ANNOUNCEMENTS
The climate of the Earth is primarily driven by the energy received from the sun’s radiation and the different physical, chemical and biological processes that transforms this energy from one form to another. It can be observed and studied at different scales. At the global scale, general circulation models (GCMs) are used to replicate the interconnections between various climatological factors and natural phenomena. With climate change no longer being a speculation, there is a need to study the present and future implications of it at a regional scale to develop policy measures for the effective mitigation and adaptation to its impacts. The present study is an attempt to evaluate India’s first indigenously developed earth system model to contribute to the CMIP6 project, the IITM-ESM in its capability to simulate one of the most complicated phenomena of the global climate system, the Indian summer monsoon and also to assess how different statistical downscaling techniques perform in improving the model simulation of the monsoon system in India. Four statistical downscaling techniques such as Viz; linear scaling, power transformation, parametric quantile mapping and empirical quantile mapping applied to the model and evaluated with reference to the IMD’s gridded rainfall data at 0.250 X 0.250 resolution. It was found that empirical quantile mapping and power transformation techniques performed best in the case of various statistical parameters. However, power transformation being a relatively simpler technique and requiring lesser computational resource, could be used for downscaling IITM-ESM model over India for regional studies on the impact of climate change.
Keyword: General Circulation models, Climate Change, Bias, Bias Correction, Downscaling, Indian Summer Monsoon, Regional Impact Models, Earth system model.
