Improved prediction of Indian Monsoon onset three months in advance using machine learning

This is encouraging because the Indian monsoon could become less frequent due to global warming in future.For the past 40 years, the onset of the Indian Summer Monsoon was predicted three months in advance. This prediction has the highest accuracy up to today. This result suggests that machine learning-based seasonal forecasts may be extended to help mitigate the effects of an unpredictable monsoon system due to future global warming. The results were published in Environmental Research Letters by Dr. Takahito Mizutai and Dr. Niklas Borers of the Potsdam Institute of Climate Impact Research, Potsdam (Germany). This work is part of European TiPES, coordinated by The Niels Bohr Institute at University of Copenhagen in Denmark and PIK potsdam.The Indian summer monsoon's rains are essential for millions of people and their natural habitats. Global warming is changing the monsoon system. This will lead to more variation in precipitation patterns and monsoon duration and onset. For farmers and other people who depend on the Indian monsoon, seasonal forecasts may be a way to get ahead of the curve and reduce the impact of interannual variabilities.The improved 3-month preseasonal forecast is now available from PIK Potsdam (Germany) using machine learning. These predictions are based on data from 1948 and cover all climate changes over the last decade. This work is a promising foundation for future research to predict the onset and dynamics of the Indian summer monsoon over the next decade, given that global warming may have accelerated.Scientists used reconstructed data from the Indian Ocean and Indian subcontinent to predict when the monsoon would start. This accuracy is a significant improvement over previous attempts to forecast Indian monsoon onset within a three-month range using traditional weather prediction models."We can confidently predict when monsoons will arrive in the future, even though global climate change is accelerating over the next decade." Takahito Mitsui says that our method of predicting monsoons has worked well over the past 40 years, when there has been gradual global warming."Our study shows the potential of machine-learning methods in forecasting climate phenomena like the monsoon onset." Niklas Boers says that the ultimate goal of our study is to combine traditional weather prediction models and machine learning models like the one presented here. This will hopefully lead to more accurate forecasts."However, it is not possible to make accurate predictions in a world experiencing a higher level of global warming. Scientifically, the outlook for India's monsoon system is uncertain in light of a changing climate. It is possible that the current monsoon system will shift to an irregular form. It could also shift slowly as global warming affects the seasonal differences in temperatures across regional landmasses, and on sea surfaces."We will be in a position to examine this using climate model simulations under global heating scenarios. Takahito Mitsui says that then we can answer more confidently whether or not our method can predict a failure in the Indian Monsoon systems in advance.TiPES is an EU Horizon 2020 interdisciplinary climate project that focuses on tipping points within the Earth system. 18 institutions from different countries collaborate in the TiPES project. TiPES is coordinated by the Niels Bohr Institute, University of Copenhagen, Denmark, and the Potsdam Institute for Climate Impact Research (Germany).TiPES has been awarded funding through the European Horizon 2020 research-and-innovation program grant agreement number 8220970.###