DETECTION AND DESIGNATION
Characterization, detection, and designation of observed extreme events.
Extreme weather has large effects on human and natural systems. Through the use of observations, climate model and statistical techniques, CASCADE researchers examine how changes in the natural environment have impacted recent weather extremes.
Increased understanding of the influence of environmental drivers on current extreme weather increases confidence in projections of changes in future extreme weather statistics. The centerpiece modeling effort of the CASCADE Detection and Designation team is the C20C+ (Climate of the 20th Century) experiment. CASCADE is a primary contributor to the World Climate Research Program (WCRP) coordinated international project. This multi-model effort aims to aid event attribution by building a database of ensemble climate model simulations describing the “world that was” in a realistic-as-possible configuration and the “worlds that might have been” in a counterfactual configuration where environmental drivers have not changed.
Associating changes in the behavior of extreme events to specific environmental drivers requires a systematic characterization of extreme events in the recent past. Recent advances in simulation capabilities and statistical methodologies allow us to focus on the impacts of a wide range of environmental drivers at regional-to-local scales, to focus on factors impacting the spatial and temporal co-occurrence of extremes, and to simulate how we might expect extremes to change in the future.
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dstone@lbl.gov
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dstone@lbl.gov2015-07-16 13:55:272020-09-18 22:52:56CASCADE climate model data can now be visualised online
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dstone@lbl.gov
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dstone@lbl.gov2015-07-16 13:46:482020-09-18 22:52:56Australian study uses CASCADE data
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mfwehner@lbl.gov2015-05-19 23:10:232020-09-18 22:52:56North American Extreme Temperature Events and Related Large Scale Meteorological Patterns: A Review of Statistical Methods, Dynamics, Modeling, and Trends
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mfwehner@lbl.gov2015-05-07 20:39:442020-09-18 22:53:27Fewer total number of hurricanes but more intense ones in a warmer worldUNDERSTANDING STRANGE WEATHER
Understanding how changes in the ocean and atmosphere make weather events more extreme.
Climate extremes – such as hurricanes, major floods, and heat waves – not only stress society, they push the bounds of what modern climate models can simulate.
While extreme weather events often have impacts at relatively small (city-wide) scales, they are often driven by planetary scale forces. Observing and simulating these events requires datasets and models with high fidelity at a wide range of scales. CASCADE is making novel use of self-similarity* in the atmosphere to define new standards for how model performance should change as model scale changes from ‘city’ to ‘planetary’. The CASCADE team is using the Department of Energy’s new Accelerated Climate Model for Energy (ACME) to simulate past weather and is using these new standards to evaluate the model. Through a tight collaboration with ACME developers, these insights are being translated in to improved model fidelity at a wide range of scales.
Designating and projecting changes in extremes requires a well-developed understanding of the processes that drive changes in extremes. In particular, for the overall goal of the CASCADE SFA, it is necessary to understand how have changes in the physical behavior of the coupled system altered the frequencies of occurrence and the characteristics of extreme climate events? To address this issue, it is also necessary to advance our understanding of the processes governing the properties of extremes that are being investigated within the CASCADE SFA. The SFA team focuses specifically on the processes that drive multivariate extremes, the processes that drive changes in the spatio-temporal characteristics of extremes, and the fidelity with which these processes are represented in climate models.
*self-similarity means that the statistics of the atmosphere change predictably depending on the scale at which the statistics are evaluated
UNCERTAINTY OF EXTREMES
Statistical methods to quantify changes in extreme weather in light of uncertainty.
Extremes are by definition rare. Statistical methods are critical for characterizing extreme weather in time and space, estimating changes in extreme weather, and quantifying our uncertainty about the frequency and trends in extremes.
The Statistics team is developing, implementing and advising on statistical methods for characterizing extremes in observations and model output. We are particularly focused on detection and designation of changes in extreme events, quantifying the evidence that the probability of extreme events are changing over time and that changes are caused by environmental drivers. As part of this work we are addressing the question of uncertainty characterization. A key focus is to identify the leading sources of uncertainty in our understanding of weather extremes (e.g., initial condition uncertainty/sampling uncertainty, forcing uncertainty, model parameter uncertainty).
Studies that aim to detect and attribute changes in extreme events have numerous sources of uncertainty, including parametric uncertainty, structural uncertainty, and even methodological uncertainty. In the current paradigm, these sources of uncertainty are dealt with in a piecemeal fashion that can result in overconfident statements of causation. This could cause, and in fact has produced, conflicts among causation statements on the same event. The sensitivity of event causation conclusions to the various sources of uncertainty remains sparsely investigated but is demonstrably important. The SFA team focuses on performing a multifaceted set of modeling experiments and analyses designed specifically to characterize, and if possible quantify, the importance of structural uncertainty, parametric uncertainty, and methodological uncertainty on our understanding of various classes of events.
Performance of CAM5.1 simulations over West Africa and Southern Africa
SciDev.net has an article today about some analysis of data produced by CASCADE. As part of his doctoral thesis at the University of Cape Town, South Africa, Kamoru Lawal (now at the Nigerian Meteorological Agency) examined how CAM5.1 climate simulations performed under the CASCADE project manage to reproduce the major seasonal weather systems affecting West Africa and Southern Africa. Results revealed some rather fundamental differences in the nature of predictability over both regions. For instance, while averaging across a large number of simulations substantially improves the skill of predicting seasonal rainfall over Southern Africa, it provides little improvement over West Africa, even though the model’s skill is similar over both regions.
Benefits of mitigation for future heat extremes under RCP4.5 compared to RCP8.5
LBNL and NCAR did a joint press release on a recent paper about heat waves. The PR went fairly viral with over 800 reposts as best I can tell. Some with interesting comments… (My favorite being that Diana Ross told us all about heat waves in the 1960s. MFW.)
Click this link for the original LBNL press release:
http://cs.lbl.gov/news-media/news/2016/new-study-details-the-searing-future-of-extreme-heat/
Here is an alternative summary:
In a recent paper in the journal Climatic Change, DOE BER RGCM funded researchers Claudia Tebaldi (NCAR) and Michael Wehner (LBNL) analyzed the effects of significant reductions in future greenhouse gas emissions on short-term extreme hot and cold events. Tebaldi and Wehner applied Generalized Extreme Value (GEV) analysis techniques to the output from the large ensemble projections of the Community Earth System Model to estimate 20-year return values of daily and 3 day average maximum and minimum temperatures over the course of this century under future high (RCP8.5) and low (RCP4.5) emissions scenarios. They found that about 95% of land regions would see reductions of 1°C or more in these measures of very extreme temperatures by reducing the future increase in global mean temperature from 3.3 to 1.9oC, and 50% or more of the land areas would benefit by at least 2°C. 6% of the land area would benefit by 3°C or more in projected extreme minimum temperatures and 13% would benefit by this amount for extreme maximum temperature. The future frequency of current extremes is also greatly reduced by mitigation: by the end of the century, under the high emissions pathway more than half the land area experiences the current 20-year events every year while only between about 10 and 25% of the area is affected by such severe changes in the reduced emission scenario.
This work is joint between two larger efforts, Benefits of Reduced Anthropogenic Climate change at NCAR, which explore a wide range of such benefits and Calibrated and Systematic Characterization, Attribution and Detection of Extremes at LBNL, which is focused on extreme weather in a changing climate. See https://chsp.ucar.edu/brace-benefits-reduced-anthropogenic-climate-change and other papers being published in the same special issue of Climatic Change.
Citation: Claudia Tebaldi and Michael Wehner (2016) Benefits of mitigation for future heat extremes under RCP4.5 compared to RCP8.5. Early online release Climatic Change. DOI:10.1007/s10584-016-1605-5
The difference in 20 year return values of annual maximum daily maximum temperature at the end of this century between a no policy scenario (RCP8.5) and a significant mitigation scenario (RCP4.5).
Quantile-based Bias Correction and Uncertainty Quantification of Extreme Event Attribution Statements
Extreme event attribution characterizes how anthropogenic climate change may have influenced the probability and magnitude of selected individual extreme weather and climate events. Attribution statements often involve quantification of the fraction of attributable risk (FAR) or the risk ratio (RR) and associated confidence intervals. Many such analyses use climate model output to characterize extreme event behavior with and without anthropogenic influence. Climate models may have biases in their representation of extreme events.
There are two important results from this work. The first result is that we present a methodology tailored to bias correct the extreme events simulated by climate models. This is necessary to make better use of the CMIP5 database of climate models. The second, and more significant result, concerns a finding about the uncertainty in attributing the human influence on individual climate and weather extreme events. We present a method to estimate the lower bound of the change in risk of events when the upper bound includes infinity. We find that this lower bound, using this one-sided estimate, is insensitive to the magnitude of the extreme event. This important finding means that observational uncertainty is not critical to determining whether humans have had a significant influence on an actual extreme event. We demonstrate the methodology using the summer 2011 central US heatwave and output from the Community Earth System Model.
Citation: Soyoung Jeon, Christopher J. Paciorek, Michael F. Wehner (2016) Quantile-based Bias Correction and Uncertainty Quantification of Extreme Event Attribution Statements. Weather and Climate Extremes. Early online release. DOI:10.1016/j.wace.2016.02.001
http://www.sciencedirect.com/science/article/pii/S2212094715300220
Video testimony of CASCADE scientists Daíthí Stone and Michael Wehner
Video highlights of Daíthí Stone and Michael Wehner at the National Academies of Sciences’ panel on “Extreme Weather Events and Climate Change Attribution” on October 22, 2012.
Wehner quoted in New Scientist about the winter UK floods
CASCADE’s Michael Wehner was recently quoted in a New Scientist article about the recent UK floods. See this link:
Wehner and Easterling opinion piece about the warming hiatus in Science magazine
Michael Wehner, of the LBNL CASCADE SFA team, with his NOAA co-author, David Easterling, returned to the subject of the so-called global warming hiatus with an editorial comment in Science on December 18. See the paywall protected link
http://www.sciencemag.org/content/350/6267/1482.4.full.pdf
Please note that the editors of Science changed the title without informing the authors. The intended title was “Is the global warming hiatus important?”
COMPUTATION AND PREDICTION
High performance computing to detect and predict changes in weather extremes.
The CASCADE computation and predictions team is developing scientific tools, workflow patterns, and scalable algorithms that can process massive model output on modern HPC systems.
The computation and predictions team is tightly integrating the detection system with the attribution framework so that statistics from the detection analyses automatically yield the probability distribution functions required to produce quantitative attribution and projection statements for extreme events. In a related effort, we are integrating event detection and analysis with the ILIAD ((InitiaLized-ensemble Identify, Analyze, Develop) framework to ensure that probabilities of event detection do not depend on model configuration, thereby mitigating the resolution dependence of hurricane detection.
The CASCADE research portfolio requires extensive computational and statistical infrastructure. Much of the SFA research requires implementation of novel statistical methods. Likewise, the formal application of UQ methods for extremes requires the implementation of a surrogate model and new developments in emulator methodology. Further, all of the SFA’s analyses require sophisticated, robust, and parallelizable data analysis tools to operate on the enormous datasets that we use (O (100{1000) TB). Therefore, the SFA focuses on three main research and development foci to support the broader goals of the project: methodological development for systematic event causation at ne spatial scales, development of a statistical framework for the holistic uncertainty characterization work, and development of a multilevel model emulator for extremes.
Performance of CAM5.1 simulations over West Africa and Southern Africa
SciDev.net has an article today about some analysis of data produced by CASCADE. As part of his doctoral thesis at the University of Cape Town, South Africa, Kamoru Lawal (now at the Nigerian Meteorological Agency) examined how CAM5.1 climate simulations performed under the CASCADE project manage to reproduce the major seasonal weather systems affecting West Africa and Southern Africa. Results revealed some rather fundamental differences in the nature of predictability over both regions. For instance, while averaging across a large number of simulations substantially improves the skill of predicting seasonal rainfall over Southern Africa, it provides little improvement over West Africa, even though the model’s skill is similar over both regions.
Benefits of mitigation for future heat extremes under RCP4.5 compared to RCP8.5
LBNL and NCAR did a joint press release on a recent paper about heat waves. The PR went fairly viral with over 800 reposts as best I can tell. Some with interesting comments… (My favorite being that Diana Ross told us all about heat waves in the 1960s. MFW.)
Click this link for the original LBNL press release:
http://cs.lbl.gov/news-media/news/2016/new-study-details-the-searing-future-of-extreme-heat/
Here is an alternative summary:
In a recent paper in the journal Climatic Change, DOE BER RGCM funded researchers Claudia Tebaldi (NCAR) and Michael Wehner (LBNL) analyzed the effects of significant reductions in future greenhouse gas emissions on short-term extreme hot and cold events. Tebaldi and Wehner applied Generalized Extreme Value (GEV) analysis techniques to the output from the large ensemble projections of the Community Earth System Model to estimate 20-year return values of daily and 3 day average maximum and minimum temperatures over the course of this century under future high (RCP8.5) and low (RCP4.5) emissions scenarios. They found that about 95% of land regions would see reductions of 1°C or more in these measures of very extreme temperatures by reducing the future increase in global mean temperature from 3.3 to 1.9oC, and 50% or more of the land areas would benefit by at least 2°C. 6% of the land area would benefit by 3°C or more in projected extreme minimum temperatures and 13% would benefit by this amount for extreme maximum temperature. The future frequency of current extremes is also greatly reduced by mitigation: by the end of the century, under the high emissions pathway more than half the land area experiences the current 20-year events every year while only between about 10 and 25% of the area is affected by such severe changes in the reduced emission scenario.
This work is joint between two larger efforts, Benefits of Reduced Anthropogenic Climate change at NCAR, which explore a wide range of such benefits and Calibrated and Systematic Characterization, Attribution and Detection of Extremes at LBNL, which is focused on extreme weather in a changing climate. See https://chsp.ucar.edu/brace-benefits-reduced-anthropogenic-climate-change and other papers being published in the same special issue of Climatic Change.
Citation: Claudia Tebaldi and Michael Wehner (2016) Benefits of mitigation for future heat extremes under RCP4.5 compared to RCP8.5. Early online release Climatic Change. DOI:10.1007/s10584-016-1605-5
The difference in 20 year return values of annual maximum daily maximum temperature at the end of this century between a no policy scenario (RCP8.5) and a significant mitigation scenario (RCP4.5).
Quantile-based Bias Correction and Uncertainty Quantification of Extreme Event Attribution Statements
Extreme event attribution characterizes how anthropogenic climate change may have influenced the probability and magnitude of selected individual extreme weather and climate events. Attribution statements often involve quantification of the fraction of attributable risk (FAR) or the risk ratio (RR) and associated confidence intervals. Many such analyses use climate model output to characterize extreme event behavior with and without anthropogenic influence. Climate models may have biases in their representation of extreme events.
There are two important results from this work. The first result is that we present a methodology tailored to bias correct the extreme events simulated by climate models. This is necessary to make better use of the CMIP5 database of climate models. The second, and more significant result, concerns a finding about the uncertainty in attributing the human influence on individual climate and weather extreme events. We present a method to estimate the lower bound of the change in risk of events when the upper bound includes infinity. We find that this lower bound, using this one-sided estimate, is insensitive to the magnitude of the extreme event. This important finding means that observational uncertainty is not critical to determining whether humans have had a significant influence on an actual extreme event. We demonstrate the methodology using the summer 2011 central US heatwave and output from the Community Earth System Model.
Citation: Soyoung Jeon, Christopher J. Paciorek, Michael F. Wehner (2016) Quantile-based Bias Correction and Uncertainty Quantification of Extreme Event Attribution Statements. Weather and Climate Extremes. Early online release. DOI:10.1016/j.wace.2016.02.001
http://www.sciencedirect.com/science/article/pii/S2212094715300220
Video testimony of CASCADE scientists Daíthí Stone and Michael Wehner
Video highlights of Daíthí Stone and Michael Wehner at the National Academies of Sciences’ panel on “Extreme Weather Events and Climate Change Attribution” on October 22, 2012.
Wehner quoted in New Scientist about the winter UK floods
CASCADE’s Michael Wehner was recently quoted in a New Scientist article about the recent UK floods. See this link:
Wehner and Easterling opinion piece about the warming hiatus in Science magazine
Michael Wehner, of the LBNL CASCADE SFA team, with his NOAA co-author, David Easterling, returned to the subject of the so-called global warming hiatus with an editorial comment in Science on December 18. See the paywall protected link
http://www.sciencemag.org/content/350/6267/1482.4.full.pdf
Please note that the editors of Science changed the title without informing the authors. The intended title was “Is the global warming hiatus important?”
Performance of CAM5.1 simulations over West Africa and Southern Africa
/in Detection and Designation /by dstone@lbl.govSciDev.net has an article today about some analysis of data produced by CASCADE. As part of his doctoral thesis at the University of Cape Town, South Africa, Kamoru Lawal (now at the Nigerian Meteorological Agency) examined how CAM5.1 climate simulations performed under the CASCADE project manage to reproduce the major seasonal weather systems affecting West Africa and Southern Africa. Results revealed some rather fundamental differences in the nature of predictability over both regions. For instance, while averaging across a large number of simulations substantially improves the skill of predicting seasonal rainfall over Southern Africa, it provides little improvement over West Africa, even though the model’s skill is similar over both regions.
Benefits of mitigation for future heat extremes under RCP4.5 compared to RCP8.5
/in Detection and Designation /by mfwehner@lbl.govLBNL and NCAR did a joint press release on a recent paper about heat waves. The PR went fairly viral with over 800 reposts as best I can tell. Some with interesting comments… (My favorite being that Diana Ross told us all about heat waves in the 1960s. MFW.)
Click this link for the original LBNL press release:
http://cs.lbl.gov/news-media/news/2016/new-study-details-the-searing-future-of-extreme-heat/
Here is an alternative summary:
In a recent paper in the journal Climatic Change, DOE BER RGCM funded researchers Claudia Tebaldi (NCAR) and Michael Wehner (LBNL) analyzed the effects of significant reductions in future greenhouse gas emissions on short-term extreme hot and cold events. Tebaldi and Wehner applied Generalized Extreme Value (GEV) analysis techniques to the output from the large ensemble projections of the Community Earth System Model to estimate 20-year return values of daily and 3 day average maximum and minimum temperatures over the course of this century under future high (RCP8.5) and low (RCP4.5) emissions scenarios. They found that about 95% of land regions would see reductions of 1°C or more in these measures of very extreme temperatures by reducing the future increase in global mean temperature from 3.3 to 1.9oC, and 50% or more of the land areas would benefit by at least 2°C. 6% of the land area would benefit by 3°C or more in projected extreme minimum temperatures and 13% would benefit by this amount for extreme maximum temperature. The future frequency of current extremes is also greatly reduced by mitigation: by the end of the century, under the high emissions pathway more than half the land area experiences the current 20-year events every year while only between about 10 and 25% of the area is affected by such severe changes in the reduced emission scenario.
This work is joint between two larger efforts, Benefits of Reduced Anthropogenic Climate change at NCAR, which explore a wide range of such benefits and Calibrated and Systematic Characterization, Attribution and Detection of Extremes at LBNL, which is focused on extreme weather in a changing climate. See https://chsp.ucar.edu/brace-benefits-reduced-anthropogenic-climate-change and other papers being published in the same special issue of Climatic Change.
Citation: Claudia Tebaldi and Michael Wehner (2016) Benefits of mitigation for future heat extremes under RCP4.5 compared to RCP8.5. Early online release Climatic Change. DOI:10.1007/s10584-016-1605-5
The difference in 20 year return values of annual maximum daily maximum temperature at the end of this century between a no policy scenario (RCP8.5) and a significant mitigation scenario (RCP4.5).
Quantile-based Bias Correction and Uncertainty Quantification of Extreme Event Attribution Statements
/in Uncertainty of Extremes /by mfwehner@lbl.govExtreme event attribution characterizes how anthropogenic climate change may have influenced the probability and magnitude of selected individual extreme weather and climate events. Attribution statements often involve quantification of the fraction of attributable risk (FAR) or the risk ratio (RR) and associated confidence intervals. Many such analyses use climate model output to characterize extreme event behavior with and without anthropogenic influence. Climate models may have biases in their representation of extreme events.
There are two important results from this work. The first result is that we present a methodology tailored to bias correct the extreme events simulated by climate models. This is necessary to make better use of the CMIP5 database of climate models. The second, and more significant result, concerns a finding about the uncertainty in attributing the human influence on individual climate and weather extreme events. We present a method to estimate the lower bound of the change in risk of events when the upper bound includes infinity. We find that this lower bound, using this one-sided estimate, is insensitive to the magnitude of the extreme event. This important finding means that observational uncertainty is not critical to determining whether humans have had a significant influence on an actual extreme event. We demonstrate the methodology using the summer 2011 central US heatwave and output from the Community Earth System Model.
Citation: Soyoung Jeon, Christopher J. Paciorek, Michael F. Wehner (2016) Quantile-based Bias Correction and Uncertainty Quantification of Extreme Event Attribution Statements. Weather and Climate Extremes. Early online release. DOI:10.1016/j.wace.2016.02.001
http://www.sciencedirect.com/science/article/pii/S2212094715300220
Video testimony of CASCADE scientists Daíthí Stone and Michael Wehner
/in Detection and Designation /by mfwehner@lbl.govVideo highlights of Daíthí Stone and Michael Wehner at the National Academies of Sciences’ panel on “Extreme Weather Events and Climate Change Attribution” on October 22, 2012.
https://youtu.be/kttdD7r7do4
Wehner quoted in New Scientist about the winter UK floods
/in Detection and Designation /by mfwehner@lbl.govCASCADE’s Michael Wehner was recently quoted in a New Scientist article about the recent UK floods. See this link:
https://www.newscientist.com/article/mg22930554-700-understanding-climate-changes-role-in-the-uks-recent-floods/
Wehner and Easterling opinion piece about the warming hiatus in Science magazine
/in Detection and Designation /by mfwehner@lbl.govMichael Wehner, of the LBNL CASCADE SFA team, with his NOAA co-author, David Easterling, returned to the subject of the so-called global warming hiatus with an editorial comment in Science on December 18. See the paywall protected link
http://www.sciencemag.org/content/350/6267/1482.4.full.pdf
Please note that the editors of Science changed the title without informing the authors. The intended title was “Is the global warming hiatus important?”