scholarly journals Spatiotemporal Analysis of Extreme Precipitation in the Missouri River Basin from 1950 – 2019

Author(s):  
Paul Flanagan ◽  
Rezaul Mahmood

AbstractExtreme precipitation events are challenging to local and regional stakeholders across the United States. The Missouri River Basin (MoRB), covering an area over 1.29 million km2, is prone to extreme precipitation events. These events are exacerbated by the complex terrain in the west and the numerous weather and climate features which impact the region on a seasonal/annual basis (low-level jets, mesoscale convective systems, extreme cold air intrusions, etc.). Without an in-depth analysis of extreme precipitation in the MoRB, the evolving nature of extreme precipitation is not known. This warrants an analysis of extreme precipitation, especially relating to sub-annual variations when extreme precipitation is more impactful. To this end, data from 131 United States Historical Climatology Network (USHCN) stations were used to determine the nature of extreme precipitation from 1950 – 2019. Annual 99th percentile and annual station maximum precipitation events occur more frequently in the eastern MoRB than in the western MoRB, in line with the annual precipitation climatology. Results show that 99th percentile events and annual station maximum precipitation events are becoming more frequent across the MoRB. Through analysis of 3-month extreme precipitation trends, areas in the eastern and southern MoRB are shown to have an increasing event frequency and intensity. Frequency shifts in the 99th percentile events, however, have occurred across the entire region. The increasing frequency of extreme events in the western MoRB represent a significant change for the hydroclimate of the region. Overall, the results from this work show that MORB extreme precipitation has increased in frequency and intensity during the 1950 – 2019 period.

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.


2015 ◽  
Vol 16 (5) ◽  
pp. 2065-2085 ◽  
Author(s):  
Allan Frei ◽  
Kenneth E. Kunkel ◽  
Adao Matonse

Abstract Recent analyses of extreme hydrological events across the United States, including those summarized in the recent U.S. Third National Climate Assessment (May 2014), show that extremely large (extreme) precipitation and streamflow events are increasing over much of the country, with particularly steep trends over the northeastern United States. The authors demonstrate that the increase in extreme hydrological events over the northeastern United States is primarily a warm season phenomenon and is caused more by an increase in frequency than magnitude. The frequency of extreme warm season events peaked during the 2000s; a secondary peak occurred during the 1970s; and the calmest decade was the 1960s. Cold season trends during the last 30–50 yr are weaker. Since extreme precipitation events in this region tend to be larger during the warm season than during the cold season, trend analyses based on annual precipitation values are influenced more by warm season than by cold season trends. In contrast, the magnitude of extreme streamflow events at stations used for climatological analyses tends to be larger during the cold season: therefore, extreme event analyses based on annual streamflow values are overwhelmingly influenced by cold season, and therefore weaker, trends. These results help to explain an apparent discrepancy in the literature, whereby increasing trends in extreme precipitation events appear to be significant and ubiquitous across the region, while trends in streamflow appear less dramatic and less spatially coherent.


2003 ◽  
Vol 30 (17) ◽  
pp. n/a-n/a ◽  
Author(s):  
Kenneth E. Kunkel ◽  
David R. Easterling ◽  
Kelly Redmond ◽  
Kenneth Hubbard

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.


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.


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