ABSTRACT: This paper presents a methodology to downscale monthly precipitation to river basin scale in Indian context
for special report of emission scenarios (SRES) using Support Vector Machine (SVM). In the methodology presented,
probable predictor variables are extracted from (1) the National Center for Environmental Prediction (NCEP) reanalysis
data set for the period 1971–2000 and (2) the simulations from the third generation Canadian general circulation model
(CGCM3) for SRES emission scenarios A1B, A2, B1 and COMMIT for the period 1971–2100. These variables include
both the thermodynamic and dynamic parameters and those which have a physically meaningful relationship with the
precipitation. The NCEP variables which are realistically simulated by CGCM3 are chosen as potential predictors for
seasonal stratification. The seasonal stratification involves identification of (1) the past wet and dry seasons through
classification of the NCEP data on potential predictors into two clusters by the use of K-means clustering algorithm
and (2) the future wet and dry seasons through classification of the CGCM3 data on potential predictors into two clusters
by the use of nearest neighbour rule. Subsequently, a separate downscaling model is developed for each season to capture
the relationship between the predictor variables and the predictand. For downscaling precipitation, the predictand is chosen
as monthly Thiessen weighted precipitation for the river basin, whereas potential predictors are chosen as the NCEP
variables which are correlated to the precipitation and are also realistically simulated by CGCM3. Implementation of the
methodology presented is demonstrated by application to Malaprabha reservoir catchment in India which is considered to
be a climatically sensitive region. The CGCM3 simulations are run through the calibrated and validated SVM downscaling
model to obtain future projections of predictand for each of the four emission scenarios considered. The results show
that the precipitation is projected to increase in future for almost all the scenarios considered. The projected increase in
precipitation is high for A2 scenario, whereas it is least for COMMIT scenario.

Full Article: http://http://onlinelibrary.wiley.com/doi/10.1002/joc.1529/abstract

Last Updated: 2011-02-09