Statistical downscaling of global models historical maximum temperature record were performed for 20 years during the base period 1986-2005 using Global Coupled Models (GCM), such as the Coupled Model Inter-comparison phase 5 (CMIP5).This period is termed as a ‘reference period’ for future projection of heat wave. The extreme weather events such as heat waves have a significant impact on the Indian climate. The frequency, intensity, duration and number of spells of these heat waves are increasing in the recent years. Local to regional scale climate cannot be predicted by GCM’s. Statistical downscaling method such as Bias-Correction Spatial Disaggregation (BCSD) method is used in generating the statistical downscaling algorithm to tackle the present limitations of GCM outputs. Four models such as CanESM2, MIROC-ESM-CHEM, IPSL-CM5A-LR and NorESM1-M from CMIP5 models were chosen and biases are corrected for Indian domain.Various geographical regions of India have been examined. Observational data is taken from India Meteorological Department (IMD) gridded daily maximum temperature data at 1 degree resolution for the same period. The CMIP5 models data has been obtained and it is downscaled using statistical methods. The performance of this downscale data is tested using parameters such as Mean Absolute Error (MAE), Root Mean square Error (RMSE), Correlation cofficienbetween each simulated model and observational data for the same time period over the study area, bias of each model from IMD observational data, Mean percentage error, Index of Agreement with given observation and model time series. By using this method biases were removed to greater extent and correlation coefficient also increased. This method can be applied to future data for bias correction and to improve the correlation.
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9 May 2022
NATIONAL CONFERENCE ON ADVANCES IN APPLIED SCIENCES AND MATHEMATICS: NCASM-20
24–25 September 2020
Rajpura, India
Research Article|
May 09 2022
Statistical downscaling in maximum temperature future climatology
N. Naveena;
N. Naveena
a)
1
Center for Atmospheric Science, K L University
, Guntur, Andhra Pradesh, India
a)Corresponding author: [email protected]
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G. Ch. Satyanarayana;
G. Ch. Satyanarayana
1
Center for Atmospheric Science, K L University
, Guntur, Andhra Pradesh, India
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N. Umakanth;
N. Umakanth
1
Center for Atmospheric Science, K L University
, Guntur, Andhra Pradesh, India
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M. C. Rao;
M. C. Rao
2
Department of Physics, Andhra Loyola College
, Vijayawada-520008, India
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B. Avinash;
B. Avinash
3
Department of ECE, K L University
, Andhra Pradesh, India
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J. Jaswanth;
J. Jaswanth
3
Department of ECE, K L University
, Andhra Pradesh, India
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M. S. Sainath Reddy
M. S. Sainath Reddy
3
Department of ECE, K L University
, Andhra Pradesh, India
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a)Corresponding author: [email protected]
AIP Conf. Proc. 2357, 030026 (2022)
Citation
N. Naveena, G. Ch. Satyanarayana, N. Umakanth, M. C. Rao, B. Avinash, J. Jaswanth, M. S. Sainath Reddy; Statistical downscaling in maximum temperature future climatology. AIP Conf. Proc. 9 May 2022; 2357 (1): 030026. https://doi.org/10.1063/5.0081087
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