IISER Bhopal Researchers Develop Model to Predict Summer Temperatures

Indian Institute of Science Education and Research (IISER) Bhopal Scientists have developed a statistical model to predict Indian summer temperatures and extended climate anomalies in India, using weather data from the preceding winter.

Funded by the Department of Science and Technology (DST), Government of India, the model predicts the temperature of an Indian summer season (March-April-May or MAM) using weather data from the previous winter (Dec-Jan-Feb).

The model has also helped in understanding the relationships among various weather parameters and how they have dynamically co-evolved over the past 69 years.

The researchers have used parameters such as the sea surface temperature, sea level pressure, zonal wind, precipitation, and maximum, minimum, and average air temperatures from the previous winter, to predict the summer temperatures throughout India. The summer temperature has seen a significant increase, especially in North India, during recent decades, IISER Bhopal researchers said.

The researchers have also shown that the summer temperature predictability is better for South India than North, due to the former’s proximity to the ocean and the greater impact of the sea surface temperature on summer heat in the subcontinent.

The research was led by Dr Pankaj Kumar, Assistant Professor, Department of Earth and Environmental Sciences, IISER Bhopal. The model development and results of the prediction studies have been recently published in the International Journal of Climatology, in a paper co-authored by Dr Kumar and his research scholar Aditya Kumar Dubey.

Highlighting the need for this research, Dr Kumar said, “With climate change and global warming being increasingly recognized as a threat to the ecosystem, socio-economy and, perhaps, life itself, it is important to understand and be able to predict seasonal patterns for better preparedness.”

A multi-linear statistical technique called Canonical Correlation Analysis was used to predict summer temperatures and understand the relationships among the various weather parameters, said Dubey.

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