**Executive Summary**
This document provides information about the efficiency of current forecasting models used by the India Meteorological Department (IMD) and the Geological Survey of India (GSI) for heavy rains and landslides. It also details government investments in new forecasting models under Mission Mausam, including the Bharat Forecast System and Mithuna Forecast System. It specifies how alerts and warnings are disseminated to the public and stakeholders through various platforms, including mass media, internet, and mobile apps. The information is current as of December 17th, 2025.
**Key Points / Main Content**
* **Forecasting Model Efficiency:**
* IMD's skill score for 24-hour advance detection of heavy rainfall stands at 85% in 2024.
* IMD's heavy rainfall forecast accuracy ranges from 85% to 58% for lead times of one to five days, respectively.
* Overall, forecast accuracy for heavy rainfall events has improved by about 40% in 2023-2024 compared to 2014.
* GSI's landslide forecast model demonstrates a hit rate of over 80% across operational districts.
* **Government Initiatives:**
* Mission Mausam is being implemented, including the installation of Doppler Weather Radars (DWRs) across India (47 in operation).
* The Bharat Forecast System (BharatFS), operating at a 6-km spatial resolution, has been developed under Mission Mausam.
* The Mithuna Forecast System (Mithuna-FS) has been introduced, operating at a 12-km resolution. Mithuna-FS suite includes a 4-km high-resolution regional model and a 330-m hyper-resolution urban model for the Delhi region.
* **Alert and Warning Dissemination:**
* IMD issues timely alerts and forecasts to the public through mass media, internet, and mobile apps.
* IMD has launched seven services via the 'UMANG' Mobile App.
* Apps like 'MAUSAM', 'Meghdoot', and 'Damini' are used for weather forecasting, agromet advisory, and lightning alerts, respectively.
* The Common Alert Protocol (CAP) is being implemented to disseminate warnings by the IMD.
* **Decision Support Systems:**
* IMD uses a Decision Support System (DSS) for real-time multi-hazard impact-based early warning.
* Meteorological Centers (MCs) and Cyclone Warning Centers are available in each impacted State.
* **Accuracy Improvement:**
* The overall skill of forecasting severe weather events has improved by 30-40% over the last 10 years.
**Impact Analysis**
**Stakeholder: General Public**
**Impact:** Increased awareness and timely alerts regarding heavy rainfall and landslides.
**Action Required:** Stay informed via various platforms provided by IMD and adhere to safety guidelines during severe weather events.
**Stakeholder: Farmers**
**Impact:** Access to Agromet advisories through the 'Meghdoot' mobile app.
**Action Required:** Utilize the information to make informed decisions about farming practices.
**Stakeholder: State Governments and Disaster Management Authorities**
**Impact:** Access to improved forecasting models and early warning systems for better disaster preparedness.
**Action Required:** Integrate IMD's data and warnings into disaster management plans and response strategies.
**Stakeholder: India Meteorological Department (IMD)**
**Impact:** Responsible for implementation and maintenance of new forecasting models and dissemination of information.
**Action Required:** Continue to enhance forecasting accuracy, expand alert dissemination channels, and maintain robust infrastructure.
**Stakeholder: Geological Survey of India (GSI)**
**Impact:** Involved in issuing regional landslide forecasts/early warnings based on rainfall thresholds.
**Action Required:** Maintain and refine the GSI's landslide forecast model based on historical rainfall and landslide occurrence data, in conjunction with daily rainfall forecast data.
Key Entities Referenced
India Meteorological Department (IMD): The primary agency responsible for weather forecasting, including heavy rains and landslides, in India.
Ministry of Earth Sciences: The ministry under which the India Meteorological Department (IMD) functions.
Mission Mausam: A major initiative by the Government of India to improve weather forecasting capabilities.
Geological Survey of India (GSI): Responsible for issuing regional landslide forecasts/early warnings based on rainfall thresholds.
Bharat Forecast System (BharatFS): An advanced weather forecasting model developed under the Mission Mausam.
GOVERNMENT OF INDIA
MINISTRY OF EARTH SCIENCES
LOK SABHA
UNSTARRED QUESTION NO. 2953
TO BE ANSWERED ON WEDNESDAY, 17TH DECEMBER, 2025
FORECASTING OF HEAVY RAINS AND LANDSLIDES
2953. SHRI SHAFI PARAMBIL:
Will the Minister of EARTH SCIENCES be pleased to state:
(a) the efficiency of the current forecasting models used by the India Meteorological
Department (IMD) in forecasting of heavy rains and landslides;
(b) the reasons for the failure of the current forecasting models in identifying the chances
of heavy rains and landslides;
(c) whether the Government has invested in the research to invent new forecasting models;
and
(d) if so, the details thereof and if not, the reasons therefor?
ANSWER
THE MINISTER OF STATE (INDEPENDENT CHARGE) FOR
MINISTRY OF SCIENCE AND TECHNOLOGY
AND EARTH SCIENCES
(DR. JITENDRA SINGH)
(a)-(b) The current forecasting models used by the India Meteorological Department (IMD) are
highly accurate. In 2024, the skill score for 24-hour (one-day) advance detection of
heavy rainfall over meteorological subdivisions stands at 85%. At present, the accuracy
of IMD's heavy rainfall forecasts, measured as the percentage of correct warnings, is
85%, 73%, 67%, 63% and 58% for lead times ranging from one to five days,
respectively. Overall, forecast accuracy for heavy rainfall events across the country
improved by about 40% in 2023–2024 compared to 2014.
The Geological Survey of India (GSI), under the Ministry of Mines, has been mandated
to issue regional landslide forecasts/early warnings based on rainfall thresholds.
Currently, GSI issues operational/experimental daily regional landslide forecast
bulletins to 21 districts in 08 (eight) States during the monsoon period. GSI's landslide
forecast model is primarily based on rainfall thresholds derived from historical rainfall
and landslide occurrence data, in conjunction with daily rainfall forecast data received
from institutions under the Ministry of Earth Sciences. Regarding the efficiency of this
current forecast model, the evaluation shows a hit rate of more than 80% across the
forecasting zones of operational districts, viz, Darjeeling, Kalimpong, Nilgiris and
Rudraprayag.
Improving the accuracy of weather forecasts requires enhanced state-of-the-art
observational networks, skilled human resources to undertake research and development
for the development of numerical weather prediction models, and robust infrastructure,
such as high-performance computing systems to run these models at the required high
resolution to predict weather patterns caused by climate change. The Ministry is in
continuous endeavour of augmenting the observational and R&D infrastructure towards
achieving better accuracy in weather forecasting.(c)-(d) The major new initiative undertaken by the Government is the implementation of the
Mission Mausam. A couple of Doppler Weather Radars (DWRs) have already been
installed under the mission. Currently, 47 radars are in operation across India, with 87%
of the country's total area under radar coverage. Under the Mission Mausam, the Bharat
Forecast System (BharatFS), an advanced weather forecasting model, has been
developed and is operational at a high spatial resolution of 6-km. It also has the
capability to provide predictions of rainfall events up to 10 days, covering the short and
medium-range forecasts. Due to its higher resolution and improved dynamics, it
generates weather forecasts at the panchayat or cluster of panchayats level. Further, a
major achievement is the introduction of the Mithuna Forecast System (Mithuna-FS).
This new-generation global coupled model integrates the atmosphere, ocean, land
surface, and sea ice components with state-of-the-art physics and an upgraded data
assimilation framework. Currently, this forecasting system operates at 12-km resolution,
marking a significant advancement in India's medium-range localized weather
forecasting capability. The Mithuna-FS suite also includes –
A 4-km high-resolution regional model for accurate simulation of monsoon
dynamics, cyclones, and mesoscale extreme events over the Indian subcontinent;
A 330-m hyper-resolution urban model for fog, visibility, and air-quality
forecasting over the Delhi region.
IMD consistently issues timely alerts and forecasts to the public and concerned
stakeholders. Various steps have been taken to ensure effective dissemination of
warnings to vulnerable populations. IMD's weather information, including alerts and
warnings to the public, is provided through various platforms:
Mass Media: Radio/TV, Newspaper network (AM, FM, Community Radio,
Private TV), Prasar Bharati, and private broadcasters.
Weekly & Daily Weather Video.
Internet (e-mail), FTP
Public Website (mausam.imd.gov.in)
IMD Apps: Mausam/Meghdoot/Damini/Rain Alarm/Umang.
Social Media: Facebook, X, Instagram, BLOG
i. X: https://twitter.com/Indiametdept
ii. Facebook: https://www.facebook.com/India.Meteorological.Department/
iii. Blog: https://imdweather1875.wordpress.com/
iv. Instagram: https://www.instagram.com/mausam_nwfc
v. YouTube:
https://www.youtube.com/channel/UC_qxTReoq07UVARm87CuyQw
IMD has launched seven of its services (Current Weather, Nowcast, City Forecast,
Rainfall Information, Tourism Forecast, Warnings, and Cyclone) with the 'UMANG'
Mobile App for use by the public. Moreover, IMD developed a mobile App, 'MAUSAM'
for weather forecasting, 'Meghdoot' for Agromet advisory dissemination, and 'Damini'
for lightning alerts. The Common Alert Protocol (CAP), developed by the NDMA, is
also being implemented to disseminate warnings by the IMD.IMD currently is equipped with a Decision Support System (DSS) based real-time multi-
hazard impact based early warning system (EWS), which integrates all types of real-
time and historical data, numerical weather prediction products, etc., to effectively
monitor, detect and provide timely forecasts and impact-based warnings with suggested
actions up to districts and city/station levels against all types of extreme weather events
such as heavy rainfall events, droughts etc. IMD has Meteorological Centres (MCs) in
each State and also special centers like Cyclone Warning Centers available for each
impacted State, which provide services during cyclones and heavy rainfall seasons
round the clock, respectively. As a result of these new initiatives, the overall skill of
forecasting these severe weather events has been improved by 30-40% over the last 10
years.
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