Multi-model ensemble schemes for predicting northeast monsoon rainfall over peninsular India

Journal of Earth system science

Nachiketa Acharya1³  S C Kar2¹  L N Sahoo3²  Makarand A Kulkarni1³  U C Mohanty1³ 

[1] National Centre for Medium Range Weather Forecasting, Noida, India.$$;Department of Statistics, Utkal University, Bhubaneswar, India.$$;Centre for Atmospheric Sciences, Indian Institute of Technology, New Delhi, India.$$

关键词: Northeast monsoon;    multi-model ensemble;    rainfall;    prediction;    principal component regression;    single value decomposition.;   

DOI  :  

学科分类：天文学(综合)

来源: Indian Academy of Sciences

【 摘 要 】

The northeast (NE) monsoon season (October, November and December) is the major period of rainfall activity over south peninsular India. This study is mainly focused on the prediction of northeast monsoon rainfall using lead-1 products (forecasts for the season issued in beginning of September) of seven general circulation models (GCMs). An examination of the performances of these GCMs during hindcast runs (1982–2008) indicates that these models are not able to simulate the observed interannual variability of rainfall. Inaccurate response of the models to sea surface temperatures may be one of the probable reasons for the poor performance of these models to predict seasonal mean rainfall anomalies over the study domain. An attempt has been made to improve the accuracy of predicted rainfall using three different multi-model ensemble (MME) schemes, viz., simple arithmetic mean of models (EM), principal component regression (PCR) and singular value decomposition based multiple linear regressions (SVD). It is found out that among these three schemes, SVD based MME has more skill than other MME schemes as well as member models.

【 授权许可】

Unknown