Global and Regional Projected Changes in 100-yr Subdaily, Daily, and Multiday Precipitation Extremes Estimated from Three Large Ensembles of Climate Simulations

AbstractMany studies have reported projected increases in the frequency and intensity of extreme precipitation events in a warmer future climate. These results challenge the assumption of climate stationarity, a standard hypothesis in the estimation of extreme precipitation quantiles (e.g., 100-yr return period) often used as key design criteria for many infrastructures. In this work, changes in hourly to 5-day precipitation extremes occurring between the 1980–99 and 2080–99 periods are investigated using three large ensembles (LE) of climate simulations. The first two are the global CanESM2 50-member ensemble at a 2.8° resolution and the global CESM1 40-member ensemble at a 1° resolution. The third is the regional CRCM5 50-member ensemble at a 0.11° resolution, driven at its boundaries by the 50-member CanESM2 ensemble over the northeastern North America (NNA) and Europe (EU) domains. Results indicate increases in the frequency of future extreme events, and, accordingly, a reduction of the return period of current extreme events for all tested spatial resolutions and temporal scales. Agreement between the three ensembles suggests that extreme precipitations, corresponding to the 100-yr return period over the reference period, become 4–5 (2–4) times more frequent on average for the NNA (EU) domain for daily and 5-day annual maximum precipitation. Projections by CRCM5-LE show even larger increases for subdaily precipitation extremes. Considering the life-span of many public infrastructures, these changes may have important implications on service levels and the design of many water infrastructures and for public safety, and should therefore be taken into consideration in establishing design criteria.

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Regional Frequency Analysis of Precipitation Extremes and Its Spatio-Temporal Patterns in the Hanjiang River Basin, China

Atmosphere ◽

10.3390/atmos10030130 ◽

2019 ◽

Vol 10 (3) ◽

pp. 130 ◽

Cited By ~ 3

Author(s):

Wenlong Hao ◽

Zhenchun Hao ◽

Feifei Yuan ◽

Qin Ju ◽

Jie Hao

Keyword(s):

River Basin ◽

Frequency Analysis ◽

Return Period ◽

Extreme Events ◽

Extreme Precipitation ◽

Precipitation Extremes ◽

Regional Frequency Analysis ◽

Hanjiang River ◽

Spatio Temporal ◽

Regional Frequency

Extreme events such as rainstorms and floods are likely to increase in frequency due to the influence of global warming, which is expected to put considerable pressure on water resources. This paper presents a regional frequency analysis of precipitation extremes and its spatio-temporal pattern characteristics based on well-known index-flood L-moments methods and the application of advanced statistical tests and spatial analysis techniques. The results indicate the following conclusions. First, during the period between 1969 and 2015, the annual precipitation extremes at Fengjie station show a decreasing trend, but the Wuhan station shows an increasing trend, and the other 24 stations have no significant trend at a 5% confidence level. Secondly, the Hanjiang River Basin can be categorized into three homogenous regions by hierarchical clustering analysis with the consideration of topography and mean precipitation in these areas. The GEV, GNO, GPA and P III distributions fit better for most of the basin and MARE values range from 3.19% to 6.41% demonstrating that the best-fit distributions for each homogenous region is adequate in predicting the quantiles estimates. Thirdly, quantile estimates are reliable enough when the return period is less than 100 years, however estimates for a higher return period (e.g., 1000 years) become unreliable. Further, the uncertainty of quantiles estimations is growing with the growing return periods and the estimates based on R95P series have a smaller uncertainty to describe the extreme precipitation in the Hanjiang river basin (HJRB). Furthermore, In the HJRB, most of the extreme precipitation events (more than 90%) occur during the rainy season between May and October, and more than 30% of these extreme events concentrate in July, which is mainly impacted by the sub-tropical monsoon climate. Finally, precipitation extremes are mainly concentrated in the areas of Du River, South River and Daba Mountain in region I and Tianmen, Wuhan and Zhongxiang stations in region III, located in the upstream of Danjiangkou Reservoir and Jianghan Plain respectively. There areas provide sufficient climate conditions (e.g., humidity and precipitation) responsible for the occurring floods and will increase the risk of natural hazards to these areas.

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Climate change attribution with large ensembles

10.5194/egusphere-egu21-3404 ◽

2021 ◽

Author(s):

Megan Kirchmeier-Young ◽

Xuebin Zhang ◽

Hui Wan

Keyword(s):

Extreme Precipitation ◽

Extreme Event ◽

Extreme Temperature ◽

Anthropogenic Forcing ◽

Robust Detection ◽

Continental Scale ◽

Extreme Precipitation Events ◽

Event Attribution ◽

Large Ensembles ◽

Precipitation Events

The large sample sizes from single-model large ensembles are beneficial for a robust attribution of climate changes to anthropogenic forcing. This presentation will review examples using large ensembles in two types of attribution:&#160; standard detection and attribution of spatio-temporal changes and extreme event attribution. First, increases in extreme precipitation have been attributed to anthropogenic forcing at large scales (global and hemispheric). We present results from a study that used three large ensembles, including two Earth System Models and one Regional Climate Model, to find a robust detection of a combined anthropogenic and natural forcing signal in the intensification of extreme precipitation at the continental scale and some regional scales in North America. Second, we use six large ensembles to assess the robustness of the attribution of extreme temperature and precipitation events. An event attribution framework is used and each large ensemble is treated as a perfect model. Robustness of the attribution is defined based on consistent agreement between the different models on a significant change in the probability of an event with the inclusion of anthropogenic forcing. We demonstrate that the attribution of extreme temperature events is robust. Meanwhile, the attribution of extreme precipitation events becomes robust in many regions under additional warming, but uncertainties pertaining to changes in atmospheric dynamics hinder attribution confidence in other regions. We also demonstrate that smaller ensembles bring larger uncertainty to event attribution.

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Comparison of spatio-temporal evolution of extreme precipitation events between two high-resolution models in a northern Europe case study

10.5194/egusphere-egu2020-18467 ◽

2020 ◽

Author(s):

Emma D. Thomassen ◽

Elisabeth Kendon ◽

Hjalte J. D. Sørup ◽

Steven Chan ◽

Peter L. Langen ◽

...

Keyword(s):

Extreme Events ◽

Climate Models ◽

Maximum Size ◽

Maximum Intensity ◽

Precipitation Extremes ◽

Movement Direction ◽

Data Sampling ◽

Threshold Method ◽

Extreme Precipitation Events ◽

Spatio Temporal

Convection Permitting Models (CPM) are believed to improve the representation of precipitation extremes at sub-daily scale compared to coarser spatial scale Regional Climate Models (RCM). This study seeks to compare how the spatio-temporal characteristics of precipitation extremes differ between a 2.2km CPM and a 12km RCM from the UK Met Office with a pan-European domain.Storm data have been re-gridded to a common 12km grid and all events in the period from 1999-2008 are tracked with the DYMECS tracking algorithm. A peak-over-threshold method is used to sample extreme events within a northern European case area. Maximum intensity and maximum area of extremes are sampled based on the maximum intensity and maximum size reached within their lifetime. Evolution in size and intensity, track patterns, and seasonal occurrence of extreme events are compared between the two models.For the top 1000 extreme events with the highest maximum intensities, the two models show disagreement in movement direction and spatial and temporal occurrence. While the CPM data are dominated by south-north moving events occurring in summer over central Europe, the RCM data are dominated by west-east moving events occurring over UK and more uniformly distribution over the year. The CPM and RCM however show good agreement in these variables for extreme events instead selected based on largest spatial area. A comparison with the COSMO REA6 reanalysis model continuously nudged towards observations indicates a similar spatial and seasonal distribution of extreme events sampled by maximum intensity as in the CPM. Analysis of the evolution of storms over their lifetime shows on average higher intensities and spatial areas of the most intense storms in the RCM data compared to the most intense storms in the CPM data. Sampling of maximum intensity extreme events in each of the four seasons show larger disagreement between the two models in the evolution in intensity and size in autumn (SON) and winter (DJF) than in spring (MAM) and summer (JJA).

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EXTREME EVENTS OF PRECIPITATION AND OCCURRENCES OF FLOODING, RUNOFF AND INUNDATION IN THE METROPOLITAN REGION OF CURITIBA, BRAZIL

Geografia em Questão ◽

10.48075/geoq.v14i02.25902 ◽

2021 ◽

Vol 14 (2) ◽

Author(s):

Nathan Felipe da Silva Caldana ◽

Leonardo Rodrigues ◽

Luis Gustavo Batista Ferreira ◽

Marcelo Augusto De Aguiar e Silva

Keyword(s):

Extreme Events ◽

Rural Areas ◽

Extreme Precipitation ◽

Rainfall Variability ◽

Metropolitan Region ◽

Severe Damage ◽

Extreme Precipitation Events ◽

Urban And Rural Areas ◽

Precipitation Events

Extreme precipitation events cause severe damage in both urban and rural areas. The objective of this work was to analyze rainfall variability, understand the dynamics of extreme precipitation events and to find out the occurrence of floods, runoff and inundation in the Metropolitan Region of Curitiba (MRC). Data from 39 rainfall stations distributed in the MRC area were used, as well as data by municipality of occurrence of flooding, runoff or inundation, from 1976 to 2018. Extreme precipitation events were identified in all months, most frequently in the summer. Totaling 48 decrees of emergency or public calamity and 397,516 people affected by one of the three socioenvironmental disasters.

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Extreme precipitation events during the South Asian summer monsoon season in the past century

10.5194/egusphere-egu21-6418 ◽

2021 ◽

Author(s):

Renaud Falga ◽

Chien Wang

Keyword(s):

South Asian ◽

Extreme Events ◽

Extreme Precipitation ◽

Monsoon Season ◽

Past Century ◽

South Asian Summer Monsoon ◽

The South ◽

The Past ◽

Extreme Precipitation Events ◽

Precipitation Events

The South Asian monsoon system impacts the livelihoods of over a billion people. While the overall monsoon rainfall is believed to have decreased during the 20th century, there is a good agreement that the extreme precipitation events have been rising in some parts of India. As an important part of the Indian population is dependent on rainfed agriculture, such a rise in extremes, along with resulting flood events, can be all the more problematic. Although studies tend to link this rise in extreme events with anthropogenic forcing, some uncertainties remain on the exact causes. In order to examine the correlation between anthropogenic forcings and the different trends in extreme events, we have analyzed the high-resolution daily rainfall data in the past century delivered by the Indian Meteorological Department alongside several other economic and ecological estimates. The results from this analysis will be presented in detail.

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Spatiotemporal Changes in Extreme Precipitation and Its Dependence on Topography over the Poyang Lake Basin, China

Advances in Meteorology ◽

10.1155/2019/1253932 ◽

2019 ◽

Vol 2019 ◽

pp. 1-15 ◽

Cited By ~ 4

Author(s):

Xianghu Li ◽

Qi Hu

Keyword(s):

Water Resources ◽

Extreme Precipitation ◽

Poyang Lake ◽

Precipitation Extremes ◽

Lake Basin ◽

Extreme Precipitation Events ◽

Poyang Lake Basin ◽

Spatiotemporal Changes ◽

Increasing Trends ◽

Precipitation Events

Spatiotemporal changes in extreme precipitation at local scales in the context of climate warming are overwhelmingly important for prevention and mitigation of water-related disasters and also provide critical information for effective water resources management. In this study, the variability and trends of extreme precipitation in both time and space in the Poyang Lake basin over the period of 1960–2012 are analyzed. Also, changes in precipitation extremes with topography are investigated, and possible causes are briefly discussed. The results show that extreme precipitation over the Poyang Lake basin is intensified during the last 50 years, especially the increasing trends are more significant before the end of the 1990s. Moreover, high contribution rates of extreme precipitation to the total rainfall (40–60%) indicated that extreme precipitation plays an important role to the total water resources in this area. The precipitation extremes also exhibited a significant spatial dependence in the basin. The northeastern and eastern areas are exposed to high risk of flood disaster with the higher frequency of extreme precipitation events. In addition, the distribution of precipitation extremes had a clear dependence on elevation, and the topography is an important factor affecting the variability of extreme precipitation over the Poyang Lake basin.

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Evaluation of NASA’s MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

Journal of Hydrometeorology ◽

10.1175/jhm-d-15-0097.1 ◽

2016 ◽

Vol 17 (2) ◽

pp. 693-711 ◽

Cited By ~ 16

Author(s):

Hamed Ashouri ◽

Soroosh Sorooshian ◽

Kuo-Lin Hsu ◽

Michael G. Bosilovich ◽

Jaechoul Lee ◽

...

Keyword(s):

United States ◽

Extreme Precipitation ◽

Gulf Coast ◽

The United States ◽

Value Theory ◽

Extreme Value ◽

Precipitation Extremes ◽

Precipitation Product ◽

Extreme Precipitation Events ◽

Precipitation Events

Abstract This study evaluates the performance of NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979–2010. The Climate Prediction Center (CPC) U.S. Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scale patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRA tends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1) MERRA shows a spurious negative trend in Nebraska and Kansas, which is most likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over the Gulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. In addition, the increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.

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Large-Scale Predictors for Extreme Hourly Precipitation Events in Convection-Permitting Climate Simulations

Journal of Climate ◽

10.1175/jcli-d-17-0404.1 ◽

2018 ◽

Vol 31 (6) ◽

pp. 2115-2131 ◽

Cited By ~ 13

Author(s):

Steven C. Chan ◽

Elizabeth J. Kendon ◽

Nigel Roberts ◽

Stephen Blenkinsop ◽

Hayley J. Fowler

Keyword(s):

Extreme Precipitation ◽

Land Surface ◽

Large Scale ◽

Future Climate ◽

Cumulus Parameterization ◽

Hourly Precipitation ◽

Vertical Stability ◽

Extreme Precipitation Events ◽

Climate Simulations ◽

Precipitation Events

Midlatitude extreme precipitation events are caused by well-understood meteorological drivers, such as vertical instability and low pressure systems. In principle, dynamical weather and climate models behave in the same way, although perhaps with the sensitivities to the drivers varying between models. Unlike parameterized convection models (PCMs), convection-permitting models (CPMs) are able to realistically capture subdaily extreme precipitation. CPMs are computationally expensive; being able to diagnose the occurrence of subdaily extreme precipitation from large-scale drivers, with sufficient skill, would allow effective targeting of CPM downscaling simulations. Here the regression relationships are quantified between the occurrence of extreme hourly precipitation events and vertical stability and circulation predictors in southern United Kingdom 1.5-km CPM and 12-km PCM present- and future-climate simulations. Overall, the large-scale predictors demonstrate skill in predicting the occurrence of extreme hourly events in both the 1.5- and 12-km simulations. For the present-climate simulations, extreme occurrences in the 12-km model are less sensitive to vertical stability than in the 1.5-km model, consistent with understanding the limitations of cumulus parameterization. In the future-climate simulations, the regression relationship is more similar between the two models, which may be understood from changes to the large-scale circulation patterns and land surface climate. Overall, regression analysis offers a promising avenue for targeting CPM simulations. The authors also outline which events would be missed by adopting such a targeted approach.

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Downscaling Extreme Precipitation from CMIP5 Simulations Using Historical Analogs

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-16-0250.1 ◽

2017 ◽

Vol 56 (9) ◽

pp. 2421-2439 ◽

Cited By ~ 6

Author(s):

Christopher M. Castellano ◽

Arthur T. DeGaetano

Keyword(s):

Return Period ◽

Extreme Precipitation ◽

Daily Precipitation ◽

Precipitation Extremes ◽

Cmip5 Models ◽

Composite Analysis ◽

Analog Method ◽

Precipitation Frequency ◽

Weather Patterns ◽

Synoptic Weather

AbstractAn approach for downscaling daily precipitation extremes using historical analogs is applied to simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The method employs a multistep procedure in which the occurrence of extreme precipitation on a given target day is determined on the basis of the probability of extreme precipitation on that day’s closest historical analogs. If extreme precipitation is expected, daily precipitation observations associated with the historical analogs are used to approximate precipitation amounts on the target day. By applying the analog method to historical simulations, the ability of the CMIP5 models to simulate synoptic weather patterns associated with extreme precipitation is assessed. Differences between downscaled and observed precipitation extremes are investigated by comparing the precipitation frequency distributions for a subset of rarely selected extreme analog days with those for all observed days with extreme precipitation. A supplemental composite analysis of the synoptic weather patterns on these rarely selected analog days is utilized to elucidate the meteorological factors that contribute to such discrepancies. Overall, the analog method as applied to CMIP5 simulations yields realistic estimates of historical precipitation extremes, with return-period precipitation biases that are comparable in magnitude to those obtained from dynamically downscaled simulations. The analysis of rarely selected analog days reveals that precipitation amounts on these days are generally larger than precipitation amounts on all days with extreme precipitation, leading to an underestimation of return-period precipitation amounts at many stations. Furthermore, the synoptic composite analysis reveals that tropical cyclones are a common feature on these rarely selected analog days.

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Spatial and Temporal Analysis of Precipitation Extremities of Eastern Nepal in the Last Two Decades (1997–2016)

10.5194/egusphere-egu2020-2784 ◽

2020 ◽

Author(s):

Sunil Subba ◽

Yaoming Ma ◽

Weiqiang Ma

Keyword(s):

Climate Change ◽

Extreme Events ◽

Extreme Precipitation ◽

Tropical Rainfall Measuring Mission ◽

Heavy Precipitation ◽

Temporal Analysis ◽

Extreme Precipitation Events ◽

Slope Estimator ◽

The Impact ◽

Precipitation Events

In recent days there have been discussions regarding the impact of climate change and its vagaries of the weather, particularly concerning extreme events. Nepal, being a mountainous country, is more susceptible to precipitation extreme events and related hazards, which hinder the socioeconomic development of the nation. In this regard, this study aimed to address this phenomenon for one of the most naturally and socioeconomically important regions of Nepal, namely, Eastern Nepal. The data were collected for the period of 1997 to 2016. The interdecadal comparison for two periods (1997&#8211;2006 and 2007&#8211;2016) was maintained for the calculation of extreme precipitation indices as per recommended by Expert Team on Climate Change Detection and Indices. Linear trends were calculated by using Mann&#8208;Kendall and Sen's Slope estimator. The average annual precipitation was found to be decreasing at an alarming rate of &#8722;20 mm/year in the last two decades' tenure. In case of extreme precipitation events, consecutive dry days, one of the frequency indices, showed a solo increase in its trend (mostly significant). Meanwhile, all the intensity indices of extreme precipitation showed decreasing trends (mostly insignificant). Thus, it can be concluded that Eastern Nepal has witnessed some significant drier days in the last two decades, as the events of heavy, very heavy, extremely heavy precipitation events, and annual wet day precipitation (PRCPTOT) were found to be decreasing. The same phenomena were also seen in the Tropical Rainfall Measuring Mission 3B42 V7 satellite precipitation product for whole Nepal.

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