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Climate Variability and the Shape of Daily Precipitation: A Case Study of ENSO and the American West
Author(s) -
Nicole Feldl,
Gerard H. Roe
Publication year - 2011
Publication title -
journal of climate
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.315
H-Index - 287
eISSN - 1520-0442
pISSN - 0894-8755
DOI - 10.1175/2010jcli3555.1
Subject(s) - precipitation , climatology , environmental science , climate change , el niño southern oscillation , atmospheric sciences , geology , geography , meteorology , oceanography
Characterizing the relationship between large-scale atmospheric circulation patterns and the shape of the daily precipitation distribution is fundamental to understanding how dynamical changes are manifest in the hydrological cycle, and it is also relevant to issues such as natural hazard mitigation and reservoir management. This relationship is pursued using ENSO variability and the American West as a case study. When considering the full range of wintertime precipitation and consistent with conventional wisdom, mean precipitation intensity is enhanced during El Niño relative to La Niña in the Southwest and vice versa in the Northwest. This change in mean is attributed to a shift in the distribution of daily precipitation toward more intense daily rainfall rates. In addition, fundamental changes in the shape of the precipitation distributions are observed, independent of shifts in the mean. Surprisingly, for intense precipitation, La Niña winters actually demonstrate a significant increase in intensity (but not frequency) across the Southwest. A main lesson from this analysis is that, in response to ENSO variability, changes in extreme events can be significantly different from changes in the mean. In some instances, even the sign of the change is reversed. This result suggests that patterns of large-scale variability have an effect on the precipitation distribution that is nuanced, and they cannot be regarded as simply causing a shift in climatic zones. It also raises interesting questions concerning how best to establish confidence in climate predictions.

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