Lok Sabha Question No. 3085 (UNSTARRED), answered on 2026-03-11
Subject: Accurate Weather Forcasting
Ministry: EARTH SCIENCES
Asked by: Shri Bhojraj Nag

## GOVERNMENT OF INDIA

## MINISTRY OF EARTH SCIENCES LOK SABHA

## UNSTARRED QUESTION NO. 3085 TO BE ANSWERED ON WEDNESDAY, 11 TH  MARCH, 2026

## ACCURATE WEATHER FORECASTING

†3085. SHRI BHOJRAJ NAG:

Will the Minister of EARTH SCIENCES be pleased to state:

- (a) the details of improvements made in the accuracy of forecasting cyclones, monsoons and heatwaves along with the quantitative assessment of its economic impact;
- (b) whether  the  Government  has  assessed  the  public  benefit  and  proposes  to  launch  a second phase of expansion; and
- (c) if so, the details thereof?

## ANSWER

## THE MINISTER OF STATE (INDEPENDENT CHARGE) FOR MINISTRY OF SCIENCE AND TECHNOLOGY AND EARTH SCIENCES (DR. JITENDRA SINGH)

- (a) There  has  been  significant  improvements  in  the  early  warning  systems,  including improvements in the accuracy of forecasting of various extreme weather events like cyclones, heat waves, heavy rainfall, and thunderstorms in recent years. The details are given below:

Improvements in Cyclone Forecasts: The annual average track forecast errors in 2025 were 80 km, 120 km, and 204 km, respectively, at 24, 48, and 72 hrs, compared with the past five-year average errors of 72, 111, and 154 km based on data from 2020-2024. The annual average landfall forecast errors for 2025 have been 76 km, 82 km, and 121 km for 24, 48, and 72 hrs lead periods, respectively, against the past five years' average errors of 16 km, 39 km, and 70 km during 2020-2024. The annual average absolute error  (AE)  in  intensity  forecast  has  been  3.1  knots,  2.7  knots,  and  3.9  knots, respectively, for 24, 48, and 72 hrs lead periods, against the past five-year average of 5.9, 8.3, and 9.8 knots during 2020-2024.

Monsoonal  rainfall  and  heavy  rainfall  warnings: The  India  Meteorological Department (IMD) has been following a seamless forecasting strategy for monsoonal rainfall. As per this strategy, it issues forecasts and warnings on different time scales and  for  different  spatial  scales.  Nowcasting-  up  to  six  hours  for  all  types  of  severe weather at all districts and around 1200 stations. Short to medium range (up to 7 days) forecasts  for  rainfall  over  cities,  blocks,  districts,  and  meteorological  subdivisions. Extended range (up to 4 weeks) forecasts for 36 meteorological subdivisions. Monthly and  seasonal  long-range  forecasts  for  rainfall  for  the  whole  country  and  for  a homogenous region.

The latest assessment of the accuracy of its seasonal long range for Southwest Monsoon in the current year 2025  shows it was highly accurate and the forecast, issued in April 2025, for the southwest monsoon (June-September) rainfall over the country as a whole was 105% of long period average (LPA) while the actual season rainfall for the country as a whole was 108 % of LPA and it was within range of the forecast issued. The spatial probability  forecasts  were  also  largely  accurate  across  most  regions  of  the  country. Similarly,  the  monthly  rainfall  forecasts  closely  matched  the  observed  values  and remained within the forecast limits. The latest assessment of Heavy rainfall Forecast Performance shows in 2025, the heavy rainfall forecast demonstrated high skill, with Probability of Detection of 0.85, indicating it was in overall accuracy.

IMD has adopted a new strategy for monthly and seasonal forecasting since 2021 based on the Multi-Model Ensemble (MME) approach. The strategy utilizes coupled global climate models (CGCMs) from various global climate prediction and research centers, including  IMD's  Monsoon  Mission  Climate  Forecasting  System  (MMCFS).  The performance of IMD's seasonal forecasting system has shown improvement following the adoption of the MME-based approach. The verification details of IMD's seasonal forecasts for All India Summer Monsoon Rainfall for the period 2021 to 2025 are given below:

|                            | ALL India Monsoon Rainfall (LPA)   | ALL India Monsoon Rainfall (LPA)   | ALL India Monsoon Rainfall (LPA)   |
|----------------------------|------------------------------------|------------------------------------|------------------------------------|
| Year                       | Actual (%)                         | Forecast (%)                       | Remark                             |
| 2021                       | 99                                 | 101                                | Accurate                           |
| 2022                       | 106.5                              | 103                                | Accurate                           |
| 2023                       | 95                                 | 96                                 | Accurate                           |
| 2024                       | 108                                | 106                                | Accurate                           |
| 2025                       | 108                                | 106                                | Accurate                           |
| ***Model error ± 4% of LPA | ***Model error ± 4% of LPA         | ***Model error ± 4% of LPA         | ***Model error ± 4% of LPA         |

Heat  waves: For  the  summer  of  2025,  the  Probability  of  Detection  of  heat  wave forecasts/warnings for the season (March-June), is 98% for a 1-day advance, indicating excellent detection capability. Forecast skill decreases with increasing lead time, with the  3-day-ahead  forecast  skill  at  75%  and  the  5-day  forecast  skill  at  46%  in  2025, compared to 68% and 50%, respectively, in 2022.

Thunderstorms: The 3-hourly thunderstorm (TS) nowcast (March-June), skill showed significant improvement for the 2025 storm season, with the Probability of Detection as  0.92  in  2025,  which  was  0.83  in  2022.  For  24-hour  thunderstorm  forecasts,  the Probability of Detection was 0.89 in 2025.

The early warnings by the IMD and the timely action taken by the Government (Central & State) have significantly reduced the loss of life due to cyclones in recent times. Recently,  the  India  Meteorological  Department  (IMD),  in  coordination  with  other centres in the MoES, has developed an end-to-end GIS-based Decision Support System (DSS), which has been working as the front end of the early warning systems for the timely detection and monitoring of all-weather hazards across the country.

- (b)-(c)  Though the Government has not assessed the direct public benefit in recent years, but the  significant  improvement  in  the  early  warning  systems,  including  the  forecast accuracy of severe weather events, has led to a significant reduction in the death toll. For example, due to cyclones, around 7000 people lost their lives in the 1999 Odisha Super Cyclone, while it has been reduced to less than 100 over the entire region from the impact of tropical cyclones during recent years. Accurate forecast of 1 cyclone saves around 1100 crore rupees in terms of expenditure towards payment of ex-gratia to kins of dead, cost towards evacuation, and savings to various sectors, e.g., Power, Marine, Aviation, Railways, etc. Similarly, heat wave-related losses of lives have been reduced during recent years.

The interventions undertaken by the India Meteorological Department have significantly contributed to measurable socio-economic benefits for farmers, fishermen, vulnerable  communities,  and  the  general  public,  particularly  in  disaster-prone  and climate-sensitive  areas.  The  manner  in  which  these  benefits  have  accrued  are  as follows:

Improved Agricultural Planning and Productivity: District-level  and  block-level weather forecasts, agrometeorological advisories, and seasonal outlooks enable farmers to make  informed  decisions  regarding  sowing,  irrigation,  fertilizer application, harvesting, and crop protection. This has resulted in reduced crop losses, optimized input costs, and improved yields.

Reduction in Loss of Life and Property: Early warnings related to cyclones, heavy rainfall,  heat  waves,  cold  waves,  thunderstorms,  and  lightning  have  enabled  timely evacuation, preparedness measures, and contingency planning. This has substantially minimized casualties and damage to livelihoods.

Enhanced Safety for Fishermen: Timely marine weather forecasts, cyclone alerts, and ocean  state  warnings  help  fishermen  avoid  venturing  into  the  sea  during  adverse conditions. This has reduced incidents of loss of life, damage to fishing vessels, and economic hardship.

Support to Disaster Management Authorities: Impact-based forecasting and realtime  monitoring  support  State  and  district  administrations  in  planning  relief  and response  operations.  Early  action  reduces  recovery  costs  and  safeguards  vulnerable communities.

Heatwave and Cold Wave Action  Plans: Forecast-based  advisories  have  enabled local administrations to implement heat action plans, adjust working hours, and ensure access to drinking water and shelters, thereby protecting outdoor workers, the elderly, and economically weaker sections.

Climate  Services  for  Long-term  Resilience  and  Anticipatory  Action  against Climate  Risk: Climate  data  services  and  seasonal  forecasts  assist  policymakers  in water  resource  management,  crop  insurance  planning,  reservoir  operations,  and infrastructure preparedness, contributing to long-term socio-economic resilience.

The measurable benefits are reflected in reduced disaster-related mortality, lower crop losses,  improved  marine  safety,  and  enhanced  preparedness  at  community  and administrative levels. Continuous modernization of forecasting systems and expansion of dissemination channels through mobile applications, SMS alerts, and coordination with State agencies further strengthen outreach to affected populations.

The Government is continuously working to strengthen weather and climate forecasting systems in the country. New techniques and technologies have been implemented from time  to  time  to  improve  weather  and  climate  forecasting  systems.  Recently,  a  new Central Sector Scheme, "Mission Mausam", has been launched by MoES with the goal of making Bharat a "Weather-ready and Climate-smart" nation to mitigate the impact of  climate  change  and  extreme  weather  events  and  strengthen  the  resilience  of communities. Some of the progress in the various components of the early warning system are given below:

-  Strengthening of the observing system with the installation of additional AWS, ARG, and DWR, etc.
-  Improvement of the data integration and development of GIS-based DSS.
-  Improvement  of  NWP  models  and  climate  models,  as  well  as  a  real-time seamless monitoring, forecasting, and early warning system.
-  Shifting  from  conventional  weather  forecast  and  warning  to  sector-specific color-coded Impact-based forecast (IBF) and risk-based warning (RBW) up to district/sub-city levels with dynamical impact and risk matrix.
-  Application of AI/ML.
-  Customisation of bulletins and warnings.
-  Substantial increase of computational power to integrate voluminous data and to run meso-scale, regional, and global models at a further higher resolution scale, with improvement  of  process understanding and model  physics. Supercomputers (Arka and Arunika) are being used for this purpose.
-  Panchayat Mausam Seva.
-  A state-of-the-art dissemination system with the use of a mobile app, Common Alerting Protocol (CAP), WhatsApp groups, etc.

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