scholarly journals Introducing Non-Stationarity Into the Development of Intensity-Duration-Frequency Curves under a Changing Climate

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1008
Author(s):  
Daniele Feitoza Silva ◽  
Slobodan P. Simonovic ◽  
Andre Schardong ◽  
Joel Avruch Goldenfum
Keyword(s):  
Return Period ◽  
Climate Models ◽  
Global Climate ◽  
Extreme Rainfall ◽  
Value Theory ◽  
Extreme Value ◽  
Global Climate Models ◽  
Water Infrastructure ◽  
Planning And Design ◽  
Intensity Duration Frequency

Intensity-duration-frequency (IDF) relationships are traditional tools in water infrastructure planning and design. IDFs are developed under a stationarity assumption which may not be realistic, neither in the present nor in the future, under a changing climatic condition. This paper introduces a framework for generating non-stationary IDFs under climate change, assuming that probability of occurrence of quantiles changes over time. Using Extreme Value Theory, eight trend combinations in Generalized Extreme Value (GEV) parameters using time as covariate are compared with a stationary GEV, to identify the best alternative. Additionally, a modified Equidistance Quantile Matching (EQMNS) method is implemented to develop IDFs for future conditions, introducing non-stationarity where justified, based on the Global Climate Models (GCM). The methodology is applied for Moncton and Shearwater gauges in Northeast Canada. From the results, it is observed that EQMNS is able to capture the trends in the present and to translate them to estimated future rainfall intensities. Comparison of present and future IDFs strongly suggest that return period can be reduced by more than 50 years in the estimates of future rainfall intensities (e.g., historical 100-yr return period extreme rainfall may have frequency smaller than 50-yr under future conditions), raising attention to emerging risks to water infrastructure systems.

scholarly journals Analysis of Climate Change and 24-Hour Design Storm Depths for a Range of Return Periods Across South Carolina

2015 ◽  
pp. 70-79
Author(s):  
Derek Hutton ◽  
Nigel B. Kaye ◽  
William D. Martin
Keyword(s):  
South Carolina ◽  
Return Period ◽  
Climate Models ◽  
Global Climate ◽  
Extreme Rainfall ◽  
The State ◽  
Global Climate Models ◽  
Total Rainfall ◽  
Extreme Rainfall Events ◽  
Design Storm

A warming climate leads to a moister atmosphere and more rapid hydrologic cycle. As such, many parts of the country are predicted to experience more total rainfall per year and more frequent extreme rainfall events. Most regions of the country have stormwater systems designed to a standard that matches outflow rates to pre-development values for specified return period storms. Increases in these return period storm depths, as predicted by many global climate models, will stress existing stormwater infrastructure. This paper examines how rainfall patterns will change over the remainder of the century across the state of South Carolina. Rainfall simulations from 134 realizations of 21 global climate models were analyzed across the state of South Carolina through 2099. Results show that there will be increases in both annual total rainfall (ATR) and 24-hour design storm depth for a range of return period storms. Across South Carolina, ATR is predicted to increase by approximately 2.3-4.0 inches over the forecast period while the 100 year design storm depth is predicted to increase by 0.5-1.2 inches depending on location. However there are significant regional variations with the Savannah River Basin experiencing smaller increases in ATR compared to the rest of the state.

scholarly journals Brief Communication: Drought Likelihood for East Africa

2017 ◽  
Author(s):  
Hui Yang ◽  
Chris Huntingford
Keyword(s):  
East Africa ◽  
Climate Models ◽  
Global Climate ◽  
Extreme Rainfall ◽  
Global Climate Models ◽  
Severe Drought ◽  
East African ◽  
Reanalysis Dataset ◽  
Weather Forecasts ◽  
Medium Range

Abstract. The on-going effects of severe drought in East Africa are causing high levels of malnutrition, hunger, illness and death. Close to 16 million people across Somalia, Ethiopia and Kenya need food, water and medical assistance (DEC, 2017). Many factors influence drought stress and ability to respond. However, inevitably it is asked: are elevated atmospheric greenhouse gas (GHG) concentrations altering the likelihood of extreme rainfall deficits? We find small increases in probability of this for East African, based on merging the observation-based reanalysis dataset by the European Centre for Medium-Range Weather Forecasts (ECMWF) (Dee et al., 2011) with Global Climate Models (GCMs) in the CMIP5 database (Taylor et al., 2012).

scholarly journals Application of a Disaggregation Method for the Generation of Climate Changed Intensity-Duration-Frequency Curves for Predicting Future Extreme Rainfall Impacts on Transportation Infrastructure

2019 ◽  
Vol 271 ◽  
pp. 04002 ◽  
Author(s):  
Cesar Do Lago ◽  
Eduardo Mendiondo ◽  
Francisco Olivera ◽  
Marcio Giocomoni
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Extreme Rainfall ◽  
Global Climate Models ◽  
Transportation Infrastructure ◽  
Rainfall Regime ◽  
Rainfall Time Series ◽  
The Future ◽  
Intensity Duration Frequency ◽  
Frequency Curves

Potential consequences of climate change are the increase in the magnitude and frequency of extreme rainfall storm events. In order to assess what are the potential impacts of climate change in the transportation infrastructure, new intensity-duration-frequency curves are needed. In this study, projected IDF curves were created based on three Global Climate Models (GCM) for the representative concentration pathways (RCP) 4.5 and 8.5. The selected GCMs are: ACCESS1-0, CSIRO-MK3-0-6 and GFDL-ESM2M. Projected IDFs for the near (2025-2049), mid (2050-2074) and far future (2075-2099) were created after disaggregating the project rainfall time series using the Bartlett-Lewis Rectangular Pulses Stochastic Model. The projected IDFs were compared with the IDF currently used and generated based on historical data. The results indicate that climate change is likely to decrease rainfall intensities in all the future horizons in the tested area of San Antonio, Texas. Further analysis is recommended, including the use of bias correction of those GCM models and use of a broader range of models that can better quantify uncertainty of the future rainfall regime.

scholarly journals Changes in the Risk of Extratropical Cyclones in Eastern Australia

2013 ◽  
Vol 26 (4) ◽  
pp. 1403-1417 ◽  
Author(s):  
Andrew J. Dowdy ◽  
Graham A. Mills ◽  
Bertrand Timbal ◽  
Yang Wang
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
East Coast ◽  
Global Climate ◽  
Absolute Risk ◽  
Extreme Rainfall ◽  
Global Climate Models ◽  
Extratropical Cyclone ◽  
Extratropical Cyclones ◽  
Eastern Australia

Abstract The east coast of Australia is a region of the world where a particular type of extratropical cyclone, known locally as an east coast low, frequently occurs with severe consequences such as extreme rainfall, winds, and waves. The likelihood of formation of these storms is examined using an upper-tropospheric diagnostic applied to three reanalyses and three global climate models (GCMs). Strong similarities exist among the results derived from the individual reanalyses in terms of their seasonal variability (e.g., winter maxima and summer minima) and interannual variability. Results from reanalyses indicate that the threshold value used in the diagnostic method is dependent on the spatial resolution. Results obtained when applying the diagnostic to two of the three GCMs are similar to expectations given their spatial resolutions, and produce seasonal cycles similar to those from the reanalyses. Applying the methodology to simulations from these two GCMs for both current and future climate in response to increases in greenhouse gases indicates a reduction in extratropical cyclone occurrence of about 30% from the late twentieth century to the late twenty-first century for eastern Australia. In addition to the absolute risk of formation of these extratropical cyclones, spatial climatologies of occurrence are examined for the broader region surrounding eastern Australia. The influence of large-scale modes of atmospheric and oceanic variability on the occurrence of these storms in this region is also discussed.

scholarly journals Disaggregation of future GCMs to generate IDF curves for the assessment of urban floods

2021 ◽  
Author(s):  
H. Tayşi ◽  
M. Özger
Keyword(s):  
Climate Change ◽  
Short Duration ◽  
Urban Areas ◽  
Climate Models ◽  
Global Climate ◽  
Drainage System ◽  
Global Climate Models ◽  
Urban Floods ◽  
Idf Curves ◽  
Intensity Duration Frequency

Abstract Urbanization and industrialization cause an increase in greenhouse gas emissions, which in turn causes changes in the atmosphere. Climate change is causing extreme rainfalls and these rainfalls are getting stronger day after day. Floods are threatening urban areas, and short-duration rainfall and outdated drainages are responsible for urban floods. Intensity–Duration–Frequency (IDF) curves are crucial for both drainage system design and assessment of flood risk. Once IDF curves are determined from historical data, they are assumed to be stationary. However, IDF curves must be non-stationary and time varying based on preparation for extreme events. This study generates future IDF curves with short-duration rainfalls under climate change. To represent future rainfall, an ensemble of four Global Climate Models generated under Representative Concentration Pathways (RCP) 4.5 and 8.5 were used in this study. A new approach to the HYETOS disaggregation model was applied to disaggregate daily future rainfall into sub-hourly using disaggregation parameters of hourly measured rainfalls. Hence, sub-hourly future rainfalls will be obtained capturing historical rainfall patterns instead of random rainfall characteristics. Finally, historical and future IDF curves were compared. The study concludes that increases in short-duration rainfalls will be highly intensified in both the near and distant futures with a high probability.

Extreme Events in High Resolution CMCC Regional and Global Climate Models

2011 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Antonella Sanna ◽  
Edoardo Bucchignani ◽  
Myriam Montesarchio
Keyword(s):  
High Resolution ◽  
Extreme Events ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models

scholarly journals Global climatology and trends in convective environments from ERA5 and rawinsonde data

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mateusz Taszarek ◽  
John T. Allen ◽  
Mattia Marchio ◽  
Harold E. Brooks
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Convective Available Potential Energy ◽  
Global Climate Models ◽  
Convective Precipitation ◽  
The Past ◽  
The Tropics ◽  
Rawinsonde Data

AbstractGlobally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.

scholarly journals Return Period Evaluation of the Largest Possible Earthquake Magnitudes in Mainland China Based on Extreme Value Theory

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3519
Author(s):  
Yanbing Bai ◽  
Ning Ma ◽  
Shengwang Meng
Keyword(s):  
Earthquake Engineering ◽  
Return Period ◽  
Extreme Value Theory ◽  
Threshold Model ◽  
Mainland China ◽  
Value Theory ◽  
Extreme Value ◽  
Geographical Information ◽  
Geographical Regions ◽  
The Right

The largest possible earthquake magnitude based on geographical characteristics for a selected return period is required in earthquake engineering, disaster management, and insurance. Ground-based observations combined with statistical analyses may offer new insights into earthquake prediction. In this study, to investigate the seismic characteristics of different geographical regions in detail, clustering was used to provide earthquake zoning for Mainland China based on the geographical features of earthquake events. In combination with geospatial methods, statistical extreme value models and the right-truncated Gutenberg–Richter model were used to analyze the earthquake magnitudes of Mainland China under both clustering and non-clustering. The results demonstrate that the right-truncated peaks-over-threshold model is the relatively optimal statistical model compared with classical extreme value theory models, the estimated return level of which is very close to that of the geographical-based right-truncated Gutenberg–Richter model. Such statistical models can provide a quantitative analysis of the probability of future earthquake risks in China, and geographical information can be integrated to locate the earthquake risk accurately.

scholarly journals Regions of intensification of extreme snowfall under future warming

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lennart Quante ◽  
Sven N. Willner ◽  
Robin Middelanis ◽  
Anders Levermann
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Observational Data ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Climate Models ◽  
Average Intensity ◽  
High Latitudes ◽  
Future Warming

AbstractDue to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century.

Sign in / Sign up

Export Citation Format

Share Document