bana oldukça ilginç gelmişti ve bu tür bir çalışma yapıldı mı sorusunu netleştirmek için araştırma yaptım ve 2021 yılında bu konuda GJI gibi bir dergide yayınlanmış bir çalışma buldum. Bu çalışma oldukça iyi bir referans H/V çalışmaları için. Önemli referans düşünceler şöyle; 1) Mevsimsel olarak yağışa bağlı olarak yeraltı kaynaklarında ki azalma ve yükselmeye bağlı olarak H/V yükseliyor, 2) H/V pik değerleri kaya zemin üzerinde yaklaşık BİR (1) oranında seyreder ve PİK vermezken, kaya zeminden uzaklaşıldıkça zemin etkisi ile PİK değerleri değişir, 3) Deprem ve Gürültü sinyallerinden hesap edilen F(PİK) nerede ise sabitken, H/V oranları %10 değişir, 4) M6.8 büyüklüğünde meydana gelen bir deprem H/V değişimlerini etkiler.
Yapılan çalışmada kullanılan yaklaşım SESAME (2004) kriterlerine uygun olarak 1) 60 dakikalık veriler analizi, 2) 1000 günden fazla gözlem süresi 3) 10'dan fazla farklı zeminlerde istasyon 4) 60 dakikalık birbirinden ayrı verilerin analiz edilmesi. Oldukça emek yoğun bir çalışma
Surface and soil moisture monitoring, estimations, variations, and retrievalsJenkins Macedo
The document discusses several studies related to monitoring surface and groundwater resources using remote sensing techniques.
1) One study compares soil moisture estimations from the Advanced Microwave Scanning Radiometer E (AMSR-E), ground-based measurements, and the Common Land Model (CLM). It finds that AMSR-E captures drying and wetting patterns but with lower variability than CLM or ground data.
2) Another evaluates global soil moisture from the ERS scatterometer and AMSR-E, finding general agreement except in deserts and dense vegetation due to limitations.
3) A third analyzes terrestrial water storage changes using GRACE satellite data and GLDAS land surface models,
This document discusses integrating lithostatic compression into velocity models for seismic depth imaging in complex geological settings. It proposes parameterizing the compression effect with a scaling function to create more geologically consistent velocity models. Testing on land seismic datasets from thrust belts showed that representing compression with a multiplicative scalar separated this effect successfully, allowing focus on defining lithological velocities and structures. This improves model consistency and efficiency.
This document discusses various geodetic remote sensing methods for estimating glacial mass balance, including altimetry, photogrammetry, and interferometric synthetic aperture radar (InSAR). It focuses on applications using the Geoscience Laser Altimeter System (GLAS) on ICESat, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and compares the advantages and limitations of different techniques. Satellite and airborne altimetry have proven most successful for monitoring elevation changes over time to estimate mass balance, though challenges remain regarding spatial and temporal resolution of data.
Ninety percent of major earthquakes of the world directly indicating the sources of subduction and collision zones with shallow, intermediate, and deep focus earthquakes. The state of Sabah not indicating a high seismic risk zone and not directly associated with the Ring of fire. Nevertheless, it is positive towards seismic risk as the state experienced more than 65 earthquakes. However, no attention of researchers on comparative analysis of PGA map recorded in literature. Therefore, this study conducted; 1) to analyze the earthquake hazard and active tectonics of Sabah using PGA map derived from three methods and; 2) to understand the intersection of faults that can create isoseismic elongation. More than 90% of earthquakes are shallow and focused at a hypo-central distance of (0 ~ 100) km as resulted from this research. Therefore, Sabah had been experienced a highest magnitude of ~6.3, which can create the maximum PGA values of ~ (0.075, 0.06 and 0.08) based on three different attenuation equations proposed in this study. These earthquakes can produce a maximum intensity of (MMI~7) that is derived from the resulted PGA values. The study on active tectonics explains about the major 12 active faults and their intersection relationship. Therefore, this whole study has been conducted based on three attenuation relation to find out the best method for preparing the PGA map and the stereo net plotting using an integrated GIS technique.
Geophysics is the study of the Earth, including its composition and structure, tectonic plates, earthquakes, and natural hazards. A geophysicist conducts seismic surveys using energy sources and geophones to collect and interpret data on subsurface structures. They use computer technology to process and visualize seismic data to find oil, gas, water, and other resources. Geophysics students gain experience through field trips and field schools. Geophysicists and technologists are employed by the petroleum industry, engineering companies, mining companies, universities, and governments.
This document reviews different height systems and vertical datums in the Australian context. It discusses two classes of height systems - geometrical systems that ignore gravity, and physical systems related to gravity. Ellipsoidal heights are an example of a geometrical system, using straight line distances from a reference ellipsoid. Physical systems use curved paths along equipotential surfaces defined by gravity. Australia uses the normal-orthometric height system embedded in the Australian Height Datum (AHD). The AHD was established using spirit leveling observations fixed to tide gauge measurements of mean sea level. Problems with the AHD and differences from the national geoid model are noted.
Deprem Verilerinin H/V Oranının Mevsimsel Değişimi Ali Osman Öncel
H/V oranının zaman içinde değişimi konusu bana oldukça ilginç gelmişti ve bu tür bir çalışma yapıldı mı sorusunu netleştirmek için araştırma yaptım ve 2021 yılında bu konuda GJI gibi bir dergide yayınlanmış bir çalışma buldum. Bu çalışma oldukça iyi bir referans H/V çalışmaları için. Önemli referans düşünceler şöyle; 1) Mevsimsel olarak yağışa bağlı olarak yeraltı kaynaklarında ki azalma ve yükselmeye bağlı olarak H/V yükseliyor, 2) H/V pik değerleri kaya zemin üzerinde yaklaşık BİR (1) oranında seyreder ve PİK vermezken, kaya zeminden uzaklaşıldıkça zemin etkisi ile PİK değerleri değişir, 3) Deprem ve Gürültü sinyallerinden hesap edilen F(PİK) nerede ise sabitken, H/V oranları %10 değişir, 4) M6.8 büyüklüğünde meydana gelen bir deprem H/V değişimlerini etkiler.
Yapılan çalışmada kullanılan yaklaşım SESAME (2004) kriterlerine uygun olarak 1) 60 dakikalık veriler analizi, 2) 1000 günden fazla gözlem süresi 3) 10'dan fazla farklı zeminlerde istasyon 4) 60 dakikalık birbirinden ayrı verilerin analiz edilmesi. Oldukça emek yoğun bir çalışma
Surface and soil moisture monitoring, estimations, variations, and retrievalsJenkins Macedo
The document discusses several studies related to monitoring surface and groundwater resources using remote sensing techniques.
1) One study compares soil moisture estimations from the Advanced Microwave Scanning Radiometer E (AMSR-E), ground-based measurements, and the Common Land Model (CLM). It finds that AMSR-E captures drying and wetting patterns but with lower variability than CLM or ground data.
2) Another evaluates global soil moisture from the ERS scatterometer and AMSR-E, finding general agreement except in deserts and dense vegetation due to limitations.
3) A third analyzes terrestrial water storage changes using GRACE satellite data and GLDAS land surface models,
Surface Soil Moisture and Groundwater Assessment and Monitoring using Remote ...Jenkins Macedo
This preview is part of the requirement for a comprehensive analysis of remotely sensed surface soil moisture and groundwater assessment and monitoring for global environmental and climate change presented by Christina Geller, candidate for the degree of MSc in Geographic Information Science for Development, and Environment and Jenkins Macedo, candidate for the MS in Environmental Science and Policy at the Department of International Development, Community, and Environmental at Clark University.
The document presents a new hydrological model called CI-SLAM (Connectivity Index-based Shallow LAndslide Model) to model shallow landslide susceptibility. The key aspects of the model are:
1) It accounts for the concept of hydrological connectivity, which is the condition where disparate saturated regions on a hillslope are linked by subsurface water flow.
2) Hydrological connectivity depends on the spatial variability of soil depth across catchments and initial soil moisture conditions.
3) The model simulates the development of a perched water table and estimates the time required for saturated conditions to develop at the soil-bedrock interface.
4) It couples the hydrological model with an infinite
Historical and Contemporary Trends in the Size, Drift, and Color of Jupiterʼs...Sérgio Sacani
The Great Red Spot on Jupiter has been shrinking over the past 150+ years based on historical records and spacecraft observations. Recent data from 1979-2017 show the Spot shrinking longitudinally at a rate of 0.194 degrees per year and latitudinally at 0.048 degrees per year. Its westward drift has also been accelerating, increasing about 0.002 degrees per day each year. High resolution images allow analysis of changes in the Spot's color, winds, and internal structure over this time period.
This document summarizes a study that used gravity data to delineate underground structure in the Beppu geothermal field in Japan. Analysis of Bouguer anomaly maps revealed high anomalies in the southern and northern parts of the study area that correspond to known geological formations. Edge detection filtering of the gravity data helped identify subsurface faults, including the northern edge of the high southern anomaly corresponding to the Asamigawa Fault. Depth modeling of the gravity basement showed differences between the southern and northern hot spring areas, with steep basement slopes along faults in the south and uplifted basement in the north.
A 3d extinction_map_of_the_northern_galactic_plane_based_on_iphas_photometrySérgio Sacani
This document presents a 3D extinction map of the Northern Galactic Plane derived using photometry from the IPHAS survey. The map was constructed using a hierarchical Bayesian method that simultaneously estimates the distance-extinction relationship and properties of ~38 million stars along each line of sight. The map has fine angular resolution of ~10 arcminutes and distance resolution of 100 pc out to a depth of 5 kpc. In addition to mean extinction, the method also measures differential extinction arising from the fractal structure of the interstellar medium. Both the extinction map and catalogue of stellar parameters are made publicly available.
This document discusses the derivation of new empirical magnitude conversion relationships for earthquakes in Turkey and surrounding regions between 1900-2012. It uses an improved earthquake catalog containing 12,674 events of magnitude 4.0 and greater. The catalog includes events reported in different magnitude scales. The study derives conversion equations to relate moment magnitude (Mw) to local magnitude (ML), duration magnitude (Md), body wave magnitude (mb), and surface wave magnitude (Ms) using 489 events that have reported Mw values. Both orthogonal regression and ordinary least squares methods are used and compared. The new relationships are meant to make the catalog more homogeneous by converting all magnitudes to the common Mw scale.
A statistical assessment of GDEM using LiDAR dataTomislav Hengl
This document presents a statistical assessment of the accuracy of the Global Digital Elevation Model (GDEM) using LiDAR data. It proposes a framework to evaluate GDEM accuracy by assessing absolute elevation errors, positional accuracy of hydrological features, surface roughness representation, and user satisfaction. Case studies in four areas show regression models can evaluate elevation fit, with an R-squared value above 0.995 indicating satisfactory accuracy for GDEM in areas of medium relief. The document concludes GDEM has little usefulness in areas of low relief.
- Researchers in China noticed significant gravity changes in a region covering the south-north earthquake belt before the 2008 Wenchuan earthquake (Mw 7.9). In 2006, they suggested a major earthquake could occur near Wenchuan in 2007-2008 based on these gravity variations.
- Repeated regional gravity surveys were conducted in 1998, 2000, 2002, and 2005 using absolute and relative gravity measurements. Gravity variations at some locations near Wenchuan were significant but more research is needed to determine if they could be considered precursors.
- Limitations in the data include measurement errors, effects of hydrology and crustal movements on gravity readings, coarse station density, and long time intervals between surveys. Improved
This document shows a suggested approach to generate geological maps from satellite images, which represent a powerful tool to characterize an area prior fieldwork, saving energy and money during the process and using the free sources from NASA and the USGS. This exercise mapped a Colombian area called Media Luna Syncline
Arctic sea ice - use of observational datatracyrogers84
This document summarizes a study that evaluated 35 global climate models from the CMIP5 project in order to refine future projections of Arctic sea ice extent. The study analyzed observed sea ice data from 1979-2013 and model hindcasts over that period. It found that the models generally underestimated the observed rate of sea ice loss. The study then applied a two-step process to select subsets of the best performing models based on their ability to match historical trends and means. Evaluating progressively smaller subsets revealed that the simulated historical trend became larger and the projected date of an ice-free Arctic became earlier. The study also examined sudden ice loss events and their potential contribution to future sea ice decline.
Gaddam et al-2017-journal_of_earth_system_science (1)Vinay G
1) The study develops seasonal sensitivity characteristics (SSCs) for four glaciers in Western Himalaya to quantify changes in specific mass balance from monthly temperature and precipitation variations.
2) Using the SSCs and climate reanalysis data, the study reconstructs the specific mass balance of the glaciers from 1900-2010, finding they experienced both positive and negative balances, except Naradu glacier which only lost mass.
3) A cumulative mass loss of -133 ± 21.5 meters water equivalent was estimated for the four glaciers over the observation period, making this the first record of Himalayan glacier mass balances over a century scale.
Modification and Climate Change Analysis of surrounding Environment using Rem...iosrjce
This document discusses the application of remote sensing (RS) and geographic information systems (GIS) in analyzing climate change and the surrounding environment. It begins by defining key terms related to climate, climate change, and RS and GIS. It then highlights several areas where RS and GIS have been applied, including glacier monitoring, vegetation change monitoring, and carbon trace/accounting. Studies are discussed that use RS and GIS to monitor glacier retreat, snow depth, land cover change, and above-ground carbon stocks. The document concludes that RS and GIS play a crucial role in understanding and managing climate change by providing important spatial data and enabling the monitoring of environmental changes over time.
This document presents new archaeomagnetic intensity data from southeastern California and northwestern Ecuador and evaluates existing regional data from California, the southwestern United States, and northwestern South America. Significant scatter exists in the existing data, making comparisons and interpretations difficult. The document analyzes sources of data scatter, including age uncertainty, experimental errors, cooling rate differences, magnetic anisotropy, and field distortion. Corrections are made where possible and questionable data are eliminated, reducing scatter. However, differences between the Southwest and South American intensity records can still be identified.
The document discusses the application of kriging in groundwater studies. Kriging is a geostatistical technique used to interpolate the value of a random field between known data points. It provides the best linear unbiased prediction and honors the observed spatial structure of the data. Two case studies are summarized that demonstrate how kriging can be used to generate groundwater level contour maps and correlate declining water levels with land cover changes detected from satellite images. The studies show that kriging produces more accurate representations of spatial variability in groundwater compared to other methods.
This document describes a project to derive geomorphological regions in Cotopaxi Province, Ecuador using GIS. Spatial data from various sources was analyzed using ArcGIS. An unsupervised classification was performed based on elevation and slope data to identify regions of similar geomorphology. The project area around Quilotoa volcano was used to assess the accuracy of the classification by correlating the derived geomorphological regions with soil and precipitation data. The results identified some limitations of the classification approach but also areas of correlation between geomorphology, soils, and precipitation patterns.
This document discusses using Love waves in active Multichannel Analysis of Surface Waves (MASW) surveys to improve data quality. It proposes recording both left and right polarized Love waves in addition to Rayleigh waves. The polarization of Love waves could help quality control data collection. Stacking the polarized Love waves in the phase velocity domain may enhance the dispersion image compared to using Rayleigh waves alone. The paper aims to test this approach on a field site and compare the shear wave velocity profiles obtained from inverting Love wave and Rayleigh wave dispersion data. References are provided on research related to improving MASW surveys through better handling of higher surface wave modes.
This study estimates the maximum volume of rock eroded from southwestern South Africa since the start of the Cretaceous period through constructing structural cross-sections and extrapolating the thickness of lithostratigraphic units. The total estimated maximum volume is 1.56 million cubic kilometers, representing an average erosion of 11 kilometers of vertical thickness across the 140,000 square kilometer study area. This volume is an order of magnitude greater than the amount of sediment estimated to have accumulated in the offshore basins, suggesting further research is needed to better understand the erosion and transport of material from the study area.
Large-scale Volcanism and the Heat Death of Terrestrial WorldsSérgio Sacani
This document discusses the potential for large igneous provinces (LIPs) to cause the "heat death" of terrestrial planets through massive volcanic eruptions that overwhelm the climate system. It examines the timing of LIP events on Earth to estimate the likelihood of nearly simultaneous eruptions. Statistical analysis of Earth's LIP record finds that eruptions within 0.1-1 million years of each other are likely. Simultaneous LIPs could have driven Venus into a runaway greenhouse effect like its current state. The timing of LIP events on Earth provides insight into potential past LIP activity on Venus that may have ended its hypothesized earlier temperate climate.
1) This study uses a deep learning model to estimate stratospheric gravity wave potential energy (GW Ep) averaged over 20-30 km using ERA5 reanalysis data and terrain data as inputs. The model is trained using GW Ep values calculated from COSMIC radio occultation data as labels.
2) The results show the model can effectively estimate the zonal trend of GW Ep but with larger errors in low latitudes than mid-latitudes. Seasonal variations are also seen in the estimated GW Ep.
3) The estimated GW Ep shows the effect of the quasi-biennial oscillation, though its amplitude may be less than that of the measured GW Ep from COSMIC data.
2005 emerging insights into the dynamics of submarine debris flowsshh315
This document summarizes recent research on the dynamics of submarine debris flows. Key points include:
1) Hydroplaning, where the flow rides on a cushion of water, allows debris flows to travel much farther than expected and may help explain long runout distances.
2) Intruding water may soften stiff clay material in the neck of the flow, facilitating separation of the head block and further accelerating the flow.
3) Laboratory experiments using materials from clay-rich to sandy revealed a transition between low-suspension plug flows to more agitated flows that generate turbidity currents.
4) Statistical analysis of a large submarine landslide found scaling behaviors that models have difficulty reproducing,
Mapping the Skies of Ultracool Worlds: Detecting Storms and Spots with Extrem...Sérgio Sacani
Extremely large telescopes (ELTs) present an unparalleled opportunity to study the magnetism,
atmospheric dynamics, and chemistry of very low mass stars (VLMs), brown dwarfs, and exoplanets.
Instruments such as the Giant Magellan Telescope - Consortium Large Earth Finder (GMT/GCLEF),
the Thirty Meter Telescope’s Multi-Objective Diffraction-limited High-Resolution Infrared Spectrograph
(TMT/MODHIS), and the European Southern Observatory’s Mid-Infrared ELT Imager and Spectrograph (ELT/METIS) provide the spectral resolution and signal-to-noise (S/N) necessary to Doppler
image ultracool targets’surfaces based on temporal spectral variations due to surface inhomogeneities.
Using our publicly-available code, Imber, developed and validated in Plummer & Wang (2022), we
evaluate these instruments’abilities to discern magnetic star spots and cloud systems on a VLM star
(TRAPPIST-1); two L/T transition ultracool dwarfs (VHS J1256−1257 b and SIMP J0136+0933); and
three exoplanets (Beta Pic b and HR 8799 d and e). We find that TMT/MODHIS and ELT/METIS are
suitable for Doppler imaging the ultracool dwarfs and Beta Pic b over a single rotation. Uncertainties
for longitude and radius are typically . 10◦
, and latitude uncertainties range from ∼ 10◦
to 30◦
.
TRAPPIST-1’s edge-on inclination and low υ sin i provide a challenge for all three instruments while
GMT/GCLEF and the HR 8799 planets may require observations over multiple rotations. We compare
the spectroscopic technique, photometry-only inference, and the combination of the two. We find
combining spectroscopic and photometric observations can lead to improved Bayesian inference of
surface inhomogeneities and offers insight into whether ultracool atmospheres are dominated by spotted
or banded features.
1) New data from the GRAIL gravity mission and LOLA altimetry is helping to determine the structure of the lunar highlands crust.
2) Preliminary GRAIL gravity models show noise levels are lower than expected, indicating signals exist at even shorter wavelengths than planned.
3) Combined analysis of gravity and topography data can provide insights into crustal thickness, elastic properties of the lithosphere, and the thermal state during and after bombardment.
Surface Soil Moisture and Groundwater Assessment and Monitoring using Remote ...Jenkins Macedo
This preview is part of the requirement for a comprehensive analysis of remotely sensed surface soil moisture and groundwater assessment and monitoring for global environmental and climate change presented by Christina Geller, candidate for the degree of MSc in Geographic Information Science for Development, and Environment and Jenkins Macedo, candidate for the MS in Environmental Science and Policy at the Department of International Development, Community, and Environmental at Clark University.
The document presents a new hydrological model called CI-SLAM (Connectivity Index-based Shallow LAndslide Model) to model shallow landslide susceptibility. The key aspects of the model are:
1) It accounts for the concept of hydrological connectivity, which is the condition where disparate saturated regions on a hillslope are linked by subsurface water flow.
2) Hydrological connectivity depends on the spatial variability of soil depth across catchments and initial soil moisture conditions.
3) The model simulates the development of a perched water table and estimates the time required for saturated conditions to develop at the soil-bedrock interface.
4) It couples the hydrological model with an infinite
Historical and Contemporary Trends in the Size, Drift, and Color of Jupiterʼs...Sérgio Sacani
The Great Red Spot on Jupiter has been shrinking over the past 150+ years based on historical records and spacecraft observations. Recent data from 1979-2017 show the Spot shrinking longitudinally at a rate of 0.194 degrees per year and latitudinally at 0.048 degrees per year. Its westward drift has also been accelerating, increasing about 0.002 degrees per day each year. High resolution images allow analysis of changes in the Spot's color, winds, and internal structure over this time period.
This document summarizes a study that used gravity data to delineate underground structure in the Beppu geothermal field in Japan. Analysis of Bouguer anomaly maps revealed high anomalies in the southern and northern parts of the study area that correspond to known geological formations. Edge detection filtering of the gravity data helped identify subsurface faults, including the northern edge of the high southern anomaly corresponding to the Asamigawa Fault. Depth modeling of the gravity basement showed differences between the southern and northern hot spring areas, with steep basement slopes along faults in the south and uplifted basement in the north.
A 3d extinction_map_of_the_northern_galactic_plane_based_on_iphas_photometrySérgio Sacani
This document presents a 3D extinction map of the Northern Galactic Plane derived using photometry from the IPHAS survey. The map was constructed using a hierarchical Bayesian method that simultaneously estimates the distance-extinction relationship and properties of ~38 million stars along each line of sight. The map has fine angular resolution of ~10 arcminutes and distance resolution of 100 pc out to a depth of 5 kpc. In addition to mean extinction, the method also measures differential extinction arising from the fractal structure of the interstellar medium. Both the extinction map and catalogue of stellar parameters are made publicly available.
This document discusses the derivation of new empirical magnitude conversion relationships for earthquakes in Turkey and surrounding regions between 1900-2012. It uses an improved earthquake catalog containing 12,674 events of magnitude 4.0 and greater. The catalog includes events reported in different magnitude scales. The study derives conversion equations to relate moment magnitude (Mw) to local magnitude (ML), duration magnitude (Md), body wave magnitude (mb), and surface wave magnitude (Ms) using 489 events that have reported Mw values. Both orthogonal regression and ordinary least squares methods are used and compared. The new relationships are meant to make the catalog more homogeneous by converting all magnitudes to the common Mw scale.
A statistical assessment of GDEM using LiDAR dataTomislav Hengl
This document presents a statistical assessment of the accuracy of the Global Digital Elevation Model (GDEM) using LiDAR data. It proposes a framework to evaluate GDEM accuracy by assessing absolute elevation errors, positional accuracy of hydrological features, surface roughness representation, and user satisfaction. Case studies in four areas show regression models can evaluate elevation fit, with an R-squared value above 0.995 indicating satisfactory accuracy for GDEM in areas of medium relief. The document concludes GDEM has little usefulness in areas of low relief.
- Researchers in China noticed significant gravity changes in a region covering the south-north earthquake belt before the 2008 Wenchuan earthquake (Mw 7.9). In 2006, they suggested a major earthquake could occur near Wenchuan in 2007-2008 based on these gravity variations.
- Repeated regional gravity surveys were conducted in 1998, 2000, 2002, and 2005 using absolute and relative gravity measurements. Gravity variations at some locations near Wenchuan were significant but more research is needed to determine if they could be considered precursors.
- Limitations in the data include measurement errors, effects of hydrology and crustal movements on gravity readings, coarse station density, and long time intervals between surveys. Improved
This document shows a suggested approach to generate geological maps from satellite images, which represent a powerful tool to characterize an area prior fieldwork, saving energy and money during the process and using the free sources from NASA and the USGS. This exercise mapped a Colombian area called Media Luna Syncline
Arctic sea ice - use of observational datatracyrogers84
This document summarizes a study that evaluated 35 global climate models from the CMIP5 project in order to refine future projections of Arctic sea ice extent. The study analyzed observed sea ice data from 1979-2013 and model hindcasts over that period. It found that the models generally underestimated the observed rate of sea ice loss. The study then applied a two-step process to select subsets of the best performing models based on their ability to match historical trends and means. Evaluating progressively smaller subsets revealed that the simulated historical trend became larger and the projected date of an ice-free Arctic became earlier. The study also examined sudden ice loss events and their potential contribution to future sea ice decline.
Gaddam et al-2017-journal_of_earth_system_science (1)Vinay G
1) The study develops seasonal sensitivity characteristics (SSCs) for four glaciers in Western Himalaya to quantify changes in specific mass balance from monthly temperature and precipitation variations.
2) Using the SSCs and climate reanalysis data, the study reconstructs the specific mass balance of the glaciers from 1900-2010, finding they experienced both positive and negative balances, except Naradu glacier which only lost mass.
3) A cumulative mass loss of -133 ± 21.5 meters water equivalent was estimated for the four glaciers over the observation period, making this the first record of Himalayan glacier mass balances over a century scale.
Modification and Climate Change Analysis of surrounding Environment using Rem...iosrjce
This document discusses the application of remote sensing (RS) and geographic information systems (GIS) in analyzing climate change and the surrounding environment. It begins by defining key terms related to climate, climate change, and RS and GIS. It then highlights several areas where RS and GIS have been applied, including glacier monitoring, vegetation change monitoring, and carbon trace/accounting. Studies are discussed that use RS and GIS to monitor glacier retreat, snow depth, land cover change, and above-ground carbon stocks. The document concludes that RS and GIS play a crucial role in understanding and managing climate change by providing important spatial data and enabling the monitoring of environmental changes over time.
This document presents new archaeomagnetic intensity data from southeastern California and northwestern Ecuador and evaluates existing regional data from California, the southwestern United States, and northwestern South America. Significant scatter exists in the existing data, making comparisons and interpretations difficult. The document analyzes sources of data scatter, including age uncertainty, experimental errors, cooling rate differences, magnetic anisotropy, and field distortion. Corrections are made where possible and questionable data are eliminated, reducing scatter. However, differences between the Southwest and South American intensity records can still be identified.
The document discusses the application of kriging in groundwater studies. Kriging is a geostatistical technique used to interpolate the value of a random field between known data points. It provides the best linear unbiased prediction and honors the observed spatial structure of the data. Two case studies are summarized that demonstrate how kriging can be used to generate groundwater level contour maps and correlate declining water levels with land cover changes detected from satellite images. The studies show that kriging produces more accurate representations of spatial variability in groundwater compared to other methods.
This document describes a project to derive geomorphological regions in Cotopaxi Province, Ecuador using GIS. Spatial data from various sources was analyzed using ArcGIS. An unsupervised classification was performed based on elevation and slope data to identify regions of similar geomorphology. The project area around Quilotoa volcano was used to assess the accuracy of the classification by correlating the derived geomorphological regions with soil and precipitation data. The results identified some limitations of the classification approach but also areas of correlation between geomorphology, soils, and precipitation patterns.
This document discusses using Love waves in active Multichannel Analysis of Surface Waves (MASW) surveys to improve data quality. It proposes recording both left and right polarized Love waves in addition to Rayleigh waves. The polarization of Love waves could help quality control data collection. Stacking the polarized Love waves in the phase velocity domain may enhance the dispersion image compared to using Rayleigh waves alone. The paper aims to test this approach on a field site and compare the shear wave velocity profiles obtained from inverting Love wave and Rayleigh wave dispersion data. References are provided on research related to improving MASW surveys through better handling of higher surface wave modes.
This study estimates the maximum volume of rock eroded from southwestern South Africa since the start of the Cretaceous period through constructing structural cross-sections and extrapolating the thickness of lithostratigraphic units. The total estimated maximum volume is 1.56 million cubic kilometers, representing an average erosion of 11 kilometers of vertical thickness across the 140,000 square kilometer study area. This volume is an order of magnitude greater than the amount of sediment estimated to have accumulated in the offshore basins, suggesting further research is needed to better understand the erosion and transport of material from the study area.
Large-scale Volcanism and the Heat Death of Terrestrial WorldsSérgio Sacani
This document discusses the potential for large igneous provinces (LIPs) to cause the "heat death" of terrestrial planets through massive volcanic eruptions that overwhelm the climate system. It examines the timing of LIP events on Earth to estimate the likelihood of nearly simultaneous eruptions. Statistical analysis of Earth's LIP record finds that eruptions within 0.1-1 million years of each other are likely. Simultaneous LIPs could have driven Venus into a runaway greenhouse effect like its current state. The timing of LIP events on Earth provides insight into potential past LIP activity on Venus that may have ended its hypothesized earlier temperate climate.
1) This study uses a deep learning model to estimate stratospheric gravity wave potential energy (GW Ep) averaged over 20-30 km using ERA5 reanalysis data and terrain data as inputs. The model is trained using GW Ep values calculated from COSMIC radio occultation data as labels.
2) The results show the model can effectively estimate the zonal trend of GW Ep but with larger errors in low latitudes than mid-latitudes. Seasonal variations are also seen in the estimated GW Ep.
3) The estimated GW Ep shows the effect of the quasi-biennial oscillation, though its amplitude may be less than that of the measured GW Ep from COSMIC data.
2005 emerging insights into the dynamics of submarine debris flowsshh315
This document summarizes recent research on the dynamics of submarine debris flows. Key points include:
1) Hydroplaning, where the flow rides on a cushion of water, allows debris flows to travel much farther than expected and may help explain long runout distances.
2) Intruding water may soften stiff clay material in the neck of the flow, facilitating separation of the head block and further accelerating the flow.
3) Laboratory experiments using materials from clay-rich to sandy revealed a transition between low-suspension plug flows to more agitated flows that generate turbidity currents.
4) Statistical analysis of a large submarine landslide found scaling behaviors that models have difficulty reproducing,
Mapping the Skies of Ultracool Worlds: Detecting Storms and Spots with Extrem...Sérgio Sacani
Extremely large telescopes (ELTs) present an unparalleled opportunity to study the magnetism,
atmospheric dynamics, and chemistry of very low mass stars (VLMs), brown dwarfs, and exoplanets.
Instruments such as the Giant Magellan Telescope - Consortium Large Earth Finder (GMT/GCLEF),
the Thirty Meter Telescope’s Multi-Objective Diffraction-limited High-Resolution Infrared Spectrograph
(TMT/MODHIS), and the European Southern Observatory’s Mid-Infrared ELT Imager and Spectrograph (ELT/METIS) provide the spectral resolution and signal-to-noise (S/N) necessary to Doppler
image ultracool targets’surfaces based on temporal spectral variations due to surface inhomogeneities.
Using our publicly-available code, Imber, developed and validated in Plummer & Wang (2022), we
evaluate these instruments’abilities to discern magnetic star spots and cloud systems on a VLM star
(TRAPPIST-1); two L/T transition ultracool dwarfs (VHS J1256−1257 b and SIMP J0136+0933); and
three exoplanets (Beta Pic b and HR 8799 d and e). We find that TMT/MODHIS and ELT/METIS are
suitable for Doppler imaging the ultracool dwarfs and Beta Pic b over a single rotation. Uncertainties
for longitude and radius are typically . 10◦
, and latitude uncertainties range from ∼ 10◦
to 30◦
.
TRAPPIST-1’s edge-on inclination and low υ sin i provide a challenge for all three instruments while
GMT/GCLEF and the HR 8799 planets may require observations over multiple rotations. We compare
the spectroscopic technique, photometry-only inference, and the combination of the two. We find
combining spectroscopic and photometric observations can lead to improved Bayesian inference of
surface inhomogeneities and offers insight into whether ultracool atmospheres are dominated by spotted
or banded features.
1) New data from the GRAIL gravity mission and LOLA altimetry is helping to determine the structure of the lunar highlands crust.
2) Preliminary GRAIL gravity models show noise levels are lower than expected, indicating signals exist at even shorter wavelengths than planned.
3) Combined analysis of gravity and topography data can provide insights into crustal thickness, elastic properties of the lithosphere, and the thermal state during and after bombardment.
This document summarizes observations of the lensed galaxy HATLAS J142935.3-002836 (H1429-0028) from the Herschel-ATLAS survey. Optical spectroscopy revealed the foreground lens is at redshift 0.218, while the background galaxy is at redshift 1.027. High-resolution imaging from Hubble Space Telescope and Keck adaptive optics show the background galaxy is comprised of two components and a tidal tail, resembling a major merger. Analysis of ALMA observations of CO emission provides a dynamical mass estimate of one component as 5.8 ± 1.7 × 1010 M☉. Modeling of the spectral energy distribution indicates the total stellar mass is 1.32
This document describes a Bayesian inversion approach to jointly interpret multiple seismic data types that provide information about anisotropic layering in the upper mantle. Surface wave dispersion curves, SKS splitting measurements, and receiver functions are traditionally interpreted separately, but sample different volumes of the Earth and have different sensitivities and uncertainties. The proposed method directly inverts seismograms for SKS and P phases using a cross-convolution approach, avoiding intermediate processing steps. A transdimensional Markov chain Monte Carlo scheme obtains probabilistic 1-D seismic velocity profiles down to 350 km depth beneath two stations, treating the number of layers and presence of anisotropy as unknown parameters. For both stations, the lithosphere-asthenosphere boundary is clearly visible and marked by
The Dynamical Consequences of a Super-Earth in the Solar SystemSérgio Sacani
Placing the architecture of the solar system within the broader context of planetary architectures is one of the
primary topics of interest within planetary science. Exoplanet discoveries have revealed a large range of system
architectures, many of which differ substantially from the solar system’s model. One particular feature of exoplanet
demographics is the relative prevalence of super-Earth planets, for which the solar system lacks a suitable analog,
presenting a challenge to modeling their interiors and atmospheres. Here we present the results of a large suite of
dynamical simulations that insert a hypothetical planet in the mass range 1–10 M⊕ within the semimajor axis range
2–4 au, between the orbits of Mars and Jupiter. We show that, although the system dynamics remain largely
unaffected when the additional planet is placed near 3 au, Mercury experiences substantial instability when the
additional planet lies in the range 3.1–4.0 au, and perturbations to the Martian orbit primarily result when the
additional planet lies in the range 2.0–2.7 au. We further show that, although Jupiter and Saturn experience
relatively small orbital perturbations, the angular momentum transferred to the ice giants can result in their ejection
from the system at key resonance locations of the additional planet. We discuss the implications of these results for
the architecture of the inner and outer solar system planets, and for exoplanetary systems
Rupture processes of the 2012 September 5 Mw 7.6 Nicoya CONSTRAINEDAllan Lopez
On September 5, 2012, a Mw 7.6 earthquake ruptured beneath the Nicoya Peninsula in northwestern Costa Rica. Extensive geodetic and seismological observations from dense near-field strong motion sensors, GPS networks, and global seismic networks provide a unique opportunity to investigate the rupture process. Through a non-linear joint inversion of high-rate GPS waveforms, static GPS offsets, strong motion data, and teleseismic body waves, the authors obtained a robust rupture model. The earthquake was dominantly a pure thrust event with a maximum slip of 3.5 m located below the hypocenter, spanning about 50 km along dip and 110 km along strike. The static stress drop was approximately 3.4 MP
Rupture processes of the 2012 September 5 Mw 7.6 Nicoya CONSTRAINEDAllan Lopez
On September 5, 2012, a Mw 7.6 earthquake ruptured beneath the Nicoya Peninsula in northwestern Costa Rica. Extensive geodetic and seismological observations were available, including static and high-rate GPS data, strong motion recordings, and teleseismic body waves. By implementing a nonlinear joint inversion of these diverse data sets, the authors obtained a robust rupture model for the 2012 Nicoya earthquake. The model indicates a predominantly thrust faulting mechanism, with a maximum slip of 3.5 m located below the hypocenter spanning about 50 km along dip and 110 km along strike. The static stress drop was approximately 3.4 MPa. Most of the seismic moment was released within the first 70 seconds due
Multicomponent Seismic - A Measure_of_Full-wave_MotionRobert Stewart
This document provides an overview of multicomponent seismic exploration and its value. It discusses how multicomponent seismic aims to fully record vibrations in the earth using multiple sensors to enhance traditional P-wave data and create S-wave and surface wave images. Of the additional wave types, converted waves (P-to-S on reflection) have found the most use in resource exploration by imaging below gas and discriminating lithology. The document outlines the history and improvements in multicomponent acquisition methods and processing, and highlights increasing commercial applications and case studies demonstrating its value. It concludes by discussing ongoing areas for further advancing multicomponent seismic methods and applications.
This document examines whether galaxy environments and the color-density relation can be robustly measured using photometric redshift (photo-z) surveys. It finds that:
1) Using optimized parameters for density measurements, a correlation between 2D projected density measurements from photo-z surveys and true 3D density can still be revealed, even with photo-z uncertainties up to 0.06.
2) The color-density relation remains visible in photo-z surveys out to z=0.8, despite photo-z uncertainties of 0.02-0.06.
3) A deep (i=25 magnitude) photo-z survey with photo-z uncertainties of 0.02 can measure small-scale galaxy
2019-10-29 Recent progress of volcano deformation studies Yosuke Aoki
Recent progress of volcano deformation studies
The summary discusses the development of volcano geodesy driven by new observational techniques like GNSS, SAR, and modeling methods. It notes that while conventional observations and simple modeling are still useful, sophisticated numerical techniques are powerful but have limitations. Deformation from phreatic eruptions is complicated. Recent unrest at Hakone Volcano may offer insights for monitoring Tatun Volcano.
This document describes a fast and reliable method for surface wave tomography to estimate 2-D models of isotropic and azimuthally anisotropic velocity variations from regional or global surface wave data. The method inverts surface wave group or phase velocity measurements to produce tomographic maps in a spherical geometry. It allows for spatial smoothing and model amplitude constraints to be applied simultaneously. Examples applying this technique globally and regionally in Eurasia and Antarctica are presented.
This document describes a fast and reliable method for surface wave tomography to estimate 2-D models of isotropic and azimuthally anisotropic velocity variations from regional or global surface wave data. The method inverts surface wave group or phase velocity measurements to produce tomographic maps in a spherical geometry. It allows for spatial smoothing and model amplitude constraints to be applied simultaneously. Examples applying this technique globally and regionally in Eurasia and Antarctica are presented.
This document summarizes the development of a new ultra-high resolution model of Earth's gravity field called GGMplus. Key points:
- GGMplus combines satellite gravity data from GOCE and GRACE with terrestrial gravity data and topography to achieve unprecedented 200m spatial resolution globally.
- It provides gridded estimates of gravity, horizontal and radial field components, and quasi-geoid heights at over 3 billion points covering 80% of the Earth's land.
- GGMplus reveals new details of small-scale gravity variations and identifies locations of minimum and maximum gravity, suggesting peak-to-peak variations are 40% larger than previous estimates. The model will benefit scientific and engineering applications.
The Mastcam instrument on the Curiosity rover observed isolated outcrops of cemented pebbles and sand grains with textures typical of fluvial sedimentary conglomerates at three locations along the rover's traverse. The rounded pebbles indicate substantial fluvial abrasion by water flows. ChemCam analysis found the conglomerate to have a predominantly feldspathic composition, consistent with minimal aqueous alteration. The sediments were mobilized by ancient water flows that were deep and fast enough to transport pebbles several centimeters in diameter. This evidence suggests Mars once had a warmer, wetter climate that could support overland water flows, in contrast to the current hyper-arid conditions.
Hot Earth or Young Venus? A nearby transiting rocky planet mysterySérgio Sacani
Venus and Earth provide astonishingly different views of the evolution of a rocky planet, raising the question of why these two rock y worlds evolv ed so differently. The recently disco v ered transiting Super-Earth LP 890-9c (TOI-4306c, SPECULOOS-2c) is a key to the question. It circles a nearby M6V star in 8.46 d. LP890-9c receives similar flux as modern Earth, which puts it very close to the inner edge of the Habitable Zone (HZ), where models differ strongly in their prediction of how long rocky planets can hold onto their water. We model the atmosphere of a hot LP890-9c at the inner edge of the HZ, where the planet could sustain several very different environments. The resulting transmission spectra differ considerably between a hot, wet exo-Earth, a steamy planet caught in a runaway greenhouse, and an exo-Venus. Distinguishing these scenarios from the planet’s spectra will provide critical new insights into the evolution of hot terrestrial planets into exo-Venus. Our model and spectra are available online as a tool to plan observations. They show that observing LP890-9c can provide key insights into the evolution of a rocky planet at the inner edge of the HZ as well as the long-term future of Earth.
Remote sensing and GIS tools can be effectively used to analyze and monitor climate change and its effects in several areas:
1) Glacier and snow monitoring through analysis of satellite images to track glacier retreat and advance over time, as well as measuring snow depth, both of which are sensitive to climate change.
2) Vegetation change monitoring using multi-temporal satellite imagery to detect land degradation and changes in vegetation phenology correlated with climate patterns like rainfall.
3) Carbon accounting and tracing, important for climate change mitigation, through high-resolution mapping of above-ground carbon stocks using field measurements, airborne LiDAR, and satellite data.
Formation of low mass protostars and their circumstellar disksSérgio Sacani
Understanding circumstellar disks is of prime importance in astrophysics, however, their birth process remains poorly constrained due to observational and numerical challenges. Recent numerical works have shown that the small-scale physics, often wrapped into a sub-grid model, play a crucial role in disk formation and evolution. This calls for a combined approach in which both the protostar and circumstellar disk are studied in concert. Aims. We aim to elucidate the small scale physics and constrain sub-grid parameters commonly chosen in the literature by resolving the star-disk interaction. Methods. We carry out a set of very high resolution 3D radiative-hydrodynamics simulations that self-consistently describe the collapse of a turbulent dense molecular cloud core to stellar densities. We study the birth of the protostar, the circumstellar disk, and its early evolution (< 6 yr after protostellar formation). Results. Following the second gravitational collapse, the nascent protostar quickly reaches breakup velocity and sheds its surface material, thus forming a hot (∼ 103 K), dense, and highly flared circumstellar disk. The protostar is embedded within the disk, such that material can flow without crossing any shock fronts. The circumstellar disk mass quickly exceeds that of the protostar, and its kinematics are dominated by self-gravity. Accretion onto the disk is highly anisotropic, and accretion onto the protostar mainly occurs through material that slides on the disk surface. The polar mass flux is negligible in comparison. The radiative behavior also displays a strong anisotropy, as the polar accretion shock is shown to be supercritical whereas its equatorial counterpart is subcritical. We also f ind a remarkable convergence of our results with respect to initial conditions. Conclusions. These results reveal the structure and kinematics in the smallest spatial scales relevant to protostellar and circumstellar disk evolution. They can be used to describe accretion onto regions commonly described by sub-grid models in simulations studying larger scale physics.
Similar to A global reference model of the lithosphere and upper mantle from joint inversion and analysis of multiple data sets (20)
The binding of cosmological structures by massless topological defectsSérgio Sacani
Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
mitigated, at least in part.
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...Sérgio Sacani
Context. With a mass exceeding several 104 M⊙ and a rich and dense population of massive stars, supermassive young star clusters
represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions
among stars.
Aims. In this paper we present the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS) project, which aims to investigate
the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars.
The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun.
Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically,
the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec.
Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within
and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation
were carried out using the ACIS-Extract software.
Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a
photon flux threshold of approximately 2 × 10−8 photons cm−2
s
−1
. The X-ray sources exhibit a highly concentrated spatial distribution,
with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known
massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.
The debris of the ‘last major merger’ is dynamically youngSérgio Sacani
The Milky Way’s (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the
‘last major merger.’ Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor
collided with the MW proto-disc 8–11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor collided with the
MW disc within the last 3 Gyr. These two scenarios make different predictions about observable structure in local phase space,
because the morphology of debris depends on how long it has had to phase mix. The recently identified phase-space folds in Gaia
DR3 have positive caustic velocities, making them fundamentally different than the phase-mixed chevrons found in simulations
at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
on a simple phase-mixing model, the observed number of caustics are consistent with a merger that occurred 1–2 Gyr ago.
We also compare the observed phase-space distribution to FIRE-2 Latte simulations of GSE-like mergers, using a quantitative
measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
the last few Gyr, consistent with the body of work surrounding the VRM.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Gliese 12 b: A Temperate Earth-sized Planet at 12 pc Ideal for Atmospheric Tr...Sérgio Sacani
Recent discoveries of Earth-sized planets transiting nearby M dwarfs have made it possible to characterize the
atmospheres of terrestrial planets via follow-up spectroscopic observations. However, the number of such planets
receiving low insolation is still small, limiting our ability to understand the diversity of the atmospheric
composition and climates of temperate terrestrial planets. We report the discovery of an Earth-sized planet
transiting the nearby (12 pc) inactive M3.0 dwarf Gliese 12 (TOI-6251) with an orbital period (Porb) of 12.76 days.
The planet, Gliese 12 b, was initially identified as a candidate with an ambiguous Porb from TESS data. We
confirmed the transit signal and Porb using ground-based photometry with MuSCAT2 and MuSCAT3, and
validated the planetary nature of the signal using high-resolution images from Gemini/NIRI and Keck/NIRC2 as
well as radial velocity (RV) measurements from the InfraRed Doppler instrument on the Subaru 8.2 m telescope
and from CARMENES on the CAHA 3.5 m telescope. X-ray observations with XMM-Newton showed the host
star is inactive, with an X-ray-to-bolometric luminosity ratio of log 5.7 L L X bol » - . Joint analysis of the light
curves and RV measurements revealed that Gliese 12 b has a radius of 0.96 ± 0.05 R⊕,a3σ mass upper limit of
3.9 M⊕, and an equilibrium temperature of 315 ± 6 K assuming zero albedo. The transmission spectroscopy metric
(TSM) value of Gliese 12 b is close to the TSM values of the TRAPPIST-1 planets, adding Gliese 12 b to the small
list of potentially terrestrial, temperate planets amenable to atmospheric characterization with JWST.
Gliese 12 b, a temperate Earth-sized planet at 12 parsecs discovered with TES...Sérgio Sacani
We report on the discovery of Gliese 12 b, the nearest transiting temperate, Earth-sized planet found to date. Gliese 12 is a
bright (V = 12.6 mag, K = 7.8 mag) metal-poor M4V star only 12.162 ± 0.005 pc away from the Solar system with one of the
lowest stellar activity levels known for M-dwarfs. A planet candidate was detected by TESS based on only 3 transits in sectors
42, 43, and 57, with an ambiguity in the orbital period due to observational gaps. We performed follow-up transit observations
with CHEOPS and ground-based photometry with MINERVA-Australis, SPECULOOS, and Purple Mountain Observatory,
as well as further TESS observations in sector 70. We statistically validate Gliese 12 b as a planet with an orbital period of
12.76144 ± 0.00006 d and a radius of 1.0 ± 0.1 R⊕, resulting in an equilibrium temperature of ∼315 K. Gliese 12 b has excellent
future prospects for precise mass measurement, which may inform how planetary internal structure is affected by the stellar
compositional environment. Gliese 12 b also represents one of the best targets to study whether Earth-like planets orbiting cool
stars can retain their atmospheres, a crucial step to advance our understanding of habitability on Earth and across the galaxy.
The importance of continents, oceans and plate tectonics for the evolution of...Sérgio Sacani
Within the uncertainties of involved astronomical and biological parameters, the Drake Equation
typically predicts that there should be many exoplanets in our galaxy hosting active, communicative
civilizations (ACCs). These optimistic calculations are however not supported by evidence, which is
often referred to as the Fermi Paradox. Here, we elaborate on this long-standing enigma by showing
the importance of planetary tectonic style for biological evolution. We summarize growing evidence
that a prolonged transition from Mesoproterozoic active single lid tectonics (1.6 to 1.0 Ga) to modern
plate tectonics occurred in the Neoproterozoic Era (1.0 to 0.541 Ga), which dramatically accelerated
emergence and evolution of complex species. We further suggest that both continents and oceans
are required for ACCs because early evolution of simple life must happen in water but late evolution
of advanced life capable of creating technology must happen on land. We resolve the Fermi Paradox
(1) by adding two additional terms to the Drake Equation: foc
(the fraction of habitable exoplanets
with significant continents and oceans) and fpt
(the fraction of habitable exoplanets with significant
continents and oceans that have had plate tectonics operating for at least 0.5 Ga); and (2) by
demonstrating that the product of foc
and fpt
is very small (< 0.00003–0.002). We propose that the lack
of evidence for ACCs reflects the scarcity of long-lived plate tectonics and/or continents and oceans on
exoplanets with primitive life.
A Giant Impact Origin for the First Subduction on EarthSérgio Sacani
Hadean zircons provide a potential record of Earth's earliest subduction 4.3 billion years ago. Itremains enigmatic how subduction could be initiated so soon after the presumably Moon‐forming giant impact(MGI). Earlier studies found an increase in Earth's core‐mantle boundary (CMB) temperature due to theaccumulation of the impactor's core, and our recent work shows Earth's lower mantle remains largely solid, withsome of the impactor's mantle potentially surviving as the large low‐shear velocity provinces (LLSVPs). Here,we show that a hot post‐impact CMB drives the initiation of strong mantle plumes that can induce subductioninitiation ∼200 Myr after the MGI. 2D and 3D thermomechanical computations show that a high CMBtemperature is the primary factor triggering early subduction, with enrichment of heat‐producing elements inLLSVPs as another potential factor. The models link the earliest subduction to the MGI with implications forunderstanding the diverse tectonic regimes of rocky planets.
Climate extremes likely to drive land mammal extinction during next supercont...Sérgio Sacani
Mammals have dominated Earth for approximately 55 Myr thanks to their
adaptations and resilience to warming and cooling during the Cenozoic. All
life will eventually perish in a runaway greenhouse once absorbed solar
radiation exceeds the emission of thermal radiation in several billions of
years. However, conditions rendering the Earth naturally inhospitable to
mammals may develop sooner because of long-term processes linked to
plate tectonics (short-term perturbations are not considered here). In
~250 Myr, all continents will converge to form Earth’s next supercontinent,
Pangea Ultima. A natural consequence of the creation and decay of Pangea
Ultima will be extremes in pCO2 due to changes in volcanic rifting and
outgassing. Here we show that increased pCO2, solar energy (F⨀;
approximately +2.5% W m−2 greater than today) and continentality (larger
range in temperatures away from the ocean) lead to increasing warming
hostile to mammalian life. We assess their impact on mammalian
physiological limits (dry bulb, wet bulb and Humidex heat stress indicators)
as well as a planetary habitability index. Given mammals’ continued survival,
predicted background pCO2 levels of 410–816 ppm combined with increased
F⨀ will probably lead to a climate tipping point and their mass extinction.
The results also highlight how global landmass configuration, pCO2 and F⨀
play a critical role in planetary habitability.
Constraints on Neutrino Natal Kicks from Black-Hole Binary VFTS 243Sérgio Sacani
The recently reported observation of VFTS 243 is the first example of a massive black-hole binary
system with negligible binary interaction following black-hole formation. The black-hole mass (≈10M⊙)
and near-circular orbit (e ≈ 0.02) of VFTS 243 suggest that the progenitor star experienced complete
collapse, with energy-momentum being lost predominantly through neutrinos. VFTS 243 enables us to
constrain the natal kick and neutrino-emission asymmetry during black-hole formation. At 68% confidence
level, the natal kick velocity (mass decrement) is ≲10 km=s (≲1.0M⊙), with a full probability distribution
that peaks when ≈0.3M⊙ were ejected, presumably in neutrinos, and the black hole experienced a natal
kick of 4 km=s. The neutrino-emission asymmetry is ≲4%, with best fit values of ∼0–0.2%. Such a small
neutrino natal kick accompanying black-hole formation is in agreement with theoretical predictions.
Detectability of Solar Panels as a TechnosignatureSérgio Sacani
In this work, we assess the potential detectability of solar panels made of silicon on an Earth-like
exoplanet as a potential technosignature. Silicon-based photovoltaic cells have high reflectance in the
UV-VIS and in the near-IR, within the wavelength range of a space-based flagship mission concept
like the Habitable Worlds Observatory (HWO). Assuming that only solar energy is used to provide
the 2022 human energy needs with a land cover of ∼ 2.4%, and projecting the future energy demand
assuming various growth-rate scenarios, we assess the detectability with an 8 m HWO-like telescope.
Assuming the most favorable viewing orientation, and focusing on the strong absorption edge in the
ultraviolet-to-visible (0.34 − 0.52 µm), we find that several 100s of hours of observation time is needed
to reach a SNR of 5 for an Earth-like planet around a Sun-like star at 10pc, even with a solar panel
coverage of ∼ 23% land coverage of a future Earth. We discuss the necessity of concepts like Kardeshev
Type I/II civilizations and Dyson spheres, which would aim to harness vast amounts of energy. Even
with much larger populations than today, the total energy use of human civilization would be orders of
magnitude below the threshold for causing direct thermal heating or reaching the scale of a Kardashev
Type I civilization. Any extraterrrestrial civilization that likewise achieves sustainable population
levels may also find a limit on its need to expand, which suggests that a galaxy-spanning civilization
as imagined in the Fermi paradox may not exist.
Jet reorientation in central galaxies of clusters and groups: insights from V...Sérgio Sacani
Recent observations of galaxy clusters and groups with misalignments between their central AGN jets
and X-ray cavities, or with multiple misaligned cavities, have raised concerns about the jet – bubble
connection in cooling cores, and the processes responsible for jet realignment. To investigate the
frequency and causes of such misalignments, we construct a sample of 16 cool core galaxy clusters and
groups. Using VLBA radio data we measure the parsec-scale position angle of the jets, and compare
it with the position angle of the X-ray cavities detected in Chandra data. Using the overall sample
and selected subsets, we consistently find that there is a 30% – 38% chance to find a misalignment
larger than ∆Ψ = 45◦ when observing a cluster/group with a detected jet and at least one cavity. We
determine that projection may account for an apparently large ∆Ψ only in a fraction of objects (∼35%),
and given that gas dynamical disturbances (as sloshing) are found in both aligned and misaligned
systems, we exclude environmental perturbation as the main driver of cavity – jet misalignment.
Moreover, we find that large misalignments (up to ∼ 90◦
) are favored over smaller ones (45◦ ≤ ∆Ψ ≤
70◦
), and that the change in jet direction can occur on timescales between one and a few tens of Myr.
We conclude that misalignments are more likely related to actual reorientation of the jet axis, and we
discuss several engine-based mechanisms that may cause these dramatic changes.
The solar dynamo begins near the surfaceSérgio Sacani
The magnetic dynamo cycle of the Sun features a distinct pattern: a propagating
region of sunspot emergence appears around 30° latitude and vanishes near the
equator every 11 years (ref. 1). Moreover, longitudinal flows called torsional oscillations
closely shadow sunspot migration, undoubtedly sharing a common cause2. Contrary
to theories suggesting deep origins of these phenomena, helioseismology pinpoints
low-latitude torsional oscillations to the outer 5–10% of the Sun, the near-surface
shear layer3,4. Within this zone, inwardly increasing differential rotation coupled with
a poloidal magnetic field strongly implicates the magneto-rotational instability5,6,
prominent in accretion-disk theory and observed in laboratory experiments7.
Together, these two facts prompt the general question: whether the solar dynamo is
possibly a near-surface instability. Here we report strong affirmative evidence in stark
contrast to traditional models8 focusing on the deeper tachocline. Simple analytic
estimates show that the near-surface magneto-rotational instability better explains
the spatiotemporal scales of the torsional oscillations and inferred subsurface
magnetic field amplitudes9. State-of-the-art numerical simulations corroborate these
estimates and reproduce hemispherical magnetic current helicity laws10. The dynamo
resulting from a well-understood near-surface phenomenon improves prospects
for accurate predictions of full magnetic cycles and space weather, affecting the
electromagnetic infrastructure of Earth.
Extensive Pollution of Uranus and Neptune’s Atmospheres by Upsweep of Icy Mat...Sérgio Sacani
In the Nice model of solar system formation, Uranus and Neptune undergo an orbital upheaval,
sweeping through a planetesimal disk. The region of the disk from which material is accreted by
the ice giants during this phase of their evolution has not previously been identified. We perform
direct N-body orbital simulations of the four giant planets to determine the amount and origin of solid
accretion during this orbital upheaval. We find that the ice giants undergo an extreme bombardment
event, with collision rates as much as ∼3 per hour assuming km-sized planetesimals, increasing the
total planet mass by up to ∼0.35%. In all cases, the initially outermost ice giant experiences the
largest total enhancement. We determine that for some plausible planetesimal properties, the resulting
atmospheric enrichment could potentially produce sufficient latent heat to alter the planetary cooling
timescale according to existing models. Our findings suggest that substantial accretion during this
phase of planetary evolution may have been sufficient to impact the atmospheric composition and
thermal evolution of the ice giants, motivating future work on the fate of deposited solid material.
Exomoons & Exorings with the Habitable Worlds Observatory I: On the Detection...Sérgio Sacani
The highest priority recommendation of the Astro2020 Decadal Survey for space-based astronomy
was the construction of an observatory capable of characterizing habitable worlds. In this paper series
we explore the detectability of and interference from exomoons and exorings serendipitously observed
with the proposed Habitable Worlds Observatory (HWO) as it seeks to characterize exoplanets, starting
in this manuscript with Earth-Moon analog mutual events. Unlike transits, which only occur in systems
viewed near edge-on, shadow (i.e., solar eclipse) and lunar eclipse mutual events occur in almost every
star-planet-moon system. The cadence of these events can vary widely from ∼yearly to multiple events
per day, as was the case in our younger Earth-Moon system. Leveraging previous space-based (EPOXI)
lightcurves of a Moon transit and performance predictions from the LUVOIR-B concept, we derive
the detectability of Moon analogs with HWO. We determine that Earth-Moon analogs are detectable
with observation of ∼2-20 mutual events for systems within 10 pc, and larger moons should remain
detectable out to 20 pc. We explore the extent to which exomoon mutual events can mimic planet
features and weather. We find that HWO wavelength coverage in the near-IR, specifically in the 1.4 µm
water band where large moons can outshine their host planet, will aid in differentiating exomoon signals
from exoplanet variability. Finally, we predict that exomoons formed through collision processes akin
to our Moon are more likely to be detected in younger systems, where shorter orbital periods and
favorable geometry enhance the probability and frequency of mutual events.
Emergent ribozyme behaviors in oxychlorine brines indicate a unique niche for...Sérgio Sacani
Mars is a particularly attractive candidate among known astronomical objects
to potentially host life. Results from space exploration missions have provided
insights into Martian geochemistry that indicate oxychlorine species, particularly perchlorate, are ubiquitous features of the Martian geochemical landscape. Perchlorate presents potential obstacles for known forms of life due to
its toxicity. However, it can also provide potential benefits, such as producing
brines by deliquescence, like those thought to exist on present-day Mars. Here
we show perchlorate brines support folding and catalysis of functional RNAs,
while inactivating representative protein enzymes. Additionally, we show
perchlorate and other oxychlorine species enable ribozyme functions,
including homeostasis-like regulatory behavior and ribozyme-catalyzed
chlorination of organic molecules. We suggest nucleic acids are uniquely wellsuited to hypersaline Martian environments. Furthermore, Martian near- or
subsurface oxychlorine brines, and brines found in potential lifeforms, could
provide a unique niche for biomolecular evolution.
Continuum emission from within the plunging region of black hole discsSérgio Sacani
The thermal continuum emission observed from accreting black holes across X-ray bands has the potential to be leveraged as a
powerful probe of the mass and spin of the central black hole. The vast majority of existing ‘continuum fitting’ models neglect
emission sourced at and within the innermost stable circular orbit (ISCO) of the black hole. Numerical simulations, however,
find non-zero emission sourced from these regions. In this work, we extend existing techniques by including the emission
sourced from within the plunging region, utilizing new analytical models that reproduce the properties of numerical accretion
simulations. We show that in general the neglected intra-ISCO emission produces a hot-and-small quasi-blackbody component,
but can also produce a weak power-law tail for more extreme parameter regions. A similar hot-and-small blackbody component
has been added in by hand in an ad hoc manner to previous analyses of X-ray binary spectra. We show that the X-ray spectrum
of MAXI J1820+070 in a soft-state outburst is extremely well described by a full Kerr black hole disc, while conventional
models that neglect intra-ISCO emission are unable to reproduce the data. We believe this represents the first robust detection of
intra-ISCO emission in the literature, and allows additional constraints to be placed on the MAXI J1820 + 070 black hole spin
which must be low a• < 0.5 to allow a detectable intra-ISCO region. Emission from within the ISCO is the dominant emission
component in the MAXI J1820 + 070 spectrum between 6 and 10 keV, highlighting the necessity of including this region. Our
continuum fitting model is made publicly available.
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptxMAGOTI ERNEST
Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024).
Brine shrimp (Artemia spp.) are used in marine aquaculture worldwide. Annually, more than 2,000 metric tons of dry cysts are used for cultivation of fish, crustacean, and shellfish larva. Brine shrimp are important to aquaculture because newly hatched brine shrimp nauplii (larvae) provide a food source for many fish fry (Mozanzadeh et al., 2021). Culture and harvesting of brine shrimp eggs represents another aspect of the aquaculture industry. Nauplii and metanauplii of Artemia, commonly known as brine shrimp, play a crucial role in aquaculture due to their nutritional value and suitability as live feed for many aquatic species, particularly in larval stages (Sorgeloos & Roubach, 2021).
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...AbdullaAlAsif1
The pygmy halfbeak Dermogenys colletei, is known for its viviparous nature, this presents an intriguing case of relatively low fecundity, raising questions about potential compensatory reproductive strategies employed by this species. Our study delves into the examination of fecundity and the Gonadosomatic Index (GSI) in the Pygmy Halfbeak, D. colletei (Meisner, 2001), an intriguing viviparous fish indigenous to Sarawak, Borneo. We hypothesize that the Pygmy halfbeak, D. colletei, may exhibit unique reproductive adaptations to offset its low fecundity, thus enhancing its survival and fitness. To address this, we conducted a comprehensive study utilizing 28 mature female specimens of D. colletei, carefully measuring fecundity and GSI to shed light on the reproductive adaptations of this species. Our findings reveal that D. colletei indeed exhibits low fecundity, with a mean of 16.76 ± 2.01, and a mean GSI of 12.83 ± 1.27, providing crucial insights into the reproductive mechanisms at play in this species. These results underscore the existence of unique reproductive strategies in D. colletei, enabling its adaptation and persistence in Borneo's diverse aquatic ecosystems, and call for further ecological research to elucidate these mechanisms. This study lends to a better understanding of viviparous fish in Borneo and contributes to the broader field of aquatic ecology, enhancing our knowledge of species adaptations to unique ecological challenges.
Or: Beyond linear.
Abstract: Equivariant neural networks are neural networks that incorporate symmetries. The nonlinear activation functions in these networks result in interesting nonlinear equivariant maps between simple representations, and motivate the key player of this talk: piecewise linear representation theory.
Disclaimer: No one is perfect, so please mind that there might be mistakes and typos.
dtubbenhauer@gmail.com
Corrected slides: dtubbenhauer.com/talks.html
Current Ms word generated power point presentation covers major details about the micronuclei test. It's significance and assays to conduct it. It is used to detect the micronuclei formation inside the cells of nearly every multicellular organism. It's formation takes place during chromosomal sepration at metaphase.
A global reference model of the lithosphere and upper mantle from joint inversion and analysis of multiple data sets
1. Geophys. J. Int. (2019) 217, 1602–1628 doi: 10.1093/gji/ggz094
Advance Access publication 2019 March 6
GJI Gravity, geodesy and tides
A global reference model of the lithosphere and upper mantle from
joint inversion and analysis of multiple data sets
Juan Carlos Afonso,1,2
Farshad Salajegheh,1
Wolfgang Szwillus ,3
Jorg Ebbing3
and
Carmen Gaina2
1Australian Research Council Centre of Excellence for Core to Crust Fluid Systems (CCFS), Department of Earth and Planetary Sciences, Macquarie
University, Sydney, Australia. E-mail: Juan.afonso@mq.edu.au
2Centre for Earth Evolution and Dynamics, Department of Geosciences, University of Oslo, Norway
3Department of Geosciences, Kiel University, Kiel, Germany
Accepted 2019 February 19. Received 2018 December 3; in original form 2018 March 8
SUMMARY
We present a new global model for the Earth’s lithosphere and upper mantle (LithoRef18) ob-
tained through a formal joint inversion of 3-D gravity anomalies, geoid height, satellite-derived
gravity gradients and absolute elevation complemented with seismic, thermal and petrological
prior information. The model includes crustal thickness, average crustal density, lithospheric
thickness, depth-dependent density of the lithospheric mantle, lithospheric geotherms, and av-
erage density of the sublithospheric mantle down to 410 km depth with a surface discretization
of 2◦
× 2◦
. Our results for lithospheric thickness and sublithospheric density structure are in
excellent agreement with estimates from recent seismic tomography models. A comparison
with higher resolution regional studies in a number of regions around the world indicates that
our values of crustal thickness and density are an improvement over a number of previous
global crustal models. Given the strong similarity with recent tomography models down to
410 km depth, LithoRef18 can be readily merged with these seismic models to include seis-
mic velocities as part of the reference model. We include several analyses of robustness and
reliability of input data, method and results. We also provide easy-to-use codes to interrogate
the model and use its predictions for the development of higher-resolution models.
Considering the model‘s features and data fitting statistics, LithoRef18 will be useful in
a wide range of geophysical and geochemical applications by serving as a reference or initial
lithospheric model for (i) higher-resolution gravity, seismological and/or integrated geophysi-
cal studies of the lithosphere and upper mantle, (ii) including far-field effects in gravity-based
regional studies, (iii) global circulation/convection models that link the lithosphere with the
deep Earth, (iv) estimating residual, static and dynamic topography, (v) thermal modelling of
sedimentary basins and (vi) studying the links between the lithosphere and the deep Earth,
among others. Several avenues for improving the reliability of LithoRef18’s predictions are
also discussed. Finally, the inversion methodology presented in this work can be applied in
other planets for which potential field data sets are either the only or major constraints to their
internal structures (e.g. Moon, Venus, etc.).
Key words: Composition and structure of the continental crust; Composition and structure
of the mantle; Gravity anomalies and Earth structure; Satellite gravity; Planetary interiors;
Seismic tomography.
1 I N T RO D U C T I O N
Global models of the physical state and properties of the Earth’s interior have improved considerably over the past decade due to the availability
of higher-quality and more comprehensive data sets, the rapid growth in computational and data processing power, new developments in both
theoretical and experimental mineral physics at high pressure and temperature conditions and the arrival of new satellite-derived datasets of
global coverage (e.g. GRACE and GOCE missions). Such models, especially those focused on the lithosphere and upper mantle, have proven
useful in a wide range of geophysical and geodynamic applications. They are needed for stripping off, or accounting for, crustal effects in
seismic tomography studies (the so-called crustal correction; e.g. Waldhauser et al. 2002; Chang & Ferreira 2017), as reference or starting
1602 C The Author(s) 2019. Published by Oxford University Press on behalf of The Royal Astronomical Society.
Downloadedfromhttps://academic.oup.com/gji/article-abstract/217/3/1602/5370085byMacquarieUniversityuseron07May2019
2. A global reference model of the lithosphere 1603
models in regional gravity and/or isostatic studies (e.g. Mechie et al. 2013; Levandowski et al. 2014; Aitken et al. 2015), as input in global
circulation/convection models and dynamic topography studies (e.g. Flament et al. 2013; Becker et al. 2014; Steinberger 2016), as anchor
points in the interpretation of a number of geochemical data (cf. Rudnick & Gao 2003; Hawkesworth et al. 2016) and as input or constraints
in evolutionary models of basins (cf. Wangen 2010), to name a few. In their own right, global models of the Earth’s internal structure and
physical parameters help in addressing fundamental questions about the nature and evolution of continents, the nature of mantle convection,
the coupling between lithospheric plates and sublithospheric mantle and the roles of crust vs mantle in the evolution of topography, among
others.
Despite their obvious importance, global models of the Earth’s interior that honour multiple data types (i.e. seismic, gravity, geoid,
magnetotelluric, etc.) are still rare. This is a significant limitation because data gathering at the required scale is expensive and different
data sets offer crucial complementary information. Moreover, it is well-known that models constrained by single data sets typically fail at
providing satisfactory fits to other observables (e.g. Forte et al. 2007; Afonso et al. 2013b, 2016a). A few whole-mantle global models that
are compatible with more than one data type (not only seismic) are available, albeit at relatively low resolutions (e.g. Ishii & Tromp 1999;
Forte et al. 2009; Simmons et al. 2006, 2010; Cammarano et al. 2011; Wang et al. 2015; Yang & Gurnis 2016; Greff-Lefftz et al. 2016a). Of
particular relevance is the whole-mantle model of Simmons et al. (2010), in which multiple seismic and geodynamic observables are inverted
and linked through empirical mineral-physics parameters. Despite being one of the most advanced approaches to date, lithospheric density
structure was not the focus of that study, as indicated by the modelling assumptions and datasets used.
The recent model LITHO1.0 (Pasyanos et al. 2014), based on Love and Rayleigh wave data (group and phase) is an extension of the
popular crustal model CRUST1.0 (Laske et al. 2013). It is a 1◦
tesselated model containing estimates of crustal velocity, density and thickness,
as well as upper mantle velocity, lithospheric thickness, and mantle density (albeit an unrealistic one). Given its resolution and the fact that it
is based on surface wave data and an a priori crustal model calibrated with gravity and seismic data, LITHO1.0 is an attractive candidate as
a reference model for the shallow structure of the Earth. However, its density structure and boundaries’ geometry have not been optimized to
satisfy potential field data and the proxy used to estimate lithospheric thickness (strictly, the thickness of a constant-velocity seismic lid) is
likely to result in under and overestimation of the lithosphere-asthenosphere boundary (LAB) beneath thin and thick continental lithosphere,
respectively. Conversely, a number of global density models for the crust and upper mantle have been obtained from modelling or inversion of
either gravity, geoid, gravity gradients or some combination of them (e.g. Kaban et al. 2004; Reguzzoni et al. 2013; Reguzzoni & Sampietro
2015; Sampietro 2016; Sj¨oberg & Bagherbandi 2011), with limited or no formal input from seismic studies (note that regional models that
combine both seismic and gravity data are more common, e.g. Maceira & Ammon 2009; O’Donnell et al. 2011; Shan et al. 2014; Afonso
et al. 2016c; Tondi et al. 2017). However, most of these ‘gravity-based’ models are crustal models only. There is therefore an ambiguity
regarding which model is more suitable as a global reference for lithospheric/upper mantle studies in the context of integrated studies or joint
inversions making use of multiple data sets (e.g. Zeyen et al. 1997; Tiberi et al. 2008; Moorkamp et al. 2011; O’Donnell et al. 2011; Fullea
et al. 2015; Shan et al. 2014; Afonso et al. 2016c; Tork Qashqai et al. 2016; Tondi et al. 2017; Syracuse et al. 2017, among many others).
In this paper, we present a global model of the lithosphere and sublithospheric upper mantle obtained via an iterative nonlinear joint
inversion scheme of gravity anomalies, geoid height, satellite-derived gravity gradients and absolute elevation. These datasets were chosen
due to their different and complementary depth sensitivities to density anomalies. First-order seismic, petrological and geothermal prior
information is also included in the inversion. The model and inversion are developed in spherical coordinates with a lateral discretization of
2◦
× 2◦
. A massively-parallel implementation of the inversion algorithm was necessary given the size of the system of equations and the large
number of model parameters resulting from the model discretization. Relevant (prior) seismic information is included by adopting CRUST1.0
(Laske et al. 2013) and a LAB model based on six recent seismic tomography models (cf. Pasyanos et al. 2014; Steinberger 2007) as prior
models, which are modified only slightly during the inversion as required by the data.
We have prepared user-friendly codes to extract information from the model, including the computations of contributions from the
entire model (or parts of it) to gravity, geoid and gravity gradients at any point on or above the surface of the planet; this is particularly
useful when dealing with the so-called far-field/edge/boundary effects in gravity-related studies. The model contains average crustal density,
crustal thickness, lithospheric thickness, depth-dependent density of the lithospheric mantle, lithospheric geotherms, and average density of
the sublithospheric mantle down to 410 km depth. These outputs are expanded by including seismic velocities from a compatible tomography
model (SL2013sv; Schaeffer & Lebedev 2013). Given its characteristics, we expect that this model will be useful to the broader community
by serving as a reference/initial model for (i) higher-resolution gravity, seismological, geodetic and/or integrated geophysical studies of the
lithosphere and upper mantle, (ii) including far-field effects in regional gravity/geoid studies, (iii) regional and global geodynamic simulations
where lithospheric thickness and structure plays a non-negligible role, (iv) assessing isostatic compensation mechanism and estimates of
residual, isostatic and dynamic topography, (v) stripping off the lithospheric signal in global and regional estimates of the deep structure of
the Earth and (vi) estimating boundary conditions for thermal modelling of sedimentary basins, among others.
In what follows, we begin by discussing the input data sets (Section 2), the solution to the forward problems (Section 3), the treatment of
temperature-, pressure- and composition-dependent parameters (Section4) and the discretization of the model (Section 5). We continue with
the description of the general inversion strategy (Section 6) and present results from illustrative synthetic tests. The final model and main
results are presented in Section 8. Finally, we discuss some relevant features of the model and possible future improvements in Section 9.
Appendices A and B provide additional information on the parallel implementation of the inversion scheme and on the global resolution
matrix, respectively.
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3. 1604 J.C. Afonso et al.
2 I N P U T DATA S E T S A N D I N I T I A L M O D E L
Elevation data were taken from the 1 × 1 arcmin global model ETOPO1, which combines land topography and ocean bathymetry (Amante &
Eakins 2009); the model is available at https://www.ngdc.noaa.gov/mgg/global/. Free-air gravity anomalies were taken from the global gravity
model WGM2012 (Balmino et al. 2012,http://bgi.omp.obs-mip.fr). Gravity gradients are provided by the satellite mission GOCE (Pail et al.
2017). In particular, we used the satellite-only global Earth model GOCO03S (http://www.goco.eu/) and computed the full Marussi tensor up
to degree and order 250 at satellite height using a spherical harmonics synthesis code (Fullea et al. 2015). Geoid heights are taken from the
global model EGM2008 (Pavlis et al. 2012); note that model WGM2012 is in principle compatible with both ETOPO1 and EGM2008.
Since the focus of this study is the upper ∼410 km of the Earth, we need to filter the total geoid by removing low orders and degrees (i.e.
long wavelengths), which are thought to be largely controlled by deep density anomalies. To this end, we used the tapering approach of Marks
et al. (1991) to minimize Gibbs oscillations in the residual (filtered) geoid. Based on previous studies (e.g. Hager 1984; Doin et al. 1996;
Featherstone 1997; Chase 1985; Bowin 1983, 2000; Chase et al. 2002; Golle et al. 2012) and numerous tests (see Supporting Information),
we chose to roll off spherical harmonic coefficients between degrees 8 and 12 using a cosine tapering function. To keep consistency between
data sets, the same filtering approach was applied to gravity and gravity gradients data. Further details on the effects of the geoid filtering on
the final results are given in Section 7.2 and in Supporting Information.
An important set of ‘input data’ are those used to construct the initial/starting model and priors for the crust and lithosphere. The
initial model for crustal thickness and density is based on the well-known global model CRUST1.0 (Laske et al. 2013), whereas the initial
lithospheric thickness is obtained from a hybrid model based on six recent global tomography models: LITHO1.0 (Pasyanos et al. 2014),
SAVANI (Auer et al. 2014), SL2013sv (Schaeffer & Lebedev 2013), GYPSUM (Simmons et al. 2010), S40RTS (Ritsema et al. 2011) and
SEMUM2 (French & Romanowicz 2014). Five of these models have been recently reviewed by Steinberger & Becker (2016), who proposed
a procedure to derive consistent estimates of (thermal) lithospheric thickness from these models. Since the predicted LAB from all these
models are comparable and highly correlated, we opted for a compromise hybrid LAB model that is a weighted average of all six tomography
models. Considering the actual features of these models (e.g. type of data, depth range of interest, resolution, etc.), we assign the largest
weights to LITHO1.0 and SL2013sv. The actual starting LAB model so obtained is introduced in Section 8.2 and shown in Fig. 8 A.
In the oceans, we choose not to use the original LAB depths provided by the above models as some of them contain a number of dubious
regions with unrealistically high values. Instead, our initial LAB model is based on a plate cooling model (Grose & Afonso 2013), which has
been constrained by bathymetric, surface heat flow, petrological and mineral physics data. To use this model, the age of the oceanic crust is
needed, which we take from M¨uller et al. (2008).
Given the lack of well-constrained density models for the sublithospheric upper mantle, we choose to start with a constant density in
this part of the model and let the inversion to modify it according to the data fit statistics. Based on results from preliminary inversions and
synthetic tests, we select ρa = 3450 kg m−3
for the initial sublithospheric density; this value is very close to the horizontally averaged value
of the preliminary inversions and results in good convergence performance during the inversion, good data fit statistics and realistic density
values (Section 8).
3 F O RWA R D P RO B L E M S
3.1 Gravity, geoid and gravity gradients
For most geophysical purposes, the spherical approximation to computing gravity signals (as opposed e.g. to the elliptical approximation)
yields results of sufficient accuracy (e.g. Novak & Grafarend 2005; Asgharzadeh et al. 2007). Considering geographical coordinates, the
so-called spherical tesseroid represents a natural mass element for subdividing a spherical Earth (cf. Anderson 1976; Gr¨uninger 1990; Heck &
Seitz 2007). A spherical tesseroid is a body bounded by two concentric spheres of radii r1 and r2, two meridional planes defined by longitudes
λ1 and λ2, and two parallels (or coaxial cones) with latitudes ϕ1 and ϕ2 (See Fig. 1 A)
The gravitational potential V at observation point O(ro
, ϕo
, λo
) produced by a spherical tesseroid with constant density ρ is given by
Netwon’s integral in spherical coordinates (cf. Heck & Seitz 2007)
V (r, ϕ, λ) = Gρ
λ2
λ1
ϕ2
ϕ1
r2
r1
(r p
)2
cos ϕp
dr p
dϕp
dλp
, (1)
where
(P, O) = (ro)2 + (r p)2 − 2ror p cos (2)
is the Euclidean distance between the computation point O(ro
, ϕo
, λo
) and the integration point P(rp
, ϕp
, λp
); is the angle between the
position vectors of O and P (Figs 1 A and B), given by
cos = sin ϕo
sin ϕp
+ cos ϕo
cos ϕp
cos (λo
− λp
) . (3)
Eq. (1) is an elliptic-type integral and has no closed-form analytical solution. A number of numerical methods in the spatial domain are
available to approximate eq. (1). Among these, those based on Taylor series expansions and/or Gauss–Legendre quadrature rules are the most
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4. A global reference model of the lithosphere 1605
(a) (b)
(c) (d)
Figure 1. (a) Geometry of a spherical tesseroid showing global (X, Y, Z) and local (xp, yp, zp; xo, yo, zo) coordinate systems. (b) Prism approximation of a
tesseroid. (c–d) 2-D view of a right rectangular prism approximating a tesseroid. The geometric relationship between vectors ep
, eg
, go
and gg
are shown.
popular (e.g. Heck & Seitz 2007; Grombein et al. 2013; Wild-Pfeiffer 2008; Asgharzadeh et al. 2007). Despite generally yielding the most
efficient solutions (especially at planetary scale), spectral or frequency-domain methods based on spherical harmonic expansions seem to be
less common due to the cumbersome formulation for representing highly variable and/or discontinuous density distributions and the need to
account for additional technical considerations (e.g. spectral coherency, global mass distributions, resolution-dependent convergence issues,
etc.; Kuhn & Featherstone 2005; Kuhn & Seitz 2005; Balmino et al. 2012; Hirt & Kuhn 2014).
Spatial methods that solve eq. (1) directly (by e.g. quadrature rules or Taylor expansions) provide efficient and accurate results at relatively
high elevations above the tesseroid, making them the preferred options when modelling satellite data. However, they are not well-suited for
computing the potential (and its derivatives) near, at, or below the surface of the tesseroid. This creates a problem when the surface of the
planet is discretized with tesseroids and terrain corrections or gravity values from land surveys need to be modelled (Grombein et al. 2013).
3.1.1 The prism approximation
A popular alternative to solving eq. (1) directly is to approximate the tesseroids with rectangular prisms having the same mass and height as the
tesseroids (e.g. Anderson 1976; Gr¨uninger 1990; Kuhn 2000; Heck & Seitz 2007; Wild-Pfeiffer 2008). This is advantageous not only because
analytical solutions for flat-topped rectangular prisms are available, but also because it is possible to obtain solutions at or near the top of the
prism or even inside it (by appropriate splitting). The validity and accuracy of this approximation rely on three conditions: (1) that the surface
area of the tesseroids are sufficiently small so a flat-topped prism offers an acceptable approximation, (2) that we have prisms/tesseroids that
are not too long along their vertical dimension and (3) that both mass elements have the same mass. If the first condition is not guaranteed, a
flat-topped prism will not be a good approximation of the tesseroid (i.e. the curvature of the tesseroid’s surface plays a significant role). If the
second condition is not met, the shape of the prism will depart from that of tesseroid which is trying to approximate (Fig. 1C). Consequently,
even when the third condition is met (see below), the results of the prism approximation will depart from the correct one. In practice, the
surface area of the tesseroids depend on the actual application, but a number of tests (see Supporting Information) indicate that even in the
unfavourable case of a tesseroid with dimensions 2◦
× 2◦
× 100 km depth, the maximum errors for geoid, gravity and gravity gradients
produced with the prism approximation are 0.6, 0.5 and 1.3 per cent, respectively, for observations points within 500 km from the tesseroid.
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5. 1606 J.C. Afonso et al.
Throughout this work, we adopt the prism approximation. We acknowledge that for global studies, spectral methods would offer a more
efficient solution. However, we are interested in a formulation general enough to allow us to model a large range of scales (local, regional,
global), highly variable density distributions, with no singularities at the surface or within the mass bodies, and importantly, that allows to
obtain fast solutions of small density perturbations (e.g. by changing the density of one prism inside the model). These requirements are
readily met by the prism approximation and are critical for forthcoming studies based on joint probabilistic inversions (e.g. Afonso et al.
2013b,a, 2016a,c).
There are two main ingredients in the prism approximation. First, a complete set of analytical solutions for a rectangular prism is
needed to compute the potential of each prism in Cartesian coordinates. Secondly, a set of coordinate transformations is required to compute
the correct vector components in spherical coordinates (account for the convergence of the plumb line). The formulae associated with the
computation of the gravity potential and its derivatives for a rectangular prism are well-known and described in detail elsewhere (cf. Mader
1951; Nagy et al. 2000; Gallardo-Delgado et al. 2003; Fullea et al. 2009, 2015); therefore, we do not repeat them here. In the following, we
describe the process of coordinate transformation and conservation of mass between the mass elements.
The formulae for gravity, geoid and gravity gradients, for instance those in Nagy et al. (2000), Fullea et al. (2009, 2015), assume that
the observation point is at the origin of a Cartesian coordinate system and the edges of the causative prism are parallel to the coordinate
axes. Therefore, referring to Figs 1(B) and (C), we must convert the vector eg
from the global Cartesian coordinates associated with the
terrestrial equatorial reference frame (X, Y, Z) to the local coordinates of the prism e (xp
, yp
, zp
). We first obtain eg
from its spherical coordinate
components
eg
=
⎡
⎢
⎣
ro
cos φo
cos λo
ro
cos φo
sin λo
ro
sin φo
⎤
⎥
⎦ −
⎡
⎢
⎣
r p
cos φp
cos λp
r p
cos φp
sin λp
r p
sin φp
⎤
⎥
⎦ . (4)
Now we can transform eg
into the local coordinates of the prism ep
by applying two rotations and a reflection operation
ep
= Py . Ry(90◦
− φp
) . Rz(180◦
− λp
) . eg
, (5)
where Ry and Rz are the Euler rotation matrices around the y- and z-axes, respectively, and Py is a reflection matrix needed to correct for the
different polarity of the local and global reference frames. The explicit forms of these matrices are (cf. Gr¨uninger 1990; Torge 2001)
Py =
⎡
⎢
⎣
1 0 0
0 −1 0
0 0 1
⎤
⎥
⎦ (6)
Ry (90◦
− φp
) =
⎡
⎢
⎣
cos (90◦
− φp
) 0 sin (90◦
− φp
)
0 1 0
− sin (90◦
− φp
) 0 cos (90◦
− φp
)
⎤
⎥
⎦ (7)
Rz (180◦
− λp
) =
⎡
⎢
⎣
cos (180◦
− λp
) − sin (180◦
− λp
) 0
sin (180◦
− λp
) cos (180◦
− λp
) 0
0 0 1
⎤
⎥
⎦ . (8)
Therefore, eq. (5) can be rewritten as
ep
= W × eg
, (9)
where
W =
⎡
⎢
⎣
cos (90◦
− φp
) cos (180◦
− λp
) − cos (90◦
− φp
) sin (180◦
− λp
) sin (90◦
− φp
)
− sin (180◦
− λp
) − cos (180◦
− λp
) 0
− sin (90◦
− φp
) cos (180◦
− λp
) sin (90◦
− φp
) sin (180◦
− λp
) cos (90◦
− φp
)
⎤
⎥
⎦ . (10)
Vector ep
can now be used in the formula of Nagy et al. (2000) to obtain the gravitational potential and its first and second derivatives.
The gravity vector gp
and Marussi tensor Mp
obtained as described above are referred to the local coordinates of the prism (parallel to
its edges). However, we need their components in the local coordinates of the observation point O(ro
, ϕo
, λo
) to be able to compute the correct
vertical (aligned with the plumb line) and horizontal (along meridians and parallels) components in the global spherical reference frame. To
obtain vector gp
in the coordinate system of the observation point (go
), the following transformation is applied (Heck & Seitz 2007)
go
= T × gp
, (11)
where
T =
⎡
⎢
⎣
cos ω sin φo
sin φp
+ cos φo
cos φp
sin ω sin φo
− cos ω sin φo
cos φp
+ cos φo
sin φp
− sin ω sin φp
cos ω sin ω cos φp
− cos ω cos φo
sin φp
+ sin φo
cos φp
− sin ω cos φo
cos ω cos φo
cos φp
+ sin φo
sin φp
⎤
⎥
⎦ . (12)
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6. A global reference model of the lithosphere 1607
ω = (λp
− λo
)
Similarly, the transformation of Mp
into M
o
(referred to the local coordinates of the observation point) can be achieved by
Mo
= T × Mp
× TT
. (13)
When replacing the tesseroid by a prism, the best results are obtained when both elements have the same mass (condition 3 above) and
the same height (Gr¨uninger 1990). Therefore, the dimensions and density of the postulated prism are given by (refer to Fig. 1)
x =
r1 + r2
2
ϕ,
y =
r1 + r2
2
cos(
ϕ1 + ϕ2
2
) λ
z = r
ρp =
Vt
Vp
ρt , (14)
where Vt is the volume of the tesseroid and Vp is the volume of the prism.
Figs S6 and S7 show results from benchmarks that validate our numerical approach.
3.2 Isostatic elevation
According to the (most popular) principle of isostasy, all regions of the Earth with identical elevation have the same buoyancy when referenced
to a same compensation level. This principle is rooted in hydrostatics, and therefore purely dynamic contributions (i.e. vertical stresses due
to velocity gradients) arising from upper mantle convection are not considered. Following previous studies (e.g. Afonso et al. 2008), here we
select the bottom of the model (i.e. Zcomp = 410 km) as the global compensation level. Since the formulae to compute isostatic elevations has
been presented in detail elsewhere (Lachenbruch & Morgan 1990; Afonso et al. 2008; 2013a Fullea et al. 2009), here we only summarize the
most relevant concepts for our purposes.
The elevation above (Ea) and below (Eb) sea level are given, respectively, by
Ea =
ρb − ρL
ρb
.L − L0 (15)
Eb =
ρb − ρL
ρb
.L − L0 .
ρb
ρb − ρw
, (16)
where L is the thickness of the column, ρb is the density of the mantle at and below the compensation depth, ρL is the depth-average density
of the column, ρw is the density of seawater (=1030 kg m−3
) and L0 is a global calibration constant.
In order to obtain L0, the average density and elevation of a reference column are required. The general practise is to choose the reference
column at a mid-ocean ridge (MOR), where these two parameters can be estimated with relatively good accuracy (e.g. Lachenbruch & Morgan
1990; Afonso et al. 2008; Fullea et al. 2009; Afonso et al. 2013b). Referring to Fig. 2, the depth-average density of the MOR column is
ρridge =
(ρc × D) + (ρlm × L) + (ρa × A)
Zcomp
, (17)
where D, L and A are thickness of the crust, the lithospheric mantle and asthenosphere of the MOR column, respectively. During the inversion,
we apply a penalty term to guarantee that not only local elevation but also the global average elevation (mean solid Earth’s radius) is fitted.
From eqs (16), (17) and Fig. 2, the calibration constant can be expressed as
L0 = Zmax −
(ρridge × Zcomp) + (Eridge × ρw)
ρb
. (18)
For this work, we selected as the reference column a region located at long = 95◦
W and lat = 3.0◦
N on the Galapagos ridge. The average
elevation, crustal thickness, crustal density and mantle density (all obtained from preliminary high-resolution inversions) at this location are
all ‘standard’ MOR values of ∼−2800 m, 7 km, 2871 kg m−3
and 3409 kg m−3
, respectively. Note that although the selection of the reference
column is arbitrary in the context of local isostatic balance (any column where we can estimate average density and elevation with confidence
would be acceptable), we chose our column in a region where most studies on large-scale global dynamic topography (e.g. Flament et al.
2013) predict relatively small dynamic contributions.
4 T E M P E R AT U R E , P R E S S U R E A N D C O M P O S I T I O NA L E F F E C T S O N D E N S I T Y
The average densities of the crust and sublithospheric mantle are assumed constant (but unknown) at each individual tesseroidal prism making
up our global model. In the lithospheric mantle, however, density is assumed to be a function of pressure and temperature (and therefore of
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7. 1608 J.C. Afonso et al.
Figure 2. Reference column used in isostatic calculations. See text for details.
lithospheric thickness) according to
ρPT = ρ0[1 − α(T − T0) + β(P − P0)], (19)
where ρ0 is the reference density at surface P-T conditions (i.e. T0, P0), α is the coefficient of thermal expansion and β the compressibility.
Therefore, the average density of the lithospheric mantle at any specific location is
¯ρm =
1
(zL AB − zM )
zL AB
zM
ρPT dz, (20)
where zM and zLAB are the depths to the Moho and LAB, respectively. If we assume no radioactive heat production in the mantle (a standard
first-order assumption in lithospheric modelling), the temperature profile in the mantle part of the lithosphere is linear and the process of
obtaining the average density of the lithospheric mantle reduces to solving eq. (19) with T = ¯Tlm and P = ¯Plm (i.e. the average temperature
and pressure within the lithospheric mantle). In the following sections we explain how we obtain these average values (and how we implement
compositional corrections to density in cratonic regions.
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8. A global reference model of the lithosphere 1609
Table 1. Parameters used in the calculation of lithospheric geotherms.
Symbol Name Value
α ◦C−1) Thermal expansion coef. 3.4 × 10−5
β (Pa−1) Compressibility coef. 1.1 × 10−6
Kuc (W m−1 K
−1
) Upper crust thermal conductivity 2.5
Klc (W m−1 K
−1
) Lower crust thermal conductivity 2.2
Km (W m−1 K
−1
) Mantle thermal conductivity 3.3
Auc (μW m−3) Upper crust radioactive heat production 1.8
Alc (μW m−3) Lower crust radioactive heat production 0.2
Am (μW m−3) Mantle radioactive heat production 0
4.1 Geotherms and average lithospheric temperatures
If the geotherm is linear within the lithospheric mantle (i.e. steady-state with no heat sources), the average lithospheric mantle temperature
¯Tlm is simply
¯Tlm =
Tmh + TL AB
2
, (21)
where TLAB is the temperature at the LAB and Tmh is the temperature at the Moho. The choice of defining the base of the lithosphere as
an isotherm is common practice and related to the fact that the lithosphere is a thermal boundary layer and its mechanical properties are
mainly controlled by temperature (cf. Burov 2011; Afonso et al. 2016a). Most commonly used values are typically centred around 1300 ◦
C, in
agreement with numerous petrological, geophysical and geodynamic lines of evidence (e.g. Zlotnik et al. 2008; Afonso et al. 2008; Ballmer
et al. 2011; Burov 2011; Mckenzie et al. 2005; McKenzie & Bickle 1988; O’Reilly & Griffin 2010; Shan et al. 2014, Afonso et al. 2016a,b;
Green & Falloon 2015; among many others). We therefore assume TLAB = 1300 ◦
C in this study.
For continental crust, we obtain Tmh by solving the 1-D steady-state heat conduction equation with prescribed radiogenic heat productions
and thermal conductivities for the crustal component. In doing so, and to better represent the actual curved crustal geotherm, we subdivide
the crust into two layers (upper and lower crust) of equal thickness but possibly different radioactive heat production terms and thermal
conductivities. Therefore, we write the final solution for Tmh as (e.g. Chapman 1986)
Tmh = Ts +
Qs D
2
1
Kuc
+
1
Klc
−
Auc
Kuc
+
2Auc + Alc
Klc
D2
8
, (22)
where Qs is surface heat flow, D is total crustal thickness, Ts (=10 ◦
C) is surface temperature, K is thermal conductivity and A is radioactive
heat production. Subscripts uc and lc refer to upper and lower crust, respectively, and adopted values are listed in Table 1.
In order to solve eq. (22) for any lithospheric thickness, we need the corresponding Qs in continents. The latter can be obtained or
approximated in a number of ways (e.g. from a database of observations, from a thermal model, etc). Here we prefer to estimate Qs from the
solution to the 1D steady-state heat conduction equation of a three-layer lithosphere rather than using global databases, which are extremely
sparse and would require treating thermal parameters in the crust (e.g. Auc, Alc) as additional free parameters of the model. We note, however,
that our predicted Qs values are comparable to those in many global databases (Fig. S4), so our final model can also be considered to the first
order compatible with most compilations and estimates of global surface heat flow data (e.g. Shapiro & Ritzwoller 2004; Davies & Davies
2010; Goutorbe et al. 2011).
The solution to the steady-state conduction equation for a three-layer (upper crust, lower crust, lithospheric mantle) lithosphere can be
written as (e.g. Afonso & Ranalli 2004)
Qs =
TL AB − Ts + Auc
Kuc
+ 2Auc+Alc
Klc
D2
8
+
Auc + Alc
2Km
D.L
D
2
1
Kuc
+ 1
Klc
+
L
Km
, (23)
where L is the thickness of the lithospheric mantle and Km its thermal conductivity. In deriving eq. (23), we assumed Am = 0 and made use of
the relation
Qm = Qs −
Au + Al
2
.D. (24)
In the oceanic domain, we compute the lithospheric thermal structure and corresponding Tmh following the plate model of Grose & Afonso
(2013) with crustal age from M¨uller et al. (2008).
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9. 1610 J.C. Afonso et al.
4.2 Pressure
At each iteration of our algorithm, the average pressure within the lithospheric mantle ¯Plm is obtained from the lithostatic formula
¯Plm = ρc.D + ρ0.
L
2
.g. (25)
Given the goals of our study, we choose not to implement an additional iterative scheme for the pressure-density coupling (e.g. Afonso et al.
2008), but instead we update the values of ρc, D and L at each iteration of the algorithm with those obtained at the previous iteration (see
Section 6). This simplification affects our results to the second order only. Eq. (25) also ignores dynamic pressure gradients arising from
sublithospheric convection (not modelled here), in agreement with our local isostasy assumption (Section 3.2). This means that dynamic
contributions to topography will be ‘lumped’ into the density anomalies of the model and therefore they should represent upper bounds. This
needs to be taken into consideration when interpreting the inversion’s results (see Section 8.1). However, the actual effect on average mantle
density values is expected to be small given the fact that elevation changes of the order of 500–600 m can be compensated by only minor
changes in Moho depth and/or average mantle density (i.e. a small change in the average density of a mantle column has a major effect on the
predicted topography; Lachenbruch & Morgan 1990; Hasterok & Chapman 2007; Molnar et al. 2015; Afonso et al. 2016b).
4.3 Compositional correction in cratonic regions
It is generally accepted that the lithospheric mantle beneath cratonic regions is more depleted in heavy elements (e.g. CaO, Al2O3 and FeO)
than the average lithospheric mantle (cf. Griffin et al. 2003, 2009; Lee et al. 2011), particularly at the shallowest levels of the lithospheric keels.
This idea is not only supported by what it is directly observed in mantle samples (Griffin et al. 2009) but also by geophysical and geodynamic
arguments (e.g. Jordan 1988; Forte & Perry 2000; Carlson et al. 2005; Afonso et al. 2008; Cammarano et al. 2011; Khan et al. 2011; Wang
et al. 2015). Based on these studies, we subdivide the lithospheric mantle beneath cratonic keels into two layers. The top layer is given a
maximum depth of 175 km and is assumed to be significantly depleted with respect to the average mantle. The second layer is assumed to be
more fertile (still slightly more depleted than sublithospheric mantle) and extends from the bottom of the top layer to the LAB. In practice,
these assumptions are implemented via the ρ0 term (reference density at surface conditions) in eq. (19), as this term is affected the most by
compositional changes (the effects on thermal expansion and compressibility are much smaller). Following the study of Lee (2003), we choose
ρ0 = 3325 kg m−2
for the top layer (‘dunitic/harzburgitic’ rocks), ρ0 = 3355 kg m−2
for the bottom cratonic layer and ρ0 = 3360 kg m−2
for
all other mantle domains. The lateral extension of cratonic domains in our model correspond that of early Proterozoic/Archean age crust in
the model CRUST1.0 (Laske et al. 2013).
5 M O D E L D I S C R E T I Z AT I O N A N D M A I N F R E E PA R A M E T E R S
The lateral discretization of our model corresponds to a 2◦
× 2◦
regular grid (see Fig. 3). Due to the convergence of meridians at the poles, the
original 2◦
× 2◦
tesseroids become too irregular at latitudes >80◦
to be accurately represented by a rectangular prism. We therefore subdivide
these tesseroids along latitude to guarantee an accurate solution; results from the inversion, however, are reported for the original 2◦
× 2◦
grid. We acknowledge that more efficient meshing/discretization approaches are possible (e.g. equal-area grid) and we are currently exploring
these possibilities.
Along the vertical direction, each tesseroidal column extends down to 410 km and is subdivided into four segments of variable thickness:
sea water (if present), crust, lithospheric mantle and sublithospheric upper mantle. Each of these segments are in turn subdivided into a variable
number of smaller tesseroidal volumes (depending on the thickness of the segment) to guarantee that the prism approximation remains valid
for the entire column.
According to the above discretization, our main model parameters are (i) crustal thickness, (ii) depth to the LAB, (iii) average density of
the crust and (iv) average density of the sublithospheric upper mantle (from the LAB down to 410 km depth) for every column in our model
(see Fig. 4). Note that the complete temperature and density structures of the entire lithosphere are by-products of the inversion and thus
considered outputs of the model (see e.g. Fig. S5).
6 I N V E R S I O N S T R AT E G Y
6.1 General problem formulation
The general formulation followed here is similar to that described in Motavalli-Anbaran et al. (2013). All input data are projected onto the
regular 2◦
× 2◦
grid. Therefore, the combined data vector has the following form and dimension
dobs = [Hi , gi , gxx
i
, gyy
i
, gzz
i
, Ni ]T
i = 1, 16200
= [d1
, ..., dN ]T
N = 1, 97200 (26)
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10. A global reference model of the lithosphere 1611
Figure 3. Horizontal discretization as a 2◦ × 2◦ fixed grid. The red points are the surface centroids of the tesseroids and indicate observation/calculation
points.
where H, g and N are the vectors containing elevation, free-air gravity anomalies and geoid heights, respectively; gxx
, gyy
and gzz
are the data vectors containing the diagonal terms of the gravity gradient tensor.
The model parameters are stored in the following combined vector
m = [ρc
j , ρa
j
, Zc
j
, Zl
j
]T
j = 1, 16200
= [m1
, ..., mM ]T
M = 1, 64800, (27)
where ρc
, ρa
, Zc
and Zl
are vectors containing the values of crustal density, sublithospheric mantle average density, crustal thickness and LAB
depth.
The basic requirement of all inverse problems is that there is a function g(m) that maps a vector of model parameters m into a data space
d. This mapping is known as the forward problem and is denoted by
dpred
= g(m), (28)
where dpred
is the predicted data vector. When g(m) is a nonlinear function, as in our case, a typical approach is to locally linearize the
problem in the vicinity of trial solutions m and solve local linear problems in an iterative manner until a predefined ‘global error’ is optimally
minimized (Tarantola 2005; Menke 2012). By global error we mean certain function that quantifies the distance between the vectors of
observed data dobs
(eq. 26) and predicted data dpred
(eq. 28). This function is commonly referred to as the misfit function, the objective
function, or simply the error function. Assuming Gaussian statistics for the errors (a standard, yet no always justified, assumption) and the
availability of a reference or a priori vector of model parameters mo, we can define the misfit function as
2 Φ(m) = [g(m) − dobs
]T
C−1
D [g(m) − dobs
] + [m − m0]T
C−1
M [m − m0], (29)
where CD is the data covariance matrix and CM is the model covariance matrix. Note that we do not include a damping factor in the second
term of the right-hand side, and therefore prior information on the model is combined with data constraints in a way more akin to a Bayesian
approach (cf. Tarantola 2005; Rawlinson et al. 2014). In this sense, including CM in eq. (29) not only allows us to make use of additional
constraints independent from the observations (e.g. prior estimates of LAB depths) but also stabilizes the solution of the (ill-posed) inverse
problem by acting as a regularization term. Both CD and CM are assumed here to be diagonal. In practice, while we may have a good idea
of the diagonal terms in CM, we rarely know the general structure of CD. At the same time, its elements are usually smaller than the errors
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11. 1612 J.C. Afonso et al.
Figure 4. Schematic of the vertical discretization and main parameteres. Encircled variables (i.e. Moho, LAB, ρa and ρc) are the main free parameters inverted
for (i.e. elements of vector m). The lithospheric geotherm and ρlm are by-products of the inversion and thus outputs of the model.
Table 2. Initial standard deviations used in the covariance matrices CD and CM.
Observations g N H gxx gyy gzz
σd (Data standard
deviation)
5 (mGal) 0.5 (m) 200 (m) 0.08 (E) 0.08 (E) 0.08 (E)
Model parameters ρc ρa Zc Zl
σp (Parameter
standard deviation)
5 (kg m−3
) 5 (kg m−3
) 500 (m) 1000 (m)
associated with the forward problem. Therefore, CD is mainly used to define the relative contribution of each data set to the global misfit
function (i.e. as a weighting matrix; Menke 2012). For instance, in this study, our main interest is to obtain models that fit well geoid heights,
free-air anomalies and gravity gradients while being simultaneously consistent with, but not strictly controlled by, topography data (since the
assumption of local isostatic equilibrium may not be a good approximation everywhere). Therefore, the elements of CD corresponding to
elevation data will have a smaller relative weight than those corresponding to the other datasets. With this in mind, we performed numerous
tests to obtain the appropriate elements of CD for each data set that would result in a (relative) satisfactory fit of all observables (see Table 2).
6.2 Inversion algorithm
A typical approach for linearizing Φ(m) is based on a Taylor series expansion about the vector of known initial parameter mk
Φ(mk + m) Φ(mk) + γ T
k m +
1
2
mT
Hk m + ..., (30)
where the matrices Hk and γ k contain the second-order (Hessian matrix) and first-order partial derivatives of the misfit function at mk,
respectively. The problem is thus to find m that makes the global error smaller in a L2-norm sense by updating the parameter vector from
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12. A global reference model of the lithosphere 1613
mk to the stationary point
mk+1 = mk + m. (31)
The solution to the inverse problem is obtained by setting the gradient of eq. (30) with respect to m to zero, which gives the following
(quasi-Newton) iterative scheme (Tarantola 2005)
mk+1 − mk = GT
k C−1
D Gk + C−1
M
−1
GT
C−1
D (dobs
− g(mk)) + C−1
M (mk − m0) , (32)
where k denotes the iteration number and Gk is the Jacobian matrix containing the partial derivatives of g(.) with respect to m ([
∂di
∂m j
]k). In
deriving eq. (32) we have made use of the following standard approximation of the Hessian (Tarantola 2005)
Hk ∼ GT
k C−1
D Gk + C−1
M . (33)
The entries of the Jacobian matrix Gk corresponding to the densities in the crust and sublithospheric mantle are linear and thus readily
calculated as the effect of body j at point i divided by the actual density of the body. In contrast, the elements associated with crustal thickness
and LAB depth are non-linear and therefore calculated numerically with a finite difference scheme.
After the first iteration, in which eq. (32) is solved with m0 from the initial model, we update the values in m0 with those obtained at the
previous iteration. In this way m is not necessarily forced to remain close to the initial model (unless dictated by the prior) and the last term
in eq. (32) vanishes. For iterations other than the first one, eq. (32) can therefore be rewritten as
mk+1 − mk = K × (dobs
− g(mk)), (34)
where K is the kernel matrix defined as
K = GT
k C−1
D Gk + C−1
M
−1
GT
C−1
D . (35)
The general parallelized procedure used to solve eqs (32)–(35) is summarized in Fig. 5 and described in Appendix A.
7 S Y N T H E T I C T E S T S A N D S E N S I T I V I T Y A NA LY S I S
7.1 Global synthetic tests
The synthetic model used here is a full 3-D, 1◦
× 1◦
spherical model of the Earth with an uneven distribution of parameters (i.e. crustal density,
crustal thickness, LAB depth, asthenospheric density; Table 3) with sharp boundaries and varying amplitudes (Fig. 6, first column). The
initial topography/bathymetry is isostatically compensated everywhere as follows: 90 per cent by the crust and 10 per cent by the lithospheric
mantle. To obtain the synthetic data we solved all forward problems and added uncorrelated random Gaussian noise with zero mean and
standard deviation of 10 per cent. Free-air and geoid anomalies are computed/provided at the Earth’s surface, whereas gravity gradients are
computed at 250 km above the Earth’s surface (average orbit height of GOCE satellite). After these synthetic data sets are computed, we
interpolate them to the 2◦
× 2◦
grid used in the inversion. The standard deviations associated with the synthetic data σd
(used to compute
the variances in CD) are the same in all tests and equal to σd
F A = 5 mGal, σd
G = 0.5 m, σd
E = 100 m, and σd
gg = 0.08 E¨o tvos, for free-air
anomalies, geoid height, elevation and gravity gradients, respectively.
For the first test, we start the inversion with an initial model that is close to the true model (see Tables 3 and 4). The parameters retrieved
by the inversion are shown in Fig. 6 (second column) and Table 4. In this case, the algorithm recovers the true parameters almost exactly in a
few iterations; all of the model parameters are drawn closer to the true values than in the initial model, even when the original data is noisy.
The results for the second test are shown in Fig. 6 (third column). Here, the starting model is farther from the true model, yet within
reasonable/realistic bounds (Tables 3 and 4). The final model still represents a clear improvement over the starting model; all the parameters
are well recovered and closer to the true model than in the initial model. Region 1 is an interesting exception, where the inversion has not been
able to recover the true LAB depth, although it did produce acceptable results for all other parameters. This case illustrates an unavoidable
limitation of linearized algorithms such as the one used in this work, which are not suited to recognize two or more possible models with
identical misfit characteristics. In the present case, our initial (deliberate) combination of model parameters (thicker LAB and thinner crust)
in region 1 balance each other to produce similar observables to those predicted by the true model (thus the inversion still gives an acceptable
fit to observations) and therefore the inversion favours a solution closer to the (wrong) starting model. Stochastic or probabilistic inversion
algorithms are less sensitive to this problem, but significantly more computationally expensive, which has rendered them impractical for this
work. The implementation of such non-linear, matrix-free algorithms for global inversions is currently under development by the authors.
In the third test (Fig. 6, fourth column), we start the inversion with a spherically symmetric model, therefore containing no information
on any type of anomaly. This case is purely illustrative as it represents a worst-case scenario, unlikely to occur in any real application. Results
in Fig. 6 (fourth column) show that, while the inversion improved the density values of the initial model in some regions, overall it could not
produce acceptable results, especially for Moho and LAB depths.
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13. 1614 J.C. Afonso et al.
Figure 5. Flowchart of the inversion scheme used in this work. Note that the temperature, pressure, and compositional corrections described in Section 4 are
included in the box ‘1-D Topography’. See also Appendix A.
Table 3. Parameters used in the synthetic model. The region numbers correspond to those in Fig. 6.
Region
Elev.
(m)
Crust den.
( kg m−3
)
Asthe. den.
( kg m−3
)
Moho
(m)
LAB
(m)
1 3000 2750 3395 43547 132331
2 2500 2770 3450 53820 217215
3 -3000 3000 3390 20805 179361
4 3500 2770 3385 45798 115514
5 4500 2740 3470 64263 234235
6 1000 2790 3410 38251 166585
7.2 Removing the effects of unmodelled density anomalies in the input data sets
Before presenting the final model and main results, we briefly discuss the issue of removing signals in the input data sets that arise from
unmodelled (deep) density anomalies. As mentioned before, it is customary to filter out long wavelengths from the total geoid to minimize
the effects of deep (depths >410 km) density anomalies (e.g. Ricard et al. 1984; Chase 1985; Bowin 1983; Marks et al. 1991; Bowin 2000;
Featherstone 1997; Chase et al. 2002; Coblentz et al. 2011; Fullea et al. 2015; Afonso et al. 2016c). Many studies have shown theoretically
and empirically that under some reasonable assumptions, removing spherical harmonics lower than 8–15 from the total geoid leave a signal
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14. A global reference model of the lithosphere 1615
Figure 6. Results from synthetic tests using different initial models in the inversion. The true model is shown in the leftmost column. Test 1 uses an initial
model that is close to the true model. Test 2 uses an initial model that is farther away from the true model, yet still within reasonable limits. In Test 3, the initial
model is a spherically symmetric model (i.e. flat surfaces) with no information of any anomaly or discontinuity; this is an unrealistic worse-case scenario in
practical applications.
Table 4. Initial and retrieved values for the main model parameters for all tests.
Inversion result Initial model
Region
Crust den.
( kg m−3
)
Asthe. den.
( kg m−3
)
Moho
(m)
LAB
(m)
Crust den.
( kg m−3
)
Asthe. den.
( kg m−3
)
Moho
(m)
LAB
(m)
Test 1
1 2748 3399 43827 133901 2760 3385 41547 136331
2 2774 3451 53931 218919 2780 3440 51820 221215
3 2994 3394 20554 180211 3010 3380 18805 183361
4 2773 3386 45993 116514 2780 3375 43798 119514
5 2739 3468 64913 233914 2750 3460 62263 238235
6 2788 3409 38911 167815 2800 3400 36251 170585
Test 2
1 2753 3387 38546 144821 2760 3375 38547 142331
2 2778 3443 48820 224022 2780 3430 46820 227215
3 2993 3386 19942 183302 3010 3370 15805 189361
4 2776 3383 43863 116413 2780 3365 40798 125514
5 2743 3462 59943 235213 2750 3450 59263 248235
6 2795 3398 36815 169894 2800 3990 33251 176585
Test 3
1 2774 3387 31586 145525 2780 3400 30000 145000
2 2755 3389 32584 144828 2780 3400 30000 145000
3 2823 3432 24987 139542 2780 3400 30000 145000
4 2752 3389 31582 146121 2780 3400 30000 145000
5 2749 3392 34374 146951 2780 3400 30000 145000
6 2784 3394 31025 144980 2780 3400 30000 145000
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15. 1616 J.C. Afonso et al.
controlled mostly to density anomalies within the first 300–410 km (e.g. Crough & Jurdy 1980; Hager 1984; Chase 1985; Hager & Richards
1989; Bowin 1983, 2000; Doin et al. 1996). Since here we jointly invert multiple fields, we filter all of them to the same degree for consistency
(except for topography given its local nature at the scale of interest). However, in principle, not all fields have the same sensitivity to
deeper/shallow anomalies, making the issue of finding an optimal filter more problematic than in the case of working with only one field.
Moreover, all masses inside the Earth contribute to all degrees (albeit differentially) in a spherical expansion and therefore wavelength filtering
can never be completely satisfactory.
We address this issue with a pragmatic two-fold approach. First, we run synthetic tests to gauge the contribution of density anomalies of
different sizes and at different depths to the total signal and to each harmonic degree for all fields used in this work. We performed these tests
for both localized anomalies and for whole-Earth mantle models (see Supporting Information). Secondly, informed by these synthetic tests,
we performed multiple inversions of the real data sets filtered at different degrees and analyse the fitting statistics. The guiding principle here
is that those fields that either retain signals/contributions from unmodelled deeper sources or do not include contributions from significant
anomalies within the modelled region, will tend to produce poorer joint fits than those where most of the causative density heterogeneity in
all fields is properly accounted for by the model. We tested five cases in which we filtered the data to leave degrees/orders ≥6, 8, 10, 12 and
14 in the spherical harmonic expansions of the fields. Both approaches converged to the same conclusion, namely that filtering up to degree
and order ∼10 is optimal in terms of both explicative power (e.g. quality of joint fit) and spectral power (see Figs S1–S3).
It can be shown, however, that the effect of density anomalies located between 410 and 1000 km depth is non-negligible on a filtered
geoid up to degree and order ∼10 in many parts of the planet (Fig. S3). Not accounting for this effect would introduce undesired biases into
the model by forcing incorrect density values to compensate for unmodelled deeper anomalies. We therefore decided to explicitly account
for density anomalies at depths >410 km (by computing their contribution using a global density model; Panning & Romanowicz 2006) and
remove their effect from the observed filtered fields. The above analyses and data processing approach give us confidence that our results
presented in the following section will not be contaminated by unmodelled density anomalies to any major extent.
8 R E S U LT S
8.1 Fits to data
Fig. 7 shows the observables used in the inversion and those predicted by the final model after 18 iterations of our algorithm. The quality of the
joint fit is satisfactory for all fields and all the main patterns in the data sets are explained to a high degree of precision. The summary statistics
in Tables 5 and 6 clearly show that our final model not only displays acceptable joint misfits, but also represents a significant improvement
over the initial/starting model. Interestingly, the long-wavelength misfit in elevation follows closely the pattern predicted by global models of
dynamic topography (see Flament et al. 2013, for a recent review), except perhaps in southeast Asia and northern Oceania. In addition, the
systematic misfit along MORs seems to be related to (at least) two limitations in the model parametrization: (1) the model does not account
for the shallow low density structure beneath MORs (i.e. the so-called melting region) and (2) a single sublithospheric column of uniform
density beneath MORs is required to simultaneously fit all data sets (those sensitive to shallow anomalies as well as those sensitive to deeper
anomalies) and therefore a biased compromise solution is required. Shallow dynamic effects are also a possible factor. Considering all of
the above, we decided not to peruse better fits to elevation, as these misfits likely contain dynamic components not included in our inversion
and/or biases due to the simple parametrization adopted for the mantle.
8.2 Final model: LithoRef18
8.2.1 Crustal thickness and LAB structure
The distribution and magnitudes of the four main model parameters corresponding to the final model, hereafter referred to as LithoRef18, are
shown in Fig. 8. We also show the initial values (i.e. m0) in this figure. As expected, the depths to the Moho and LAB have not been changed
dramatically by the inversion from their initial values. This is simply a consequence of the relatively tight constraints (prior information)
used in the inversion for these parameters (Table 2). Nevertheless, the predicted crustal thickness in LithoRef18 has changed by ±5 km from
the initial values in a significant part of the globe. In continental regions with little or no seismic constrains (as per USGS Global Seismic
Catalogue, e.g. Africa, South America, Far-east Russia, Northern Canada), our predicted crustal thickness tend to be smaller than that in the
initial model(Fig. 8C). In the oceans, most of the differences are found in the surroundings of sea mounts, ridges, and fracture zones. For
instance, LithoRef18 predicts deeper Moho depths than CRUST1.0 beneath oceanic features such as the Walvis and Ninetyeast ridges, in
closer agreement with recent high-resolution seismic studies (e.g. Fromm et al. 2017).
In Fig. 9 we compare the predictions of Moho depth from LithoRef18, LITHO1.0, CRUST1.0 and a recent gravity-derived global model
(GEMMA; Reguzzoni & Sampietro 2015) against results from higher-resolution models informed by various seismic and/or potential field
data in Australia (AusMoho; Kennett et al. 2011), South America (GMSA12; van der Meijde et al. 2013), Europe (EPcrust; Molinari &
Morelli 2011), US (US-CrustVs-2015; Schmandt et al. 2015), the North Atlantic (NAGTEC; Funck et al. 2017) and continental China
(China2014; He et al. 2014). This comparison, although illustrative and informative, needs to be taken with caution, as (i) some of these
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16. A global reference model of the lithosphere 1617
Figure 7. (a) Observed data used in the inversion. (b) Predicted data by the final model. (c) Data residuals (predicted - observed) of the final model. All fields
have been interpolated to a 1◦ × 1◦ for illustration purposes.
Table 5. RMS of data misfits associated with LithoRef18.
Iteration
Elev.
(m)
Geoid
(m)
Free air
(mGal)
Grad.xx
(Eotvos)
Grad.yy
(Eotvos)
Grad.zz
(Eotvos)
Initial model 2.1255e+03 561.1871 269.1086 1.2269 1.3436 2.2365
1 654.3586 3.3718 7.4776 0.0492 0.0550 0.0800
2 552.0082 1.5816 4.6181 0.0403 0.0403 0.0583
: : : : : : :
18 220.8516 0.6965 3.3833 0.0353 0.0364 0.0494
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17. 1618 J.C. Afonso et al.
Table 6. RMS of model parameters relative to initial (starting) model.
Iteration
Moho.
(Km)
LAB
(Km)
Crust Den.
(kg m−3
)
Asthe. Den.
(kg m−3
)
Initial model 0 0 0 0
1 1.1173 2.1186 51.7115 19.0724
2 1.3951 2.7454 55.1163 19.7398
: : : : :
18 2.4309 7.3097 57.6777 20.6026
Figure 8. (a) Initial model used in the inversion. (b) Retrieved model parameters. (c) differences between the initial and final models. All fields have been
interpolated to a 1◦ × 1◦ for illustration purposes.
regional models are actually either informed or constrained by CRUST1.0 (e.g. NAGTEC, EPcrust) and (ii) the latest updates of CRUST1.0
may include data either similar or identical to what was used in these studies (the full data set used in the latest versions of CRUST1.0 is not
publicly available). It is not surprising then that CRUST1.0 shows the best agreement with the regional models, except in the case of GMSA12
(mostly constrained by gravity data), where our predictions agree slightly better than those of CRUST1.0. In all cases, however, the absolute
mean discrepancy and the associated spread of LithoRef18 are comparable to those in CRUST1.0 and significantly smaller than those in the
global GEMMA and LITHO1.0 models. In Africa, where seismic constraints are scarce, most recent models predict smaller crustal thickness
values than those in CRUST1.0 (cf. van der Meijde et al. 2015), and so does our model. In particular, our results are more similar to the
models of Tugume et al. (2013) and Reguzzoni et al. (2013), which also used gravity data as constraints.
The results for the LAB depth show a modest variation within some continents, as per the original (seismic-based) restrictions in the
inversion. Most of the change in LAB depths recorded in the oceans is concentrated at and around mid-ocean ridges (MORs). This is to be
expected as the initial LAB in the oceans was based on a plate cooling model Grose & Afonso (2013) with the LAB beneath MORs set at
25 km depth everywhere (Section 2. We note that our final LAB depths resemble very closely those obtained from the multi-mode surface
wave tomography model CAM2016Vsv (Ho et al. 2016), as shown in http://ds.iris.edu/ds/products/emc-cam2016/.
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18. A global reference model of the lithosphere 1619
Figure 9. Comparison of predictions for crustal thickness (in km) from LithoRef18, GEMMA, Litho1.0 and CRUST1.0 against values given by regional,
high-resolution models in Australia (AusMoho; Kennett et al. 2011), South America (GMSA12; van der Meijde et al. 2013), US (US-CrustVs-2015; Schmandt
et al. 2015), continental China (China2014; He et al. 2014), Europe (EPcrust; Molinari & Morelli 2011) and the North Atlantic region (NAGTEC; Funck et al.
2017). Each panel includes the mean of the point-wise discrepancies between the global and regional models as well as associated standard deviations (SD, a
measure of dispersion). Smaller values of these two statistics indicate a closer agreement with the regional models.
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19. 1620 J.C. Afonso et al.
The rest of the short wavelength variability related to sea mounts, oceanic plateaus and large fracture zones likely represents an upper
bound in terms of lithospheric thickness. This is due to the combination of two factors. First, the oceanic Moho is in general poorly constrained
by CRUST1.0. Second, we let the inversion to change the initial oceanic Moho only slightly, thus exaggerating changes in lithospheric thickness
to fit the data. The use of more accurate estimates of Moho depths (Hoggard et al. 2017) in the oceans could help in obtaining a more reliable
LAB model; this is work in progress.
8.2.2 Crustal and mantle densities
The pattern and magnitude of crustal density in continents remained relatively similar to that in the starting model (Fig. 8C), with most of
the differences being within ±50 kg m−3
. However, these differences can be important in some cases (e.g. in gravity modelling), as they
represent considerable changes in the average bulk density of a thick crust (i.e. their effect is integrated over the thickness of the entire
continental crust). Most of the high amplitude differences are found in the oceans. Our model generally predicts lower densities along MORs
and slightly higher densities in mature oceanic crust. Interestingly, LithoRef18’s density structure highlights features that were absent in the
initial model. For instance, while the Walvis, Ninetyeast, Broken and Nazca ridges are indistinguishable in the initial density model, they are
clearly visible in ours (Fig. 8B; see also Section 8.2.1). This is also the case in the other related parameters (i.e. LAB, Moho depth; see also
Fig. 10). In continental interiors, LithoRef18 predicts somewhat higher average crustal densities than the input model. A comparison with
higher-resolution density models in different parts of the world (e.g. Kozlovskaya et al. 2004; Yegorova et al. 2013; Hasterok & Gard 2016;
Gradmann et al. 2017; Sippel et al. 2017; Alghamdi et al. 2018; Wang et al. 2018) shows a close agreement with our crustal density values.
The results for sublithospheric mantle density are shown in Fig. 8(B). The resulting density structure follows a pattern similar to that
of lithospheric thickness. In this context, it is important to recall that the sublithospheric density values in Fig. 8(B) are the depth-averaged
densities of the mantle between the LAB and the bottom of the model (410 km depth) and therefore there is an intrinsic ‘depth effect’ included
in them (i.e. the average of an adiabatic density profile increases with average depth). The MORs are clearly distinguishable as relative low
density zones, whereas stable continental areas with thick lithospheres are generally underlaid by higher density mantle. Although this is
to be expected given the depth effect mentioned above, these observations raise the question of whether our results for the sublithospheric
mantle are the product of real sensitivity to data or an artifact of the inversion/parametrization controlled somehow by the initial LAB depth.
We discuss this further in the next section, where we show that our results are indeed supported by recent global seismic tomography models
as well as by independent resolution analyses of gravity gradients and results from mineral physics.
The mean density of the lithosphere is not shown in Fig. 8 because it is not strictly part of the vector of model parameters m. However,
it is an output of the model and therefore it is shown in Fig. 10 and discussed in the next section.
9 D I S C U S S I O N
9.1 Lithospheric and sublithospheric densities: a comparison with seismic tomography models
If the density structure of LithoRef18 in the mantle is a reliable data-driven result and the density of the sublithospheric mantle is primarily
controlled by temperature anomalies (a good first-order assumption), we should expect to see a correlation with seismic tomography models
(i.e. high densities should correlate with regions of high seismic velocity and vice versa). Fig. 10 shows a comparison of our lithospheric
and sublithospheric density models with three well-known global Vs tomography models (Kustowski et al. 2008; Schaeffer & Lebedev 2013;
French & Romanowicz 2014). Other models (e.g. SAVANI, GYPSUM, S40RTS, SEMUM2) show comparable features to those in Fig. 10
and therefore they are not shown here. In order to make a fair and valid comparison, the wavespeeds from all three tomography models were
averaged over the same depth range as in our density models (i.e. the wavespeeds depicted in Fig. 10 do not represent wavespeeds at specific
depths, but average values for the depth range LAB < d < 410 km depth).
All three tomographic models are shear wave velocity models, but differ in the data and methods used. SL2013sv (Schaeffer & Lebedev
2013) is an isotropic global upper mantle and transition zone Sv velocity model constrained by 521 705 vertical-component broad-band
seismograms (selected from a data set of ∼3/4 million). It is based on a linearized (perturbation) inversion scheme (Schaeffer & Lebedev
2013), using a new 1-D reference model derived by these authors, and covers a period range from 11 to 450 sec with maximum estimated
resolutions of ∼6◦
. SEMUCB-WM1 (French & Romanowicz 2014) is a global whole-mantle shear wave velocity model based on a ‘hybrid’
full-waveform approach that combines spectral finite element simulations of the wavefield (for the forward problem) with an iterative,
nonlinear least-squares formalism. It is constrained by 447 800 waveforms from surface a body wave phases with an estimated maximum
lateral resolution of ∼1200 km. S362WMANI (Kustowski et al. 2008) is a whole-mantle anisotropic shear wave velocity model based on a
waveform iterative linearized least-squares inversion of both surface and body wave data in which the 1-D reference model is updated at each
iteration (similar to what is done here). Although no formal resolution analyses were provided, a nominal lateral resolution of ∼1000 km is
claimed for the uppermost mantle.
Fig. 10 shows that all three tomography models agree well on the long-wavelength patterns of averaged velocity anomalies at both
lithospheric and sublithospheric depths. The two most recent models, SL2013sv and SEMUCB-WM1, show the most agreement and a greater
high-frequency content than S362WMANI. Although all three seismic models show a consistent structure to that in our density model of the
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20. A global reference model of the lithosphere 1621
Figure 10. Comparison between the density structure of the lithosphere and sublithospheric upper mantle as predicted by LithoRef18 and seismic anomalies
from three global tomography models: SL2013sv (Schaeffer & Lebedev 2013), SEMUCB-WM1 (French & Romanowicz 2014) and S362WMANI (Kustowsky
et al. 2008). See text for details. All fields have been interpolated to a 1◦ × 1◦ for illustration purposes.
Table 7. Cross-correlation coefficients between lithospheric and sublithospheric densities and seismic velocity fields
as shown in Fig. 10.
Tomography
models
Lithospheric
mantle density
Asthenosphere
density
SL2013sv 0.7437 0.7860
SEMUCB-WM1 0.4092 0.7879
S362WMANI 0.5572 0.8067
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21. 1622 J.C. Afonso et al.
lithosphere, the correlation between LithoRef18 with velocity anomalies in SL2013sv is the clearest (Table 7). This is somewhat expected
given the role that this tomography model had in the initial LAB model (Section 2). We also note that except for SL2013sv (Schaeffer &
Lebedev 2013), the other two models do not contain reliable/complete data at depths <50 km depth and therefore they do not show as detailed
information as SL2013sv at shallow lithospheric depths (Figs 10D, F and H).
In the sublithospheric mantle, our density structure model correlates well with the pattern of seismic anomalies in the tomographic
models, especially those in SL2013sv and SEMUCB-WM1. We recall here that the average density of the sublithospheric mantle (Figs 8B and
10A) was a free parameter in our inversion, not informed by seismic data. The fact that the retrieved density structure exhibits an excellent
correlation with shear wave anomalies is a strong indication that the general pattern in our model is robust. Another piece of evidence that
supports our suggestion that the retrieved sublithospheric density anomalies are the result of true sensitivity of the data is offered by (1) the
fact that geoid anomalies are sensitive to deep density anomalies (Hager & Richards 1989; Bowin 1983, 2000; Featherstone 1997; Chase et al.
2002; Afonso et al. 2013b) and (2) the recent studies of Panet et al. (2014), Martinec (2014) and Greff-Lefftz et al. (2016b). These authors
showed that satellite-derived gravity gradients have sensitivity to mantle mass anomalies down to mid-mantle depths. A last point worth
mentioning is the fact that the absolute density values in the sublithospheric mantle retrieved by our inversion are in excellent agreement with
estimates from seismic constraints (e.g. Kennett 1998) and from thermodynamic modelling of mantle rocks (e.g. Ganguly et al. 2009; Chust
et al. 2017).
9.2 Using LithoRef18 to suppress far-field effects in regional studies
A common difficulty in any study that uses gravity information is the need to minimize the so-called edge or far-field effect, arising from
the fact that the structure outside the model is not explicitly included in the modelling/inversion of the data. A common strategy to minimize
this effect is to increase the size of the model (Aitken et al. 2014; Szwillus et al. 2016). This approach is valid when working with gravity
anomalies, as the effect of unmodelled density anomalies tend to decay rapidly with distance (depending on the size of the density anomaly).
However, despite unnecessarily increasing the computational cost, it is generally not a practical option when working with geoid height,
gravity potential and/or long-wavelength gravity gradients as they are sensitive to density anomalies located relatively far from the modelled
region (Szwillus et al. 2016). Other options are possible. For instance, it is sometimes feasible to ‘copy’ or extend the density structure along
the boundaries of the modelled region into a larger surrounding area (Zeyen & Fern`andez 1994; Fullea et al. 2009; Afonso et al. 2016b).
This is more computationally efficient, but problematic when the outside region is highly heterogeneous. It thus becomes unclear how much
the modelled structure is affected by the unmodelled ones or by the assumptions made about them (see Szwillus et al. 2016,for a recent
discussion).
The ideal situation is to have a way to account for the unmodelled structure at any distance from the region of interest as accurately as
possible contingent on the goals of the study. We argue here that LithoRef18 is well suited to this end. We have prepared an easy-to-use, wrap-
around code (both serial and parallel versions) that computes the contribution to gravity, geoid, and gravity gradients of the global structure at
any observation point of interest (i.e. at any resolution). In this way, any local or regional model can be effectively embedded into the global
LithoRef18 model and locally refined as desired while still accounting for the first-order density structure outside the modelled region. The
user only needs to run the code once, indicating the boundaries of the domain of interest and the number and location of the observations
points at which gravity, geoid or and/gravity gradients are required. These values can then be added to the contribution from the local structure
as the latter is being refined by forward modelling or via an inversion algorithm; thus eliminating unnecessary domain extensions and/or
assumptions about the density structure of the surrounding areas. The code can be downloaded at https://www.juanafonso.com/software or
obtained from the first two authors upon request.
9.3 Future refinements
In this work, we restricted our attention to obtaining an internally consistent, first-order global model of the structure and density of the whole
of the lithosphere and sublithospheric upper mantle on the basis of observable data (i.e. gravity anomalies, geoid heigh, absolute elevation
and gravity gradients) and tenable prior information (e.g. seismic models, mantle composition). In doing so, the intended use of the model,
available prior knowledge, parsimony of parameters, an computational complexity were the main guiding principles. Although the model so
obtained is based on well-known geophysical principles and satisfies a large number of data, it is necessarily an approximation at best, and a
physical abstraction at worst.
Specific areas for improvement that we will consider in the near future are:
(i) The use of the full Marussi tensor: In this work we inverted for the diagonal terms of the Marussi tensor only. Although they do provide
individual sensitivities, the diagonal terms are not all independent, as the trace of the tensor is zero. Including the off-diagonal components
would therefore provide additional sensitivity to the modelled structures.
(ii) The use of an internally consistent data set, such as XGM2016 (Pail et al. 2017) or the planned EGM2020, for gravity anomalies,
geoid height and gravity gradients would help iron out potential inconsistencies that may arise from combining different data sets for these
observables.
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22. A global reference model of the lithosphere 1623
(iii) Expand the model parameter vector to include crustal thermal parameters and use surface heat flow data as an additional observable.
However, we foresee advantages and drawbacks with this approach, as the uncertainties associated with this observable are large in most of
the globe.
(iv) Include a more efficient surface grid and a dynamic parametrization of the sublithospheric mantle that will allow to subdivide the
sublithospheric mantle into more than one region, thus making more efficient use of the sensitivity of the data sets and improving the model’s
resolution/applicability. This is particularly important in regions with thin lithosphere.
(v) In this study, we relied on a global compilation of crustal structure (CRUST1.0) and did not take full advantage of the most recent
high-resolution regional seismic models based on dense arrays (e.g. US Array, ChinaArray, IberArray, etc.). Such regional models will be
included as additional constraints in future releases of LithoRef18.
(vi) Modify the inversion scheme to formally include surface wave dispersion and receiver functions data into the inversion. This is perhaps
the single most important improvement necessary to obtain a truly consistent global model. This will likely require the implementation of
more comprehensive petrological and thermodynamic constraints into the inversion and model, but all the necessary components are in place
(e.g. Schaeffer & Lebedev 2013; Afonso et al. 2016a, b).
Also, as with any model made available to the scientific community, we plan to perform regular refinements to the model as more and/or
better information becomes available to us. Finally, this work represents the necessary starting point towards a more ambitious reference
model of the thermochemical structure of the Earth’s lithosphere and upper mantle based on multi-observable probabilistic tomography at
global scale (Afonso et al. 2013a,b; 2016b). This presents a grand challenge in terms of computational cost and algorithm development, but
guided by the recent developments in reduced order modelling and parallel probabilistic techniques, we are confident that it will be a practical
task in the next few years.
1 0 C O N C LU S I O N S
The main objective of this work was to derive a global lithospheric and upper mantle model that can serve as a reference/initial model for (i)
higher-resolution gravity, seismological, geodetic and/or integrated geophysical studies of the lithosphere and upper mantle, (ii) accounting for
far-field effects in regional gravity/geoid studies, (iii) regional and global geodynamic simulations where the effects of lithospheric structure
are not negligible, (iv) assessing isostatic compensation mechanisms and estimates of residual, isostatic and dynamic topography, (v) stripping
off the lithospheric signal in global estimates of the deep structure of the Earth and (vi) estimating boundary conditions for thermal modelling
of sedimentary basins, among others. For this, we have simultaneously inverted global data sets of gravity anomalies, geoid height, absolute
elevation, and gravity gradients with constraints from seismic models of the crust and mantle to derive a 2◦
× 2◦
global model (LithoRef18) of
crustal thickness, average crustal density, lithospheric thickness, depth-dependent density of the lithospheric mantle, lithospheric geotherms,
and average density of the sublithospheric mantle down to 410 km. The general inversion methodology presented in this work can also be
applied in other planets for which potential field data are commonly the only (or main) constraint to their internal structures (e.g. Moon,
Venus, etc.).
A comparison of LithoRef18’s predictions for crustal structure with recent higher-resolution regional models indicate that our model
represents an improvement over other popular global crustal models. The LAB structure predicted by LithoRef18 is compatible with recent,
high-resolution tomography models (e.g. Schaeffer & Lebedev 2013; French & Romanowicz 2014; Pasyanos et al. 2014; Ho et al. 2016),
which makes it possible to combine these tomography models with LithoRef18 into a single density-seismic model compatible with a large
number of seismic and potential field observations. Although this is not a completely satisfactory strategy, the strong similarities between
LithoRef18 and e.g. SL2013sv (Schaeffer & Lebedev 2013) warrant it as a pragmatic approach especially in the context of serving as a
starting models for detailed regional studies. Further efforts to produce internally consistent global reference models that honour multiple
data sets of different nature (e.g. geochemistry, seismic, potential field, etc.; Afonso et al. 2016b) will likely play a key role in improving our
understanding of the complex physiochemical interactions between the lithosphere and the deep mantle.
AC K N OW L E D G E M E N T S
We are indebted to H. Zeyen for sharing his codes and for suggestions on the inversion approach, to B. Steinberger for sharing his LAB
models, and to A. Forte and an anonymous reviewer for their insightful reviews. The work of JCA has been supported by an ARC DP project
(DP160103502) and CEED. JCA and FS acknowledge support from the ARC Centre of Excellence Core to Crust Fluids Systems (CCFS).
JCA, FS, WS and JE acknowledge support from the Australia-Germany Joint Research Cooperation Scheme. This study has been done in the
framework of the project ‘3D Earth - A Dynamic Living Planet’ funded by ESA as a Support to Science Element (STSE) and is contribution
1234 from the ARC Centre of Excellence for Core to Crust Fluid Systems (http://www.ccfs.mq..du.au) and 1273 in the GEMOC Key Centre
(http://www.gemoc.mq.edu.au).
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23. 1624 J.C. Afonso et al.
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