Season’s end: On the India Meteorological Department forecasts, rainfall deficit

Published 2026-10-05 · Updated 2026-10-05 · 3 min · 578 words

What does this development mean for UPSC preparation?

IMD's monsoon forecast underestimated the rainfall deficit, with actual rainfall at 87% of LPA against a 'below normal' prediction.

IMD's monsoon forecast underestimated the rainfall deficit, with actual rainfall at 87% of LPA against a 'below normal' prediction.

Geography (climatology), Agriculture, Disaster Management, and Science & Technology (weather forecasting).

Important for understanding monsoon variability, El Niño impact, and challenges in weather forecasting for policy planning.

IMD's conservative monsoon forecast masked severe regional deficits.

IMD predicted 'below normal' monsoon but actual rainfall was 87% of LPA, a 'deficient' category.

El Niño is the warming of central equatorial Pacific, generally suppressing Indian monsoon rainfall.

Useful for questions on monsoon forecasting, climate variability, and agricultural planning.

Long Period Average (LPA) is the average rainfall over a 50-year period, currently 880mm for all-India.
Western disturbances are extra-tropical storms bringing winter rain to northwest India, increasingly affecting monsoon.

IMD issues operational forecasts for monsoon using statistical and dynamical models.
Drought declaration by states follows norms like rainfall deficit and crop condition.

IMD's conservative bias may stem from risk aversion, but it undermines trust in forecasts.
Sub-regional forecast accuracy is poor, as seen in northeast and south peninsula errors.
Climate change is altering monsoon dynamics, making traditional models less reliable.
Need for improved dynamical models and higher resolution data for better predictions.

Delayed and deficient rainfall affected kharif sowing, though late recovery narrowed the gap.
Rabi season faces threat due to low soil moisture and reservoir levels from deficient monsoon.
Government's MSP hike for wheat and mustard aims to encourage diversification but may not offset losses.

Accurate early warning is crucial for drought preparedness and mitigation.
Underestimation of deficit can delay government response and relief measures.
State-level drought declarations highlight the need for timely and accurate data.

IMD's institutional credibility is at stake if forecasts consistently miss magnitude.
There is a need for transparency in forecast models and uncertainty communication.
Policy decisions, such as crop planning and water management, rely on accurate forecasts.
Investment in weather infrastructure and research is essential for better services.

IMD's conservative forecasting may be a deliberate choice to avoid panic, but it reduces the utility of warnings.
Climate change is increasing monsoon variability, demanding more adaptive forecasting systems.
Regional disparities in rainfall require decentralized drought management and tailored advisories.
Accurate monsoon forecasts are critical for food security and rural livelihoods.

Northeast India recorded its driest monsoon since 1901, with 26% rainfall deficit.
Karnataka declared drought in over 100 taluks, Maharashtra in 265 of 358 taluks.

IMD's forecast was within the 4-5% error margin, technically accurate.
Global models also predicted a strong El Niño, but magnitude was uncertain.
Late-season rains partially compensated for early deficits, reducing overall impact.

Enhance sub-regional forecast accuracy by investing in high-resolution models and data assimilation.
Communicate forecast uncertainty more effectively to enable risk-based decision making.
Strengthen drought early warning systems linking rainfall, soil moisture, and crop conditions.
Promote climate-resilient agriculture through crop diversification and water conservation.
Increase collaboration between IMD and state agricultural departments for localized advisories.

Primary/reference source: thehindu.com