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Predictors and their domain for statistical downscaling of climate in Bangladesh

Alamgir, Mahiuddin and Pour, Sahar Hadi and Mohsenipour, Morteza and Hasan, M. Mehedi and Ismail, Tarmizi (2016) Predictors and their domain for statistical downscaling of climate in Bangladesh. Jurnal Teknologi, 78 (6-12). pp. 51-56. ISSN 0127-9696

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Official URL: http://dx.doi.org/10.11113/jt.v78.9232

Abstract

Reliable projection of future rainfall in Bangladesh is very important for the assessment of possible impacts of climate change and implementation of necessary adaptation and mitigation measures. Statistical downscaling methods are widely used for downscaling coarse resolution general circulation model (GCM) output at local scale. Selection of predictors and their spatial domain is very important to facilitate downscaling future climate projected by GCMs. The present paper reports the finding of the study conducted to identify the GCM predictors and demarcate their climatic domain for statistical downscaling in Bangladesh at local or regional scale. Twenty-six large scale atmospheric variables which are widely simulated GCM predictors from 45 grid points around the country were analysed using various statistical methods for this purpose. The study reveals that large-scale atmospheric variables at the grid points located in the central-west part of Bangladesh have the highest influence on rainfall. It is expected that the finding of the study will help different meteorological and agricultural organizations of Bangladesh to project rainfall and temperature at local scale in order to provide various agricultural or hydrological services.

Item Type:Article
Additional Information:RADIS System Ref No:PB/2016/10393
Uncontrolled Keywords:General circulation model, statistical downscaling
Subjects:T Technology > TA Engineering (General). Civil engineering (General)
Divisions:Advanced Informatics School
ID Code:66661
Deposited By: Fazli Masari
Deposited On:22 Nov 2017 00:45
Last Modified:22 Nov 2017 00:45

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