scholarly journals Changes in Intense Precipitation over the Central United States

2012 ◽  
Vol 13 (1) ◽  
pp. 47-66 ◽  
Author(s):  
Pavel Ya. Groisman ◽  
Richard W. Knight ◽  
Thomas R. Karl

Abstract In examining intense precipitation over the central United States, the authors consider only days with precipitation when the daily total is above 12.7 mm and focus only on these days and multiday events constructed from such consecutive precipitation days. Analyses show that over the central United States, a statistically significant redistribution in the spectra of intense precipitation days/events during the past decades has occurred. Moderately heavy precipitation events (within a 12.7–25.4 mm day−1 range) became less frequent compared to days and events with precipitation totals above 25.4 mm. During the past 31 yr (compared to the 1948–78 period), significant increases occurred in the frequency of “very heavy” (the daily rain events above 76.2 mm) and extreme precipitation events (defined as daily and multiday rain events with totals above 154.9 mm or 6 in.), with up to 40% increases in the frequency of days and multiday extreme rain events. Tropical cyclones associated with extreme precipitation do not significantly contribute to the changes reported in this study. With time, the internal precipitation structure (e.g., mean and maximum hourly precipitation rates within each preselected range of daily or multiday event totals) did not noticeably change. Several possible causes of observed changes in intense precipitation over the central United States are discussed and/or tested.

Author(s):  
Olivia VanBuskirk ◽  
Paulina Ćwik ◽  
Renee A. McPherson ◽  
Heather Lazrus ◽  
Elinor Martin ◽  
...  

AbstractHeavy precipitation events and their associated flooding can have major impacts on communities and stakeholders. There is a lack of knowledge, however, about how stakeholders make decisions at the sub-seasonal to seasonal (S2S) timescales (i.e., two weeks to three months). To understand how decisions are made and S2S predictions are or can be used, the project team for “Prediction of Rainfall Extremes at Sub-seasonal to Seasonal Periods” (PRES2iP) conducted a two-day workshop in Norman, Oklahoma, during July 2018. The workshop engaged 21 professionals from environmental management and public safety communities across the contiguous United States in activities to understand their needs for S2S predictions of potential extended heavy precipitation events. Discussions and role-playing activities aimed to identify how workshop participants manage uncertainty and define extreme precipitation, the timescales over which they make key decisions, and the types of products they use currently. This collaboration with stakeholders has been an integral part of PRES2iP research and has aimed to foster actionable science. The PRES2iP team is using the information produced from this workshop to inform the development of predictive models for extended heavy precipitation events and to collaboratively design new forecast products with our stakeholders, empowering them to make more-informed decisions about potential extreme precipitation events.


2008 ◽  
Vol 21 (1) ◽  
pp. 22-39 ◽  
Author(s):  
Siegfried D. Schubert ◽  
Yehui Chang ◽  
Max J. Suarez ◽  
Philip J. Pegion

Abstract In this study the authors examine the impact of El Niño–Southern Oscillation (ENSO) on precipitation events over the continental United States using 49 winters (1949/50–1997/98) of daily precipitation observations and NCEP–NCAR reanalyses. The results are compared with those from an ensemble of nine atmospheric general circulation model (AGCM) simulations forced with observed SST for the same time period. Empirical orthogonal functions (EOFs) of the daily precipitation fields together with compositing techniques are used to identify and characterize the weather systems that dominate the winter precipitation variability. The time series of the principal components (PCs) associated with the leading EOFs are analyzed using generalized extreme value (GEV) distributions to quantify the impact of ENSO on the intensity of extreme precipitation events. The six leading EOFs of the observations are associated with major winter storm systems and account for more than 50% of the daily precipitation variability along the West Coast and over much of the eastern part of the country. Two of the leading EOFs (designated GC for Gulf Coast and EC for East Coast) together represent cyclones that develop in the Gulf of Mexico and occasionally move and/or redevelop along the East Coast producing large amounts of precipitation over much of the southern and eastern United States. Three of the leading EOFs represent storms that hit different sections of the West Coast (designated SW for Southwest coast, WC for the central West Coast, and NW for northwest coast), while another represents storms that affect the Midwest (designated by MW). The winter maxima of several of the leading PCs are significantly impacted by ENSO such that extreme GC, EC, and SW storms that occur on average only once every 20 years (20-yr storms) would occur on average in half that time under sustained El Niño conditions. In contrast, under La Niña conditions, 20-yr GC and EC storms would occur on average about once in 30 years, while there is little impact of La Niña on the intensity of the SW storms. The leading EOFs from the model simulations and their connections to ENSO are for the most part quite realistic. The model, in particular, does very well in simulating the impact of ENSO on the intensity of EC and GC storms. The main model discrepancies are the lack of SW storms and an overall underestimate of the daily precipitation variance.


Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1089 ◽  
Author(s):  
Yifeng Peng ◽  
Xiang Zhao ◽  
Donghai Wu ◽  
Bijian Tang ◽  
Peipei Xu ◽  
...  

Extreme precipitation events, which have intensified with global warming over the past several decades, will become more intense in the future according to model projections. Although many studies have been performed, the occurrence patterns for extreme precipitation events in past and future periods in China remain unresolved. Additionally, few studies have explained how extreme precipitation events developed over the past 58 years and how they will evolve in the next 90 years as global warming becomes much more serious. In this paper, we evaluated the spatiotemporal characteristics of extreme precipitation events using indices for the frequency, quantity, intensity, and proportion of extreme precipitation, which were proposed by the World Meteorological Organization. We simultaneously analyzed the spatiotemporal characteristics of extreme precipitation in China from 2011 to 2100 using data obtained from the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Despite the fixed threshold, 95th percentile precipitation values were also used as the extreme precipitation threshold to reduce the influence of various rainfall events caused by different geographic locations; then, eight extreme precipitation indices (EPIs) were calculated to evaluate extreme precipitation in China. We found that the spatial characteristics of the eight EPIs exhibited downward trends from south to north. In the periods 1960–2017 and 2011–2100, trends in the EPIs were positive, but there were differences between different regions. In the past 58 years, the extreme precipitation increased in the northwest, southeast, and the Tibet Plateau of China, while decreased in northern China. Almost all the trends of EPIs are positive in the next two periods (2011–2055 and 2056–2100) except for some EPIs, such as intensity of extreme precipitation, which decrease in southeastern China in the second period (2056–2100). This study suggests that the frequency of extreme precipitation events in China will progressively increase, which implies that a substantial burden will be placed on social economies and terrestrial ecological processes.


2011 ◽  
Vol 139 (2) ◽  
pp. 332-350 ◽  
Author(s):  
Charles Jones ◽  
Jon Gottschalck ◽  
Leila M. V. Carvalho ◽  
Wayne Higgins

Abstract Extreme precipitation events are among the most devastating weather phenomena since they are frequently accompanied by loss of life and property. This study uses reforecasts of the NCEP Climate Forecast System (CFS.v1) to evaluate the skill of nonprobabilistic and probabilistic forecasts of extreme precipitation in the contiguous United States (CONUS) during boreal winter for lead times up to two weeks. The CFS model realistically simulates the spatial patterns of extreme precipitation events over the CONUS, although the magnitudes of the extremes in the model are much larger than in the observations. Heidke skill scores (HSS) for forecasts of extreme precipitation at the 75th and 90th percentiles showed that the CFS model has good skill at week 1 and modest skill at week 2. Forecast skill is usually higher when the Madden–Julian oscillation (MJO) is active and has enhanced convection occurring over the Western Hemisphere, Africa, and/or the western Indian Ocean than in quiescent periods. HSS greater than 0.1 extends to lead times of up to two weeks in these situations. Approximately 10%–30% of the CONUS has HSS greater than 0.1 at lead times of 1–14 days when the MJO is active. Probabilistic forecasts for extreme precipitation events at the 75th percentile show improvements over climatology of 0%–40% at 1-day lead and 0%–5% at 7-day leads. The CFS has better skill in forecasting severe extremes (i.e., events exceeding the 90th percentile) at longer leads than moderate extremes (75th percentile). Improvements over climatology between 10% and 30% at leads of 3 days are observed over several areas across the CONUS—especially in California and in the Midwest.


2021 ◽  
Author(s):  
Renaud Falga ◽  
Chien Wang

<p>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 20<sup>th</sup> 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.</p>


2020 ◽  
Vol 51 (3) ◽  
pp. 484-504 ◽  
Author(s):  
Linchao Li ◽  
Yufeng Zou ◽  
Yi Li ◽  
Haixia Lin ◽  
De Li Liu ◽  
...  

Abstract Extreme precipitation events vary with different sub-regions, sites and years and show complex characteristics. In this study, the temporal variations, trends with significance and change points in the annual time series of 10 extreme precipitation indices (EPIs) at 552 sites and in seven sub-regions were analyzed using the modified Mann–Kendall test and sequential Mann–Kendall analysis. Three representative (extremely wet, normal and extremely dry) years from 1961 to 2017 were selected by the largest, 50%, and smallest empirical frequency values in China. The spatiotemporal changes in the EPIs during the three representative years were analyzed in detail. The results showed that during 1961–2017, both the consecutive wet or dry days decreased significantly, while the number of heavy precipitation days had no significant trend, and the other seven wet EPIs increased insignificantly. The abrupt change years of the 10 EPIs occurred 32 and 40 times from 1963 to 1978 and from 1990 to 2016, respectively, regardless of sub-region. The extremely dry (or wet) events mainly occurred in western (or southwestern) China, implying a higher extreme event risk. The extremely wet, normal and extremely dry events from 1961 to 2017 occurred in 2016, 1997 and 2011 with empirical frequencies of 1.7%, 50% and 98.3%, respectively. In addition, 1998 was the second-most extremely wet year (empirical frequency was 3.7%). The monthly precipitation values were larger from February to August in 1998, forming a much earlier flood peak than that of 2016. The 10 EPIs had close connections with Normalized Difference Vegetation Indexes during the 12 months of 1998 and 2016. This study provides useful references for disaster prevention in China.


2019 ◽  
Vol 11 (1) ◽  
pp. 70 ◽  
Author(s):  
Chaoying Huang ◽  
Junjun Hu ◽  
Sheng Chen ◽  
Asi Zhang ◽  
Zhenqing Liang ◽  
...  

This study assesses the performance of the latest version 05B (V5B) Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (GPM) (IMERG) Early and Final Runs over southern China during six extremely heavy precipitation events brought by six powerful typhoons from 2016 to 2017. Observations from a dense network composed of 2449 rain gauges are used as reference to quantify the performance in terms of spatiotemporal variability, probability distribution of precipitation rates, contingency scores, and bias analysis. The results show that: (1) both IMERG with gauge calibration (IMERG_Cal) and without gauge correction (IMERG_Uncal) generally capture the spatial patterns of storm-accumulated precipitation with moderate to high correlation coefficients (CCs) of 0.57–0.87, and relative bias (RB) varying from −17.21% to 30.58%; (2) IMERG_Uncal and IMERG_Cal capture well the area-average hourly series of precipitation over rainfall centers with high CCs ranging from 0.78 to 0.94; (3) IMERG_Cal tends to underestimate precipitation especially the rainfall over the rainfall centers when compared to IMERG_Uncal. The IMERG Final Run shows promising potentials in typhoon-related extreme precipitation storm applications. This study is expected to give useful feedbacks about the latest V5B Final Run IMERG product to both algorithm developers and the scientific end users, providing a better understanding of how well the V5B IMERG products capture the typhoon extreme precipitation events over southern China.


2016 ◽  
Vol 17 (2) ◽  
pp. 693-711 ◽  
Author(s):  
Hamed Ashouri ◽  
Soroosh Sorooshian ◽  
Kuo-Lin Hsu ◽  
Michael G. Bosilovich ◽  
Jaechoul Lee ◽  
...  

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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