Researchers at IIT Bombay develop improved model of predicting monsoon

Rain predictions in India is far from accurate because the meteorological models used at present reportedly ignores the conditions emanating from the sprawling 8,60,000 sq km Ganga river basin.
Image used for representational purpose only. (File photo| PTI)
Image used for representational purpose only. (File photo| PTI)

NEW DELHI: Researchers at IIT-Bombay along with a collaborator from University of Maryland, US have developed what is being touted as a “more accurate model to predict monsoon in India”. The new method uses improved representation of land processes, along with mountainous Himalayan topography.

Those in the know say that one of the main reasons why rain predictions in India is far from accurate because the meteorological models used at present ignores the conditions emanating from the sprawling 8,60,000 sq km Ganga river basin. 

“Every year, the June-September forecasts simulated by the operational model of the India Meteorological Department seem to predict less rain will fall than actually does,” said Subimal Ghosh, one of the researchers.  To overcome this major shortcoming, decided to use their model to zoom in closer to earth’s surface. 

“The standard models for predicting Indian monsoons don’t take into account local topographical details such as the western Himalaya. These models often miss complex interactions between the land and atmosphere, such as how moisture evaporates from the land, then falls back down as precipitation,” said Ghosh.

The team corrected this by combining a regional climate model called the weather research and forecasting model with two land-surface models that can simulate interactions between the atmosphere and north central India’s agricultural land, along with Himalayan mountainous topography.“The operational monsoon prediction model for India, Climate Forecast System version 2, has significant dry bias in precipitation over the Ganga basin, and this restricts the use of model output for hydrologic prediction,” the finding summary of the study, published in an international weather science journal, said. 

“We attribute such bias to the lack of representation of land surface processes and characteristics in the model. We show that an improved representation of land characteristics in a regional coupled atmospheric land model improves not only the land atmosphere interactions but also the moisture contributions from distant oceanic sources,” the researchers further added.This finally results into improved simulations of monsoon.

To verify their model’s accuracy, the researchers checked it against real-world weather data from 1981 to 2015.Inaccurate monsoon prediction in the country has long been a butt of joke in India where majority of the population relies heavily on rains for drinking water, agriculture and raising livestock. 

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