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

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

<p>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.</p><p>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.</p><p>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).</p>

scholarly journals Projected Seasonal Changes in Large-Scale Global Precipitation and Temperature Extremes Based on the CMIP5 Ensemble

2020 ◽  
Vol 33 (13) ◽  
pp. 5651-5671 ◽  
Author(s):  
Wang Zhan ◽  
Xiaogang He ◽  
Justin Sheffield ◽  
Eric F. Wood
Keyword(s):  
Extreme Events ◽  
Large Scale ◽  
Climate Models ◽  
Spatial Scales ◽  
Extreme Temperature ◽  
Economic Losses ◽  
Temperature And Precipitation ◽  
Extreme Precipitation Events ◽  
The Future ◽  
Precipitation Events

AbstractOver the past decades, significant changes in temperature and precipitation have been observed, including changes in the mean and extremes. It is critical to understand the trends in hydroclimatic extremes and how they may change in the future as they pose substantial threats to society through impacts on agricultural production, economic losses, and human casualties. In this study, we analyzed projected changes in the characteristics, including frequency, seasonal timing, and maximum spatial and temporal extent, as well as severity, of extreme temperature and precipitation events, using the severity–area–duration (SAD) method and based on a suite of 37 climate models archived in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Comparison between the CMIP5 model estimated extreme events and an observation-based dataset [Princeton Global Forcing (PGF)] indicates that climate models have moderate success in reproducing historical statistics of extreme events. Results from the twenty-first-century projections suggest that, on top of the rapid warming indicated by a significant increase in mean temperature, there is an overall wetting trend in the Northern Hemisphere with increasing wet extremes and decreasing dry extremes, whereas the Southern Hemisphere will have more intense wet extremes. The timing of extreme precipitation events will change at different spatial scales, with the largest change occurring in southern Asia. The probability of concurrent dry/hot and wet/hot extremes is projected to increase under both RCP4.5 and RCP8.5 scenarios, whereas little change is detected in the probability of concurrent dry/cold events and only a slight decrease of the joint probability of wet/cold extremes is expected in the future.

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

Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 130 ◽  
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.

scholarly journals Water Pathways for the Hindu-Kush-Himalaya and an Analysis of Three Flood Events

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 489 ◽  
Author(s):  
Robert Boschi ◽  
Valerio Lucarini
Keyword(s):  
Extreme Events ◽  
Arabian Sea ◽  
Climate Models ◽  
Extreme Event ◽  
Monsoon Season ◽  
Indus Basin ◽  
Monsoon Period ◽  
Gangetic Plain ◽  
Extreme Precipitation Events ◽  
Hindu Kush

The climatology of major sources and pathways of moisture for three locales along the Hindu-Kush-Himalayan region are examined, by use of Lagrangian methods applied to the ERA-Interim dataset, over the period from 1980 to 2016 for both summer (JJA) and winter (NDJ) periods. We also investigate the major flooding events of 2010, 2013, and 2017 in Pakistan, Uttarakhand, and Kathmandu, respectively, and analyse a subset of the climatology associated with the 20 most significant rainfall events over each region of interest. A comparison is made between the climatology and extreme events, in the three regions of interest, during the summer monsoon period. For Northern Pakistan and Uttarakhand, the Indus basin plays the largest role in moisture uptake. Moisture is also gathered from Eastern Europe and Russia. Extreme events display an increased influence of sub-tropical weather systems, which manifest themselves through low-level moisture transport; predominantly from the Arabian sea and along the Gangetic plain. In the Kathmandu region, it is found that the major moisture sources come from the Gangetic plain, Arabian Sea, Red Sea, Bay of Bengal, and the Indus basin. In this case, extreme event pathways largely match those of the climatology, although an increased number of parcels originate from the western end of the Gangetic plain. These results provide insights into the rather significant influence of mid-latitudinal weather systems, even during the monsoon season, in defining the climatology of the Hindu-Kush-Himalaya region, as well as how extreme precipitation events in this region represent atypical moisture pathways. We propose a detailed investigation of how such water pathways are represented in climate models for the present climate conditions and in future climate scenarios, as this may be extremely relevant for understanding the impacts of climate change on the cryosphere and hydrosphere of the region.

The Resolution Dependence of Contiguous U.S. Precipitation Extremes in Response to CO2 Forcing

2016 ◽  
Vol 29 (22) ◽  
pp. 7991-8012 ◽  
Author(s):  
Karin van der Wiel ◽  
Sarah B. Kapnick ◽  
Gabriel A. Vecchi ◽  
William F Cooke ◽  
Thomas L. Delworth ◽  
...  
Keyword(s):  
Extreme Events ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Precipitation Extremes ◽  
Model Resolution ◽  
Intrinsic Variability ◽  
Regional Patterns ◽  
Co2 Concentrations ◽  
Resolution Model ◽  
Atmospheric Co2 Concentrations

Abstract Precipitation extremes have a widespread impact on societies and ecosystems; it is therefore important to understand current and future patterns of extreme precipitation. Here, a set of new global coupled climate models with varying atmospheric resolution has been used to investigate the ability of these models to reproduce observed patterns of precipitation extremes and to investigate changes in these extremes in response to increased atmospheric CO2 concentrations. The atmospheric resolution was increased from 2° × 2° grid cells (typical resolution in the CMIP5 archive) to 0.25° × 0.25° (tropical cyclone permitting). Analysis has been confined to the contiguous United States (CONUS). It is shown that, for these models, integrating at higher atmospheric resolution improves all aspects of simulated extreme precipitation: spatial patterns, intensities, and seasonal timing. In response to 2 × CO2 concentrations, all models show a mean intensification of precipitation rates during extreme events of approximately 3%–4% K−1. However, projected regional patterns of changes in extremes are dependent on model resolution. For example, the highest-resolution models show increased precipitation rates during extreme events in the hurricane season in the U.S. Southeast; this increase is not found in the low-resolution model. These results emphasize that, for the study of extreme precipitation there is a minimum model resolution that is needed to capture the weather phenomena generating the extremes. Finally, the observed record and historical model experiments were used to investigate changes in the recent past. In part because of large intrinsic variability, no evidence was found for changes in extreme precipitation attributable to climate change in the available observed record.

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

2020 ◽  
Vol 33 (3) ◽  
pp. 1089-1103 ◽  
Author(s):  
Jean-Luc Martel ◽  
Alain Mailhot ◽  
François Brissette
Keyword(s):  
Return Period ◽  
Extreme Events ◽  
Extreme Precipitation ◽  
Precipitation Extremes ◽  
Design Criteria ◽  
Service Levels ◽  
Extreme Precipitation Events ◽  
Climate Simulations ◽  
Large Ensembles ◽  
Projected Changes

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.

scholarly journals Space-Time Assessment of Extreme Precipitation in Cuba between 1980 and 2019 from Multi-Source Weighted-Ensemble Precipitation Dataset

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 995
Author(s):  
Gleisis Alvarez-Socorro ◽  
José Carlos Fernández-Alvarez ◽  
Rogert Sorí ◽  
Albenis Pérez-Alarcón ◽  
Raquel Nieto ◽  
...  
Keyword(s):  
Extreme Events ◽  
Extreme Precipitation ◽  
Grid Point ◽  
Extreme Rainfall ◽  
Precipitation Anomaly ◽  
Rainy Period ◽  
Enso Events ◽  
Extreme Precipitation Events ◽  
Daily Data ◽  
Spatio Temporal

Precipitation extremes such as heavy rainfall and floods are of great interest for climate scientists, particularly for small islands vulnerable to weather phenomena such as hurricanes. In this study, we investigated the spatio-temporal evolution of extreme rainfall over Cuba from 1980 to 2019, separating the dry and rainy periods. In addition, a ranking of extreme precipitation events was performed, which provides the number of events, the area affected, and a ranking of their magnitude by considering the magnitude of anomalies. The analysis was conducted using daily data from the multi-source weighted-ensemble precipitation (MSWEPv2). In determining the extreme precipitation ranking, the daily extreme precipitation anomaly was calculated with respect to the 95th percentile climatological distribution, giving a measure of the rarity of the event for each day and each grid point. For a more detailed analysis regarding the ranking, a separation was made by regions applying the K-mean methodology. The months belonging to the rainy period of the year presented the highest amount of precipitation above the 95th percentile compared to results obtained for the dry period. Of the six months belonging to the cyclonic season, in five of them Cuba was affected, directly or indirectly, by a tropical cyclone. The years 1982–83 and 1998 presented the highest-ranking value for the dry and rainy periods, respectively. Moreover, a trend analysis revealed an increase in the trend of occurrence of extreme events and a decrease in the percentage of the area affected. The analysis by regions showed a similar behavior to that carried out for all of Cuba. It was found that the warm phase of the ENSO events influenced approximately ~22% of the occurrence of extreme events for both periods.

scholarly journals A climatology of sub-seasonal temporal clustering of extreme precipitation in Switzerland and its impacts

2021 ◽  
Author(s):  
Alexandre Tuel ◽  
Olivia Martius
Keyword(s):  
Extreme Precipitation ◽  
Precipitation Extremes ◽  
Flood Events ◽  
Temporal Clustering ◽  
Extreme Precipitation Events ◽  
Southern Side ◽  
Northern Side ◽  
The Alps ◽  
Spatio Temporal ◽  
Seasonal Time Scale

Abstract. The successive occurrence of extreme precipitation events on a sub-seasonal time-scale can lead to large precipitation accumulations, a classic trigger of flood events. Here we analyse sub-seasonal clustering in Switzerland, first characterizing the tendency of precipitation extremes to cluster in time for each season separately, and second, linking the occurrence of persistent flood events to sub-seasonal clusters of precipitation extremes. We find a distinct spatio-temporal pattern in temporal clustering behavior of precipitation extremes, with temporal clustering occurring on the northern side of the Alps in winter, and on their southern side in fall. In winter, the magnitude of precipitation extremes is generally lower, and much of the precipitation falls as snow, therefore temporal clusters contribute little to the occurrence of persistent flood events. In fall, however, temporal clusters associated with large precipitation accumulations over the southern Alps are found to be almost systematically followed by floods. In addition, discharge magnitudes decrease more slowly after clustered extremes.

scholarly journals Data-driven distinction between convective, frontal and mixed extreme rainfall events in radar data

2020 ◽  
Author(s):  
Emma Dybro Thomassen ◽  
Hjalte Jomo Danielsen Sørup ◽  
Marc Scheibel ◽  
Thomas Einfalt ◽  
Karsten Arnbjerg-Nielsen
Keyword(s):  
Extreme Events ◽  
Extreme Event ◽  
Principal Component ◽  
Extreme Rainfall ◽  
Radar Data ◽  
Threshold Method ◽  
Extreme Rainfall Events ◽  
Temporal Properties ◽  
Peak Over Threshold ◽  
Spatio Temporal

Abstract. This study examines characteristics of extreme events based on a high-resolution precipitation dataset (5-minute temporal resolution, 1 &times 1 km spatial resolution) over an area of 1824 km2 covering the catchment of the river Wupper, North Rhine-Westphalia, Germany. Extreme events were sampled by a Peak Over Threshold method using several sampling strategies, all based on selecting an average of three events per year. A simple identification- and tracking algorithm for rain cells based on intensity threshold and fitting of ellipsoids, is developed for the study. Extremes were selected based on maximum intensities for 15-minute, hourly and daily durations and described by a set of 17 variables. The spatio-temporal properties of the extreme events are explored by means of a principal component analysis (PCA) and a cluster analysis for these 17 variables. We found that these analyses enabled us to distinguish and characterise types of extreme events useful for urban hydrology applications. The PCA indicated between 5 and 9 dimensions in the extreme event characteristic data. The cluster analyses identified four rainfall types: convective extremes, frontal extremes, mixed very extreme events and other extreme events, the last group consisting of events that are less extreme than the other events. The result is useful for selecting events of particular interest when assessing performance of e.g. urban drainage systems.

scholarly journals Future precipitation increase from very high resolution ensemble downscaling of extreme atmospheric river storms in California

2020 ◽  
Vol 6 (29) ◽  
pp. eaba1323 ◽  
Author(s):  
Xingying Huang ◽  
Daniel L. Swain ◽  
Alex D. Hall
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Global Climate Model ◽  
Flood Management ◽  
Global Climate Models ◽  
Precipitation Extremes ◽  
Atmospheric River ◽  
Extreme Precipitation Events

Precipitation extremes will likely intensify under climate change. However, much uncertainty surrounds intensification of high-magnitude events that are often inadequately resolved by global climate models. In this analysis, we develop a framework involving targeted dynamical downscaling of historical and future extreme precipitation events produced by a large ensemble of a global climate model. This framework is applied to extreme “atmospheric river” storms in California. We find a substantial (10 to 40%) increase in total accumulated precipitation, with the largest relative increases in valleys and mountain lee-side areas. We also report even higher and more spatially uniform increases in hourly maximum precipitation intensity, which exceed Clausius-Clapeyron expectations. Up to 85% of this increase arises from thermodynamically driven increases in water vapor, with a smaller contribution by increased zonal wind strength. These findings imply substantial challenges for water and flood management in California, given future increases in intense atmospheric river-induced precipitation extremes.

scholarly journals The Value of High-Resolution Met Office Regional Climate Models in the Simulation of Multihourly Precipitation Extremes

2014 ◽  
Vol 27 (16) ◽  
pp. 6155-6174 ◽  
Author(s):  
Steven C. Chan ◽  
Elizabeth J. Kendon ◽  
Hayley J. Fowler ◽  
Stephen Blenkinsop ◽  
Nigel M. Roberts ◽  
...  
Keyword(s):  
High Resolution ◽  
Time Scales ◽  
Return Period ◽  
Extreme Events ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Value Theory ◽  
Precipitation Extremes ◽  
Return Levels

Abstract Extreme value theory is used as a diagnostic for two high-resolution (12-km parameterized convection and 1.5-km explicit convection) Met Office regional climate model (RCM) simulations. On subdaily time scales, the 12-km simulation has weaker June–August (JJA) short-return-period return levels than the 1.5-km RCM, yet the 12-km RCM has overly large high return levels. Comparisons with observations indicate that the 1.5-km RCM is more successful than the 12-km RCM in representing (multi)hourly JJA very extreme events. As accumulation periods increase toward daily time scales, the erroneous 12-km precipitation extremes become more comparable with the observations and the 1.5-km RCM. The 12-km RCM fails to capture the observed low sensitivity of the growth rate to accumulation period changes, which is successfully captured by the 1.5-km RCM. Both simulations have comparable December–February (DJF) extremes, but the DJF extremes are generally weaker than in JJA at daily or shorter time scales. Case studies indicate that “gridpoint storms” are one of the causes of unrealistic very extreme events in the 12-km RCM. Caution is needed in interpreting the realism of 12-km RCM JJA extremes, including short-return-period events, which have return values closer to observations. There is clear evidence that the 1.5-km RCM has a higher degree of realism than the 12-km RCM in the simulation of JJA extremes.

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