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Home India Ministry of Earth Sciences Notifications PARLIAMENT QUESTION: STRENGTHENING LONG RANGE FORE... (Official PDF)
Date: 13th August 2026 Category: Press Release Jurisdiction: India, Central Government

PARLIAMENT QUESTION: STRENGTHENING LONG RANGE FORECASTING CAPABILITIES

Issued by Ministry of Earth Sciences

Read or download the official PDF of this gazette notification issued by the Ministry of Earth Sciences on 13th August 2026. Classified under Press Release.

Executive Summary & Key Takeaways

Executive Summary The India Meteorological Department (IMD) has upgraded its Long Range Forecast (LRF) system by adopting a Multi-Model Ensemble (MME) approach, significantly reducing forecast error from 7.8% to 2.2%. To address the "Spring Predictability Barrier," the government has implemented a sequential two-stage forecasting strategy for the Southwest Monsoon starting annually in April. Key initiatives include the Mission Mausam Program and the expansion of observation networks to improve extreme weather predictions across all States and Union Territories.

Key Points / Main Content

Forecasting Advancements and Accuracy

  • Adoption of MME: The IMD now utilizes an advanced Multi-Model Ensemble forecasting approach based on coupled dynamical climate models to reduce uncertainties and improve seasonal forecast reliability.
  • Error Reduction: The average absolute error in forecasts decreased from 7.8% of the Long Period Average (LPA) during 2016–2020 to 2.2% during 2021–2025.
  • Climate Driver Representation: The MME system provides better consistency in representing major climate drivers, including the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD).

Monsoon Forecasting Strategy

  • Two-Stage Strategy: To mitigate the "Spring Predictability Barrier" (SPB), a first-stage forecast is issued in April, followed by an update in May.
  • Sequential Updates: Monthly forecasts are issued for June through September, with a specific update for the second half of the monsoon season provided in late July.
  • Scientific Monitoring: Continuous monitoring of oceanic and atmospheric parameters is supported by the Monsoon Mission Coupled Forecasting System (MMCFS) and international climate centers.

Infrastructure and Technological Measures

  • Observation Network: Strengthening of the national network through additional Doppler Weather Radars, Automatic Weather Stations, Rain Gauges, and wind profilers.
  • Satellite Observations: Expansion of data collection through indigenous meteorological satellites and improved data assimilation into numerical models.
  • Advanced Computing: Integration of high-performance computing systems, AI/ML-based tools, and improved model physics to increase spatial resolution.
  • Early Warning Systems: Development of multi-hazard early warning systems for extreme events such as heavy rainfall, heatwaves, cyclones, and lightning.
  • Modernization: Capacity enhancement under the Mission Mausam Program to modernize Earth system modeling.

Impact Analysis

India Meteorological Department (IMD) / Ministry of Earth Sciences Impact The agency has seen a substantial enhancement in the reliability and skill of seasonal prediction systems through operational refinement and modernized infrastructure. Action Required Must continue the continuous monitoring of atmospheric parameters and the systematic upgradation of numerical weather prediction models.

State and Central Government Agencies Impact These agencies receive improved, impact-based forecasting and multi-hazard warnings to better manage regional weather-related risks. Action Required Coordinate with the MoES to disseminate weather forecasts and warnings through multiple platforms, including APIs, mobile applications, and social media.

General Public and Residents of States/UTs Impact Benefit from more accurate and timely warnings regarding extreme weather events like thunderstorms, floods, and heatwaves, leading to better disaster preparedness. Action Required Monitor official communication channels (SMS, mobile apps, radio, television) for rainfall updates and hazard warnings issued by the government.

Key Entities Referenced

India Meteorological Department (IMD): The primary agency responsible for meteorological observations and weather forecasting, which has upgraded its Long Range Forecast (LRF) system using advanced dynamical climate models. Ministry of Earth Sciences (MoES): The nodal ministry overseeing meteorological initiatives, responsible for augmenting high-performance computing systems and implementing the Mission Mausam Program. Mission Mausam Program: A government initiative focused on capacity enhancement through the modernization of observation systems and advanced Earth system modeling. Monsoon Mission Coupled Forecasting System (MMCFS): A specialized forecasting system utilized to improve the accuracy and reliability of long-range monsoon forecasts and address the Spring Predictability Barrier. Dr. Jitendra Singh: The Minister of State (Independent Charge) for Earth Sciences who presented the updates on forecasting capabilities in the Rajya Sabha.
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Ministry of Earth Sciences PARLIAMENT QUESTION: STRENGTHENING LONG RANGE FORECASTING CAPABILITIES प्रव तथ: 13 AUG 2026 2:12PM by PIB Delhi The India Meteorological Department (IMD), under the Ministry of Earth Sciences (MoES), has progressively upgraded its Long Range Forecast (LRF) system by adopting an advanced Multi-Model Ensemble (MME) forecasting approach based on coupled dynamical climate models. The MME system combines forecasts from multiple climate models, thereby reducing uncertainties associated with individual models and improving the reliability and skill of seasonal forecasts. The adoption of the MME forecasting system has led to a significant improvement in the reliability of seasonal monsoon forecasts. During the period 2021–2025, the average absolute error of the first-stage forecast was 3.1% of the Long Period Average (LPA), while the average absolute error of the second-stage forecast further reduced to 2.2% of the LPA. In comparison, the average absolute error during 2016–2020 was 7.8% of the LPA. Thus, the average absolute error has reduced from 7.8% to 2.2% of the LPA, indicating a substantial enhancement in the reliability and skill of the seasonal prediction system following the adoption and operational refinement of the MME forecasting system. The MME system has also enhanced the consistency of forecasts by improving the representation of large-scale climate drivers such as the El Nino–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), leading to more reliable seasonal monsoon predictions. The Spring Predictability Barrier (SPB) is a well-recognized scientific challenge in seasonal climate prediction, particularly in forecasting the evolution of the ENSO, which significantly influences the Indian summer monsoon. IMD addresses this challenge through continuous monitoring of oceanic and atmospheric parameters and by utilizing forecasts from the Monsoon Mission Coupled Forecasting System (MMCFS) and other leading international climate centers. These inputs are considered to improve the accuracy and reliability of long-range monsoon forecasts. To effectively address forecast uncertainties associated with the SPB, IMD follows a two-stage forecasting strategy for the Southwest Monsoon Season (June–September). The first stage forecast is issued in April, followed by an updated second stage forecast in May. Thereafter, monthly forecasts are issued for June, July, August, and September, along with updates of the seasonal rainfall forecast. In addition, an updated forecast for the second half of the monsoon season (August–September) is issued in late July, incorporating the latest observed oceanic and atmospheric conditions and model guidance. This sequential forecast strategy enables IMD to progressively improve forecast accuracy as the monsoon season approaches and evolves. The Government has taken several measures to further improve long-range monsoon forecasting and prediction of extreme weather events in the country, including hilly and coastal regions. These include:Adoption of advanced Multi-Model Ensemble and coupled dynamical climate models for operational long-range forecasting. Continuous upgradation of numerical weather prediction models through improved model physics, higher spatial resolution, advanced data assimilation techniques supported by enhanced computational capabilities, i.e., augmentation of new high-performance computing systems within MoES, and artificial intelligence/machine learning-based forecasting tools. Strengthening of the national meteorological observation network through the installation of additional Doppler Weather Radars, Automatic Weather Stations, Automatic Rain Gauges, upper-air observing systems, wind profilers, and other observing platforms. Expansion of satellite-based observations through indigenous meteorological satellites and the data assimilation of satellite, weather radar, and in situ observations into numerical models to improve weather forecast accuracy. Development of impact-based forecasting and multi-hazard early warning systems for extreme weather events, including heavy rainfall, thunderstorms, lightning, heatwaves, coldwaves, cyclones, and dense fog. Dissemination of weather forecasts and warnings through multiple communication platforms, including mobile applications, APIs, web portals, SMS, television, radio, and social media, in coordination with Central and State Government agencies. Capacity enhancement under the Mission Mausam Program through modernization of observation systems and advanced Earth system modeling. The above measures are being implemented across the country and benefit all States and Union Territories. This information was given by the Minister of State (Independent Charge) for Earth Sciences Dr. Jitendra Singh in a written reply in Rajya Sabha today. ***** NKR/JKP (रलीज़ आईडी: 2298810) आगंतुक पटल : 391 इस वज्ञ को इन भाषाओ ंम पढ़: Urdu , ही , Tamil

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