Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model
A 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. Quasi-geostrophic theory suggests that extratropical precipitation amounts should depend multiplicat...
Main Authors: | , , , |
---|---|
Format: | Article in Journal/Newspaper |
Language: | unknown |
Published: |
American Meteorological Society
2006
|
Subjects: | |
Online Access: | https://centaur.reading.ac.uk/5144/ |
id |
ftunivreading:oai:centaur.reading.ac.uk:5144 |
---|---|
record_format |
openpolar |
spelling |
ftunivreading:oai:centaur.reading.ac.uk:5144 2024-06-23T07:55:13+00:00 Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model Sapiano, M. R. P. Stephenson, D. B. Grubb, H. J. Arkin, P. A. 2006 https://centaur.reading.ac.uk/5144/ unknown American Meteorological Society Sapiano, M. R. P., Stephenson, D. B., Grubb, H. J. and Arkin, P. A. (2006) Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model. Journal Of Climate, 19 (17). pp. 4154-4166. ISSN 1520-0442 551 Geology hydrology meteorology Article NonPeerReviewed 2006 ftunivreading 2024-06-11T14:41:45Z A 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. Quasi-geostrophic 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 q(s) 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. Article in Journal/Newspaper North Atlantic North Atlantic oscillation CentAUR: Central Archive at the University of Reading |
institution |
Open Polar |
collection |
CentAUR: Central Archive at the University of Reading |
op_collection_id |
ftunivreading |
language |
unknown |
topic |
551 Geology hydrology meteorology |
spellingShingle |
551 Geology hydrology meteorology Sapiano, M. R. P. Stephenson, D. B. Grubb, H. J. Arkin, P. A. Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model |
topic_facet |
551 Geology hydrology meteorology |
description |
A 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. Quasi-geostrophic 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 q(s) 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. |
format |
Article in Journal/Newspaper |
author |
Sapiano, M. R. P. Stephenson, D. B. Grubb, H. J. Arkin, P. A. |
author_facet |
Sapiano, M. R. P. Stephenson, D. B. Grubb, H. J. Arkin, P. A. |
author_sort |
Sapiano, M. R. P. |
title |
Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model |
title_short |
Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model |
title_full |
Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model |
title_fullStr |
Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model |
title_full_unstemmed |
Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model |
title_sort |
diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model |
publisher |
American Meteorological Society |
publishDate |
2006 |
url |
https://centaur.reading.ac.uk/5144/ |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_relation |
Sapiano, M. R. P., Stephenson, D. B., Grubb, H. J. and Arkin, P. A. (2006) Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model. Journal Of Climate, 19 (17). pp. 4154-4166. ISSN 1520-0442 |
_version_ |
1802647714056372224 |