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The precipitation climate of Central Asia—intercomparison of observational and numerical data sources in a remote semiarid region
Author(s) -
Schiemann Reinhard,
Lüthi Daniel,
Vidale Pier Luigi,
Schär Christoph
Publication year - 2008
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.1532
Subject(s) - climatology , precipitation , environmental science , coupled model intercomparison project , climate model , spatial distribution , homogeneity (statistics) , water cycle , climate change , atmospheric sciences , meteorology , geology , geography , remote sensing , statistics , oceanography , ecology , mathematics , biology
Abstract In this study, we systematically compare a wide range of observational and numerical precipitation datasets for Central Asia. Data considered include two re‐analyses, three datasets based on direct observations, and the output of a regional climate model simulation driven by a global re‐analysis. These are validated and intercompared with respect to their ability to represent the Central Asian precipitation climate. In each of the datasets, we consider the mean spatial distribution and the seasonal cycle of precipitation, the amplitude of interannual variability, the representation of individual yearly anomalies, the precipitation sensitivity (i.e. the response to wet and dry conditions), and the temporal homogeneity of precipitation. Additionally, we carried out part of these analyses for datasets available in real time. The mutual agreement between the observations is used as an indication of how far these data can be used for validating precipitation data from other sources. In particular, we show that the observations usually agree qualitatively on anomalies in individual years while it is not always possible to use them for the quantitative validation of the amplitude of interannual variability. The regional climate model is capable of improving the spatial distribution of precipitation. At the same time, it strongly underestimates summer precipitation and its variability, while interannual variations are well represented during the other seasons, in particular in the Central Asian mountains during winter and spring. Copyright © 2007 Royal Meteorological Society