scholarly journals Synoptic Characteristics of 14-Day Extreme Precipitation Events across the United States

2020 ◽  
Vol 33 (15) ◽  
pp. 6423-6440 ◽  
Author(s):  
Gregory C. Jennrich ◽  
Jason C. Furtado ◽  
Jeffrey B. Basara ◽  
Elinor R. Martin
Keyword(s):  
United States ◽  
North Pacific ◽  
Extreme Precipitation ◽  
Extreme Precipitation Event ◽  
Precipitation Event ◽  
Synoptic Patterns ◽  
The North ◽  
Extreme Precipitation Events ◽  
The North Pacific ◽  
Precipitation Events

AbstractAlthough significant improvements have been made to the prediction and understanding of extreme precipitation events in recent decades, there is still much to learn about these impactful events on the subseasonal time scale. This study focuses on identifying synoptic patterns and precursors ahead of an extreme precipitation event over the contiguous United States (CONUS). First, we provide a robust definition for 14-day “extreme precipitation events” and partition the CONUS into six different geographic regions to compare and contrast the synoptic patterns associated with events in those regions. Then, several atmospheric variables from ERA-Interim (e.g., geopotential height and zonal winds) are composited to understand the evolution of the atmospheric state before and during a 14-day extreme precipitation event. Common synoptic signals seen during events include significant zonally oriented trough–ridge patterns, an energized subtropical jet stream, and enhanced moisture transport into the affected area. Also, atmospheric-river activity increases in the specific region during these events. Modes of climate variability and lagged composites are then investigated for their potential use in lead-time prediction. Key findings include synoptic-scale anomalies in the North Pacific Ocean and regional connections to modes such as the Pacific–North American pattern and the North Pacific Oscillation. Taken together, our results represent a significant step forward in understanding the evolution of 14-day extreme precipitation events for potential damage and casualty mitigation.

scholarly journals On the links between sub-seasonal clustering of extreme precipitation and high discharge in Switzerland and Europe

2021 ◽  
Author(s):  
Alexandre Tuel ◽  
Bettina Schaefli ◽  
Jakob Zscheischler ◽  
Olivia Martius
Keyword(s):  
Extreme Precipitation ◽  
Temporal Structure ◽  
Extreme Precipitation Event ◽  
Precipitation Event ◽  
Discharge Data ◽  
High Discharge ◽  
Temporal Clustering ◽  
Extreme Precipitation Events ◽  
The Impact ◽  
Precipitation Events

Abstract. River discharge is impacted by the sub-seasonal (weekly to monthly) temporal structure of precipitation. One example is the successive occurrence of extreme precipitation events over sub-seasonal timescales, referred to as temporal clustering. Its potential effects on discharge have received little attention. Here, we address this question by analysing discharge observations following extreme precipitation events either clustered in time or occurring in isolation. We rely on two sets of precipitation and discharge data, one centered on Switzerland and the other over Europe. We identify "clustered" extreme precipitation events based on the previous occurrence of another extreme precipitation within a given time window. We find that clustered events are generally followed by a more prolonged discharge response with a larger amplitude. The probability of exceeding the 95th discharge percentile in the five days following an extreme precipitation event is in particular up to twice as high for situations where another extreme precipitation event occurred in the preceding week compared to isolated extreme precipitation events. The influence of temporal clustering decreases as the clustering window increases; beyond 6–8 weeks the difference with non-clustered events is negligible. Catchment area, streamflow regime and precipitation magnitude also modulate the response. The impact of clustering is generally smaller in snow-dominated and large catchments. Additionally, particularly persistent periods of high discharge tend to occur in conjunction with temporal clusters of precipitation extremes.

Subseasonal to Seasonal Extreme Precipitation Events in the Contiguous United States: Generation of a Database and Climatology

2021 ◽  
pp. 1-47
Author(s):  
Ty A. Dickinson ◽  
Michael B. Richman ◽  
Jason C. Furtado
Keyword(s):  
United States ◽  
New England ◽  
Extreme Precipitation ◽  
Extreme Event ◽  
Significant Risk ◽  
Optimal Number ◽  
Precipitation Event ◽  
Hybrid Index ◽  
Extreme Precipitation Events ◽  
Precipitation Events

AbstractExtreme precipitation across multiple timescales is a natural hazard that creates a significant risk to life, with a commensurately large cost through property loss. We devise a method to create 14-day extreme event windows that characterize precipitation events in the contiguous United States (CONUS) for the years 1915 through 2018. Our algorithm imposes thresholds for both total precipitation and the duration of the precipitation to identify events with sufficient length to accentuate the synoptic and longer time scale contribution to the precipitation event. Kernel density estimation is employed to create extreme event polygons which are formed into a database spanning from 1915 through 2018. Using the developed database, we clustered events into regions using a k-means algorithm. We define the “Hybrid Index”, a weighted composite of silhouette score and number of clustered events, to show the optimal number of clusters is 14. We also show that 14-day extreme precipitation events are increasing in the CONUS, specifically in the Dakotas and much of New England. The algorithm presented in this work is designed to be sufficiently flexible to be extended to any desired number of days on the subseasonal-to-seasonal (S2S) timescale (e.g., 30 days). Additional databases generated using this framework are available for download from our GitHub. Consequently, these S2S databases can be analyzed in future works to determine the climatology of S2S extreme precipitation events and be used for predictability studies for identified events.

scholarly journals Large-Scale Influences on Atmospheric River–Induced Extreme Precipitation Events along the Coast of Washington State

2020 ◽  
Vol 21 (9) ◽  
pp. 2139-2156
Author(s):  
Allison B. Marquardt Collow ◽  
Haiden Mersiovsky ◽  
Michael G. Bosilovich
Keyword(s):  
Water Vapor ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Washington State ◽  
Vapor Transport ◽  
Extreme Precipitation Event ◽  
Water Vapor Transport ◽  
Precipitation Event ◽  
Extreme Precipitation Events ◽  
Precipitation Events

AbstractTransient, narrow plumes of strong water vapor transport, referred to as atmospheric rivers (ARs), are responsible for much of the precipitation along the West Coast of the United States. The most intense precipitation events are almost always induced by an AR on the coast of Oregon and Washington and can result in detrimental impacts on society due to mudslides and flooding. To accurately predict AR events on numerical weather prediction, subseasonal, and seasonal time scales, it is important to understand the large-scale impacts on extreme AR events. Here, characteristics of ARs that result in an extreme precipitation event are compared to typical ARs on the coast of Washington State. In addition to more intense water vapor transport, notable differences in the synoptic forcing are present during extreme precipitation events that are not present during typical AR events. Subseasonal and seasonal teleconnection patterns are known to influence the weather in the Pacific Northwest and are investigated here. The Madden–Julian oscillation (MJO) plays a role in determining the strength of precipitation associated with an AR on the Washington coast. Phase 5 of the MJO (convection centered over the Maritime Continent) is the most common phase during an extreme precipitation event, while phase 2 (convection over the Indian Ocean) discourages an extreme event from occurring. Interactions between El Niño–Southern Oscillation (ENSO) and the propagation speed of the MJO result in extreme events during phase 1 of the MJO and El Niño but phase 8 during neutral ESNO conditions.

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
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Heavy Precipitation ◽  
The Past ◽  
Extreme Precipitation Events ◽  
Intense Precipitation ◽  
Central United States ◽  
Extreme Rain ◽  
Rain Events ◽  
Precipitation Events

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.

scholarly journals ENSO and Wintertime Extreme Precipitation Events over the Contiguous United States

2008 ◽  
Vol 21 (1) ◽  
pp. 22-39 ◽  
Author(s):  
Siegfried D. Schubert ◽  
Yehui Chang ◽  
Max J. Suarez ◽  
Philip J. Pegion
Keyword(s):  
United States ◽  
West Coast ◽  
Extreme Precipitation ◽  
East Coast ◽  
Daily Precipitation ◽  
Precipitation Variability ◽  
The West ◽  
Extreme Precipitation Events ◽  
The Impact ◽  
Precipitation Events

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.

Listening to Stakeholders: Initiating Research on Sub-seasonal to Seasonal Heavy Precipitation Events in the Contiguous U.S. by First Understanding What Stakeholders Need

2021 ◽  
pp. 1-35
Author(s):  
Olivia VanBuskirk ◽  
Paulina Ćwik ◽  
Renee A. McPherson ◽  
Heather Lazrus ◽  
Elinor Martin ◽  
...  
Keyword(s):  
United States ◽  
Environmental Management ◽  
Predictive Models ◽  
Extreme Precipitation ◽  
Heavy Precipitation ◽  
Role Playing ◽  
Extreme Precipitation Events ◽  
Rainfall Extremes ◽  
Actionable Science ◽  
Precipitation Events

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.

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
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Western Hemisphere ◽  
Boreal Winter ◽  
Lead Times ◽  
Madden Julian Oscillation ◽  
Extreme Precipitation Events ◽  
Skill Scores ◽  
Probabilistic Forecasts ◽  
Precipitation Events

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.

Skillful Subseasonal Prediction of United States Extreme Warm Days and Standardized Precipitation Index in Boreal Summer

2021 ◽  
pp. 1-34
Author(s):  
Douglas E. Miller ◽  
Zhuo Wang ◽  
Bo Li ◽  
Daniel S. Harnos ◽  
Trent Ford
Keyword(s):  
United States ◽  
Heat Flux ◽  
Soil Moisture ◽  
Statistical Model ◽  
North Pacific ◽  
Standardized Precipitation Index ◽  
Boreal Summer ◽  
The North ◽  
Moisture Conditions ◽  
The North Pacific

AbstractSkillful subseasonal prediction of extreme heat and precipitation greatly benefits multiple sectors, including water management, public health, and agriculture, in mitigating the impact of extreme events. A statistical model is developed to predict the weekly frequency of extreme warm days and 14-day standardized precipitation index (SPI) during boreal summer in the United States (US). We use a leading principal component of US soil moisture and an index based on the North Pacific sea surface temperature (SST) as predictors. The model outperforms the NCEP’s Climate Forecast System version 2 (CFSv2) at weeks 3-4 in the eastern US. It is found that the North Pacific SST anomalies persist several weeks and are associated with a persistent wave train pattern (WTZ500), which leads to increased occurrences of blocking and extreme temperature over the eastern US. Extreme dry soil moisture conditions persist into week 4 and are associated with an increase in sensible heat flux and decrease in latent heat flux, which may help maintain the overlying anticyclone. The clear sky conditions associated with blocking anticyclones further decrease soil moisture conditions and increase the frequency of extreme warm days. This skillful statistical model has the potential to aid in irrigation scheduling, crop planning, reservoir operation, and provide mitigation of impacts from extreme heat events.

scholarly journals Large-Scale Flow Patterns Associated with Extreme Precipitation and Atmospheric Rivers over Norway

2019 ◽  
Vol 147 (4) ◽  
pp. 1415-1428 ◽  
Author(s):  
Imme Benedict ◽  
Karianne Ødemark ◽  
Thomas Nipen ◽  
Richard Moore
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Moisture Flux ◽  
Cold Season ◽  
Fuzzy Cluster ◽  
The South ◽  
Atmospheric Rivers ◽  
The North ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract A climatology of extreme cold season precipitation events in Norway from 1979 to 2014 is presented, based on the 99th percentile of the 24-h accumulated precipitation. Three regions, termed north, west, and south are identified, each exhibiting a unique seasonal distribution. There is a proclivity for events to occur during the positive phase of the NAO. The result is statistically significant at the 95th percentile for the north and west regions. An overarching hypothesis of this work is that anomalous moisture flux, or so-called atmospheric rivers (ARs), are integral to extreme precipitation events during the Norwegian cold season. An objective analysis of the integrated vapor transport illustrates that more than 85% of the events are associated with ARs. An empirical orthogonal function and fuzzy cluster technique is used to identify the large-scale weather patterns conducive to the moisture flux and extreme precipitation. Five days before the event and for each of the three regions, two patterns are found. The first represents an intense, southward-shifted jet with a southwest–northeast orientation. The second identifies a weak, northward-shifted, zonal jet. As the event approaches, regional differences become more apparent. The distinctive flow pattern conducive to orographically enhanced precipitation emerges in the two clusters for each region. For the north and west regions, this entails primarily zonal flow impinging upon the south–north-orientated topography, the difference being the latitude of the strong flow. In contrast, the south region exhibits a significant southerly component to the flow.

scholarly journals Evaluation of NASA’s MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

2016 ◽  
Vol 17 (2) ◽  
pp. 693-711 ◽  
Author(s):  
Hamed Ashouri ◽  
Soroosh Sorooshian ◽  
Kuo-Lin Hsu ◽  
Michael G. Bosilovich ◽  
Jaechoul Lee ◽  
...  
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Gulf Coast ◽  
The United States ◽  
Value Theory ◽  
Extreme Value ◽  
Precipitation Extremes ◽  
Precipitation Product ◽  
Extreme Precipitation Events ◽  
Precipitation Events

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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