Influence of the Madden–Julian Oscillation on Forecasts of Extreme Precipitation in the Contiguous United States

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.

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.


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.


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.


2017 ◽  
Vol 30 (4) ◽  
pp. 1307-1326 ◽  
Author(s):  
Siyu Zhao ◽  
Yi Deng ◽  
Robert X. Black

Abstract Regional patterns of extreme precipitation events occurring over the continental United States are identified via hierarchical cluster analysis of observed daily precipitation for the period 1950–2005. Six canonical extreme precipitation patterns (EPPs) are isolated for the boreal warm season and five for the cool season. The large-scale meteorological pattern (LMP) inducing each EPP is identified and used to create a “base function” for evaluating a climate model’s potential for accurately representing the different patterns of precipitation extremes. A parallel analysis of the Community Climate System Model, version 4 (CCSM4), reveals that the CCSM4 successfully captures the main U.S. EPPs for both the warm and cool seasons, albeit with varying degrees of accuracy. The model’s skill in simulating each EPP tends to be positively correlated with its capability in representing the associated LMP. Model bias in the occurrence frequency of a governing LMP is directly related to the frequency bias in the corresponding EPP. In addition, however, discrepancies are found between the CCSM4’s representation of LMPs and EPPs over regions such as the western United States and Midwest, where topographic precipitation influences and organized convection are prominent, respectively. In these cases, the model representation of finer-scale physical processes appears to be at least equally important compared to the LMPs in driving the occurrence of extreme precipitation.


2016 ◽  
Vol 17 (12) ◽  
pp. 3045-3061 ◽  
Author(s):  
Allison B. Marquardt Collow ◽  
Michael G. Bosilovich ◽  
Randal D. Koster

Abstract Observations indicate that over the last few decades there has been a statistically significant increase in precipitation in the northeastern United States and that this can be attributed to an increase in precipitation associated with extreme precipitation events. Here a state-of-the-art atmospheric reanalysis is used to examine such events in detail. Daily extreme precipitation events defined at the 75th and 95th percentile from gridded gauge observations are identified for a selected region within the Northeast. Atmospheric variables from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), are then composited during these events to illustrate the time evolution of associated synoptic structures, with a focus on vertically integrated water vapor fluxes, sea level pressure, and 500-hPa heights. Anomalies of these fields move into the region from the northwest, with stronger anomalies present in the 95th percentile case. Although previous studies show tropical cyclones are responsible for the most intense extreme precipitation events, only 10% of the events in this study are caused by tropical cyclones. On the other hand, extreme events resulting from cutoff low pressure systems have increased. The time period of the study was divided in half to determine how the mean composite has changed over time. An arc of lower sea level pressure along the East Coast and a change in the vertical profile of equivalent potential temperature suggest a possible increase in the frequency or intensity of synoptic-scale baroclinic disturbances.


2015 ◽  
Vol 143 (3) ◽  
pp. 718-741 ◽  
Author(s):  
Benjamin J. Moore ◽  
Kelly M. Mahoney ◽  
Ellen M. Sukovich ◽  
Robert Cifelli ◽  
Thomas M. Hamill

Abstract This paper documents the characteristics of extreme precipitation events (EPEs) in the southeastern United States (SEUS) during 2002–11. The EPEs are identified by applying an object-based method to 24-h precipitation analyses from the NCEP stage-IV dataset. It is found that EPEs affected the SEUS in all months and occurred most frequently in the western portion of the SEUS during the cool season and in the eastern portion during the warm season. The EPEs associated with tropical cyclones, although less common, tended to be larger in size, more intense, and longer lived than “nontropical” EPEs. Nontropical EPEs in the warm season, relative to those in the cool season, tended to be smaller in size and typically involved more moist, conditionally unstable conditions but weaker dynamical influences. Synoptic-scale composites are constructed for nontropical EPEs stratified by the magnitude of vertically integrated water vapor transport (IVT) to examine distinct scenarios for the occurrence of EPEs. The composite results indicate that “strong IVT” EPEs occur within high-amplitude flow patterns involving strong transport of moist, conditionally unstable air within the warm sector of a cyclone, whereas “weak IVT” EPEs occur within low-amplitude flow patterns featuring weak transport but very moist and conditionally unstable conditions. Finally, verification of deterministic precipitation forecasts from a reforecast dataset based on the NCEP Global Ensemble Forecast System reveals that weak-IVT EPEs were characteristically associated with lower forecast skill than strong-IVT EPEs. Based on these results, it is suggested that further research should be conducted to investigate the forecast challenges associated with EPEs in the SEUS.


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