alexa Bias Correction for RCM Predictions of Precipitation and Temperature in the Chaliyar River Basin | OMICS International | Abstract
ISSN : 2332-2594

Journal of Climatology & Weather Forecasting
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Research Article

Bias Correction for RCM Predictions of Precipitation and Temperature in the Chaliyar River Basin

Raneesh KY1*Thampi SG2
1Ex-research Scholar, Department of Civil Engineering, National Institute of Technology, Calicut - 673601, Kerala, India
2Associate Professor, Department of Civil Engineering, National Institute of Technology, Calicut - 673601, Kerala, India
Corresponding Author : Raneesh. K. Y
Ex - research Scholar, Department of Civil Engineering
National Institute of Technology, Calicut 673601, Kerala, India
E-mail: [email protected]
Received July 16, 2013; Accepted August 07, 2013; Published August 12, 2013
Citation: Raneesh KY, Thampi SG (2013) Bias Correction for RCM Predictions of Precipitation and Temperature in the Chaliyar River Basin. J Climatol Weather Forecasting 1:105. doi:10.4172/2332-2594.1000105
Copyright: © 2013 Raneesh KY, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Abstract

Global climate models (GCMs) relate greenhouse gas (GHG) forcing to future potential climate states and enable development of climate projections for the future. GCMs exhibit some limitations when focusing on smaller scales (regional to local) or to resolve the processes caused by topography and land use. To overcome this problem, regional climate models (RCMs) and other downscaling methods have been developed. The Indian Institute of Tropical Meteorology (IITM), Pune, in collaboration with the Hadley Centre, UK has developed future climate scenarios for India. Climate data (precipitation and temperature) for the Chaliyar river basin in Kerala for both A2 and B2 scenarios were utilized in this study. Bias correction was performed to ensure that important statistics (coefficient of variation, mean and standard deviation) of the downscaled output matched the corresponding statistics of the observed data. This method of bias correction does not correct for the fraction of wet and dry days and lag inverse autocorrelation. But, it was observed that a relatively simple non-linear correction, adjusting both the biases in the mean and variability, leads to better reproduction of observed extreme daily and multi-daily precipitation amounts. A marked improvement was achieved with a nonlinear transformation, adjusting the mean as well as the coefficient of variation of daily precipitation. Predictions show that annual rainfall in the Chaliyar river basin may decrease by about 20-25% from the present day annual average value in the A2 scenario. In the B2 scenario, the decrease was in the range of 10-15%. Annual average temperature may increase by 3.3oC and 1.8oC from the present day average values in the A2 and the B2 scenarios respectively.

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