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

Understanding Model-based Probable Maximum Precipitation Estimation as a Function of Location and... AbstractExtreme 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, we present a statistical analysis of the relationship between extreme 3-day precipitation and atmospheric instability, moisture availability and large-scale convergence over the Contiguous US (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 US mountain regions are also controlled by atmospheric instability. Vertical velocity and relative humidity have domain-wide 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. Our analyses can directly help in configuring the numerical models for PMP estimation at a given location for a given storm. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Hydrometeorology American Meteorological Society

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

Loading next page...
 
/lp/ams/understanding-model-based-probable-maximum-precipitation-estimation-as-0DYnRasZ92
Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1525-7541
D.O.I.
10.1175/JHM-D-17-0170.1
Publisher site
See Article on Publisher Site

Abstract

AbstractExtreme 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, we present a statistical analysis of the relationship between extreme 3-day precipitation and atmospheric instability, moisture availability and large-scale convergence over the Contiguous US (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 US mountain regions are also controlled by atmospheric instability. Vertical velocity and relative humidity have domain-wide 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. Our analyses can directly help in configuring the numerical models for PMP estimation at a given location for a given storm.

Journal

Journal of HydrometeorologyAmerican Meteorological Society

Published: Feb 1, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off