Machine learning for Earth System Science (ESS): A survey, status and future directions for South Asia
This is an incremental survey paper that organizes existing knowledge about ML applications in Earth System Science for researchers and practitioners in South Asia.
This survey examines how machine learning can address current problems in Earth System Science, focusing on South Asia and covering atmospheric, ocean, seismology, and biosphere components, with applications to statistical downscaling and forecasting.
This survey focuses on the current problems in Earth systems science where machine learning algorithms can be applied. It provides an overview of previous work, ongoing work at the Ministry of Earth Sciences, Gov. of India, and future applications of ML algorithms to some significant earth science problems. We provide a comparison of previous work with this survey, a mind map of multidimensional areas related to machine learning and a Gartner's hype cycle for machine learning in Earth system science (ESS). We mainly focus on the critical components in Earth Sciences, including atmospheric, Ocean, Seismology, and biosphere, and cover AI/ML applications to statistical downscaling and forecasting problems.