D S Pai
Articles written in Journal of Earth System Science
Volume 118 Issue 2 April 2009 pp 123-135
The summer monsoon onset over Kerala (MOK)marks the beginning of the rainy season for the country.Associated with the MOK,signiﬁcant transitions of large scale atmospheric and oceanic circulation patterns are observed over the Asia –Paciﬁc region.In this study,a new method for the objective identiﬁcation of MOK,based on large scale circulation features and rainfall over Kerala,is discussed.Further,a set of empirical models based on the principal component regression (PCR)technique was developed for the prediction of the date of MOK by keeping in mind the IMD ’s operational forecasting service requirements.Predictors for the models were derived using correlation analysis from the thermal,convective and circulation patterns.Only ﬁve predictors pertaining to the second half of April were used in the ﬁrst model (Model-1)so that the prediction of MOK can be prepared by the end of April itself.The second model (Model-2)used four additional predictors pertaining up to the ﬁrst half of May along with two predictors used in the Model-1 for update prediction at the end of the ﬁrst half of May.To develop each of the PCR models, Principal Components Analysis (PCA)of the respective predictor data was carried out followed by regression analysis of ﬁrst two principal components (PCs)with the date of MOK.Both these models showed good skill in predicting the date of MOK during the independent test period of 1997 –2007.The root mean square error (RMSE)of the predictions from both the models during the independent test period was about four days which was nearly half the RMSE of the predictions based on climatology.
Volume 124 Issue 2 March 2015 pp 321-333
The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the Indian region during June–September (JJAS) by using hindcast of the Japan Meteorological Agency (JMA) seasonal ensemble prediction system (EPS) model, based on five ensembles of March, April and May initial states for a period of 32 years (1979–2010).
The hindcast climatology during JJAS simulates the mean monsoon circulation at lower and upper tropospheres very well in JMA model using March, April and May ensembles with a more realistic simulation of Webster and Yang’s broad scale monsoon circulation index. The JMA hindcast climatology during JJAS simulates the rainfall maxima over the west-coast of India and the head Bay of Bengal reasonably well, although, the latter is slightly shifted southwestward. Associated with better forecast skills of El Nino in the JMA model, the interannual variability of All India Summer Monsoon Rainfall (AISMR) during the 32-year period has also been very well simulated with a high significant (99% level) correlation in April ensemble followed by that of March and May ensembles. Thus, the present analysis indicates that the JMA seasonal forecast model can prove to be a useful tool for the dynamical seasonal forecast of AISMR.
Volume 128 | Issue 8
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