Quantifying uncertainty in changes in extreme event frequency in response to doubled CO2 using a large ensemble of GCM simulations

2006 ◽  
Vol 26 (5) ◽  
pp. 489-511 ◽  
Author(s):  
David N. Barnett ◽  
Simon J. Brown ◽  
James M. Murphy ◽  
David M. H. Sexton ◽  
Mark J. Webb
Keyword(s):  
Extreme Event ◽  
Large Ensemble ◽  
Event Frequency ◽  
Quantifying Uncertainty

scholarly journals Impact of air–sea coupling on the probability of occurrence of heat waves in Japan

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Akira Hasegawa ◽  
Yukiko Imada ◽  
Hideo Shiogama ◽  
Masato Mori ◽  
Hiroaki Tatebe ◽  
...  
Keyword(s):  
General Circulation Model ◽  
General Circulation ◽  
Extreme Event ◽  
Heat Waves ◽  
Circulation Model ◽  
Silk Road ◽  
Atmospheric Variability ◽  
Large Ensemble ◽  
Probability Of Occurrence ◽  
The Silk Road

AbstractIn extreme event attribution, which aims to answer whether and to what extent a particular extreme weather event can be attributed to global warming, the probability of an event is generally estimated through large ensemble simulations, using an atmospheric general circulation model (AGCM). In islands, such as Japan, it has been considered that surface air temperature (SAT) can be significantly affected by the surrounding sea surface temperature (SST), which mostly is affected by atmospheric circulation at mid- and high-latitudes. Therefore, the absence of SST responses to atmospheric variability in AGCMs impacts the estimation of the occurrence of extreme events, such as heat waves in Japan. In this study, we examined the impact of air–sea coupling on the probability of occurrence of severe heat waves that occurred in Japan in the summer of 2010 by analyzing the probability differences obtained from AGCM and coupled general circulation model (CGCM) large-ensemble experiments. The observed ocean temperature, salinity, and sea ice were assimilated in the 100-member CGCM experiments, as they were assigned as boundary conditions in the 100-member AGCM experiments. The SAT around Japan in the northern summer is largely related to the Bonin high, whose interannual variability is largely affected by the Silk Road and Pacific-Japan (PJ) pattern teleconnections in the real world. The SAT anomaly over Japan was related to the pressure variability due to the Silk Road and PJ patterns in the CGCM experiment. By contrast, the SAT over Japan simulated by AGCM was less sensitive to such pressure variability, and the SAT ensemble spread became narrower in AGCM. The results suggest that the probability of occurrence of the 2010 heat wave in Japan would tend to be underestimated by the AGCM ensemble compared to the CGCM ensemble, provided that the ensemble averages of the SAT anomalies were equal between CGCM and AGCM experiments. This study raised the issue of the absence of SST response to atmospheric variability in AGCMs, which can critically impact the estimation of extreme event probability, particularly in mid-latitude islands, such as Japan.

National coastal management challenges and needs

Shore & Beach ◽  
2020 ◽  
pp. 34-43
Author(s):  
Nicole Elko ◽  
Tiffany Roberts Briggs
Keyword(s):  
Coastal Management ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Local Community ◽  
Extreme Event ◽  
Technical Information ◽  
Interdisciplinary Approach ◽  
Beach Erosion ◽  
The U.S

In partnership with the U.S. Geological Survey Coastal and Marine Hazards and Resources Program (USGS CMHRP) and the U.S. Coastal Research Program (USCRP), the American Shore and Beach Preservation Association (ASBPA) has identified coastal stakeholders’ top coastal management challenges. Informed by two annual surveys, a multiple-choice online poll was conducted in 2019 to evaluate stakeholders’ most pressing problems and needs, including those they felt most ill-equipped to deal with in their day-to-day duties and which tools they most need to address these challenges. The survey also explored where users find technical information and what is missing. From these results, USGS CMHRP, USCRP, ASBPA, and other partners aim to identify research needs that will inform appropriate investments in useful science, tools, and resources to address today’s most pressing coastal challenges. The 15-question survey yielded 134 complete responses with an 80% completion rate from coastal stakeholders such as local community representatives and their industry consultants, state and federal agency representatives, and academics. Respondents from the East, Gulf, West, and Great Lakes coasts, as well as Alaska and Hawaii, were represented. Overall, the prioritized coastal management challenges identified by the survey were: Deteriorating ecosystems leading to reduced (environmental, recreational, economic, storm buffer) functionality, Increasing storminess due to climate change (i.e. more frequent and intense impacts), Coastal flooding, both Sea level rise and associated flooding (e.g. nuisance flooding, king tides), and Combined effects of rainfall and surge on urban flooding (i.e. episodic, short-term), Chronic beach erosion (i.e. high/increasing long-term erosion rates), and Coastal water quality, including harmful algal blooms (e.g. red tide, sargassum). A careful, systematic, and interdisciplinary approach should direct efforts to identify specific research needed to tackle these challenges. A notable shift in priorities from erosion to water-related challenges was recorded from respondents with organizations initially formed for beachfront management. In addition, affiliation-specific and regional responses varied, such as Floridians concern more with harmful algal blooms than any other human and ecosystem health related challenge. The most common need for additional coastal management tools and strategies related to adaptive coastal management to maintain community resilience and continuous storm barriers (dunes, structures), as the top long-term and extreme event needs, respectively. In response to questions about missing information that agencies can provide, respondents frequently mentioned up-to-date data on coastal systems and solutions to challenges as more important than additional tools.

Methods for Calculation of Annual and Extreme Overflow Events from Combined Sewer Systems

1984 ◽  
Vol 16 (8-9) ◽  
pp. 311-325 ◽  
Author(s):  
N B Johansen ◽  
P Harremoës ◽  
M Jensen
Keyword(s):  
Extreme Event ◽  
Short Term ◽  
Sewer Systems ◽  
Extreme Load ◽  
Combined Sewer ◽  
Receiving Waters ◽  
Water Problems ◽  
Source Of Pollution ◽  
Receiving Water

Overflow from combined systems constitute an increasing source of pollution of receiving waters, as compared to daily wastewater discharges which undergo treatment to a still higher extent. The receiving water problems from overflows are significant both in a long term scale (mean annual load) and in a short term scale (extreme event load). A method for computation of both annual and extreme load is presented. It is based on historical rain series and the use of a time-area model and simple pollutant mixing model in runoff calculation. Statistical calculations for both mean annual load and extreme events have been applied to the computed overflow series. Based on the computerized method simple manual calculations methods have been developed, resulting in graphs and tables for annual load and extreme load.

Quantifying Uncertainty to Improve Decision Making in Machine Learning.

2018 ◽  
Author(s):  
David John Stracuzzi ◽  
Michael Christopher Darling ◽  
Matthew Gregor Peterson ◽  
Maximillian Gene Chen
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Quantifying Uncertainty

scholarly journals Evaluating the accuracy and uncertainty of atmospheric and wave model hindcasts during severe events using model ensembles

2021 ◽  
Author(s):  
Ali Abdolali ◽  
Andre van der Westhuysen ◽  
Zaizhong Ma ◽  
Avichal Mehra ◽  
Aron Roland ◽  
...  
Keyword(s):  
Extreme Event ◽  
Numerical Models ◽  
Model Performance ◽  
Ground Truth ◽  
Wave Model ◽  
Atmospheric Model ◽  
Stationary Source ◽  
Source Point ◽  
Spectral Wave Model ◽  
Model Ensembles

AbstractVarious uncertainties exist in a hindcast due to the inabilities of numerical models to resolve all the complicated atmosphere-sea interactions, and the lack of certain ground truth observations. Here, a comprehensive analysis of an atmospheric model performance in hindcast mode (Hurricane Weather and Research Forecasting model—HWRF) and its 40 ensembles during severe events is conducted, evaluating the model accuracy and uncertainty for hurricane track parameters, and wind speed collected along satellite altimeter tracks and at stationary source point observations. Subsequently, the downstream spectral wave model WAVEWATCH III is forced by two sets of wind field data, each includes 40 members. The first ones are randomly extracted from original HWRF simulations and the second ones are based on spread of best track parameters. The atmospheric model spread and wave model error along satellite altimeters tracks and at stationary source point observations are estimated. The study on Hurricane Irma reveals that wind and wave observations during this extreme event are within ensemble spreads. While both Models have wide spreads over areas with landmass, maximum uncertainty in the atmospheric model is at hurricane eye in contrast to the wave model.

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