Lok Sabha Question No. 1876 (UNSTARRED), answered on 2026-02-11
Subject: Monsoon Forecasting and Climate Resilience in Assam
Ministry: EARTH SCIENCES
Asked by: Shri Gaurav Gogoi

## GOVERNMENT OF INDIA MINISTRY OF EARTH SCIENCES LOK SABHA UNSTARRED QUESTION NO. 1876

## TO BE ANSWERED ON WEDNESDAY, 11 TH  FEBRUARY, 2026

## MONSOON FORECASTING AND CLIMATE RESILIENCE IN ASSAM

## 1876.   SHRI GAURAV GOGOI:

Will the Minister of EARTH SCIENCES be pleased to state:

- (a) the  details  of  accuracy  and  performance  of  the  India  Meteorological  Department's monsoon forecasting models during the 2025 South-West monsoon in Assam including rainfall deviation from forecasts and the improvements proposed for the ongoing and subsequent monsoon periods, district-wise;
- (b) the measures taken/being taken during the current year to strengthen climate resilience in  Assam's  monsoon-dependent  and  flood-prone  agricultural  regions  particularly  in districts affected by recurrent flooding, riverbank erosion and rainfall variability; and
- (c) the  role  of  satellite-based  monitoring,  real-time  data  integration  and  early-warning systems in enhancing weather prediction, flood forecasting and disaster preparedness in Assam during the 2025 monsoon season?

## ANSWER

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

- (a) The India Meteorological Department (IMD) provides seamless forecasts across time scales, ranging from seasonal forecasts to short-range and nowcasts. For the Southwest Monsoon  2025,  IMD  had  predicted  below-normal  seasonal  rainfall  over  Northeast India  region  (which  includes  Assam)  as  well  as  for  the    subdivision  of  Assam  and Meghalaya.  For this newly implemented Multi-Model Ensemble (MME) forecasting System was used. The realized seasonal rainfall during the 2025 southwest monsoon over both the Northeast India region and Assam and Meghalaya subdivision was also below normal, in line with the IMD's seasonal forecast. The details are provided in Annexure-1.  For  issuing  short-range  rainfall  forecasts  and  heavy  rainfall  warnings, IMD primarily uses outputs from various global models. For heavy rainfall prediction during the Southwest Monsoon 2025, the skill of heavy rainfall forecasts for the Assam State as a whole is 89-94%, while at the district scale in Assam, it is 75-80% at lead time of Day 1 to Day 5.

Under  the  Mission  Mausam,  several  initiatives  have  been  taken  to  further  improve forecast  capabilities  of  the  Multi-Model  Ensemble  framework  like  upgradation  of coupled atmosphere-ocean models, assimilation of improved observational datasets, and  greater  use  of  high-resolution  numerical  weather  prediction  (NWP)  models.  In addition, initiatives are taken to explore the use of Artificial Intelligence and Machine Learning  (AI/ML)  techniques  for  weather  forecasting,  including  for  understanding uncertainties at sub-seasonal and regional scales.

- (b) To  enhance  climate  resilience  in  monsoon-dependent  and  flood-prone  agricultural regions of Assam, the Government, through the IMD, has been increasing investment with the new Mission Mausam project to further improve its early warning system. IMD  is  also  issuing  Impact-based  forecasts  and  agrometeorological  advisories  to support preparedness and risk mitigation. IMD also extends support to State agencies and  the  Central  Water  Commission  (CWC)  by  timely  sharing  both  observed  and forecast rainfall to improve flood forecasts up to a 7-day lead time, which aids planning in districts affected by recurrent flooding, riverbank erosion, and rainfall variability. For timely dissemination to the last mile, various new digital platforms are currently in use in real time, including Common Alerting Protocol (CAP)-based alerts, and apps like MAUSAM, Meghdoot, and Damini, for the benefit of farmers, policymakers, and the general public. In addition, IMD conducts Climate Service User Forum meetings jointly  with  the  State  Government  to  facilitate  stakeholder  interaction  and  promote effective utilisation of weather and climate services.
- (c) The  role of  satellite-based  monitoring  immensely  helps  in  enhancing  weather prediction,  flood  forecasting,  and  disaster  preparedness,  especially  for  the  State  of Assam, by integrating various satellite data, e.g., cloud cover, winds, etc, with surfacebased  observations  from  rain  gauges,  Automatic  Weather  Stations  (AWS),  and Doppler Weather Radars (DWRs). Based on these inputs, IMD issued heavy rainfall warnings,  flood-related  advisories,  and  impact-based  forecasts  to  support  timely preparedness and response by State authorities. For climate resilience, IMD provides Extended  Range  Forecasts  (ERF)  with  lead  times  of  up  to  two  weeks  to  support agricultural  planning  and  reduce  exposure  to  extreme  rainfall,  which  complements seasonal climate outlooks. IMD also supplies high-resolution gridded rainfall data and historical  climate  data  to  assist  hydrological  studies  and  the  planning  of  climateresilient infrastructure. In addition, district-level agrometeorological advisories issued under the Gramin Krishi Mausam Sewa (GKMS) support farmers in crop planning, irrigation, and other field operations under variable weather conditions.

Annexure-1

Rainfall during the Southwest Monsoon 2025 over Assam and the Northeast Region:

| Region                                     | 2025 Forecast Category of the LPA   | Climatological Normal inmm (1971-2020)   | Observed Rainfall Percentage Departure from LPA (Actual Rainfall in mm)   | Remarks                   |
|--------------------------------------------|-------------------------------------|------------------------------------------|---------------------------------------------------------------------------|---------------------------|
| Assam and Meghalaya (sub-division)         | Below Normal (<93% of the LPA)      | 1762.2mm                                 | -49% of LPA (906.4 mm)                                                    | The forecast was accurate |
| East&NE India (Homogenous rainfall Region) | Below Normal (<94% of the LPA)      | 1367.3mm                                 | -33% of LPA (920 mm)                                                      | The forecast was accurate |

********