NYUAD Center Wins Grant from Indian Government to Study Monsoon
Cycle rickshaws and a passenger with a suitcase try to make headway through a central street in Varanasi, India despite the heavy monsoon rain and the increasingly risky rising water level as a result of a flash flood. (Daniel Bhim-Rao / iStock.com)

Weather prediction, even over a short period of time, is extremely difficult. There are so many variables in the atmosphere that it's impossible to say for sure what the weather will be like next year, next month, or even tomorrow. But that doesn’t mean that forecasters can’t try, and advancements in both data collection and computer modeling have dramatically improved prediction.

The premise of forecasting is that by knowing something about past and current weather, one can predict, with some accuracy, weather in the future. That said, "knowing that it rained a certain amount in one place at a time in the past isn't enough to predict how much and when it will rain in the future," said Dr. Ajaya Ravindran, senior scientist at NYUAD's Center for Prototype Climate Modeling (CPCM). This is why a huge amount of data about past weather and computers that can process these massive data sets are required to make forecasts.

Ravindran's center won a grant from the Indian Institute of Tropical Meteorology that supports the effort to improve weather forecasting. The initiative, called the Monsoon Mission, will use historical data about rainfall in India to generate predictions of the monsoon, the yearly wet season that is not just important for India, but also for a huge swath of land stretching from Afghanistan to the Philippines.

The project is led by Ravindran, Dimitris Ginnaakis, assistant professor at the Courant Institute at NYU, and Andrew Majda, professor at Courant and lead principal investigator of CPCM. The grant provides funding for two post-doctoral researchers to work exclusively for the project in Abu Dhabi and New York.

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Knowing that it rained a certain amount in one place at a time in the past isn't enough to predict how much and when it will rain in the future.

Dr. Ajaya Ravindran, Center for Prototype Climate Modeling

The agricultural industry and Indian economy depend on the monsoon, and irregularities in the seasonal rains can disrupt life for hundreds of millions of people. For example, a dry season could diminish the yield of certain crops, leading to an increase in price. But if the monsoon could be predicted more accurately, farmers and governments could prepare accordingly.

Dr. Ajaya Ravindran, senior scientist at the Center for Prototype Climate Modeling.

India has an extensive monitoring system of rain gauges that have been used for over a hundred years to gather information about rainfall. This historical data is a great source of information about past monsoons. But the trick is to make meaningful predictions about the future using information from the past.

Once data is gathered from the rain gauge system, the researchers will use a cutting-edge mathematical technique called Non-Linear Laplacian Spectral Analysis to analyze it.

"It's like collecting the memory of a time series," Ravindran said. (The time series is the data that has been collected from the network or rain gauges.) "The new technique is a way to extract the predictive capability of the time series as accurately as possible," he said.

The project aims to improve prediction accuracy on three different time scales: short (10 days or less); extended range (two weeks); and seasonal (about four months). CPCM scientists and their colleagues are collaborating with researchers from the Indian Institute of Science, Bangalore and the India Meteorology Department. Experts from the US, Canada, Japan, and Australia are also participating in this scientifically challenging effort.

By Matthew Corcoran, NYUAD Public Affairs