The European [SHARE] Seismic Hazard Model: Genesis, Evolution and Key, Aspects, L. Danciu , J. Woessner, D. Giardini and the SHARE Consortium, GEM reveal 2013
This document summarizes a seismic hazard model for the Middle East region. It includes 3 area source models, 9 fault source models, and a spatially smoothed seismicity model developed based on a declustered earthquake catalog. The models were constructed through a collaborative process involving multiple experts. The key elements summarized are:
- 143 area source zones defined based on seismicity patterns and tectonic features.
- Fault sources were selected based on being capable and having slip rates above 0.1 mm/year, with 3 confidence classes.
- Maximum magnitudes were assigned through various methods with sensitivity analysis performed.
- A logic tree incorporates the alternative source models and characterizations.
- The models were developed to be stable
This study conducted a seismic risk assessment for Portugal using probabilistic seismic hazard analysis and developing new exposure and vulnerability models. A probabilistic seismic hazard model was developed considering logic trees for ground motion models, seismic source characterizations, and other parameters. An exposure model was created using a national building census to characterize Portugal's building stock. Fragility functions were developed for reinforced concrete and masonry structures. Probabilistic loss estimates were calculated at different spatial scales to identify regions in Portugal where risk mitigation measures should be prioritized.
The document summarizes the development of satellite modeling for the National Solar Radiation Database (NSRDB) to provide accurate surface solar radiation data. It describes the evolution from empirical to physical models using satellite measurements and ancillary data as inputs to radiative transfer models. Validation shows the new 2005-2012 dataset has a mean bias error of less than 5% for GHI and DNI compared to surface measurements, though uncertainty remains for cloudy cases. Future work aims to improve the model with higher resolution data and better representation of aerosols and surfaces.
1. The document discusses using sky imagers for short-term solar forecasting, as traditional methods lack sufficient spatial and temporal resolution for small-scale applications.
2. The proposed sky imager forecast model involves 7 steps: image analysis, cloud detection, cloud projection, shadow projection, irradiance modeling, predicting cloud motion to generate forecasts, and PV power modeling.
3. Accurate cloud detection, projection, and shadow projection are challenging due to issues like cloud inhomogeneity, perspective errors with distance from camera, and sensitivity to errors in estimated cloud base height.
This document discusses using satellite data to generate time series of spectrally resolved solar irradiance data for analyzing the impact of the solar spectrum on photovoltaic module performance. It describes the PVKLIMA project which uses a combination of atmospheric models, satellite imagery, and radiative transfer calculations to estimate spectral irradiance worldwide. Methods for speeding up the calculations and accounting for effects like clouds, aerosols, and module tilt angle are discussed. Future work includes further validation and expanding the method to additional geostationary satellites.
This document summarizes a seismic hazard model for the Middle East region. It includes 3 area source models, 9 fault source models, and a spatially smoothed seismicity model developed based on a declustered earthquake catalog. The models were constructed through a collaborative process involving multiple experts. The key elements summarized are:
- 143 area source zones defined based on seismicity patterns and tectonic features.
- Fault sources were selected based on being capable and having slip rates above 0.1 mm/year, with 3 confidence classes.
- Maximum magnitudes were assigned through various methods with sensitivity analysis performed.
- A logic tree incorporates the alternative source models and characterizations.
- The models were developed to be stable
This study conducted a seismic risk assessment for Portugal using probabilistic seismic hazard analysis and developing new exposure and vulnerability models. A probabilistic seismic hazard model was developed considering logic trees for ground motion models, seismic source characterizations, and other parameters. An exposure model was created using a national building census to characterize Portugal's building stock. Fragility functions were developed for reinforced concrete and masonry structures. Probabilistic loss estimates were calculated at different spatial scales to identify regions in Portugal where risk mitigation measures should be prioritized.
The document summarizes the development of satellite modeling for the National Solar Radiation Database (NSRDB) to provide accurate surface solar radiation data. It describes the evolution from empirical to physical models using satellite measurements and ancillary data as inputs to radiative transfer models. Validation shows the new 2005-2012 dataset has a mean bias error of less than 5% for GHI and DNI compared to surface measurements, though uncertainty remains for cloudy cases. Future work aims to improve the model with higher resolution data and better representation of aerosols and surfaces.
1. The document discusses using sky imagers for short-term solar forecasting, as traditional methods lack sufficient spatial and temporal resolution for small-scale applications.
2. The proposed sky imager forecast model involves 7 steps: image analysis, cloud detection, cloud projection, shadow projection, irradiance modeling, predicting cloud motion to generate forecasts, and PV power modeling.
3. Accurate cloud detection, projection, and shadow projection are challenging due to issues like cloud inhomogeneity, perspective errors with distance from camera, and sensitivity to errors in estimated cloud base height.
This document discusses using satellite data to generate time series of spectrally resolved solar irradiance data for analyzing the impact of the solar spectrum on photovoltaic module performance. It describes the PVKLIMA project which uses a combination of atmospheric models, satellite imagery, and radiative transfer calculations to estimate spectral irradiance worldwide. Methods for speeding up the calculations and accounting for effects like clouds, aerosols, and module tilt angle are discussed. Future work includes further validation and expanding the method to additional geostationary satellites.
Modellistica Lagrangiana in ISAC Torino - risultati e nuovi sviluppiARIANET
The MicroSwift-Spray modelling system has been validated against experimental test cases from wind tunnel and field trials, showing it can reliably simulate particle dispersion. The MILORD long-range dispersion model was revived and applied to simulate the Fukushima nuclear accident and identify the source of CO2 peaks observed at a high-altitude Italian site, with results comparable to other models. Reviving MILORD demonstrated its ability to simulate long-range and regional-scale dispersion, including backwards trajectories, using less computation than some other models.
This document discusses using deep learning techniques to detect extreme weather patterns in climate data. It begins by outlining the scientific motivation and successes of deep learning in computer vision. It then describes early successes applying deep learning to climate science tasks like classifying tropical cyclones, atmospheric rivers, and weather fronts. Challenges include dealing with multi-variate climate data and lack of labeled examples. Future work involves creating unified deep learning models that can perform detection, localization, and segmentation of extreme weather across different climate datasets.
This document provides an overview of the Meteonorm software and its process for generating Typical Meteorological Year (TMY) climate data. It details how Meteonorm combines ground measurements from over 1700 stations with satellite data using interpolation algorithms to produce hourly climate values. It then describes Meteonorm's uncertainty model which estimates the uncertainty in the data to be between 2-10% based on factors like measurement accuracy, interpolation distance, and effects of using satellite data. The document concludes that Meteonorm provides a useful input for simulation tools despite its uncertainties and that its data archive can be enhanced in the future.
This document summarizes the results of a validation study of clear sky and all-weather solar irradiance models. It analyzed over 22 ground measurement sites in Europe and the Mediterranean over periods of up to 8 years. Key findings included:
- Hourly global irradiance models showed no bias and a standard deviation of 17-20%. Beam models had no bias and standard deviation of 34-50%.
- Daily models had no bias for global irradiance with a standard deviation of 8-12%, and no bias for beam with a standard deviation of 20-32%.
- Monthly models had negligible bias and standard deviations of 3-6% for global and 9-17% for beam irradiance.
Physical processes in the earth system are modeled with mathematical representations called parameterizations. This talk will describe some of the conceptual approaches and mathematics used do describe physical parameterizations focusing on cloud parameterizations. This includes tracing physical laws to discrete representations in coarse scale models. Clouds illustrate several of the complexities and techniques common to many physical parameterizations. This includes the problem of different scales, sub-grid scale variability. Discussions of mathematical methods for dealing with the sub-grid scale will be discussed. In-exactness or indeterminate problems for both weather and climate will be discussed, including the problems of indeterminate parameterizations, and inexact initial conditions. Different mathematical methods, including the use of stochastic methods, will be described and discussed, with examples from contemporary earth system models.
CSP Training series : solar resource assessment 2/2Leonardo ENERGY
Fifth session of the 2nd Concentrated Solar Power Training dedicated to solar resource assessment.
* DNI Variability, Frequency Distributions
* Typical Meteorological Years
* DNI measurements: broadband vs. spectral, and their limitations
* What is circumsolar radiation and why should we care in CSP/CPV?
* How much diffuse irradiance can be used in concentrators?
* How to measure and model the circumsolar irradiance?
* Spectral irradiance standards and their use for PV/CPV rating
* The AM1.5 direct standard spectrum: Why did it change? Why AM1.5?
* Use of the SMARTS radiative code to evaluate clear-sky spectral irradiances
* Sources of measured spectral irradiance data
* Spectral effects on silicon and multijunction cells and their dependence on climate
Testing the global grid of master events for waveform cross correlation with ...Ivan Kitov
Abstract
The Comprehensive Nuclear-Test-Ban Treaty’s verification regime requires uniform distribution of monitoring capabilities over the globe. The use of waveform cross correlation as a monitoring technique demands waveform templates from master events outside regions of natural seismicity and test sites. We populated aseismic areas with masters having synthetic templates for predefined sets (from 3 to 10) of primary array stations of the International Monitoring System. Previously, we tested the global set of master events and synthetic templates using IMS seismic data for February 12, 2013 and demonstrated excellent detection and location capability of the matched filter technique. In this study, we test the global grid of synthetic master events using seismic events from the Reviewed Event Bulletin. For detection, we use standard STA/LTA (SNR) procedure applied to the time series of cross correlation coefficient (CC). Phase association is based on SNR, CC, and arrival times. Azimuth and slowness estimates based f-k analysis cross correlation traces are used to reject false arrivals.
This document provides an overview of seismic hazard analysis, including both deterministic and probabilistic procedures. It discusses key aspects of probabilistic seismic hazard analysis such as determining earthquake sources, developing ground motion estimates, and representing hazards in the form of uniform hazard spectra or seismic hazard curves. The document uses examples and illustrations to explain concepts like attenuation relationships, recurrence models, and incorporating uncertainty in probabilistic analyses.
The Research Center for Renewable Energy Mapping and Assessment at Masdar Institute aims to develop regional knowledge and leadership in renewable energy assessment and mapping for arid environments. The Center has over 26 staff members and has succeeded in developing the UAE Solar Atlas and playing a key role in the Global Solar and Wind Atlas initiative. Some of the Center's facilities and capabilities include a satellite ground station, 200TB storage system, and tools for solar resource forecasting and performance modeling of solar power technologies.
Ricostruzione della meteorologia urbana con WRFARIANET
The document summarizes meteorological modeling experiments using the WRF model to simulate urban areas in several Italian cities. It configured WRF to run at 1km resolution over the cities, using building data to represent urban areas. It tested different urban parameterization schemes and evaluated their ability to capture differences between urban and rural meteorological measurements in Rome and Milan in 2015. The results showed that WRF with urban schemes improved wind speeds but overestimated temperature and humidity changes between urban and rural areas. Further tuning of urban parameters was recommended to better match observations.
The document discusses the goals and activities of the Year of Polar Prediction (YOPP) in improving polar prediction models through enhanced observational data from field sites. It describes YOPP's efforts to standardize data collection and model output across sites to facilitate direct comparisons between observations and multiple models. This includes developing common file formats, defining essential climate variables to be collected, and making both observation and model output available through a central data portal. The goals are to evaluate model performance against observations to identify areas for model improvement and advance polar prediction capabilities.
TH1.T04.2_MULTI-FREQUENCY MICROWAVE EMISSION OF THE EAST ANTARCTIC PLATEAU_IG...grssieee
The document summarizes an experiment called Domex-2 that was conducted at Dome C, Antarctica between 2008-2010 to measure microwave emission from the East Antarctic plateau using ground-based and satellite instruments. Measurements from the Domex-2 radiometers showed high temporal stability of brightness temperatures at vertical polarization but more fluctuation at horizontal polarization as expected. Angular trends from Domex-2 matched well with data from the SMOS satellite. An electromagnetic model was developed and validated against the satellite and ground measurements, demonstrating the mechanisms controlling microwave emission from the ice sheet.
This problem represents an interesting opportunity for scientists and statisticians to collaborate since the problem is too big for either community. The science is not well established, although fairly sophisticated ice flow models exist. They are even becoming relevant to explain some of the complexity seen in observational data. At the same time, the complex phenomena we see in observations may not be particularly relevant to assessing the risks of significant increases in sea level rise over the near future. The talk will review what we have learned about this problem through the PISCEES SciDAC project. This problem is rich with challenges and opportunities, particularly for realigning how our two communities engage each other. The talk will review the computational, scientific, and mathematical "reality checks" that might stop any reasonable person from considering this topic further. I then will point out how each of these challenges could be mitigated if these different perspectives were better integrated.
The document discusses methods for characterizing the global environment using satellite data to help overcome challenges posed by weather effects on missile defense sensors. It describes adjusting infrared imagery thresholds to approximate radar observations, extracting weather event boundaries, projecting 3D shapes onto a model Earth, and using an existing satellite constellation to provide continuous coverage. The goal is to determine visibility and sensor performance to optimize sensor selection and placement for missile defense.
The document discusses plans to improve the Global Fire Assimilation System (GFAS) within the Copernicus Atmosphere Monitoring Service (CAMS). Key points include:
1) GFAS will use more satellite observations of fire radiative power (FRP), including from geostationary satellites, to better characterize fires over time and reduce errors from individual satellites.
2) It will develop the capability to forecast FRP using weather data and fire indices and represent changes in emission factors over time.
3) These improvements aim to provide a more accurate and stable representation of the global FRP distribution at an hourly temporal resolution.
Future guidelines the meteorological view - Isabel Martínez (AEMet)IrSOLaV Pomares
This document discusses nowcasting and forecasting of solar irradiance using meteorological data. Nowcasting uses observations from the past 6 hours to predict clouds and irradiance up to 2 hours ahead for a specific site. Forecasting uses numerical weather prediction models to predict clouds and irradiance out to days or weeks ahead on regional to global scales. The document outlines various nowcasting techniques including the use of sky cameras, satellites, and neural networks. It also describes several forecast models run operationally at ECMWF and AEMET including HIRLAM, HARMONIE, and the ECMWF model. Prognostic aerosols are also modeled to improve irradiance forecasts.
The document describes a displaced ensemble variational data assimilation method to incorporate microwave imager brightness temperatures (TBs) into a cloud-resolving model. It uses an ensemble-based variational assimilation approach with a displacement error correction scheme to address errors from misplaced rainfall areas between observations and forecasts. The method is applied to assimilate TMI TBs for Typhoon CONSON on June 9, 2004, improving precipitation forecasts up to 4 hours later by reducing displacement errors and avoiding misinterpretation of TB increments.
Towards Exascale Simulations for Regional-Scale Earthquake Hazard and Riskinside-BigData.com
The document discusses the goals and progress of the Department of Energy's Exascale Computing Project (ECP) to develop exascale simulations for regional-scale earthquake hazard and risk assessments. The ECP aims to (1) develop computational frameworks coupling geophysics and infrastructure modeling codes, (2) increase frequency resolution and reduce runtimes through advances in hardware, software, and algorithms, and (3) establish performance benchmarks to track progress towards exascale capabilities. Initial regional demonstrations in 2017 showed promising realism in simulated ground motions and infrastructure response. Further work includes waveform inversions, GPU optimizations, and assessing how far simulations can augment probabilistic hazard assessments.
New features presentation: meteodyn WT 4.8 software - Wind EnergyJean-Claude Meteodyn
New feature of meteodyn WT, CFD software for wind resource assessment and wind park optimisation. Worldwide terrain database, convergence improvements and others improvements.
The document summarizes the objectives and methodology of the SHARE project, which aims to harmonize seismic hazard assessment across Europe and the Mediterranean region. The project develops a community-based seismic hazard model through harmonizing data, modeling approaches, engineering requirements, and other factors. It presents several novel source models at the regional scale and uses a logic tree to incorporate epistemic uncertainty in ground motion predictions. Quality assurance is performed and the results will be disseminated by November 2012 to create a new reference hazard model for the region.
Product & technology portfolio of gridworldlinkedin admin
Gridworld is a software company established in 2003 that develops geological modeling software. It has 50 employees across offices in Beijing, Nanjing, and Houston. The company's software allows for complex 3D geological structural modeling without simplification. Key features include simple and efficient modeling, large-scale collaborative modeling, and various analysis and simulation capabilities. Products include structural modeling, velocity modeling, attribute modeling, reservoir modeling, and structural restoration software. The software has been applied to numerous oil fields in case studies covering a wide range of geological scenarios. Gridworld traces its origins back to 1990 in the Computational Geometry Lab at Beihang University.
Modellistica Lagrangiana in ISAC Torino - risultati e nuovi sviluppiARIANET
The MicroSwift-Spray modelling system has been validated against experimental test cases from wind tunnel and field trials, showing it can reliably simulate particle dispersion. The MILORD long-range dispersion model was revived and applied to simulate the Fukushima nuclear accident and identify the source of CO2 peaks observed at a high-altitude Italian site, with results comparable to other models. Reviving MILORD demonstrated its ability to simulate long-range and regional-scale dispersion, including backwards trajectories, using less computation than some other models.
This document discusses using deep learning techniques to detect extreme weather patterns in climate data. It begins by outlining the scientific motivation and successes of deep learning in computer vision. It then describes early successes applying deep learning to climate science tasks like classifying tropical cyclones, atmospheric rivers, and weather fronts. Challenges include dealing with multi-variate climate data and lack of labeled examples. Future work involves creating unified deep learning models that can perform detection, localization, and segmentation of extreme weather across different climate datasets.
This document provides an overview of the Meteonorm software and its process for generating Typical Meteorological Year (TMY) climate data. It details how Meteonorm combines ground measurements from over 1700 stations with satellite data using interpolation algorithms to produce hourly climate values. It then describes Meteonorm's uncertainty model which estimates the uncertainty in the data to be between 2-10% based on factors like measurement accuracy, interpolation distance, and effects of using satellite data. The document concludes that Meteonorm provides a useful input for simulation tools despite its uncertainties and that its data archive can be enhanced in the future.
This document summarizes the results of a validation study of clear sky and all-weather solar irradiance models. It analyzed over 22 ground measurement sites in Europe and the Mediterranean over periods of up to 8 years. Key findings included:
- Hourly global irradiance models showed no bias and a standard deviation of 17-20%. Beam models had no bias and standard deviation of 34-50%.
- Daily models had no bias for global irradiance with a standard deviation of 8-12%, and no bias for beam with a standard deviation of 20-32%.
- Monthly models had negligible bias and standard deviations of 3-6% for global and 9-17% for beam irradiance.
Physical processes in the earth system are modeled with mathematical representations called parameterizations. This talk will describe some of the conceptual approaches and mathematics used do describe physical parameterizations focusing on cloud parameterizations. This includes tracing physical laws to discrete representations in coarse scale models. Clouds illustrate several of the complexities and techniques common to many physical parameterizations. This includes the problem of different scales, sub-grid scale variability. Discussions of mathematical methods for dealing with the sub-grid scale will be discussed. In-exactness or indeterminate problems for both weather and climate will be discussed, including the problems of indeterminate parameterizations, and inexact initial conditions. Different mathematical methods, including the use of stochastic methods, will be described and discussed, with examples from contemporary earth system models.
CSP Training series : solar resource assessment 2/2Leonardo ENERGY
Fifth session of the 2nd Concentrated Solar Power Training dedicated to solar resource assessment.
* DNI Variability, Frequency Distributions
* Typical Meteorological Years
* DNI measurements: broadband vs. spectral, and their limitations
* What is circumsolar radiation and why should we care in CSP/CPV?
* How much diffuse irradiance can be used in concentrators?
* How to measure and model the circumsolar irradiance?
* Spectral irradiance standards and their use for PV/CPV rating
* The AM1.5 direct standard spectrum: Why did it change? Why AM1.5?
* Use of the SMARTS radiative code to evaluate clear-sky spectral irradiances
* Sources of measured spectral irradiance data
* Spectral effects on silicon and multijunction cells and their dependence on climate
Testing the global grid of master events for waveform cross correlation with ...Ivan Kitov
Abstract
The Comprehensive Nuclear-Test-Ban Treaty’s verification regime requires uniform distribution of monitoring capabilities over the globe. The use of waveform cross correlation as a monitoring technique demands waveform templates from master events outside regions of natural seismicity and test sites. We populated aseismic areas with masters having synthetic templates for predefined sets (from 3 to 10) of primary array stations of the International Monitoring System. Previously, we tested the global set of master events and synthetic templates using IMS seismic data for February 12, 2013 and demonstrated excellent detection and location capability of the matched filter technique. In this study, we test the global grid of synthetic master events using seismic events from the Reviewed Event Bulletin. For detection, we use standard STA/LTA (SNR) procedure applied to the time series of cross correlation coefficient (CC). Phase association is based on SNR, CC, and arrival times. Azimuth and slowness estimates based f-k analysis cross correlation traces are used to reject false arrivals.
This document provides an overview of seismic hazard analysis, including both deterministic and probabilistic procedures. It discusses key aspects of probabilistic seismic hazard analysis such as determining earthquake sources, developing ground motion estimates, and representing hazards in the form of uniform hazard spectra or seismic hazard curves. The document uses examples and illustrations to explain concepts like attenuation relationships, recurrence models, and incorporating uncertainty in probabilistic analyses.
The Research Center for Renewable Energy Mapping and Assessment at Masdar Institute aims to develop regional knowledge and leadership in renewable energy assessment and mapping for arid environments. The Center has over 26 staff members and has succeeded in developing the UAE Solar Atlas and playing a key role in the Global Solar and Wind Atlas initiative. Some of the Center's facilities and capabilities include a satellite ground station, 200TB storage system, and tools for solar resource forecasting and performance modeling of solar power technologies.
Ricostruzione della meteorologia urbana con WRFARIANET
The document summarizes meteorological modeling experiments using the WRF model to simulate urban areas in several Italian cities. It configured WRF to run at 1km resolution over the cities, using building data to represent urban areas. It tested different urban parameterization schemes and evaluated their ability to capture differences between urban and rural meteorological measurements in Rome and Milan in 2015. The results showed that WRF with urban schemes improved wind speeds but overestimated temperature and humidity changes between urban and rural areas. Further tuning of urban parameters was recommended to better match observations.
The document discusses the goals and activities of the Year of Polar Prediction (YOPP) in improving polar prediction models through enhanced observational data from field sites. It describes YOPP's efforts to standardize data collection and model output across sites to facilitate direct comparisons between observations and multiple models. This includes developing common file formats, defining essential climate variables to be collected, and making both observation and model output available through a central data portal. The goals are to evaluate model performance against observations to identify areas for model improvement and advance polar prediction capabilities.
TH1.T04.2_MULTI-FREQUENCY MICROWAVE EMISSION OF THE EAST ANTARCTIC PLATEAU_IG...grssieee
The document summarizes an experiment called Domex-2 that was conducted at Dome C, Antarctica between 2008-2010 to measure microwave emission from the East Antarctic plateau using ground-based and satellite instruments. Measurements from the Domex-2 radiometers showed high temporal stability of brightness temperatures at vertical polarization but more fluctuation at horizontal polarization as expected. Angular trends from Domex-2 matched well with data from the SMOS satellite. An electromagnetic model was developed and validated against the satellite and ground measurements, demonstrating the mechanisms controlling microwave emission from the ice sheet.
This problem represents an interesting opportunity for scientists and statisticians to collaborate since the problem is too big for either community. The science is not well established, although fairly sophisticated ice flow models exist. They are even becoming relevant to explain some of the complexity seen in observational data. At the same time, the complex phenomena we see in observations may not be particularly relevant to assessing the risks of significant increases in sea level rise over the near future. The talk will review what we have learned about this problem through the PISCEES SciDAC project. This problem is rich with challenges and opportunities, particularly for realigning how our two communities engage each other. The talk will review the computational, scientific, and mathematical "reality checks" that might stop any reasonable person from considering this topic further. I then will point out how each of these challenges could be mitigated if these different perspectives were better integrated.
The document discusses methods for characterizing the global environment using satellite data to help overcome challenges posed by weather effects on missile defense sensors. It describes adjusting infrared imagery thresholds to approximate radar observations, extracting weather event boundaries, projecting 3D shapes onto a model Earth, and using an existing satellite constellation to provide continuous coverage. The goal is to determine visibility and sensor performance to optimize sensor selection and placement for missile defense.
The document discusses plans to improve the Global Fire Assimilation System (GFAS) within the Copernicus Atmosphere Monitoring Service (CAMS). Key points include:
1) GFAS will use more satellite observations of fire radiative power (FRP), including from geostationary satellites, to better characterize fires over time and reduce errors from individual satellites.
2) It will develop the capability to forecast FRP using weather data and fire indices and represent changes in emission factors over time.
3) These improvements aim to provide a more accurate and stable representation of the global FRP distribution at an hourly temporal resolution.
Future guidelines the meteorological view - Isabel Martínez (AEMet)IrSOLaV Pomares
This document discusses nowcasting and forecasting of solar irradiance using meteorological data. Nowcasting uses observations from the past 6 hours to predict clouds and irradiance up to 2 hours ahead for a specific site. Forecasting uses numerical weather prediction models to predict clouds and irradiance out to days or weeks ahead on regional to global scales. The document outlines various nowcasting techniques including the use of sky cameras, satellites, and neural networks. It also describes several forecast models run operationally at ECMWF and AEMET including HIRLAM, HARMONIE, and the ECMWF model. Prognostic aerosols are also modeled to improve irradiance forecasts.
The document describes a displaced ensemble variational data assimilation method to incorporate microwave imager brightness temperatures (TBs) into a cloud-resolving model. It uses an ensemble-based variational assimilation approach with a displacement error correction scheme to address errors from misplaced rainfall areas between observations and forecasts. The method is applied to assimilate TMI TBs for Typhoon CONSON on June 9, 2004, improving precipitation forecasts up to 4 hours later by reducing displacement errors and avoiding misinterpretation of TB increments.
Towards Exascale Simulations for Regional-Scale Earthquake Hazard and Riskinside-BigData.com
The document discusses the goals and progress of the Department of Energy's Exascale Computing Project (ECP) to develop exascale simulations for regional-scale earthquake hazard and risk assessments. The ECP aims to (1) develop computational frameworks coupling geophysics and infrastructure modeling codes, (2) increase frequency resolution and reduce runtimes through advances in hardware, software, and algorithms, and (3) establish performance benchmarks to track progress towards exascale capabilities. Initial regional demonstrations in 2017 showed promising realism in simulated ground motions and infrastructure response. Further work includes waveform inversions, GPU optimizations, and assessing how far simulations can augment probabilistic hazard assessments.
New features presentation: meteodyn WT 4.8 software - Wind EnergyJean-Claude Meteodyn
New feature of meteodyn WT, CFD software for wind resource assessment and wind park optimisation. Worldwide terrain database, convergence improvements and others improvements.
New features presentation: meteodyn WT 4.8 software - Wind Energy
Similar to The European [SHARE] Seismic Hazard Model: Genesis, Evolution and Key, Aspects, L. Danciu , J. Woessner, D. Giardini and the SHARE Consortium, GEM reveal 2013
The document summarizes the objectives and methodology of the SHARE project, which aims to harmonize seismic hazard assessment across Europe and the Mediterranean region. The project develops a community-based seismic hazard model through harmonizing data, modeling approaches, engineering requirements, and other factors. It presents several novel source models at the regional scale and uses a logic tree to incorporate epistemic uncertainty in ground motion predictions. Quality assurance is performed and the results will be disseminated by November 2012 to create a new reference hazard model for the region.
Product & technology portfolio of gridworldlinkedin admin
Gridworld is a software company established in 2003 that develops geological modeling software. It has 50 employees across offices in Beijing, Nanjing, and Houston. The company's software allows for complex 3D geological structural modeling without simplification. Key features include simple and efficient modeling, large-scale collaborative modeling, and various analysis and simulation capabilities. Products include structural modeling, velocity modeling, attribute modeling, reservoir modeling, and structural restoration software. The software has been applied to numerous oil fields in case studies covering a wide range of geological scenarios. Gridworld traces its origins back to 1990 in the Computational Geometry Lab at Beihang University.
UH Professor Arthur Weglein's M-OSRP Annual Report, 2013Arthur Weglein
UH Physic Professor & the Director of the Mission Oriented Seismic Research Program Arthur B. Weglein's introduction of the annual report for the year 2013. Arthur B. Weglein, a professor in the Department of Physics & the Department of Earth & Atmospheric science, he holds the Hugh Roy and Lillie distinguished chair in Physic at University of Houston
ABC methods allow researchers to infer population histories and processes from molecular data without calculating likelihoods. Researchers simulate genetic data under different population models and parameter values. They compare summary statistics of the simulated and observed data, retaining simulations where the summary statistics are close. Local regression on the retained simulations provides estimates of parameter posteriors and model probabilities. ABC is increasingly sophisticated but challenging to implement for complex models.
This document discusses optimization techniques for sampling strategies in long-term environmental monitoring of gamma dose rates. It presents regression kriging and simulated annealing as methods for optimizing sampling locations to minimize prediction errors while accounting for spatial autocorrelation. An example application to a gamma radiation monitoring network in Europe demonstrates that minor changes to the existing network could improve mapped predictions along borders. The document notes several shortcomings and areas for further improvement, such as dealing with extreme values and incorporating dynamic and multi-criteria optimization that considers monitoring purposes and constraints.
Backscatter Working Group Software Inter-comparison ProjectRequesting and Co...Giuseppe Masetti
Backscatter mosaics of the seafloor are now routinely produced from multibeam sonar data, and used in a wide range of marine applications. However, significant differences (up to 5 dB) have been observed between the levels of mosaics produced by different software processing a same dataset. This is a major detriment to several possible uses of backscatter mosaics, including quantitative analysis, monitoring seafloor change over time, and combining mosaics. A recently concluded international Backscatter Working Group (BSWG) identified this issue and recommended that “to check the consistency of the processing results provided by various software suites, initiatives promoting comparative tests on common data sets should be encouraged […]”. However, backscatter data processing is a complex (and often proprietary) sequence of steps, so that simply comparing end-results between software does not provide much information as to the root cause of the differences between results.
In order to pinpoint the source(s) of inconsistency between software, it is necessary to understand at which stage(s) of the data processing chain do the differences become substantial. We have invited willing software developers to discuss this framework and collectively adopt a list of intermediate processing steps. We provided a small dataset consisting of various seafloor types surveyed with the same multibeam sonar system, using constant acquisition settings and sea conditions, and have the software developers generate these intermediate processing results, to be eventually compared. If the experiment proves fruitful, we may extend it to more datasets, software and intermediate results. Eventually, software developers may consider making the results from intermediate stages a standard output as well as adhering to a consistent terminology, as advocated by Schimel et al. (2018). To date, the developers of four software (Sonarscope, QPS FMGT, CARIS SIPS, MB Process) have expressed their interest in collaborating on this project.
This document provides an overview of the Variation Response Method (VRM) simulation toolkit. VRM is a modular CAE simulation toolkit that can model, simulate, and optimize multi-stage production systems considering dimensional variation. It addresses challenges like variation propagation in multi-stage systems. Example applications discussed include optimizing fixture layout and assembly sequence for automotive body parts and controlling gaps for aerospace assemblies. The framework incorporates variation modeling, CAE simulation, and links to artificial intelligence/deep learning modules.
BEES is an end-to-end mission performance simulator for the BIOMASS satellite designed to evaluate expected performance of the mission. It consists of modules for scene generation, system simulation, ionospheric effects, processing, and performance evaluation. BEES simulates the full processing chain from raw data to level 1 and 2 products in a realistic way while including major error sources. Validation of BEES is challenging due to its complexity and random components, requiring statistical comparison to theoretical expectations using large homogeneous scenes and Monte Carlo simulations.
3D oil reservoir model uncertainty: model-derived uncertainty or uncertainty ...Geovariances
Find out more about the importance of the model uncertainty quantification according to the reservoir study stage.
The presentation highlights the difference between the uncertainty quantification and the capacity of prediction of a model. Model uncertainty is due to various factors such as the lack of precise data, the use of imprecise data or the impossibility to conceive with certainty a conceptual model. Some of the factors can be accounted for (known source of uncertainty) and therefore be captured in a model, leading to classical uncertainty quantification. Other factors cannot be accounted for (unknown source of uncertainty), therefore limiting the capacity of prediction of the model.
The document discusses tools and datasets for seismic hazard analysis from site-specific to global scales. It describes the OpenQuake engine and Hazard Modeller's Toolkit (HMTK) which can be used for classical and event-based probabilistic seismic hazard analysis (PSHA) at various scales. The OpenQuake Ground Motion Toolkit helps with selection and weighting of ground motion prediction equations. These tools are applied in site-specific analyses, and for developing national, regional, and global seismic hazard models using various data sources on earthquakes, faults, and strain.
Particle Swarm Optimization for the Path Loss Reduction in Suburban and Rural...IJECEIAES
In the present work, a precise optimization method is proposed for tuning the parameters of the COST231 model to improve its accuracy in the path loss propagation prediction. The Particle Swarm Optimization is used to tune the model parameters. The predictions of the tuned model are compared with the most popular models. The performance criteria selected for the comparison of various empirical path loss models is the Root Mean Square Error (RMSE). The RMSE between the actual and predicted data are calculated for various path loss models. It turned out that the tuned COST 231 model outperforms the other studied models.
How might machine learning help advance solar PV research?Anubhav Jain
Machine learning techniques can help optimize solar PV systems in several ways:
1) Clear sky detection algorithms using ML were developed to more accurately classify sky conditions from irradiance data, improving degradation rate calculations.
2) Site-specific modeling of module voltages over time, validated with field data, allows more optimal string sizing compared to traditional worst-case assumptions.
3) ML and data-driven approaches may help optimize other aspects of solar plant design like climate zone definitions and extracting module parameters from production data.
Acoustic Scene Classification by using Combination of MODWPT and Spectral Fea...ijtsrd
Acoustic Scene Classification ASC is classified audio signals to imply about the context of the recorded environment. Audio scene includes a mixture of background sound and a variety of sound events. In this paper, we present the combination of maximal overlap wavelet packet transform MODWPT level 5 and six sets of time domain and frequency domain features are energy entropy, short time energy, spectral roll off, spectral centroid, spectral flux and zero crossing rate over statistic values average and standard deviation. We used DCASE Challenge 2016 dataset to show the properties of machine learning classifiers. There are several classifiers to address the ASC task. We compare the properties of different classifiers K nearest neighbors KNN , Support Vector Machine SVM , and Ensembles Bagged Trees by using combining wavelet and spectral features. The best of classification methodology and feature extraction are essential for ASC task. In this system, we extract at level 5, MODWPT energy 32, relative energy 32 and statistic values 6 from the audio signal and then extracted feature is applied in different classifiers. Mie Mie Oo | Lwin Lwin Oo "Acoustic Scene Classification by using Combination of MODWPT and Spectral Features" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27992.pdfPaper URL: https://www.ijtsrd.com/computer-science/multimedia/27992/acoustic-scene-classification-by-using-combination-of-modwpt-and-spectral-features/mie-mie-oo
This document describes a Kriging component for spatial interpolation of climatological variables in the OMS modeling framework. Kriging is a geostatistical technique that interpolates values based on measured data and the spatial autocorrelation between data points. The component implements ordinary and detrended Kriging algorithms using 10 semivariogram models. It can interpolate both raster and point data and outputs the interpolated climatological variable values. Links are provided for downloading the component code, data, and OMS project files needed to run the interpolation.
This document presents a Bayesian methodology for retrieving soil parameters like moisture from SAR images. It begins by introducing the importance of soil moisture monitoring and the opportunity provided by Argentina's upcoming SAOCOM SAR satellite. It then discusses limitations of traditional retrieval models in accounting for speckle noise and terrain heterogeneity. The document proposes a Bayesian approach using a multiplicative speckle model within a likelihood function to estimate soil moisture and roughness from SAR backscatter measurements. Simulation results show the Bayesian method retrieves soil moisture across the full measurement space and provides error estimates, with improved precision at higher numbers of looks.
Genetic programming for prediction of local scour at vertical bridge abutmenteSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
The document summarizes GeoScience Software (GS), a geotechnical software package developed by petroleum professionals to provide powerful yet easy-to-use tools for well data analysis, petrophysics, seismic synthetics, mapping, and more at an affordable price. Key features highlighted include GIS integration, well correlations, comprehensive petrophysical analysis, pore pressure and fracture gradient calculations, seismic functions, data extraction and mapping capabilities. The software was designed by professionals to eliminate complex menus and high costs while putting technical tools directly in the hands of users.
The document discusses GeoScience Software, a company that develops affordable yet powerful geotechnical software. It was founded in 1989 by petroleum exploration professionals to create user-friendly software without large costs or need for IT support. The software called GS was developed by geoscience professionals to provide technical tools that are accessible to a wide range of expertise. It has over 600 installations worldwide and offers integrated well data management, petrophysical analysis, correlations, seismic functions, and other capabilities.
In developing complex engineering systems, model-based design approaches often face critical challenges due to pervasive uncertainties and high computational expense. These challenges could be alleviated to a significant extent though informed modeling decisions, such as model substitution, parameter estimation, localized re-sampling, or grid refine- ment. Informed modeling decisions therefore necessitate (currently lacking) design frame- works that effectively integrate design automation and human decision-making. In this paper, we seek to address this necessity in the context of designing wind farm layouts, by taking an information flow perspective of this typical model-based design process. Specif- ically, we develop a visual representation of the uncertainties inherited and generated by models and the inter-model sensitivities. This framework is called the Visually-Informed Decision-Making Platform (VIDMAP) for wind farm design. The eFAST method is used for sensitivity analysis, in order to determine both the first-order and the total-order in- dices. The uncertainties in the independent inputs are quantified based on their observed variance. The uncertainties generated by the upstream models are quantified through a Monte Carlo simulation followed by probabilistic modeling of (i) the error in the output of the models (if high-fidelity estimates are available), or (ii) the deviation in the outputs estimated by different alternatives/versions of the model. The GUI in VIDMAP is cre- ated using value-proportional colors for each model block and inter-model connector, to respectively represent the uncertainty in the model output and the impact (downstream) of the information being relayed by the connector. Wind farm layout optimization (WFLO) serves as an excellent platform to develop and explore VIDMAP, where WFLO is generally performed using low fidelity models, as high-fidelity models (e.g. LES) tend to be compu- tationally prohibitive in this context. The final VIDMAP obtained sheds new light into the sensitivity of wind farm energy estimation on the different models and their associated uncertainties.
Similar to The European [SHARE] Seismic Hazard Model: Genesis, Evolution and Key, Aspects, L. Danciu , J. Woessner, D. Giardini and the SHARE Consortium, GEM reveal 2013 (20)
This document summarizes an integrated probabilistic risk assessment for Turkey. It presents models for seismic hazard, exposure, physical vulnerability, and economic loss for Turkey's major cities. Seismic hazard was modeled using ground motion prediction equations in OpenQuake. Building exposure was captured from census data. Fragility curves related ground shaking to building damage. Combined models calculated physical risk and economic loss. A socio-economic vulnerability index incorporated demographic indicators. Integrating physical risk and vulnerability produced an overall integrated risk assessment for cities like Istanbul and Van.
During the first phase of GEM Risk, several key datasets and tools were developed by the scientific community and made available through GEM. This includes a building taxonomy, exposure models, vulnerability assessment guidelines, and global earthquake consequences and exposure databases that are accessible on the OpenQuake platform. GEM also conducted regional workshops and technical training to facilitate risk assessment collaboration and technology transfer.
The document describes the GEM Foundation's efforts to create a centralized database of global seismic hazard models using common data formats and open-source software. This will allow models to be more easily compared, reproduced and inspected. It will also facilitate combining models and generating new data. Currently the database includes major models from regions around the world. Quality assurance testing has revealed some differences between models when reproduced, calling for further investigation.
The document discusses the development of the GEM Vulnerability Database. The database contains over 750 vulnerability models including fragility functions, vulnerability functions, damage-to-loss functions, and capacity curves. These models describe the probability of damage or loss given various ground motion intensity measures. The database facilitates modeling, comparison of functions, and sharing of results with the scientific community. It contains functions for 37 countries/regions.
The document discusses the OpenQuake-engine software for seismic risk assessment. It can perform probabilistic and scenario-based hazard and risk calculations considering various uncertainties. Different calculators within OpenQuake allow scenario risk assessment, scenario damage assessment, probabilistic event-based risk analysis, and benefit-cost analysis of retrofitting options. The software is open source and can be run on single computers or cloud platforms.
This document summarizes a study that analyzed the damage scenarios for reinforced concrete precast industrial structures in Tuscany, Italy due to earthquakes. The study generated a population of building models based on inventory data and fragility curves. Nonlinear analyses were performed under earthquake ground motions. Limit states like yielding and collapse were defined. The results showed that accounting for both flexural and connection failures provided more accurate fragility curves compared to flexural failures alone. Connection failures were highly dependent on the assumed friction coefficient. Finally, probabilistic collapse maps for a Mw 6.5 scenario earthquake in Tuscany were presented.
This document discusses an integrated risk modeling toolkit and database for earthquake risk assessment. It presents frameworks for integrated risk assessment and modeling social and economic vulnerability. Methods are described for selecting indicators, standardizing data, conducting statistical analysis, weighting factors, and linking results to physical risk estimates. The toolkit allows incorporation of data on populations, economy, infrastructure, and other factors. Areas for further improvement include accounting for uncertainties, qualitative analysis, and application to specific use cases.
Social Vulnerability Datasets through the OpenQuake Platform and Description of a Case-Scenario of Integrated Risk and Resilience using OpenQuake Tools.
The document summarizes the products and applications of GEM's Hazard program. It outlines five global datasets created through international projects including historical earthquake archives, instrumental seismicity catalogs, active fault databases, and ground motion prediction equations. It also describes regional seismic hazard models compiled in a database and the OpenQuake open-source software for calculating seismic hazard and risk. Key applications of the products include use in building codes, insurance catastrophe modeling, and site-specific engineering analyses.
This document discusses city scenario applications of the EMME (Earthquake Model of the Middle East) project. Seven cities - Mashhad, Iran; Gulshan-Karachi, Pakistan; Irbid, Jordan; Tbilisi, Georgia; Yerevan, Armenia; and Tyr City, Lebanon - were selected for deterministic seismic risk assessments involving specified earthquake scenarios. For each city, information on building inventories, site conditions, vulnerability, and expected damage distributions from scenario earthquakes is presented. The document concludes that the city scenario activities provided valuable risk information for local municipalities that could be updated over time.
The document discusses the South America Integrated Risk Assessment (SARA) project, which aims to develop risk models for 13 countries in South America with a total population of over 402 million people. The project focuses on developing exposure and vulnerability models for major cities in the region with informal construction. Several countries, including Colombia, Chile, Ecuador, Peru, and Venezuela, plan to create detailed exposure models and fragility functions for major cities to analyze risk and inform mitigation efforts.
Vitor Silva of the GEM Foundation in Italy analyzed the costs and benefits of retrofitting buildings in Nepal. The analysis considered 2221 locations, 9144 assets across 5 categories, and an area of around 140,000 square kilometers. Models were used to calculate expected damage and losses from earthquakes of different magnitudes, and to compare the annual losses expected with and without retrofitting to determine the benefit-cost ratio of retrofitting. Maps of seismic hazard and optimal retrofit designs were also produced to inform decision making.
The EMME (Earthquake Model of the Middle East) project developed a probabilistic seismic hazard model and seismic risk assessments for multiple countries in the Middle East region from 2009-2014. The project involved compiling strong motion data, developing ground motion prediction equations, performing probabilistic seismic hazard computations, building inventories and vulnerability assessments, and validating models with past earthquake damage observations. Key to the success of the EMME project was obtaining a high level of contribution from partner countries and basing all aspects of the model on local data and expertise.
- Expert elicitation was used to develop fragility functions characterizing building vulnerability to earthquakes around the world. Thirteen experts evaluated vulnerability for generic building types in eight countries, and twelve US and one Canadian experts evaluated selected building types in the US.
- Cooke's method was used to score experts based on their accuracy on seed questions and assign weights to their responses on target questions. This allowed fragility curves to be developed accounting for expert uncertainties.
- The exercises generated over 50 new fragility functions for use in earthquake modeling, providing critical data where empirical models are lacking. Further research is needed to better understand the expert scoring approach.
The document discusses earthquake risk in Nepal and collaboration between the National Society for Earthquake Technology-Nepal (NSET) and the Global Earthquake Model (GEM). It notes that Nepal sits at a plate boundary and faces significant earthquake hazards. Over 60% of buildings in Kathmandu could be destroyed by a major quake, leaving over 1.5 million homeless. While NSET has conducted risk assessments and education, more remains to be done. The document calls for increased collaboration between NSET and GEM to further research, training, and risk reduction efforts.
This document presents a toolkit for integrated risk assessment that combines physical risk and social vulnerability. It describes representing concepts of social vulnerability and integrated risk through data and various statistical and expert opinion approaches. The document then discusses operationalizing concepts of social vulnerability and integrated risk through the development of an open-source integrated risk modeling toolkit and SVIR data viewer. Finally, it introduces a self-evaluation tool for urban earthquake resilience.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
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Speakers:
Bob Boule
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UiPath Test Automation using UiPath Test Suite series, part 5
The European [SHARE] Seismic Hazard Model: Genesis, Evolution and Key, Aspects, L. Danciu , J. Woessner, D. Giardini and the SHARE Consortium, GEM reveal 2013
1. The European [SHARE] Seismic
Hazard Model:
Genesis, Evolution and Key Aspects
L. Danciu , J. Woessner, D. Giardini and the SHARE Consortium
3. European
PSHA
Model:
Goals
Harmonize
hazard
assessment
across
na.onal
borders
On
data
level,
modeling
level
and
procedural
level
Create
a
community-‐based
Cme-‐independent
(rock)
reference
hazard
model
for
the
Euro-‐Mediterranean
region
Keep
close
connec.on
to
engineering
requirements
of
EC8
and
its
future
revision
4. European
PSHA
Model:
Goals
Hazard
So@ware
“Black
Box”
INPUT
OUTPUT
“Easy
Review”
Box
Data
Interpreta.ons
Assump.ons
All
steps
of
the
seismic
hazard
assessment
have
to
be:
• Validated
• Benchmarked
• Reproducible
All
data
is
documented
and
open
to
access!
11. Building the SHARE Source Model
TradiConal
Area
Source
(AS)
Model
Fault
Source
(FS)
+
Background
(BG)
Model
Smoothed
Seismicity
Model
(Woo,
1996;
Grünthal
et
al.,
in
prep)
StochasCc
Earthquake
Source
Model
(Hiemer
et
al.;
Woessner
et
al.;
in
prep.)
31. R.
Basili
et
al
2013
hbp://diss.rm.ingv.it/share-‐edsf/
32. SHARE Source Model Logic Tree
StochasCc
Earthquake
Source
Model
(Hiemer
et
al.;
Woessner
et
al.;
in
prep.)
33. Kernel Smooth Seismicity and Fault Model
Seismicity
Faults
(SSZ)
Procedure
1. Calculate spatial location PDFs
Smoothed Seismicity: PE
Smoothed Faults: PF
2. Weighting
Linear weighting according to
probabilities PF and PE
3. Calculate earthquake rate
Only Seismicity: R=PE*N(MW=6.5)
Only Faults: R=PF*N(MW=8.5)
Seismicity
Faults
Normalized
Earthquake
Rate
34. Kernel Smooth Seismicity and Fault Model
Optimize kernel using a
CSEP likelihood tests
Split catalog in learning and
target period
Optimize on 5 year target
period
Use best likelihood-value to
generate model rates
Learning Period Target Period
1000 2002 2007
38. Procedure to the SHARE-GMPE Logic Tree
Engineering requirements
were (WP2) defined as
constraint at the beginning of
the project (a “wish list”)
Differences in coverage of
magnitude – distance and
frequency range poses
challenges for hazard
computation
Delavaud
et
al.,
2012,
J.
Seis.
39. Procedure to the SHARE-GMPE Logic Tree
SHARE
-‐
Strong
Ground
Mo.on
Dataset
(Scherbaum
et
al.
[2009];
Delavaud
et
al.
[2009])
Experts
Opinion
Data
Driven
40. SHARE - GMPE Logic Tree
Delavaud
et
al.,
2012,
J.
Seis.
41. SHARE Logic Tree Weights
• Proposed weighting schemes for active shallow crust:!
45. Quality Checks
Moment comparisons to strain rate model for
the single source models
CSEP rate forecast test vs. independent
data of USGS / NEIC
Comparison to previous hazard
assessments
Sensitivity analysis on
Depth distribution
Point source vs. Extended source
calculations