scholarly journals Understanding Model-Based Probable Maximum Precipitation Estimation as a Function of Location and Season from Atmospheric Reanalysis

2018 ◽  
Vol 19 (2) ◽  
pp. 459-475 ◽  
Author(s):  
Xiaodong Chen ◽  
Faisal Hossain
Keyword(s):  
Vertical Velocity ◽  
Extreme Precipitation ◽  
Numerical Models ◽  
Engineering Practice ◽  
Probable Maximum Precipitation ◽  
Maximum Precipitation ◽  
Extreme Precipitation Events ◽  
Atmospheric Instability ◽  
Moisture Availability ◽  
Precipitation Events

Abstract Extreme precipitation events bring huge societal and economic loss around the world every year, and they have undergone spatially heterogeneous changes in the past half-century. They are fundamental to probable maximum precipitation (PMP) estimation in engineering practice, making it important to understand how extreme storm magnitudes are related to key meteorological conditions. However, there is currently a lack of information that can potentially inform the engineering profession on the controlling factors for PMP estimation. In this study, the authors present a statistical analysis of the relationship between extreme 3-day precipitation and atmospheric instability, moisture availability, and large-scale convergence over the continental United States (CONUS). The analysis is conducted using the North America Regional Reanalysis (NARR) and ECMWF ERA-Interim reanalysis data and a high-resolution regional climate simulation. While extreme 3-day precipitation events across the CONUS are mostly related to vertical velocity and moisture availability, those in the southwestern U.S. mountain regions are also controlled by atmospheric instability. Vertical velocity and relative humidity have domainwide impacts, while no significant relationship is found between extreme precipitation and air temperature. Such patterns are stable over different seasons and extreme precipitation events of various durations between 1 and 3 days. These analyses can directly help in configuring the numerical models for PMP estimation at a given location for a given storm.

scholarly journals Overview of Observed Clausius-Clapeyron Scaling of Extreme Precipitation in Midlatitudes

Atmosphere ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 786 ◽  
Author(s):  
Marta Martinkova ◽  
Jan Kysely
Keyword(s):  
Extreme Precipitation ◽  
Observational Studies ◽  
Dew Point ◽  
Point Temperature ◽  
Dew Point Temperature ◽  
Weather Patterns ◽  
Extreme Precipitation Events ◽  
Moisture Availability ◽  
Increasing Temperature ◽  
Precipitation Events

This paper presents an overview of recent observational studies on the Clausius-Clapeyron precipitation-temperature (P-T) scaling in midlatitudes. As the capacity of air to hold moisture increases in connection with increasing temperature, extreme precipitation events may become more abundant and intense. The capacity of air to hold moisture is governed by the Clausius-Clapeyron (CC) relation, approximately 7% per °C. Departures from this, so called super-CC scaling and sub-CC scaling, are consequences of different factors (moisture availability, type of precipitation, annual cycle, the percentile of precipitation intensity and regional weather patterns). Since the moisture availability and enhanced convection were considered as the most important drivers governing the P-T scaling, dew point temperature as a scaling variable is discussed in detail and methods of disaggregation of precipitation events into convective and non-convective are also reviewed.

scholarly journals Study of NWP parameterizations on extreme precipitation events over Basque Country

2016 ◽  
Vol 13 ◽  
pp. 137-144 ◽  
Author(s):  
Iván R. Gelpi ◽  
Santiago Gaztelumendi ◽  
Sheila Carreño ◽  
Roberto Hernández ◽  
Joseba Egaña
Keyword(s):  
Extreme Precipitation ◽  
Numerical Models ◽  
Basque Country ◽  
Wrf Model ◽  
Cumulus Parameterization ◽  
Precipitation Forecast ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract. The Weather Research and Forecasting model (WRF), like other numerical models, can make use of several parameterization schemes. The purpose of this study is to determine how available cumulus parameterization (CP) and microphysics (MP) schemes in the WRF model simulate extreme precipitation events in the Basque Country. Possible combinations among two CP schemes (Kain–Fritsch and Betts–Miller–Janjic) and five MP (WSM3, Lin, WSM6, new Thompson and WDM6) schemes were tested. A set of simulations, corresponding to 21st century extreme precipitation events that have caused significant flood episodes have been compared with point observational data coming from the Basque Country Automatic Weather Station Mesonetwork. Configurations with Kain–Fritsch CP scheme produce better quantity of precipitation forecast (QPF) than BMJ scheme configurations. Depending on the severity level and the river basin analysed different MP schemes show the best behaviours, demonstrating that there is not a unique configuration that solve exactly all the studied events.

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

2021 ◽  
Author(s):  
Paul Flanagan ◽  
Rezaul Mahmood
Keyword(s):  
United States ◽  
River Basin ◽  
Extreme Precipitation ◽  
Missouri River ◽  
Spatiotemporal Analysis ◽  
The United States ◽  
Maximum Precipitation ◽  
Extreme Precipitation Events ◽  
Depth Analysis ◽  
Precipitation Events

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.

scholarly journals Semiarid grasslands and extreme precipitation events: Do experimental results scale to the landscape?

Ecology ◽  
2021 ◽  
Author(s):  
Alison K. Post ◽  
Kristin P. Davis ◽  
Jillian LaRoe ◽  
David L. Hoover ◽  
Alan K. Knapp
Keyword(s):  
Extreme Precipitation ◽  
Experimental Results ◽  
Extreme Precipitation Events ◽  
Precipitation Events

scholarly journals Recognizing the Aggregation Characteristics of Extreme Precipitation Events Using Spatio-Temporal Scanning and the Local Spatial Autocorrelation Model

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 218
Author(s):  
Changjun Wan ◽  
Changxiu Cheng ◽  
Sijing Ye ◽  
Shi Shen ◽  
Ting Zhang
Keyword(s):  
Spatial Autocorrelation ◽  
Extreme Precipitation ◽  
Eastern China ◽  
Temporal Aggregation ◽  
Global Changes ◽  
Percentile Method ◽  
Extreme Precipitation Events ◽  
Spatio Temporal ◽  
Precipitation Events ◽  
Local Spatial Autocorrelation

Precipitation is an essential climate variable in the hydrologic cycle. Its abnormal change would have a serious impact on the social economy, ecological development and life safety. In recent decades, many studies about extreme precipitation have been performed on spatio-temporal variation patterns under global changes; little research has been conducted on the regionality and persistence, which tend to be more destructive. This study defines extreme precipitation events by percentile method, then applies the spatio-temporal scanning model (STSM) and the local spatial autocorrelation model (LSAM) to explore the spatio-temporal aggregation characteristics of extreme precipitation, taking China in July as a case. The study result showed that the STSM with the LSAM can effectively detect the spatio-temporal accumulation areas. The extreme precipitation events of China in July 2016 have a significant spatio-temporal aggregation characteristic. From the spatial perspective, China’s summer extreme precipitation spatio-temporal clusters are mainly distributed in eastern China and northern China, such as Dongting Lake plain, the Circum-Bohai Sea region, Gansu, and Xinjiang. From the temporal perspective, the spatio-temporal clusters of extreme precipitation are mainly distributed in July, and its occurrence was delayed with an increase in latitude, except for in Xinjiang, where extreme precipitation events often take place earlier and persist longer.

Extreme precipitation events and their relationships with circulation types in Italy

2021 ◽  
Author(s):  
Maurizio Iannuccilli ◽  
Giorgio Bartolini ◽  
Giulio Betti ◽  
Alfonso Crisci ◽  
Daniele Grifoni ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Circulation Types ◽  
Extreme Precipitation Events ◽  
Precipitation Events
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