The Gauging and Modeling of Rivers in the Sky

Lavers, David A.; Rodwell, Mark J.; Richardson, David S.; Ralph, F. Martin; Doyle, James D.; Reynolds, Carolyn A.; Tallapragada, Vijay; Pappenberger, Florian

doi:10.1029/2018gl079019

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The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners. As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.

i

The Gauging and Modeling of Rivers in the Sky

2018
By Lavers, David A. ; Rodwell, Mark J. ; Richardson, David S. ; ...
Source: Geophysical Research Letters, 45(15), 7828-7834

[PDF-3.62 MB]

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Details:

Journal Title:

Geophysical Research Letters
Personal Author:

Lavers, David A. ; Rodwell, Mark J. ; Richardson, David S. ; Ralph, F. Martin ; Doyle, James D. ; ... More +

Lavers, David A. ; Rodwell, Mark J. ; Richardson, David S. ; Ralph, F. Martin ; Doyle, James D. ; Reynolds, Carolyn A. ; Tallapragada, Vijay ; Pappenberger, Florian Less -
NOAA Program & Office:

NWS (National Weather Service) ; EMC (Environmental Modelling Center) ; NCEP (National Centers for Environmental Prediction)

NWS (National Weather Service) ; EMC (Environmental Modelling Center) ; NCEP (National Centers for Environmental Prediction) Less -
Description:

Atmospheric rivers (ARs) are responsible for most of the horizontal water vapor ﬂux outside of the tropics and can cause extreme precipitation and affect the atmospheric dynamics and predictability. For their impacts to be skillfully predicted, it is essential for weather forecasting systems to accurately represent AR characteristics. Using the European Centre for Medium-Range Weather Forecasts IntegratedForecasting System and dropsonde observations from the 2018 AR Reconnaissance ﬁeld campaign over the Northeast Paci ﬁc Ocean, it is shown that the AR structure is modeled well but that short-range water vapor ﬂux forecasts have a root-mean-square error of 60.0 kgm /C01s/C01(21.9% of mean observed ﬂux). These
Keywords:

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General Earth And Planetary Sciences Geophysics
Source:

Geophysical Research Letters, 45(15), 7828-7834
DOI:

https://doi.org/10.1029/2018gl079019
ISSN:

0094-8276;1944-8007;
Format:

PDF
Publisher:

American Geophysical Union (AGU)
Document Type:

Journal Article
License:

https://creativecommons.org/licenses/by-nc-nd/4.0/
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CC BY-NC-ND
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Main Document Checksum:

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urn:sha256:e019859c92ec9a61dda6ffc50a5b463b6b9455f530bd30f49f7fbe0fd3985a39
Download URL:

https://repository.library.noaa.gov/view/noaa/53778/noaa_53778_DS1.pdf
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