scholarly journals Downscaling Extreme Precipitation from CMIP5 Simulations Using Historical Analogs

2017 ◽  
Vol 56 (9) ◽  
pp. 2421-2439 ◽  
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.

Simulation of Northeast U.S. Extreme Precipitation and Its Associated Circulation by CMIP5 Models

2020 ◽  
Vol 33 (22) ◽  
pp. 9817-9834
Author(s):  
Laurie Agel ◽  
Mathew Barlow ◽  
Joseph Polonia ◽  
David Coe
Keyword(s):  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Coupled Model ◽  
Precipitation Intensity ◽  
Cmip5 Models ◽  
Seasonal Cycles ◽  
Precipitation Frequency ◽  
Circulation Patterns ◽  
Intercomparison Project ◽  
Approximate Magnitude

AbstractHistorical simulations from 14 models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated for their ability to reproduce observed precipitation in the northeastern United States and its associated circulation, with particular emphasis on extreme (top 1%) precipitation. The models are compared to observations in terms of the spatial variations of extreme precipitation, seasonal cycles of precipitation and extreme precipitation frequency and intensity, and extreme precipitation circulation regimes. The circulation regimes are identified using k-means clustering of 500-hPa geopotential heights on extreme precipitation days, in both observations and in the models. While all models capture an observed northwest-to-southeast gradient of precipitation intensity (reflected in the top 1% threshold), there are substantial differences from observations in the magnitude of the gradient. These differences tend to be more substantial for lower-resolution models. However, regardless of resolution, and despite a bias toward too-frequent precipitation, many of the models capture the seasonality of observed daily precipitation intensity, and the approximate magnitude and seasonality of observed extreme precipitation intensity. Many of the simulated extreme precipitation circulation patterns are visually similar to the set of observed patterns. However, the location and magnitude of specific troughs and ridges within the patterns, as well as the seasonality of the patterns, may differ substantially from the observed corresponding patterns. A series of metrics is developed based on the observed regional characteristics to facilitate comparison between models.

scholarly journals Precipitation Extremes Estimated by GPCP and TRMM: ENSO Relationships

2007 ◽  
Vol 8 (4) ◽  
pp. 678-689 ◽  
Author(s):  
Scott Curtis ◽  
Ahmed Salahuddin ◽  
Robert F. Adler ◽  
George J. Huffman ◽  
Guojun Gu ◽  
...  
Keyword(s):  
El Niño ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Precipitation Climatology Project ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Precipitation Frequency ◽  
Rain Rates

Abstract Global monthly and daily precipitation extremes are examined in relation to the El Niño–Southern Oscillation phenomenon. For each month around the annual cycle and in each 2.5° grid block, extremes in the Global Precipitation Climatology Project dataset are defined as the top five (wet) and bottom five (dry) mean rain rates from 1979 to 2004. Over the tropical oceans El Niño–Southern Oscillation events result in a spatial redistribution and overall increase in extremes. Restricting the analysis to land shows that El Niño is associated with an increase in frequency of dry extremes and a decrease in wet extremes resulting in no change in net extreme months. During La Niña an increase in frequency of dry extremes and no change in wet extremes are observed. Thus, because of the juxtaposition of tropical land areas with the ascending branches of the global Walker Circulation, El Niño (La Niña) contributes to generally dry (wet) conditions in these land areas. In addition, daily rain rates computed from the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis are used to define extreme precipitation frequency locally as the number of days within a given season that exceeded the 95th percentile of daily rainfall for all seasons (1998–2005). During this period, the significant relationships between extreme daily precipitation frequency and Niño-3.4 in the Tropics are spatially similar to the significant relationships between seasonal mean rainfall and Niño-3.4. However, to address the shortness of the record extreme daily precipitation frequency is also related to seasonal rainfall for the purpose of identifying regions where positive seasonal rainfall anomalies can be used as proxies for extreme events. Finally, the longer (1979–2005) but coarser Global Precipitation Climatology Project analysis is reexamined to pinpoint regions likely to experience an increase in extreme precipitation during El Niño–Southern Oscillation events. Given the significance of El Niño–Southern Oscillation predictions, this information will enable the efficient use of resources in preparing for and mitigating the adverse effects of extreme precipitation.

Evaluation of extreme precipitation over the Nordic region using a convection-permitting regional climate model

2020 ◽  
Author(s):  
Erika Toivonen ◽  
Danijel Belušić ◽  
Emma Dybro Thomassen ◽  
Peter Berg ◽  
Ole Bøssing Christensen ◽  
...  
Keyword(s):  
High Resolution ◽  
Regional Climate Model ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Daily Precipitation ◽  
Regional Climate ◽  
Precipitation Extremes ◽  
Nordic Region ◽  
Mesh Resolution ◽  
Grid Mesh

<p>Extreme precipitation events have a major impact upon our society. Although many studies have indicated that it is likely that the frequency of such events will increase in a warmer climate, little has been done to assess changes in extreme precipitation at a sub-daily scale. Recently, there is more and more evidence that <span>high-resolution convection-permitting models </span><span>(CPMs)</span> (grid-mesh typically < 4 km) can represent especially short-duration precipitation extremes more accurately when compared with coarser-resolution <span>regional climate model</span><span>s </span><span>(RCMs)</span><span>.</span></p><p>This study investigates sub-daily and daily precipitation characteristics based on hourly <span>output data from the HARMONIE-Climate model </span>at 3-km and 12-km grid-mesh resolution over the Nordic region between 1998 and 2018. The RCM modelling chain uses the ERA-Interim reanalysis to drive a 12-km grid-mesh simulation which is further downscaled to 3-km grid-mesh resolution using a non-hydrostatic model set-up.</p><p>The statistical properties of the modeled extreme precipitation are compared to several sub-daily and daily observational products, including gridded and in-situ gauge data, from April to September. We investigate the skill of the model to represent different aspects of the frequency and intensity of extreme precipitation as well as intensity–duration–frequency (IDF) curves that are commonly used to investigate short duration extremes from an urban planning perspective. The high grid resolution combined with the 20-year-long simulation period allows for a robust assessment at a climatological time scale <span>and enables us to examine the added value of high-resolution </span><span>CPM</span><span> in reproducing precipitation extremes over the Nordic </span><span>region</span><span>. </span><span>Based on the tentative results, the high-resolution CPM can realistically capture the </span><span>characteristics </span><span>of precipitation extremes, </span><span>for instance, </span><span>in terms of improved diurnal cycle and maximum intensities of sub-daily precipitation.</span></p>

Investigating the seasonal response of precipitation extremes to global warming using observations and large-ensembles of coupled climate models

2020 ◽  
Author(s):  
Andrew Williams ◽  
Paul O'Gorman
Keyword(s):  
Global Warming ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Precipitation Extremes ◽  
Cmip5 Models ◽  
Historical Period ◽  
Societal Relevance ◽  
Coupled Climate Models

<p>Changes in extreme precipitation are amongst the most impactful consequences of global warming, with potential effects ranging from increased flood risk and landslides to crop failures and impacts on ecosystems. Thus, understanding historical and future changes in extreme precipitation is not only important from a scientific perspective, but also has direct societal relevance.</p><p>However, while most current research has focused on annual precipitation extremes and their response to warming, it has recently been noted that climate model projections show a distinct seasonality to future changes in extreme precipitation. In particular, CMIP5 models suggest that over Northern Hemisphere (NH) land the summer response is weaker than the winter response in terms of percentage changes.</p><p>Here we investigate changes in seasonal precipitation extremes using observations and simulations with coupled climate models. First, we analyse observed trends from the Hadley Centre’s global climate extremes dataset (HadEX2) to investigate to what extent there is already a difference between summer and winter trends over NH land. Second, we use 40 ensemble members from the CESM Large Ensemble to characterize the role played by internal variability in trends over the historical period. Lastly, we use CMIP5 simulations to explore the possibility of a link between the seasonality of changes in precipitation extremes and decreases in surface relative humidity over land.</p>

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 Long term changes of the sub-daily precipitation extremes in Hungary

2021 ◽  
Author(s):  
Monika Lakatos ◽  
Olivér Szentes
Keyword(s):  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Heavy Precipitation ◽  
Data Series ◽  
Precipitation Frequency ◽  
Maximum Rainfall ◽  
Extreme Precipitation Events ◽  
Digital Database ◽  
Precipitation Changes

<p>The warming climate evokes increasing frequency of extreme precipitation in some region. Analysis of long-term measurements could support the better understanding of the processes that cause extreme precipitation events.</p><p>Automatic stations replaced the ombrometer in many places in Hungary, particularly from the late 1990s. The change of the measurement practice do not allow simply merging the data recorded form the registering paper in the past and the recent 10 minutes measurements.   The most intense 5, 10, 20, 30, 60, 180 min sub-totals per rainfall events were recorded from the ombrometer registering paper before atomization, typically until 1993. By contrast, the 10 min precipitation sum from the AWSs are stored in the meteorological database of the Hungarian Meteorological Service from automatization. In order to join together the older and the AWS measurements it was necessary to develop a method to make this possible. Therefore we downscaled the 10 min data in time. The sampling of the AWSs is one minute, although the 1-minute data are available only for some stations in the digital database.  We applied a linear regression model to downscale the 10-miniute data for 1 min. After this, we can derive the most intense sub-totals per events from the AWS data as if they have been measured with the ombrometers.</p><p>Thereby a set of sub-daily precipitation indices defined in the INTENSE project (https://research.ncl.ac.uk/intense/aboutintense/ can be computed for longer data series. Some of the indices specified in INTENSE project describes the maximum rainfall totals and timing, the intensity, duration and frequency of heavy precipitation, frequency of rainfall above specific thresholds and some of them is related to diurnal cycle. A few of these indices are analysed for long data series to detect the sub-daily precipitation changes in Hungary.</p>

scholarly journals Global trends in extreme precipitation: climate models versus observations

2015 ◽  
Vol 19 (2) ◽  
pp. 877-891 ◽  
Author(s):  
B. Asadieh ◽  
N. Y. Krakauer
Keyword(s):  
Global Warming ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Daily Precipitation ◽  
Average Rate ◽  
Global Scale ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
Annual Maximum ◽  
Rate Of Increase

Abstract. Precipitation events are expected to become substantially more intense under global warming, but few global comparisons of observations and climate model simulations are available to constrain predictions of future changes in precipitation extremes. We present a systematic global-scale comparison of changes in historical (1901–2010) annual-maximum daily precipitation between station observations (compiled in HadEX2) and the suite of global climate models contributing to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). We use both parametric and non-parametric methods to quantify the strength of trends in extreme precipitation in observations and models, taking care to sample them spatially and temporally in comparable ways. We find that both observations and models show generally increasing trends in extreme precipitation since 1901, with the largest changes in the deep tropics. Annual-maximum daily precipitation (Rx1day) has increased faster in the observations than in most of the CMIP5 models. On a global scale, the observational annual-maximum daily precipitation has increased by an average of 5.73 mm over the last 110 years, or 8.5% in relative terms. This corresponds to an increase of 10% K−1 in global warming since 1901, which is larger than the average of climate models, with 8.3% K−1. The average rate of increase in extreme precipitation per K of warming in both models and observations is higher than the rate of increase in atmospheric water vapor content per K of warming expected from the Clausius–Clapeyron equation. We expect our findings to help inform assessments of precipitation-related hazards such as flooding, droughts and storms.

Global scaling of observed sub-daily precipitation extremes to dewpoint temperature

2020 ◽  
Author(s):  
Haider Ali ◽  
Hayley Fowler ◽  
Geert Lenderink ◽  
Elizabeth Lewis
Keyword(s):  
Air Temperature ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
The United States ◽  
Precipitation Extremes ◽  
Precipitation Data ◽  
Lower Altitude ◽  
Dewpoint Temperature ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data

<p>The intensity and frequency of extreme precipitation events have increased globally and are likely to rise further under the warming climate. The Clausius-Clapeyron (CC) relationship (scaling) provides a physical basis to understand the relationship of precipitation extremes with temperature. Recent studies have used global sub-daily precipitation data from satellite, reanalysis and climate model outputs (due to the limited availability of long term observed sub-daily data at global scales) and have reported a higher sensitivity of sub-daily precipitation extremes to surface air temperature than for daily extremes. Moreover, at higher temperatures, moisture availability becomes the dominant driver of extreme precipitation, therefore, dewpoint temperature can be a better scaling variable to overcome humidity limitations as compared to air temperature. Here, we used hourly precipitation data from the Global Sub-daily Rainfall (GSDR) dataset and daily dewpoint temperature data (DPT) from the Met Office Hadley Centre observations dataset (HadISD) at 6695 locations across the United States of America, Australia, Europe, Japan, India and Malaysia. We found that more than 60% of locations (scaling estimated for individual location) show scaling greater than 7%/K (CC rate). Moreover, more than 55% of locations across Europe, Japan, Australia and Malaysia show scaling greater than 1.5CC. Furthermore, when locations across selected regions are pooled within similar climatic zones (based on Koppen Geiger classification), scaling curves show around 7%/K scaling. The scaling curves for locations at greater altitude (>400m MSL) are flat compared to locations at relatively lower altitude. The difference in scaling rates at-station and for pooled regions highlight the importance of understanding the thermodynamic and dynamic processes governing precipitation extremes at different spatial scales and indicate that local processes are driving the super-CC sensitivities in most regions.</p>

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.

Daily precipitation characteristics of RegCM4 and WRF in China and their interannual variations

2020 ◽  
Vol 82 ◽  
pp. 97-115
Author(s):  
X Kong ◽  
A Wang ◽  
X Bi ◽  
J Wei
Keyword(s):  
Extreme Precipitation ◽  
Climate Models ◽  
Daily Precipitation ◽  
Regional Climate ◽  
Precipitation Amount ◽  
Extreme Rainfall ◽  
Horizontal Resolution ◽  
Interannual Variations ◽  
Precipitation Frequency ◽  
Precipitation Characteristics

To evaluate and clarify the daily precipitation characteristics (i.e. amount, frequency and intensity) of the regional climate models (RCMs) in China, long-term simulations were carried out using RegCM4.5 and Weather Research and Forecasting model (WRF), which were nested within the European Centre for Medium-Range Weather Forecasts (ECMWF)’s 20th century reanalysis (ERA-20C) between 1901 and 2010. The 2 RCMs were initially run at a resolution of 50 km. Analyses mainly compared the model-simulated climatic means and interannual variations of precipitation characteristics with those of dense and high-quality station observations (STN) from 1961-2010. Both models satisfactorily reproduced the seasonal mean precipitation amount, but they overestimated its frequency and underestimated its intensity. Extreme rainfall frequency was also underestimated by both RCMs. In winter (DJF), the interannual variabilities in dry days, light precipitation and moderate precipitation were well represented by both models. However, they poorly reproduced the counterparts of extreme precipitation in winter. In summer (JJA), the 2 RCMs performed well in simulating the interannual variability of extreme precipitation. Comparably, RegCM outperformed WRF in reproducing the spatial patterns of precipitation amount, interannual variations in extreme precipitation and rain events. By contrast, WRF better represented precipitation frequency in different sub-regions overall. Moreover, when the horizontal resolution of RegCM was increased from 50 to 25 km, there was a slight improvement in the representation of precipitation amount and intensity. Our results show that RCMs perform well in reproducing actual climatic means and interannual variations of daily precipitation characteristics in China, and that high-resolution RCM simulations can produce improved results for precipitation amount and intensity.

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