JUNE TO SEPTEMBER 2001
 
 
 

Around this time, the India Meteorological Department (IMD) issues long range seasonal forecast for the ensuing southwest monsoon rainfall spanning the four moall spanning the four month period (June to September) over the country as a whole as well as for three homogeneous regions, viz., Northwest India, Peninsula and Northeast India. IMD has developed different models like Parametric, Power Regression, Multiple Regression, Dynamic Stochastic Transfer, Power Transfer, Principal Component Regression and Neural Network models for issuing these long-range seasonal forecasts.
 

2.    FORECASTS FOR MONSOON RAINFALL OVER THE COUNTRY AS A WHOLE

2.1 Operational Models

Since 1988, IMD has been issuing long range forecast for the monsoon rainfall over the country as a whole using the 16 parameter power regression model which was operationalised by the IMD in 1988. Last year, this 16 parameter model was updated model was updated by replacing the 4 predictors . No further modification has been made this year. The official long range forecast for the country as a whole is issued based on this 16 parameter Power Regression and Parametric models.

2.1.1 Parametric Model

This model provides qualitative forecast and utilizes the signals from 16 antecedent global and regional land-ocean-atmospheric parameters. Analysis of the signals from these parameters indicates that this year, 63% of them are favourable for a normal monsoon. The seasonal rainfall for the country as a whole is thus expected to be normal (defined as ±10 % of the long period average value).

2.1.2 Power Regression Model

This model provides quantitative forecast and is based on the physical relationship of monsoon rainfall with 16 different individual parameters. According to this model, the total amount of rainfall over the country as a whole during the monsoon season from June to September 2001 is likely to be 98% of its Long Period Average (LPA), with an estimated model error of ±4 %.

2.2 Experimental Models

Five different types of experimental models viz., Multiple Regression Model with 6 parameters, Dynamic Stochastic Transfer Model with East Coast India Minimum Temperature, Power Transfer Model with 10 parameters, Principal Component Regression Model with 8 parameters and Artificial Neural Network Model with 8 parameters have been used. The forecasts obtained from different models are 101% of LPA from the LPA from the Multiple Regression Model, 101% of LPA from the DST Model, 101% of LPA from the Power Transfer Model, 103% of LPA from the Principal Component Regression Model and 100% of LPA from the Neural Network Model.

2.3 Summary of the Long Range Forecast for 2001 monsoon over the country as a whole
 

The long range forecast for the 2001 Southwest Monsoon formulated on the basis of Parametric and Power Regression Model is given below:

a)In 2001, the rainfall for the South-west monsoon season (June to September) for the country as a whole is likely to be normal, thus making the year 2001 the 13th normal monsoon year in succession. The normal is defined as rainfall within ± 10% of its long period average.

b) Quantitatively, the rainfall over the country as a whole for the 2001 South-west monsoon season (June to September) is likely to be 98% of its long period average with an estimated model error of ±4%.
 
 
 

3.FORECASTS FOR MONSOON RAINFALL OVER THE HOMOGENEOUS REGIONS OF INDIA

In 1999, IMD issued for the first time region-wise long-range forecasts for three homogeneous regions of the country viz., North-west India, Peninsula and North-east India. This year also IMD issued long-range forecasts for these three homogeneous regions of India.

3.1 Forecasts for Northwest India

For the purpose of this forecast, Northwest India is taken to consist of Jammu & Kashmir, Himachal Pradesh, Punjab, Haryana, Delhi, Uttaranchal, Uttar Pradesh and Rajasthan.

Five different types of models viz., Power Regression with 6 parameters, Multiple Regression with 5 parameters, Dynamic Stochastic Transfer with Indian Equatorial Ocean Sea surface temperature and climatic forcings as inputs, Principal Component Regression with 8 parameters and Neural Network with 8 parameters have been used. The forecast obtained from different models are 100% of LPA from the Power Regression model, 105% of LPA from the Multiple Regression model, 91% of LPA from the Dynamic Stochastic Transfer Model, 100% of LPA from the Principal Component Regression model and 99% of LPA from the Neural Network model.

Based on the Power Regr>Based on the Power Regression Model, the monsoon rainfall over Northwest India for the entire monsoon season (June to September), 2001 is likely to be 100% of its long period average.

3.2 Forecasts for Peninsula

For the purpose of this forecast, Peninsula is taken to consist of Gujarat, Madhya Pradesh, Chattisgarh, Maharashtra, Andhra Pradesh, Karnataka, Kerala, Tamil Nadu and Lakshadweep.
 

Five different types of models viz., Power Regression with 10 parameters, Multiple Regression with 5 parameters, Dynamic Stochastic Transfer with Indian Equatorial Ocean SST and climatic forcings as inputs, Principal Component Regression with 8 parameters and Neural Network with 8 parameters have been used. The forecasts obtained from different models are 96% of LPA from the Power Regression Model, 96% of LPA from the Multiple Regression Model, 91% of LPA from the Dynamic Stochastic Transfer Model, 104% of LPA from the Principal Component Reression Model and 106% of LPA from the Neural Network Model.

Based on the Power Regression Model, the monsoon rainfall over Peninsula for the entire monsoon season (June to September), 2001 is likely to be 96% of its long period average.

3.3. Forecasts for Northeast India

For the purpose of this forecast, Northeast India is taken to consist of Arunachal Pradesh, Assam and Meghalaya, Nagaland, Manipur, Mizoram, Tripura, Sikkim, West Bengal, Orissa, Bihar, Jharkhand and Andaman and Nicobar Islands.

Three different types of models viz., Power ferent types of models viz., Power Regression Model with 7 parameters, Multiple Regression Model with 3 parameters and Dynamic Stochastic Transfer Model with East Coast India Minimum Temperature and climatic forcings as inputs have been used. The forecasts obtained from different models are 100% of LPA from the Power Regression Model, 102% of LPA from the Multiple Regression Model and 103% of LPA from the Dynamic Stochastic Transfer Model.

Based on the Power Regression Model, the monsoon rainfall over Northeast India for the entire monsoon season (June to September), 2001 is likely to be 100% of its LPA.
 
 

4. SUMMARY OF THE FORECASTS

The long-range forecasts for the 2001 Southwest Monsoon over the country as a whole and the three broad homogene three broad homogeneous regions of India, viz., NW India, Peninsula and NE India are given below.

In 2001, the rainfall for the South-west monsoon season (June to September) for the country as a whole is likely to be normal thus making the year 2001 thirteenth normal monsoon year in succession. The normal is defined as rainfall within ±10 % of its long period average.

Quantitatively, the rainfall over the country as a whole for the 2001 South-west monsoon season (June to September) is likely to be 98% of its long period average with an estimated model error of ±4%.

Over the three broad homogeneous regions of India, the rainfall for the 2001 South-west monsoon season is likely to be 100% of its long period average over North-west India, 96% of the long period average over the Peninsula and 100% of the long period average over North-east India with an estimated model error of ±8 %.
 
 
 

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Details can be found by contacting directly :
 

The Director General of Meteorology

URL : http://www.imd.ernet.in