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Evaluation of the added value of a high‐resolution regional climate model simulation of the South Asian summer monsoon climatology
Author(s) -
Karmacharya J.,
Jones R.,
MoufoumaOkia W.,
New M.
Publication year - 2017
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.4944
Subject(s) - orography , climatology , precipitation , environmental science , monsoon , downscaling , climate model , percentile , spatial ecology , climate change , atmospheric sciences , meteorology , geography , geology , mathematics , oceanography , ecology , statistics , biology
The South Asian summer monsoon ( SASM ) is a continental scale weather phenomenon, which fluctuates at a range of temporal and spatial scales. Although majority of global climate models are broadly able to simulate the large scale characteristics of the SASM , they generally have major deficiencies such as constraints in reproducing observed mean precipitation. It is generally anticipated that higher resolution regional climate models ( RCMs ) would be able to simulate an improved mean state owing to their capacity to better simulate fine temporal and spatial scale features and variability. Here, we analyse SASM simulations using a contemporary Hadley Centre RCM , forced by ERA ‐Interim reanalysis and observed sea surface temperature, at medium (0.44°) and high (0.11°) horizontal resolutions. Evaluation of the results show that, compared to the medium resolution RCM , the high resolution RCM is able to better resolve the interaction of the low level monsoon flow with the Himalayan orography leading to added value in simulating many aspects of SASM precipitation such as the seasonal mean, relative frequency distribution of daily precipitation, and various metrics of precipitation extremes. In contrast to many previous studies, maximum added value is note along the Indo‐Gangetic plain rather than over the complex Himalayas, and the added values of up to 5 mm day −1 and 50 days are noted for mean precipitation and number of wet days, respectively over the region. Similarly, added values of up to 15 and 3 mm day −1 are noted for 95th percentile of daily precipitation and simple daily intensity index, respectively over central India and the Himalayan range. These results suggest that higher resolution RCMs have the potential to add more value when downscaling global climate model climate change projections.