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North American extreme precipitation events and related large-scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends

Mathew Barlow; William J. Gutowski; John R. Gyakum; Richard W. Katz; Young-Kwon Lim; Russ S. Schumacher; Michael F. Wehner; Laurie Agel; Michael Bosilovich; Allison Collow; Alexander Gershunov; Richard Grotjahn; Ruby Leung; Shawn Milrad; Seung-Ki Min
Climate Dynamics · Vol. 53, Issue 11 · pp. 6835-6875 · 2019

Abstract

This paper surveys the current state of knowledge regarding large-scale meteorological patterns (LSMPs) associated with short-duration (less than 1 week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of “extreme” are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some promising analysis techniques have been identified and the LSMP perspective is useful for evaluating the model dynamics associated with extremes.

Bibliographic Information

JournalClimate Dynamics
PublisherSpringer
Publication Date2019-12-01
Publication Year2019
Volume53
Issue11
Pages6835-6875
Document TypeJournal Article
Print ISSN0930-7575
eISSN1432-0894
DOI10.1007/s00382-019-04958-z

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NARA Access Coverage1986-01-01~Current
Journal Homepagehttps://www.springer.com/journal/382
Publisher PageOpen Publisher Page
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