HomeNewsTrendsWhy extreme rainfall in Mumbai is getting harder to predict

Why extreme rainfall in Mumbai is getting harder to predict

As the coastal city surpasses its monthly average rainfall of July in just two weeks, here’s a look at why prediction models often miss the mark and the factors that influence.

July 21, 2024 / 10:04 IST
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Mumbai rains: Rainfall prediction in the tropics is inherently complex, and the dynamic nature of the monsoon only adds to the challenge. Mumbai's location on the Konkan coast, combined with the highly variable local topography of the Mumbai Metropolitan Region (MMR), further complicates predictions. (Photo credit: Debjyotiarr via Wikimedia Commons)
Mumbai rains: Rainfall prediction in the tropics is inherently complex, and the dynamic nature of the monsoon only adds to the challenge. Mumbai's location on the Konkan coast, combined with the highly variable local topography of the Mumbai Metropolitan Region (MMR), further complicates predictions. (Photo credit: Debjyotiarr via Wikimedia Commons)

Mumbai is on orange alert again following days of heavy rainfall, with the weather department predicting more heavy rain in some areas in the coming days. On July 20, the Andheri Subway had to be closed temporarily due to waterlogging.

Why it is getting harder to predict extreme rainfall in Mumbai

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Early Monday morning on July 8, heavy rainfall drenched Mumbai, causing widespread waterlogging. This deluge disrupted train services and led to flight cancellations, while numerous BEST buses were rerouted due to flooded streets. Later in the day, the Brihanmumbai Municipal Corporation (BMC) reported that the city had received over 300 mm of rainfall in various locations between 1 am and 7 am. By July 14, it recorded 862 mm of rainfall, surpassing its monthly average (855.7 mm) in just two weeks.

While some forecast models had predicted a wet spell, none had anticipated the amount and intensity of rain, particularly on July 8. As a result, the India Meteorological Department (IMD) faced criticism on social media, with citizens questioning the accuracy of their forecasts.