Lok Sabha Question No. 3105 (UNSTARRED), answered on 2019-12-06
Subject: Accuracy of IMD Forecasts
Ministry: EARTH SCIENCES
Asked by: Raju Bista, Kanakmal Katara, Pankaj Chowdhary

## GOVERNMENT OF INDIA MINISTRY OF EARTH SCIENCES LOK SABHA

## UNSTARRED QUESTION No. 3105 TO BE ANSWERED ON FRIDAY, DECEMBER 06, 2019

## ACCURACY OF IMD FORECASTS

3105. SHRI RAJU BISTA: SHRI KANAKMAL KATARA: SHRI PANKAJ CHAUDHARY :

Will the Minister of EARTH SCIENCES be pleased to state:

- (a) the techniques being used by meteorologists for accurate weather forecasts including monsoon forecasts;
- (b) whether the Government has taken note of the inaccurate forecasts of Indian Meteorological  Department (IMD) including  monsoon rainfall;
- (c)
- if so, the details thereof and the reasons therefor;
- (d) whether the Government  has any proposal for accurate and localised weather forecasts for every region including upgradation of  weather  forecasting  technology/instruments  for  more  accurate forecasting of weather; and
- (e) if  so,  the  details  thereof  along  with  the  steps  taken  by  the Government in this regard?

## ANSWER MINISTER FOR SCIENCE AND TECHNOLOGY AND MINISTRY OF EARTH SCIENCES (DR. HARSH VARDHAN)

- (a) India  Meteorological  Department  (IMD)  uses  scientifically  based models for accurate weather forecasts including monsoon forecasts. IMD uses state-of-the-art mathematical models (prediction  models)  for  generating  forecasts  on  short  to  medium range  (up  to  10  days),  extended  range  (10  days  to  30  days)  and seasonal forecasts (for the whole season). Ministry of Earth Sciences  (MoES)  has  launched  National  Monsoon  Mission  (NMM) with a vision to develop state-of-the-art dynamical prediction system for the monsoon rainfall on different time scales.

Under NMM, Indian Institute of Tropical Meteorology (IITM), Pune is coordinating  and  working  along  with  different  climate  research centers  from  India  and  abroad  on  the  development  of  a  coupled atmosphere-ocean model for long and extended range forecasting of Indian summer monsoon rainfall.

For preparing the long range forecast for monsoon, currently, latest state-of-the-art  statistical  models  and  Monsoon  Mission  Climate Forecast  System  (MMCFS)  model  are  used.  IMD  has  been  using MMCFS  model  for  preparing operational forecasts since 2017 monsoon season along with present statistical models.

- (b) & (c) For monsoon forecasts, IMD utilizes the products from the dynamical model developed under the National Monson Mission and a  statistical  model  for  generating  Long  Range  Forecast  (LRF)  for Monsoon Season. With respect to LRF, the performance of the model for last three years gave mixed results.

The seasonal monsoon rainfall forecast issued by IMD using MMCFS for the past three years along with observed rainfall are given in the table below. However, the  MMCFS model forecast correctly indicated the spatial distribution of rainfall over most of the region.

| The verification of MMCFS monsoon rainfall forecast for the years 2017 to 2019   | The verification of MMCFS monsoon rainfall forecast for the years 2017 to 2019   | The verification of MMCFS monsoon rainfall forecast for the years 2017 to 2019   | The verification of MMCFS monsoon rainfall forecast for the years 2017 to 2019   | The verification of MMCFS monsoon rainfall forecast for the years 2017 to 2019   | The verification of MMCFS monsoon rainfall forecast for the years 2017 to 2019   | The verification of MMCFS monsoon rainfall forecast for the years 2017 to 2019   | The verification of MMCFS monsoon rainfall forecast for the years 2017 to 2019   |
|----------------------------------------------------------------------------------|----------------------------------------------------------------------------------|----------------------------------------------------------------------------------|----------------------------------------------------------------------------------|----------------------------------------------------------------------------------|----------------------------------------------------------------------------------|----------------------------------------------------------------------------------|----------------------------------------------------------------------------------|
| 2017                                                                             | 2017                                                                             | 2017                                                                             | 2018                                                                             | 2018                                                                             | 2018                                                                             | 2019                                                                             | 2019                                                                             |
| Forecasted RF (% LPA)                                                            | Forecasted RF (% LPA)                                                            | Obse rved RF (% LPA)                                                             | Forecasted LPA)                                                                  | Forecasted LPA)                                                                  | Obser ved RF (% LPA)                                                             | Forecasted RF (% LPA) Observed                                                   | Forecasted RF (% LPA) Observed                                                   |
| Apr                                                                              | Jun                                                                              |                                                                                  | RF (%                                                                            | May                                                                              |                                                                                  | May                                                                              | RF (% LPA)                                                                       |
|                                                                                  |                                                                                  |                                                                                  | Apr                                                                              |                                                                                  | Apr                                                                              |                                                                                  |                                                                                  |
| 96± 5                                                                            | 100± 4                                                                           | 95                                                                               | 99± 5                                                                            | 102± 4                                                                           | 91 96± 5                                                                         | 96± 4                                                                            | 110                                                                              |

Forecast  generated  using  MMCFS  for  monsoon  season  rainfall  for the  year  2017  was  within  the  forecast  limit.  For  2018,  the  model forecast was overestimate and for 2019, it was underestimate with respect to the realized rainfall.

- (d)  &  (e)  It  has  been  planned  to  further  enhance  the  accuracy  of  weather forecasts and their effective & timely dissemination in the coming years. For this purpose, under the Umbrella Scheme 'Atmosphere & Climate Research -Modeling Observing Systems & Services (ACROSS)',  there  is  a  program,  'Upgradation  of  Forecast  System'. The various components of this sub-scheme include (i) Development of  an  advanced  operational  forecast  system.  (ii)  Upgradation  and sustenance  of  communication  systems  for  weather  services  (iii) Capacity building & outreach etc. As a part of the first component, it is planned to have a Decision Support System to enable the weather forecasters to view and analyze huge volume of data and products efficiently  within  given  time  frame,  and  decide  the  forecast  and warning. A forecast & warning dissemination tool which will enable the inclusion of user friendly textual & graphical products as well as videos is also envisaged under this programme.

This along with further improvements in the observational network and  numerical  modeling  capability  as  planned  under  ACROSS  are also expected to increase the accuracy of weather forecasts.

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