This document provides a retrospective on the past 30 years (1975-2004) of dynamical seasonal prediction and conjectures about its future. It discusses key historical contributions in weather predictability and prediction from researchers around the world. It outlines progress from numerical weather prediction to dynamical seasonal prediction, including early work demonstrating monthly and seasonal predictability. Factors limiting predictability of the coupled climate system are discussed. Challenges remaining include improving coupled climate models, observations, computing power, and applications. The document concludes that while weather prediction skill has improved 50% over 25 years, seasonal prediction skill remains limited by incomplete understanding and models, though continued progress is expected.
Numerous studies have found an average increase in extreme precipitation for both the U.S. and Northern Hemisphere mid-latitude land areas, consistent with the expectations arising from the observed increase in greenhouse gas concentrations (now more than 40% above pre-industrial levels). However, there are important regional variations in these trends that are not fully explained. These trend studies are typically based on direct analyses of observational station data. Such analyses confront multiple challenges, such as incomplete data and uneven spatial coverage of stations. Central scientific questions related to this general finding are: Are there changes in weather system phenomenology that are contributing to this observed increase? What is the contribution of increases in atmospheric water vapor? There are also questions related to application of potential future changes in planning. Because of the rarity (by definition) of extreme events, trends are mostly found only when aggregating over space. When would we expect to see a signal at the local level? What are the uncertainties surrounding future changes and their potential incorporation into future design? Further development of statistical/mathematical methods, or innovative application of existing methods, is desirable to aid scientists in exploring these central scientific questions. This talk will describe characteristics of the observation record and the issues surrounding the above questions.
Modern weather forecasting relies on numerical weather prediction (NWP) models that integrate systems of equations governing atmospheric processes. NWP models have evolved from early conceptual models to high-resolution global and regional models run on supercomputers. Continuous observations from satellites and other sensors are assimilated using data assimilation techniques to initialize models. Ensemble modeling addresses forecast uncertainty. Though limited by incomplete understanding and observations, NWP provides increasingly accurate forecasts out to around two weeks.
Proposal Presentation - Morphology of cyclonic storms in the South Pacific Re...Ashneel Chandra
This presentation discusses using Very Low Frequency (VLF) radio waves emitted during lightning strikes to track tropical cyclones in the South Pacific region. The objectives are to analyze lightning activity during cyclone and non-cyclone seasons, quantify lightning variation along cyclone tracks, and examine correlations between cyclones and solar/geomagnetic activity. The methodology involves analyzing lightning and geomagnetic data, as well as sea surface temperature and wind speed data along cyclone tracks. The results could help forecast cyclone intensification using VLF radio waves and understand long-term trends related to solar activity.
Climate science part 3 - climate models and predicted climate changeLPE Learning Center
Many lines of evidence, from ice cores to marine deposits, indicate that Earth’s temperature, sea level, and distribution of plant and animal species have varied substantially throughout history. Ice cores from Antarctica suggest that over the past 400,000 years global temperature has varied as much as 10 degrees Celsius through ice ages and periods warmer than today. Before human influence, natural factors (such as the pattern of earth’s orbit and changes in ocean currents) are believed to be responsible for climate changes. For more, visit: http://www.extension.org/69150
Climate Change effect in Thailand and ASEAN regionipcc-media
A changing climate leads to more extreme weather and climate events. This document discusses climate change projections for Thailand using downscaled global climate models. It summarizes observed temperature and rainfall trends from 1965-1989 to 1990-2006 and projects further increases in temperature and changes in rainfall patterns for Thailand through the 21st century depending on greenhouse gas emission scenarios. Time series, maps and bar charts are presented to illustrate observed trends and modeled projections at regional and local scales down to 200 meters.
Numerical weather prediction has greatly improved forecast accuracy over the past 50 years. Prior to 1955, forecasting was subjective and not very skillful, relying on extrapolating weather patterns. Developments like computers, satellites, radar, and the establishment of observation networks allowed creating numerical models based on atmospheric equations. Ensemble prediction now provides probabilistic forecasts capturing forecast uncertainty by running models with different initializations. While resolution has increased, the chaotic nature of the atmosphere means uncertainty remains, requiring probabilistic forecasts over single predictions.
This document summarizes research on monsoon rainfall forecasting in India. It discusses:
1) The importance of monsoon prediction and approaches to long-term and short-term forecasting. Long-term prediction models use statistical correlations with ocean and atmospheric parameters, while short-term relies on numerical weather prediction models.
2) Factors used in the Indian Meteorological Department's long-term statistical forecasts in March/April and May/June, which include sea surface temperatures and pressures.
3) Evidence that short-term daily rainfall shows a scale-invariant power law distribution, making it difficult to predict precisely at a single location but easier when averaged over multiple locations.
4) The use of
Numerous studies have found an average increase in extreme precipitation for both the U.S. and Northern Hemisphere mid-latitude land areas, consistent with the expectations arising from the observed increase in greenhouse gas concentrations (now more than 40% above pre-industrial levels). However, there are important regional variations in these trends that are not fully explained. These trend studies are typically based on direct analyses of observational station data. Such analyses confront multiple challenges, such as incomplete data and uneven spatial coverage of stations. Central scientific questions related to this general finding are: Are there changes in weather system phenomenology that are contributing to this observed increase? What is the contribution of increases in atmospheric water vapor? There are also questions related to application of potential future changes in planning. Because of the rarity (by definition) of extreme events, trends are mostly found only when aggregating over space. When would we expect to see a signal at the local level? What are the uncertainties surrounding future changes and their potential incorporation into future design? Further development of statistical/mathematical methods, or innovative application of existing methods, is desirable to aid scientists in exploring these central scientific questions. This talk will describe characteristics of the observation record and the issues surrounding the above questions.
Modern weather forecasting relies on numerical weather prediction (NWP) models that integrate systems of equations governing atmospheric processes. NWP models have evolved from early conceptual models to high-resolution global and regional models run on supercomputers. Continuous observations from satellites and other sensors are assimilated using data assimilation techniques to initialize models. Ensemble modeling addresses forecast uncertainty. Though limited by incomplete understanding and observations, NWP provides increasingly accurate forecasts out to around two weeks.
Proposal Presentation - Morphology of cyclonic storms in the South Pacific Re...Ashneel Chandra
This presentation discusses using Very Low Frequency (VLF) radio waves emitted during lightning strikes to track tropical cyclones in the South Pacific region. The objectives are to analyze lightning activity during cyclone and non-cyclone seasons, quantify lightning variation along cyclone tracks, and examine correlations between cyclones and solar/geomagnetic activity. The methodology involves analyzing lightning and geomagnetic data, as well as sea surface temperature and wind speed data along cyclone tracks. The results could help forecast cyclone intensification using VLF radio waves and understand long-term trends related to solar activity.
Climate science part 3 - climate models and predicted climate changeLPE Learning Center
Many lines of evidence, from ice cores to marine deposits, indicate that Earth’s temperature, sea level, and distribution of plant and animal species have varied substantially throughout history. Ice cores from Antarctica suggest that over the past 400,000 years global temperature has varied as much as 10 degrees Celsius through ice ages and periods warmer than today. Before human influence, natural factors (such as the pattern of earth’s orbit and changes in ocean currents) are believed to be responsible for climate changes. For more, visit: http://www.extension.org/69150
Climate Change effect in Thailand and ASEAN regionipcc-media
A changing climate leads to more extreme weather and climate events. This document discusses climate change projections for Thailand using downscaled global climate models. It summarizes observed temperature and rainfall trends from 1965-1989 to 1990-2006 and projects further increases in temperature and changes in rainfall patterns for Thailand through the 21st century depending on greenhouse gas emission scenarios. Time series, maps and bar charts are presented to illustrate observed trends and modeled projections at regional and local scales down to 200 meters.
Numerical weather prediction has greatly improved forecast accuracy over the past 50 years. Prior to 1955, forecasting was subjective and not very skillful, relying on extrapolating weather patterns. Developments like computers, satellites, radar, and the establishment of observation networks allowed creating numerical models based on atmospheric equations. Ensemble prediction now provides probabilistic forecasts capturing forecast uncertainty by running models with different initializations. While resolution has increased, the chaotic nature of the atmosphere means uncertainty remains, requiring probabilistic forecasts over single predictions.
This document summarizes research on monsoon rainfall forecasting in India. It discusses:
1) The importance of monsoon prediction and approaches to long-term and short-term forecasting. Long-term prediction models use statistical correlations with ocean and atmospheric parameters, while short-term relies on numerical weather prediction models.
2) Factors used in the Indian Meteorological Department's long-term statistical forecasts in March/April and May/June, which include sea surface temperatures and pressures.
3) Evidence that short-term daily rainfall shows a scale-invariant power law distribution, making it difficult to predict precisely at a single location but easier when averaged over multiple locations.
4) The use of
This document compares in situ wind speed observations from Wave Glider deployments in the Southern Ocean to several satellite-derived and reanalysis wind products. The study finds that the ECMWF reanalysis product best represents the temporal variability of winds compared to in situ data. However, the NCEP/NCAR Reanalysis II product matches observed trends in deviation from the mean wind speed and best depicts the mean wind state, especially during high wind periods. Overall, the high-resolution ECMWF product performs best during lower wind conditions with lower wind speed biases across categories.
This document discusses using an Earth System Model (ESM) based on the NCEP Climate Forecast System (CFS) to project future changes in the South Asian monsoon under changing climate conditions. It notes challenges in modeling the monsoon including uncertainties in present-day simulations. It outlines the ESM development strategy at the Indian Institute of Tropical Meteorology including incorporating aerosol, biogeochemistry and ecosystem modules into CFS. Validation of CFS shows reasonable representation of climatological rainfall and variability. Analyses of CFS droughts suggest atmosphere-ocean coupling and monsoon-midlatitude interactions can influence droughts.
The document discusses equations of motion used in weather forecasting and climate change studies. It begins with an introduction to geophysical fluid dynamics and the distinguishing effects of rotation and stratification. It then outlines the basic equations of motion, including conservation of momentum, mass, energy, and state. It describes how these equations are solved on grids using numerical models. It discusses the challenges of modeling processes at different spatial scales from synoptic to urban. It also addresses challenges in tropical weather prediction and how dynamical prediction of weather over South Asia has improved.
DSD-INT 2017 Moth plant dispersion Modelling based on synoptic weather patter...Deltares
Presentation by Chris van Diemen, University of Amsterdam (UvA), Netherlands, at the Delft3D - User Days (Day 1: Hydrodynamics), during Delft Software Days - Edition 2017. Monday, 30 October 2017, Delft.
Climate models are mathematical representations of physical processes that determine climate. They are used to understand climate processes and project future climate scenarios. Simplifications are needed due to complex interactions and limited computational capabilities. Models have improved over time with increased resolution and process representation. Observational evidence shows unequivocal warming globally with some regional precipitation variability. Projections show continued warming and changes in precipitation patterns for South Asia over the 21st century, but models have uncertainties. Continued improvements aim to better capture regional climate impacts.
This document provides an introduction to a university course on meteorology and weather forecasting. It outlines the course content which includes 10 lectures on basic meteorology concepts and 8 workshops on hands-on forecasting exercises. It also lists core reading materials and meteorological resources available online. The document describes different methods of weather forecasting from simple persistence to modern numerical weather prediction models run on powerful computers.
01 introduction TO METEROLOGY AND WEATHER FORECASTINGAbdulkarim Shaik
This document provides an introduction to a university course on meteorology and weather forecasting. It outlines the course content which includes 10 lectures on basic meteorology concepts and 8 workshops on hands-on forecasting exercises. It also lists core reading materials and meteorological resources available online. The document describes different methods of weather forecasting from simple persistence to modern numerical weather prediction models run on powerful computers.
This document provides an introduction to a university course on meteorology and weather forecasting. It outlines the course content which includes 10 lectures on basic meteorology concepts and 8 workshops on hands-on forecasting exercises. It also lists core reading materials and meteorological resources available online. The document describes different methods of weather forecasting from simple persistence to modern numerical weather prediction models run on powerful computers.
This document provides an introduction to a university course on meteorology and weather forecasting. It outlines the course content which includes 10 lectures on basic meteorology concepts and 8 workshops on hands-on forecasting exercises. It also lists core reading materials and meteorological resources available online. The document describes different methods of weather forecasting from simple persistence to modern numerical prediction and how forecasts have evolved with increasing computational power.
Day 2 divas basnet, nepal development research institute (ndri), nepal, arrcc...ICIMOD
This document discusses a climate risk assessment of the hydropower sector in Nepal and the issues around using climate projections. It notes that Nepal has complex climate, hydrology and topography that makes future climate change highly uncertain. Some challenges in using climate projections include deep uncertainty in the projections due to data scarcity and model limitations. Downscaling and bias correction of projections is difficult due to scarce observations and current climate variability. Climate models have varying skill in modeling the Asian monsoon, especially in mountainous regions like the Himalayas. There are also communication gaps between climate scientists, hydrologists, and decision makers regarding the principles and dynamics of climate models.
Models provide a 4D framework for assimilating observations over time and smoothing measurements. Satellite data provides numerous measurements like visible imagery, infrared imagery, sea surface temperatures, and winds that increase understanding of atmospheric conditions, though some data represents vertical integrals or surface values that are difficult to locate precisely. Reanalysis allows improved modeling of past weather.
ROLE OF INDIAN INSTITUTE OF TROPICAL INSTITUTEAbhimanyu Tomar
The document discusses the history and functions of the Indian Institute of Tropical Meteorology (IITM). It notes that IITM was established in 1962 to study tropical weather and the Indian monsoon. Its research focuses on weather forecasting, climatology, monsoon studies, and other areas. IITM conducts both fundamental research and more application-oriented studies to understand atmospheric processes and their impacts. It carries out field experiments and develops forecasting models to advance knowledge in meteorology and support national development goals.
Climate Modeling and Future Climate Change ProjectionsJesbin Baidya
Climate models are mathematical representations of the physical processes that control the climate system. The most sophisticated climate models are called General Circulation Models (GCMs) which attempt to simulate all relevant atmospheric and oceanic processes. GCMs are based on fundamental laws of physics and solve complex equations using computers. They allow scientists to project potential future climate changes from increasing greenhouse gases by assessing how the climate system may respond to restore equilibrium. While climate models have uncertainties, they provide valuable insights when evaluated against historical climate data.
This document discusses using MODIS time-series data and eddy-covariance flux data to analyze phenological patterns in boreal forests. The research aims to determine the reliability of using satellite-derived NDVI data compared to ground-based CO2 flux data for identifying the start and end dates of the growing season. The study area is located in Hyytiälä, Finland. 10 years of MODIS NDVI and eddy covariance CO2 flux data from 2003-2012 are analyzed to compare the growing season start and end dates derived from each dataset. The results show some differences in the timing identified by the two methods, highlighting challenges in accurately determining phenological transition dates.
1) The document reconstructs sparse dissolved inorganic carbon (DIC) observations in the Southern Ocean using a neural network mapping method.
2) The mean amplitude of the surface seasonal cycle in DIC is estimated to be 13 μmol/kg, with maxima occurring in austral spring and minima in austral autumn.
3) Estimates of net community production in summer indicate a drawdown of 1.3±0.9 petagrams of carbon, with most removal occurring north of the Antarctic Circumpolar Current.
4) Preliminary results suggest inter-annual variability in DIC is dominated by an anthropogenic trend, strongest in ocean uptake regions between 35-55°S.
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.
The document discusses a methodology for improving wind speed forecasts through synergizing outputs from two numerical weather prediction (NWP) models - the Global Environmental Multiscale model (GEM) and the North American Mesoscale model (NAM). Wind speed measurements from four meteorological towers are used to evaluate the individual NWP models and their combined forecasts. Results show the combined GEM-NAM forecasts reduce root mean square error by up to 20% compared to the individual models, indicating improved forecast accuracy through optimal combination of the two NWP models.
The document discusses the possibility of controlling global weather through small, precise perturbations to the atmosphere. It describes how the chaotic nature of the atmosphere implies sensitivity to small changes and suggests a series of small perturbations may control weather evolution. It outlines components a global weather control system may have, including advanced numerical weather prediction, satellite sensing, and methods to introduce perturbations. It also presents an experiment using data assimilation to calculate perturbations needed to slightly alter a hurricane's track as a proof of concept.
1. The document discusses methods for separating forced and unforced climate variability and identifying patterns of multidecadal predictability.
2. A new statistical method is used to identify an unforced, multidecadal sea surface temperature pattern in simulations and observations.
3. Forced warming is estimated to contribute 0.1K per decade, while an identified internal multidecadal pattern explains about 0.1C fluctuations in global average sea surface temperature over decades.
This document provides an overview of the Center for Ocean-Land-Atmosphere Studies (COLA). COLA conducts research on climate variability and predictability using climate models and reanalysis data. It has a team of climate scientists and supports PhD students at George Mason University. COLA receives multi-agency funding through a jointly peer-reviewed grant and has been recognized as a national center of excellence for its work on seasonal to decadal prediction and understanding land-atmosphere interactions. COLA scientists collaborate with modeling centers like NCAR, NASA, NOAA and contribute to climate model development and multi-model ensembles to advance predictive capability.
This document discusses global warming and presents evidence that it is real and poses serious risks. It summarizes the greenhouse effect and increasing carbon dioxide levels in the atmosphere. Observed impacts include rising temperatures worldwide, melting glaciers and sea ice, and shifting species ranges. Projected impacts include more extreme heat waves, worsening droughts and wildfires, rising sea levels submerging coastal areas, and altered precipitation patterns exacerbating problems for agriculture and water resources. Addressing global warming requires international cooperation given uneven contributions to the problem and effects. Improving climate prediction is important to managing associated risks through adaptation and mitigation efforts.
This document compares in situ wind speed observations from Wave Glider deployments in the Southern Ocean to several satellite-derived and reanalysis wind products. The study finds that the ECMWF reanalysis product best represents the temporal variability of winds compared to in situ data. However, the NCEP/NCAR Reanalysis II product matches observed trends in deviation from the mean wind speed and best depicts the mean wind state, especially during high wind periods. Overall, the high-resolution ECMWF product performs best during lower wind conditions with lower wind speed biases across categories.
This document discusses using an Earth System Model (ESM) based on the NCEP Climate Forecast System (CFS) to project future changes in the South Asian monsoon under changing climate conditions. It notes challenges in modeling the monsoon including uncertainties in present-day simulations. It outlines the ESM development strategy at the Indian Institute of Tropical Meteorology including incorporating aerosol, biogeochemistry and ecosystem modules into CFS. Validation of CFS shows reasonable representation of climatological rainfall and variability. Analyses of CFS droughts suggest atmosphere-ocean coupling and monsoon-midlatitude interactions can influence droughts.
The document discusses equations of motion used in weather forecasting and climate change studies. It begins with an introduction to geophysical fluid dynamics and the distinguishing effects of rotation and stratification. It then outlines the basic equations of motion, including conservation of momentum, mass, energy, and state. It describes how these equations are solved on grids using numerical models. It discusses the challenges of modeling processes at different spatial scales from synoptic to urban. It also addresses challenges in tropical weather prediction and how dynamical prediction of weather over South Asia has improved.
DSD-INT 2017 Moth plant dispersion Modelling based on synoptic weather patter...Deltares
Presentation by Chris van Diemen, University of Amsterdam (UvA), Netherlands, at the Delft3D - User Days (Day 1: Hydrodynamics), during Delft Software Days - Edition 2017. Monday, 30 October 2017, Delft.
Climate models are mathematical representations of physical processes that determine climate. They are used to understand climate processes and project future climate scenarios. Simplifications are needed due to complex interactions and limited computational capabilities. Models have improved over time with increased resolution and process representation. Observational evidence shows unequivocal warming globally with some regional precipitation variability. Projections show continued warming and changes in precipitation patterns for South Asia over the 21st century, but models have uncertainties. Continued improvements aim to better capture regional climate impacts.
This document provides an introduction to a university course on meteorology and weather forecasting. It outlines the course content which includes 10 lectures on basic meteorology concepts and 8 workshops on hands-on forecasting exercises. It also lists core reading materials and meteorological resources available online. The document describes different methods of weather forecasting from simple persistence to modern numerical weather prediction models run on powerful computers.
01 introduction TO METEROLOGY AND WEATHER FORECASTINGAbdulkarim Shaik
This document provides an introduction to a university course on meteorology and weather forecasting. It outlines the course content which includes 10 lectures on basic meteorology concepts and 8 workshops on hands-on forecasting exercises. It also lists core reading materials and meteorological resources available online. The document describes different methods of weather forecasting from simple persistence to modern numerical weather prediction models run on powerful computers.
This document provides an introduction to a university course on meteorology and weather forecasting. It outlines the course content which includes 10 lectures on basic meteorology concepts and 8 workshops on hands-on forecasting exercises. It also lists core reading materials and meteorological resources available online. The document describes different methods of weather forecasting from simple persistence to modern numerical weather prediction models run on powerful computers.
This document provides an introduction to a university course on meteorology and weather forecasting. It outlines the course content which includes 10 lectures on basic meteorology concepts and 8 workshops on hands-on forecasting exercises. It also lists core reading materials and meteorological resources available online. The document describes different methods of weather forecasting from simple persistence to modern numerical prediction and how forecasts have evolved with increasing computational power.
Day 2 divas basnet, nepal development research institute (ndri), nepal, arrcc...ICIMOD
This document discusses a climate risk assessment of the hydropower sector in Nepal and the issues around using climate projections. It notes that Nepal has complex climate, hydrology and topography that makes future climate change highly uncertain. Some challenges in using climate projections include deep uncertainty in the projections due to data scarcity and model limitations. Downscaling and bias correction of projections is difficult due to scarce observations and current climate variability. Climate models have varying skill in modeling the Asian monsoon, especially in mountainous regions like the Himalayas. There are also communication gaps between climate scientists, hydrologists, and decision makers regarding the principles and dynamics of climate models.
Models provide a 4D framework for assimilating observations over time and smoothing measurements. Satellite data provides numerous measurements like visible imagery, infrared imagery, sea surface temperatures, and winds that increase understanding of atmospheric conditions, though some data represents vertical integrals or surface values that are difficult to locate precisely. Reanalysis allows improved modeling of past weather.
ROLE OF INDIAN INSTITUTE OF TROPICAL INSTITUTEAbhimanyu Tomar
The document discusses the history and functions of the Indian Institute of Tropical Meteorology (IITM). It notes that IITM was established in 1962 to study tropical weather and the Indian monsoon. Its research focuses on weather forecasting, climatology, monsoon studies, and other areas. IITM conducts both fundamental research and more application-oriented studies to understand atmospheric processes and their impacts. It carries out field experiments and develops forecasting models to advance knowledge in meteorology and support national development goals.
Climate Modeling and Future Climate Change ProjectionsJesbin Baidya
Climate models are mathematical representations of the physical processes that control the climate system. The most sophisticated climate models are called General Circulation Models (GCMs) which attempt to simulate all relevant atmospheric and oceanic processes. GCMs are based on fundamental laws of physics and solve complex equations using computers. They allow scientists to project potential future climate changes from increasing greenhouse gases by assessing how the climate system may respond to restore equilibrium. While climate models have uncertainties, they provide valuable insights when evaluated against historical climate data.
This document discusses using MODIS time-series data and eddy-covariance flux data to analyze phenological patterns in boreal forests. The research aims to determine the reliability of using satellite-derived NDVI data compared to ground-based CO2 flux data for identifying the start and end dates of the growing season. The study area is located in Hyytiälä, Finland. 10 years of MODIS NDVI and eddy covariance CO2 flux data from 2003-2012 are analyzed to compare the growing season start and end dates derived from each dataset. The results show some differences in the timing identified by the two methods, highlighting challenges in accurately determining phenological transition dates.
1) The document reconstructs sparse dissolved inorganic carbon (DIC) observations in the Southern Ocean using a neural network mapping method.
2) The mean amplitude of the surface seasonal cycle in DIC is estimated to be 13 μmol/kg, with maxima occurring in austral spring and minima in austral autumn.
3) Estimates of net community production in summer indicate a drawdown of 1.3±0.9 petagrams of carbon, with most removal occurring north of the Antarctic Circumpolar Current.
4) Preliminary results suggest inter-annual variability in DIC is dominated by an anthropogenic trend, strongest in ocean uptake regions between 35-55°S.
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.
The document discusses a methodology for improving wind speed forecasts through synergizing outputs from two numerical weather prediction (NWP) models - the Global Environmental Multiscale model (GEM) and the North American Mesoscale model (NAM). Wind speed measurements from four meteorological towers are used to evaluate the individual NWP models and their combined forecasts. Results show the combined GEM-NAM forecasts reduce root mean square error by up to 20% compared to the individual models, indicating improved forecast accuracy through optimal combination of the two NWP models.
The document discusses the possibility of controlling global weather through small, precise perturbations to the atmosphere. It describes how the chaotic nature of the atmosphere implies sensitivity to small changes and suggests a series of small perturbations may control weather evolution. It outlines components a global weather control system may have, including advanced numerical weather prediction, satellite sensing, and methods to introduce perturbations. It also presents an experiment using data assimilation to calculate perturbations needed to slightly alter a hurricane's track as a proof of concept.
1. The document discusses methods for separating forced and unforced climate variability and identifying patterns of multidecadal predictability.
2. A new statistical method is used to identify an unforced, multidecadal sea surface temperature pattern in simulations and observations.
3. Forced warming is estimated to contribute 0.1K per decade, while an identified internal multidecadal pattern explains about 0.1C fluctuations in global average sea surface temperature over decades.
This document provides an overview of the Center for Ocean-Land-Atmosphere Studies (COLA). COLA conducts research on climate variability and predictability using climate models and reanalysis data. It has a team of climate scientists and supports PhD students at George Mason University. COLA receives multi-agency funding through a jointly peer-reviewed grant and has been recognized as a national center of excellence for its work on seasonal to decadal prediction and understanding land-atmosphere interactions. COLA scientists collaborate with modeling centers like NCAR, NASA, NOAA and contribute to climate model development and multi-model ensembles to advance predictive capability.
This document discusses global warming and presents evidence that it is real and poses serious risks. It summarizes the greenhouse effect and increasing carbon dioxide levels in the atmosphere. Observed impacts include rising temperatures worldwide, melting glaciers and sea ice, and shifting species ranges. Projected impacts include more extreme heat waves, worsening droughts and wildfires, rising sea levels submerging coastal areas, and altered precipitation patterns exacerbating problems for agriculture and water resources. Addressing global warming requires international cooperation given uneven contributions to the problem and effects. Improving climate prediction is important to managing associated risks through adaptation and mitigation efforts.
This document summarizes recent evidence on the co-benefits of climate policies from various studies and models. Key points include:
1) Energy efficiency measures often have negative costs and provide direct financial benefits to consumers without considering externalities of energy use. However, free markets are sub-optimal and underinvest in efficiency.
2) Climate policies that stabilize emissions at 450 ppm have significant co-benefits like reducing health costs from air pollution, lowering energy imports and costs, and increasing economic productivity.
3) Models like the IEA WEO and ETP show the energy sector investments needed to transition to low-carbon technologies can be largely offset by fuel savings over time, even with a 10% discount
This document summarizes research conducted at Mt. Almagre, Colorado to update the bristlecone pine tree ring chronology originally developed in the 1980s. 64 new core samples were taken from 36 trees, with 38 cores from 20 trees near the original Graybill site. Preliminary analysis found the new chronology matched the original well but showed a "divergence problem" of declining ring widths in recent decades, inconsistent with expectations of increasing growth due to warming. The findings suggest this high elevation, southern site is moisture-limited and its tree rings may not be reliable temperature proxies as previously thought. Challenges in modeling growth of trees with strip bark were also noted.
1) The document summarizes key findings from the IPCC's Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) regarding trends and projections for various climate extremes including floods, hurricanes, tornadoes, heat waves, drought, and wildfires.
2) The SREX found low confidence in attributed changes to many extremes due to lack of historical trends, but projected increases in some extremes like heat waves and drought in some regions.
3) The document discusses examples of extreme events from history that challenge the notion that recent extremes are unprecedented, such as the deadly 1936 North American heat wave.
1. The document summarizes key findings from an NRC panel and McIntyre's work that are critical of some climate reconstruction studies.
2. It notes that the NRC panel agreed with McIntyre that bristlecone pines are flawed proxies that should be avoided, and that some reconstructions could not claim the warmest years or decades.
3. The document also shows that just a few problematic proxies like bristlecone pines and the Yamal chronology seem to drive conclusions of modern warming being unprecedented, and that alternative reconstructions without these proxies show more comparable medieval warming.
This document provides context and background related to the "Climategate" emails by summarizing key events and studies from 1998-2010 involving climate scientists whose communications were released. It discusses proxy temperature reconstructions by Briffa and Mann that showed warming trends, debates around presenting this data to policymakers, concerns about the "divergence problem" in tree-ring data after 1960, and the handling of proxy data in IPCC reports. The author aims to give a factual perspective on the scientists' discussions and decisions revealed in the Climategate emails without making a judgment on the validity of climate science.
1) The document summarizes Stephen McIntyre's presentation to the House Energy and Commerce Committee on issues with the "hockey stick" temperature reconstruction and climate data access.
2) Key points from multiple panels and studies are that Mann's principal components method was biased towards producing a hockey stick shape, claims of statistical significance were overstated, and using bristlecone pines should be avoided.
3) The document argues that simple measures could improve data access policies regardless of views on climate policy.
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.
ESPP presentation to EU Waste Water Network, 4th June 2024 “EU policies driving nutrient removal and recycling
and the revised UWWTD (Urban Waste Water Treatment Directive)”
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Leonel Morgado
Current descriptions of immersive learning cases are often difficult or impossible to compare. This is due to a myriad of different options on what details to include, which aspects are relevant, and on the descriptive approaches employed. Also, these aspects often combine very specific details with more general guidelines or indicate intents and rationales without clarifying their implementation. In this paper we provide a method to describe immersive learning cases that is structured to enable comparisons, yet flexible enough to allow researchers and practitioners to decide which aspects to include. This method leverages a taxonomy that classifies educational aspects at three levels (uses, practices, and strategies) and then utilizes two frameworks, the Immersive Learning Brain and the Immersion Cube, to enable a structured description and interpretation of immersive learning cases. The method is then demonstrated on a published immersive learning case on training for wind turbine maintenance using virtual reality. Applying the method results in a structured artifact, the Immersive Learning Case Sheet, that tags the case with its proximal uses, practices, and strategies, and refines the free text case description to ensure that matching details are included. This contribution is thus a case description method in support of future comparative research of immersive learning cases. We then discuss how the resulting description and interpretation can be leveraged to change immersion learning cases, by enriching them (considering low-effort changes or additions) or innovating (exploring more challenging avenues of transformation). The method holds significant promise to support better-grounded research in immersive learning.
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
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/
Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...Travis Hills MN
Travis Hills of Minnesota developed a method to convert waste into high-value dry fertilizer, significantly enriching soil quality. By providing farmers with a valuable resource derived from waste, Travis Hills helps enhance farm profitability while promoting environmental stewardship. Travis Hills' sustainable practices lead to cost savings and increased revenue for farmers by improving resource efficiency and reducing waste.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
The technology uses reclaimed CO₂ as the dyeing medium in a closed loop process. When pressurized, CO₂ becomes supercritical (SC-CO₂). In this state CO₂ has a very high solvent power, allowing the dye to dissolve easily.
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.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Deep Software Variability and Frictionless Reproducibility
shukla_jnwp50.ppt
1. Center for Ocean-Land-
Atmosphere Studies
Dynamical Season Prediction: A
Personal Retrospective of the Past 30
Years (1975-2004), and Conjectures
about the Future
J. Shukla
George Mason University (GMU)
Center for Ocean-Land-Atmosphere Studies (COLA)
with contributions from:
J. Kinter (COLA)
Symposium on the 50th Anniversary of Operational Numerical
Weather Prediction
University of Maryland, June 14-17, 2004
2. Center for Ocean-Land-
Atmosphere Studies
Outline
• Historical Overview: The 50 years Preceding JNWP50
• International Contributions to NWP
• The First 90-day Integration of the NMC Forecast Model
– DERF: NMC-COLA Collaboration (1983-1984)
• From NWP to DSP to Coupled Model Prediction
• Dynamical Seasonal Prediction: The Current Status
• Dynamical Seasonal Prediction: Future Prospects
• Conclusions, Conjectures and Suggestions
3. Center for Ocean-Land-
Atmosphere Studies
The 50 Years Preceding JNWP50
• V. Bjerknes (1904) Equations of Motion
– Father of J. Bjerknes, son and research assistant of C. Bjerknes (Hertz, Helmholtz)
• L. F. Richardson (1922) Manual Numerical Weather Prediction
– Military background, later a pacifist, estimated death toll in wars
• C. G. Rossby (1939) Barotropic Vorticity Equation
– First “Synoptic and Dynamic” Meteorologist; Founder of Meteorology Programs at
MIT, Chicago, Stockholm
• J. Charney (1949) Filtered Dynamical Equations for NWP
– First Ph.D. student at UCLA; Chicago, Oslo, Institute for Advanced Study, MIT
• N. A. Phillips (1956) General Circulation Model
– Father of Climate Modeling; Chicago, Institute for Advanced Study, MIT
4. Center for Ocean-Land-
Atmosphere Studies
Global Contributions Towards Research on
Predictability and Prediction of Weather
– USA: Predictability: Charney et al., Lorenz;
NWP: Cressman, Phillips, Miyakoda
– Canada: Numerical methods: Robert; Data assimilation: Daley
– Australia: Spectral model: Bourke
– France: Data assimilation: Talagrand
– U.K.: Theory: Eady; NWP: Sutcliff, Sawyer
– Germany:Theory: Ertel; NWP: Hinkelmann
– Norway: Theory: Eliassen
– Russia: Theory: Obukhov, Monin, Kibel; Adjoint: Marchuk
Data assimilation: Gandin
– Japan: NWP: Fujiwara, Syono, Gambo
– Sweden: Initialization: Machenauer; NWP: Bengtsson
5. Center for Ocean-Land-
Atmosphere Studies
Weather Predictability and Prediction
• Predictability and theory: Charney et al., Lorenz, Eady; Ertel, Eliassen,
Obukhov, Monin, Kibel
• NWP: Cressman, Phillips, Miyakoda, Hinkelmann, Sutcliff, Sawyer, Syono,
Gambo, Bengtsson
• Numerical methods: Robert, Bourke, Marchuk
• Data assimilation: Daley, Talagrand, Gandin
• Initialization: Machenauer, Baer and Tribbia
• Physical parameterizations - Convection, Radiation, Boundary Layer,
Clouds, etc.
• Ensembles: Farrell, Kalnay, Palmer, Toth
6. Center for Ocean-Land-
Atmosphere Studies
The First 90-day Integration of the
NMC Forecast Model
DERF: NMC-COLA Collaboration (1983-1984)
• Meeting with Bonner, Rasmusson, Phillips and Brown (3 Oct 1983)
• Statement of Intent for NMC-COLA Work on DERF (14 Feb 1984)
• Acronym “DERF” created by Gerrity (24 Aug 1984)
• NMC Committee on DERF created
• Tracton Named CAC DERF Project Leader (11 Jun 1985)
• Large Number of NMC Scientists Involved in DERF
• Major Logistical Arrangements Required to Make 90-day Run
First 90-day Run of NMC Model Approved by Brown (30 Sep 1985)
7.
8.
9.
10.
11. Center for Ocean-Land-
Atmosphere Studies
Monthly and Seasonal
Predictability and Prediction
• Dynamical Predictability: Shukla (1981, 1984), Miyakoda,
Gordon, Caverly, Stern, Sirutis, and Bourke (1983)
• Boundary-Forced Predictability: Charney and Shukla (1977,
1981), Shukla (1984)
• Theory: Hoskins and Karoly (1981), Webster (1972, 1981)
• Programs: PROVOST (Europe); DSP (USA); SMIP (WCRP)
12. Center for Ocean-Land-
Atmosphere Studies
Simulation of (Uncoupled) Boundary-Forced
Response: Ocean, Land and Atmosphere
INFLUENCE OF OCEAN
ON ATMOSPHERE
– Tropical Pacific SST
– Arabian Sea SST
– North Pacific SST
– Tropical Atlantic SST
– North Atlantic SST
– Sea Ice
– Global SST (MIPs)
INFLUENCE OF LAND
ON ATMOSPHERE
– Mountain / No-Mountain
– Forest / No-Forest (Deforestation)
– Surface Albedo (Desertification)
– Soil Wetness
– Surface Roughness
– Vegetation
– Snow Cover
13. Center for Ocean-Land-
Atmosphere Studies
From Numerical Weather Prediction (NWP)
To Dynamical Seasonal Prediction (DSP) (1975-2004)
• Operational Short-Range NWP: was already in place
• 15-day & 30-day Mean Forecasts: demonstrated by Miyakoda (basis for creating
ECMWF-10 days)
• Dynamical Predictability of Monthly Means: demonstrated by analysis of variance
• Boundary Forcing: predictability of monthly & seasonal means (Charney & Shukla)
• AGCM Experiments: prescribed SST, soil wetness, & snow to explain observed
atmospheric circulation anomalies
• OGCM Experiments: prescribed observed surface wind to simulate tropical Pacific sea
level & SST (Busalacchi & O’Brien; Philander & Seigel)
• Prediction of ENSO: simple coupled ocean-atmosphere model (Cane, Zebiak)
• Coupled Ocean-Land-Atmosphere Models: predict short-term climate fluctuations
22. Standard Deviation of Monthly Equatorial Pacific SSTA
COLA Predictions
(1980-1999)
COLA Coupled Simulation
(250 years)
GFDL MOM3 ODA
(1980-1999)
Observations Forecast (JUL ICs) Simulation
25. 20 Years: 1980-1999
4 Times per Year: Jan., Apr., Jul., Oct.
6 Member Ensembles
Kirtman, 2003
Current Limit of Predictability of ENSO (Nino3.4)
Potential Limit of Predictability of ENSO
28. Center for Ocean-Land-
Atmosphere Studies
Challenges
Conceptual/Theoretical
Modeling
Observational
Computational
Institutional
Applications for Benefit to Society
29. Center for Ocean-Land-
Atmosphere Studies
Challenges
Conceptual/Theoretical
ENSO: unstable oscillator?
ENSO: stochastically forced, damped linear system?
(The past 50 years of observations support both theories)
– Role of weather noise?
Modeling
• Systematic errors of coupled models - too large
• Uncoupled models not appropriate to simulate Nature in some
regions/seasons: CLIMATE IS A COUPLED PROCESS
• Atmospheric response to warm and cold ENSO events is nonlinear
(SST, rainfall and circulation)
• Distinction between ENSO-forced and internal dynamics variability
30. Center for Ocean-Land-
Atmosphere Studies
Challenges
Observational
• Observations of ocean variability
• Initialization of coupled models
Computational
• Very high resolution models of climate system need million fold
increases in computing
• Storage, retrieval and analysis of huge model outputs
• Power (cooling) and space requirements-too large
31. Center for Ocean-Land-
Atmosphere Studies
Challenges
Institutional
• Development of accurate climate (O-L-A) models, assimilation and
initialization techniques, require a dedicated team with a critical mass of
scientists (~200) and resources (~$100 million per year: $50M
computing; $30M research; $20M experiments)
• Climate modeling and prediction efforts should be 10 times NWP but is
currently only ~10% of NWP
Applications for Benefit to Society
• Educate the consumers about the limits of predictability (uncertainty
and unreliability)
• Decision making and risk management using probabilistic predictions
37. Center for Ocean-Land-
Atmosphere Studies
Conclusions, Conjectures and Suggestions
• The estimates of the growth rate of initial errors in NWP models is well
known, and the current limits of predictability of weather are well
documented. The most promising way to improve forecasts for days 2-15
is to improve the forecast at day 1.
• The limits of predictability for short-term climate predictions (seasons 1-
4), are not well known, because the estimates of predictability remain
model-dependent. Our ability to make more accurate seasonal predictions
is limited by:
– Inadequate understanding of coupled dynamics
– Insufficient observations
– Inaccurate models
– Insufficient computing
– Inefficient institutional arrangements
38. Center for Ocean-Land-
Atmosphere Studies
• During the past 25 years, the weather forecast error
at day 1 has been reduced by more than 50%. At
present, forecasts for day 4 are, in general, as good
as forecasts for day 2 made 25 years ago.
• With improved observations, better models and faster
computers, it is reasonable to expect that the
forecast error at day 1 will be further reduced by
50% during the next 10-20 years. Therefore, at that
time, the forecasts at day 3 could be as good as
forecasts for day 2 are today.
Conclusions, Conjectures and Suggestions
39. Center for Ocean-Land-
Atmosphere Studies
• 25 years ago, a dynamical seasonal climate prediction was not conceivable.
• In the past 20 years, dynamical seasonal climate prediction has achieved a
level of skill that is considered useful for some societal applications. However,
such successes are limited to periods of large, persistent anomalies at the
Earth’s surface. Dynamical seasonal predictions for one month lead are not yet
superior to statistical forecasts.
• There is significant unrealized seasonal predictability. Progress in dynamical
seasonal prediction in the future depends critically on improvement of
coupled ocean-atmosphere-land models, improved observations, and the
ability to assimilate those observations.
Conclusions, Conjectures and Suggestions
40. Center for Ocean-Land-
Atmosphere Studies
• Improvements in dynamical weather prediction over the past 30 years did not
occur because of any major scientific breakthroughs in our understanding of
the physics or dynamics of the atmosphere
• Dynamical weather prediction is challenging: progress takes place slowly
and through a great deal of hard work that is not necessarily scientifically
stimulating, performed in an environment that is characterized by frequent
setbacks and constant criticism by a wide range of consumers and clients
• Nevertheless, scientists worldwide have made tremendous progress in
improving the skill of weather forecasts by advances in data assimilation,
improved parameterizations, improvements in numerical techniques and
increases in model resolution and computing power
Conclusions, Conjectures and Suggestions
41. Center for Ocean-Land-
Atmosphere Studies
• Currently, about 10 centers worldwide are making dynamical weather forecasts
every day with a lead time of 5-15 days with about 5-50 ensemble members, so
that there are about 500,000 daily weather maps that can be verified each
year
– It is this process of routine verification by a large number of scientists
worldwide, followed by attempts to improve the models and data
assimilation systems, that has been the critical element in the improvement
of dynamical weather forecasts
• In contrast, if we assume that dynamical seasonal predictions, with a lead time
of 1-3 seasons, could be made by about 10 centers worldwide every month with
about 10-20 ensemble members, there would be less than 5,000 seasonal
mean predictions worldwide that can be verified each year
– This is a factor of 100 fewer cases compared to NWP, so improvement in
dynamical seasonal prediction might proceed at a pace that is much slower
than that for NWP if we didn’t do something radically different
Conclusions, Conjectures and Suggestions
42. Center for Ocean-Land-
Atmosphere Studies
• NWP (World Wide)
– 10 Centers
– 5-15 day forecasts each day
– 5-15 ensemble size
– 500,000 daily weather maps each year
• DSP (World Wide)
– 10 Center
– 1-3 seasons predictions each month
– 10-20 ensemble size
– 5,000 seasonal maps each year
DSP is a factor of 100 fewer cases than NWP
Conclusions, Conjectures and Suggestions
43. Center for Ocean-Land-
Atmosphere Studies
Consumers could save $1 billion per
year in energy costs if the average
weather forecast could be improved by
just 1º Fahrenheit.
David S. Broder
Washington Post, 22 April 2004
Excerpt from NOAA report in interview with
Admiral Conrad Lautenbacher
Under Secretary of Commerce, NOAA
Conclusions, Conjectures and Suggestions
44. Center for Ocean-Land-
Atmosphere Studies
Suggestion for Accelerating Progress
in Modeling and Prediction of the
Physical Climate System
• There is a scientific basis for extending the
successes of NWP to climate prediction
• The problem is beyond a person, a center, a nation
…
• A multi-national collaboration is required
45. Center for Ocean-Land-
Atmosphere Studies
Suggestion for Accelerating Progress
in Dynamical Seasonal Prediction
Reanalyze and Reforecast
the seasonal variations for the past 50 years,
every year
• Exercise state-of-the-art coupled ocean-atmosphere-land models and
data assimilation systems for a large number of seasonal prediction
cases and verify them against observations
– Equivalent to producing reanalysis and 1-2 season dynamical forecasts
for each month of one year, every week
• Conduct model development experiments (sensitivity to
parameterizations, resolution, coupling strategy, etc.) with the specific
goal of reducing seasonal prediction errors