IMD Unveils Block-Level Monsoon Forecast Model
Context:
Ahead of the upcoming monsoon season, the India Meteorological Department (IMD) has unveiled a pioneering forecast system capable of generating highly localized, "block-level" predictions regarding the monsoon's arrival.
Features of the New System:
Historically, monsoon predictions were limited to broader state or district-level estimations.
This lack of granularity often led to discrepancies where specific blocks or villages remained dry even after the official "arrival" of the monsoon in their district.
The new hyper-local system aims to rectify this, enabling farmers to time their crop sowing activities with unprecedented precision.
At its core, the system functions by "blending" the predictions of two separate forecasting models to sharpen accuracy.
Starting from the monsoon's onset in Kerala, the system leverages AI-based analysis, an extensive archive containing nearly a century of IMD meteorological data, and global weather models to issue probabilistic forecasts valid for four weeks.
Developed specifically at the request of the Ministry of Agriculture and Farmers' Welfare, the system currently covers 3,196 blocks across 15 States and one Union Territory.
These areas constitute India's "monsoon core zone," comprising largely rainfed regions that are highly sensitive to the dynamics of the southwest monsoon.
The system's accuracy will face a formidable real-world test this year, as both the IMD and global models are anticipating "below normal" rainfall due to a developing El Nino weather pattern.
The 'Mithuna' Model in UP:
In a related development, the IMD has also launched a specific, highly granular monsoon forecast model for Uttar Pradesh with a remarkable 1-km resolution (valid for 10 days).
This was achieved by taking an existing weather model named Mithuna—which typically operates at a 12.5-km resolution—and "downscaling" it.
This granular downscaling was made possible by the extensive coverage of automatic weather stations deployed throughout the State.