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Multisite stochastic weather models for impact studies
Author(s) -
Qian Budong,
CorteReal João,
Xu Hong
Publication year - 2002
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.808
Subject(s) - downscaling , climatology , environmental science , precipitation , model output statistics , meteorology , consistency (knowledge bases) , general circulation model , climate model , climate change , stochastic modelling , atmospheric circulation , numerical weather prediction , geography , computer science , statistics , mathematics , geology , oceanography , artificial intelligence
Stochastic weather models have been developed for simultaneous simulations of daily precipitation, and daily maximum and minimum temperatures at multiple sites in a river basin in order to reproduce the interstation correlations and self‐consistency in weather series. The basic structure of the stochastic weather models was adopted from Wilks (1999. Agricultural and Forest Meteorology 96 : 85–101), but an extension was made to condition the model parameters on daily circulation patterns. Model parameters were also estimated without conditioning on daily circulation patterns, so that both conditional and unconditional simulations were conducted and compared. Statistical analyses on the synthetic weather data imply a better performance of the conditional simulations, on most aspects of the required statistics. In addition, the conditional weather models on daily circulation patterns can be applied directly in impact studies, for the purpose of downscaling climate scenarios from climate model simulations, and some related aspects are also discussed. Copyright © 2002 Royal Meteorological Society.