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contributor authorSapiano, M. R. P.
contributor authorStephenson, D. B.
contributor authorGrubb, H. J.
contributor authorArkin, P. A.
date accessioned2017-06-09T17:02:12Z
date available2017-06-09T17:02:12Z
date copyright2006/09/01
date issued2006
identifier issn0894-8755
identifier otherams-78315.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4220971
description abstractA physically motivated statistical model is used to diagnose variability and trends in wintertime (October?March) Global Precipitation Climatology Project (GPCP) pentad (5-day mean) precipitation. Quasigeostrophic theory suggests that extratropical precipitation amounts should depend multiplicatively on the pressure gradient, saturation specific humidity, and the meridional temperature gradient. This physical insight has been used to guide the development of a suitable statistical model for precipitation using a mixture of generalized linear models: a logistic model for the binary occurrence of precipitation and a Gamma distribution model for the wet day precipitation amount. The statistical model allows for the investigation of the role of each factor in determining variations and long-term trends. Saturation specific humidity qs has a generally negative effect on global precipitation occurrence and with the tropical wet pentad precipitation amount, but has a positive relationship with the pentad precipitation amount at mid- and high latitudes. The North Atlantic Oscillation, a proxy for the meridional temperature gradient, is also found to have a statistically significant positive effect on precipitation over much of the Atlantic region. Residual time trends in wet pentad precipitation are extremely sensitive to the choice of the wet pentad threshold because of increasing trends in low-amplitude precipitation pentads; too low a choice of threshold can lead to a spurious decreasing trend in wet pentad precipitation amounts. However, for not too small thresholds, it is found that the meridional temperature gradient is an important factor for explaining part of the long-term trend in Atlantic precipitation.
publisherAmerican Meteorological Society
titleDiagnosis of Variability and Trends in a Global Precipitation Dataset Using a Physically Motivated Statistical Model
typeJournal Paper
journal volume19
journal issue17
journal titleJournal of Climate
identifier doi10.1175/JCLI3849.1
journal fristpage4154
journal lastpage4166
treeJournal of Climate:;2006:;volume( 019 ):;issue: 017
contenttypeFulltext


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