This technique that predicts extreme rainfall can help India negotiate floods

Alok Mukherjee July 28, 2017

Story Highlights

  • Professor Subimal Ghosh and his team from IIT-B have come up with a technique that can forecast extreme rainfall events at a regional scale
  • In this model, the researchers have considered parameters like geo-potential height, relative humidity, air temperature, eastward wind field, and northward wind field at pressure levels of 1000hPa and 500hPa
  • Ghosh said that the model can definitely be employed to forecast extreme precipitation events in regions across India

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On July 26, 2005, Mumbai, the city that neither sleeps nor stops, was forced to a standstill due to incessant rain. The city was drowned in a deluge, and all one could hear were cries for help as more than a thousand people lost their lives. The Mumbai floods forced us to think about how we could prevent such tragedies in future.

For the past many years, professor Subimal Ghosh and his team of researchers from Indian Institute of Technology Bombay (IIT-B) have been working on forecasting models that can predict heavy downpours in the hope of saving lives. The result is a technique that can forecast extreme rainfall events at a regional scale.

Professor Subimal Ghosh and his team of researchers from IIT-Bombay have been working on forecasting models that can predict heavy downpours in the hope of saving lives. The result is a technique that can forecast extreme rainfall events at a regional scale

Ghosh and his PhD student Hiteshri Shastri, in collaboration with professor Subhankar Karmakar from the Centre of Environmental Science and Engineering, IIT-B, published their new model in the Journal of Geophysical Research: Atmospheres. This model, the researchers say, is highly accurate and takes into consideration regional factors that influence the intensity of rain.

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The researchers say that the rainfall forecast model is highly accurate and takes into consideration regional factors that influence the intensity of rain

“Spatio-temporal complexities of precipitation events breed uncertainties, which can effectively be tackled by quantifying the predictive assessments of extreme rainfall. The technique developed by us does this using the quantile regression method. Thus, it succeeds in overcoming the limitation of global models in forecasting extreme rainfall at a regional scale,” says Ghosh, talking about his newly proposed model.

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But what makes predicting extreme precipitation events so complex? It is their dependence on various atmospheric processes, which occurs at different scales, say the researchers. For instance, it is a difficult task to predict extreme events when atmospheric processes associated with monsoon interact with land processes associated with the urban canopy. In addition, trends of extreme rainfall events are not uniform due to the influence of regional processes such as urbanisation and land use change. Hence, it becomes necessary to include the most optimal set of predictor variables in the forecasting system to represent various dimensions of precipitation events, which are selected based on conditions such as data availability.

In this model, the researchers have considered parameters like geo-potential height, relative humidity, air temperature, eastward wind field, and northward wind field at pressure levels of 1000hPa and 500hPa

In this model, the researchers have considered parameters like geo-potential height, relative humidity, air temperature, eastward wind field, and northward wind field at pressure levels of 1000hPa and 500hPa. The model consists of two modules — the first module focuses on training and calibration of the regression model using observed/reanalysed data and the second module applies the calculated values to the synoptic scale forecasts.

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The Mumbai floods of 2005 forced us to think about how we could prevent such tragedies in future

The researchers have tested the proposed model with data on Mumbai’s weather conditions to predict extreme precipitation events and found that it overcame many limitations of global models in predicting precipitation over Mumbai. The hitherto used global models forecast precipitation events over Mumbai with a very low probability and high false alarm ratio. For comparison, the new model could forecast 17 extreme events out of 29, while a global model such as the Global Ensemble Forecast System could predict only six out of 29.

The researchers have tested the proposed model with data on Mumbai’s weather conditions to predict extreme precipitation events and found that it overcame many limitations of global models in predicting precipitation over Mumbai

When asked about the applicability of this model to other regions of the country, Ghosh said, “The model can definitely be employed to forecast extreme precipitation events in other regions of India.”

How about adding newer parameters to this model? “As far as the possibility of including new variables is concerned to upgrade the model, it can be done according to the requirement. But, for now, the best possible set of predictors have been considered based on scientific understanding,” he adds.

Over the years, we have increasingly realised that science and technology can be a wonderful tool to serve the human society. Man may never really be able to beat nature, but advances in computation and techniques to predict nature’s fury can go a long in finding such scientific solutions to serve the society. Ghosh says, “We are reviewing literature and working to extend our work in this direction.”

Also read: Solar-powered boat clinics in flood-ravaged Assam deliver essential healthcare

               
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