A model based on principle component regression (PCR) technique is used for the prediction of monsoon onset over Kerala (MOK). The details of the 6 predictors are given below.
|S. No||Name of the Predictor||Temporal Domain||Geographical Domain||C.C 1975-2000|
|1||SE Indian Ocean SST anomaly||JAN||24S-14S, 80E-100E||0.41|
|2||NW India Minimum Surface air Temperature Anomaly||1. Deesa 2.Rajko 3. Guna 4. Bikaner 5. Akola 6. Barmer||16th April to 15th May||-0.63|
|3||Zonal Wind Anomaly at 1000hpa over Equatorial South Indian Ocean||1-15 may||10S-0, 80E-100E||0.52|
|4||OLR Anomaly Over Indo-China||1-15 may||17.5N-27.5N, 95E-105E||0.43|
|5||OLR Anomaly Over Southwest Pacific||1-15 may||30S,20S, 145E-160E||-0.54|
|6||Pre-Monsoon Rainfall Peak Date||Pre-monsoon||South Peninsula (8N-13N, 74E-78E)||0.65|
The PC analysis was applied over the predictor set containing all the 6 predictors for the 26 years (1975-2000) and first 3 principle components(PC1, PC2 and PC3) explaining about 79% of the total variability of the predictor set were retained for further analysis. A multiple linear regression model was then developed using the retained 3 PCs as the input variables and MOK as the predictand. Model was developed using the same 26 years (1975-2000). This model was then used for predicting the MOK.