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Relative role of sea surface temperature and snow on Indian summer monsoon seasonal simulation using a GCM
Authors:Srinivasarao Karri  S K Dash  S K Panda  Manish Paliwal  Saroj K Mishra  Jai-Ho Oh
Institution:1.Centre for Atmospheric Sciences,Indian Institute of Technology Delhi,New Delhi,India;2.National Remote Sensing Centre,Indian Space Research Organisation (ISRO),Hyderabad,India;3.Depatment of Atmospheric Science,Central University of Rajasthan,Ajmer,India;4.Department of Environmental Atmospheric Sciences,Pukyong National University,Busan,South Korea
Abstract:Indian summer monsoon is a global scale phenomenon controlled by different land, ocean, and atmospheric parameters. Sea surface temperature (SST) and snow are two of the major parameters, which may alter the spatial and temporal patterns of circulation and rainfall during Indian summer monsoon. In the current paper, we study the monsoon variability using long integrations (20 years) of the Indian Institute of Technology Delhi (IITD) Spectral model at T80L18 resolution with observed and climatological SST and snow. Study shows response of IITD GCM in simulating the Indian summer monsoon rainfall and circulation relative to the snow and SST as boundary conditions. The model’s response to SST and snow is examined by conducting four types of experiments by varying observed and climatological values of snow and SST. This paper discusses the seasonal total rainfall for country as a whole and 850 and 200 hPa wind for the period of 20 years starting from 1985 to 2004. The model has been integrated in the ensemble mode with five different initial conditions from the last week of April and first week of May. The model is able to capture the climatological patterns of seasonal total rainfall and averaged wind at lower and upper levels. Observed snow in the presence of climatological SST as a boundary condition shows much impact on rainfall and circulation than observed SST in the presence of climatological snow. Model performance is good in simulating the normal and excess monsoon conditions; it shows poor skill in capturing deficit monsoon years.
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