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On the skill of numerical weather prediction models to forecast atmospheric rivers over the central United States
Author(s) -
Nayak Munir A.,
Villarini Gabriele,
Lavers David A.
Publication year - 2014
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1002/2014gl060299
Subject(s) - extratropical cyclone , meteorology , environmental science , global forecast system , climatology , forecast skill , flooding (psychology) , preparedness , lead time , numerical weather prediction , lead (geology) , atmospheric sciences , geography , geology , engineering , psychology , operations management , geomorphology , political science , law , psychotherapist
Flooding over the central United States is responsible for large socioeconomic losses. Atmospheric rivers (ARs), narrow regions of intense moisture transport within the warm conveyor belt of extratropical cyclones, can give rise to high rainfall amounts leading to flooding. Short‐term forecasting of AR activity can provide basic information toward improving preparedness for these events. This study focuses on the verification of the skill of five numerical weather prediction models in forecasting AR activity over the central United States. We find that these models generally forecast AR occurrences well at short lead times, with location errors increasing from one to three decimal degrees as the lead time increases to about 1 week. The skill (both in terms of occurrence and location errors) decreases with increasing lead time. Overall, these models are not skillful in forecasting AR activity over the central United States beyond a lead time of about 7 days.