ML Insights into Precipitation: Implicitly Learning Cloud Organization for Improved Predictions
0In climate modeling, achieving precise prediction of precipitation intensity remains a persistent challenge. While global models yield indispensable data, many consistently exhibit shortcomings in capturing the complexities of precipitation extremes. One plausible explanation lies in the omitted details of subgrid-scale cloud organization, which significantly influences both precipitation intensity and its stochastic behavior. Objectively modeling these patterns has been a challenging task, leaving gaps in our representation of subgrid-scale processes and potential precipitation. Our recent approach, anchored in machine learning methodologies, enables the implicit learning and integration of this subgrid organization from high-resolution precipitable water fields. Notably, we implicitly learn this information using advanced nonlinear dimensionality reduction techniques. The inclusion of the learnt subgrid scale structure significantly improves precipitation prediction. Furthermore, our research highlights the crucial role of memory processes, influenced by subgrid-scale structures, emphasizing their significance in precipitation variability and intensity. \n\nSpeakers:\nSara Shamekh\nPostdoctoral researcher, Gentine Lab\nColumbia University\n\nModerators:\nDuncan Watson-Parris\nAssistant Professor\nUniversity of California San Diego\n\nPhilip Stier\nProfessor of Atmospheric Physics\nUniversity of Oxford\n\nJoin the Neural Network!\nhttps://aiforgood.itu.int/neural-network/\nThe AI for Good networking community platform powered by AI. \nDesigned to help users build connections with innovators and experts, link innovative ideas with social impact opportunities, and bring the community together to advance the SDGs using AI.\n\n Watch the latest #AIforGood videos!\n\n\n Stay updated and join our weekly AI for Good newsletter:\nhttp://eepurl.com/gI2kJ5\n\nCheck out the latest AI for Good news:\nhttps://aiforgood.itu.int/newsroom/\n\nExplore the AI for Good blog:\nhttps://aiforgood.itu.int/ai-for-good-blog/\n\n Connect on our social media:\nWebsite: https://aiforgood.itu.int/\nTwitter: https://twitter.com/AIforGood\nLinkedIn Page: https://www.linkedin.com/company/26511907 \nLinkedIn Group: https://www.linkedin.com/groups/8567748 \nInstagram: https://www.instagram.com/aiforgood \nFacebook: https://www.facebook.com/AIforGood\n\nWhat is AI for Good?\nWe have less than 10 years to solve the UN SDGs and AI holds great promise to advance many of the sustainable development goals and targets.\nMore than a Summit, more than a movement, AI for Good is presented as a year round digital platform where AI innovators and problem owners learn, build and connect to help identify practical AI solutions to advance the United Nations Sustainable Development Goals.\nAI for Good is organized by ITU in partnership with 40 UN Sister Agencies and co-convened with Switzerland.\n\nDisclaimer:\nThe views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.