{"id":15759,"date":"2023-02-20T15:39:54","date_gmt":"2023-02-20T15:39:54","guid":{"rendered":"https:\/\/ambassadornews.org\/?p=15759"},"modified":"2023-02-20T15:39:58","modified_gmt":"2023-02-20T15:39:58","slug":"using-ai-to-unlock-the-mystery-of-el-ninos-impact-on-droughts-and-floods","status":"publish","type":"post","link":"https:\/\/ambassadornews.org\/en\/using-ai-to-unlock-the-mystery-of-el-ninos-impact-on-droughts-and-floods\/","title":{"rendered":"Using AI to unlock the mystery of El Nino’s impact on droughts and floods"},"content":{"rendered":"

For centuries, fishermen in Peru have noticed a connection between warmer than usual ocean waters\u2014what is now known as the El Ni\u00f1o phenomenon\u2014and droughts and floods on land<\/p>\n\n\n\n

But making accurate hydrologic predictions about El Ni\u00f1o’s impact on regional weather patterns\u2014and even understanding the complex El Ni\u00f1o phenomenon itself\u2014has stymied\u00a0climate scientists<\/a>\u00a0for decades<\/p>\n\n\n\n

It was believed making the connection required developing an incredibly complex physics model, one involving hard-to-measure flows between ocean and atmosphere and between atmosphere and land, says Auroop Ganguly, co-director of Northeastern’s Global Resilience Institute<\/p>\n\n\n\n

In a recent paper published in\u00a0Nature Communications<\/em>, Ganguly and three co-authors showed that using machine learning to crunch existing data can yield explainable insights about the impact of El Ni\u00f1o on the world’s great river systems\u2014the Ganges, Congo and Amazon\u2014and ultimately, regional weather patterns<\/p>\n\n\n\n

Treasure troves of data<\/h2>\n\n\n\n

Climate scientists have collected a vast amount of data, based on both observation and models, related to weather patterns, ocean temperatures from across the globe, flood levels, droughts and other climate phenomena, Ganguly says<\/p>\n\n\n\n

Up to now, the treasure trove of data has not been fully exploited, he says, adding that it has sometimes been stored in separate climate science silos<\/p>\n\n\n\n

But\u00a0new developments<\/a>\u00a0in machine or\u00a0deep learning<\/a>\u00a0make it possible to use servers with high computing power to harness the immense stores of data to develop predictive algorithms, Ganguly says<\/p>\n\n\n\n

“This explainable deep learning is new,” he says. “We can say that here is how sea surface temperature correlates to itself and influences\u00a0river flow<\/a>. And we learn that from the past. That was not in the realm of feasibility before”<\/p>\n\n\n\n

Deep learning can discover what is essentially a long-distance connection between\u00a0sea surface temperatures<\/a>\u00a0in the eastern Pacific, where El Ni\u00f1o or La Nina intermittently occurs, and what that implies for river flows across the world, says Ganguly. who is also the lead for Climate-AI at the Institute for Experiential AI<\/p>\n\n\n\n

Deep learning to tackle society’s big challenges<\/h2>\n\n\n\n

“The power of these approaches is in the ability to extract this information from the vast ocean\u2014pun intended!\u2014of data, rather than through oversimplified indices of this complex phenomenon,” he says<\/p>\n\n\n\n

Think of being able to assess what is happening by connecting\u00a0ocean temperatures<\/a>\u00a0to cloud development to precipitation affecting rivers, in different parts of the world, says co-author Yumin Liu of Amazon, who worked on the study as a Northeastern Ph.D. student<\/p>\n\n\n\n

“Now people realize they can mutually benefit by connecting the machine learning community and the climate community,” he says<\/p>\n\n\n\n

The forthcoming information would be able to help stakeholders better prepare for floods, droughts and other climate events that affect lives, homes, industry, transportation and food production<\/p>\n\n\n\n

“Developing and adapting machine learning methods to address societal grand challenges is an urgent need of our age,” says co-author Jennifer Dy, Northeastern electrical and computer engineering professor<\/p>\n\n\n\n

“This paper is an interesting demonstration of how data sciences, specifically deep learning and complex network constructs, can fill gaps in our predictive understanding about hydroclimates,” says co-author Kate Duffy, who worked on the study as a Ph.D. student in Northeastern’s Sustainability and Data Science Lab<\/p>\n\n\n\n

Developing predictive models<\/h2>\n\n\n\n

Temperature is relatively easy to measure, though massive amounts of data are needed to keep track of temperatures across the planet’s wide expanse of oceans<\/p>\n\n\n\n

Precipitation is more difficult to measure, because precipitation systems “can be somewhat random and evolve very rapidly,” according to NASA. The deep learning model allows scientists to leverage both types of information to develop a potentially predictive model, the scientists say<\/p>\n\n\n\n

Duffy says the paper also shows that improvements in earth systems models can also improve\u00a0software systems<\/a>, called couplers, that connect large model components such as ocean, atmospheric and land models, and facilitate better feedback and information flow. One example of such a coupler is the\u00a0Energy Exascale Earth System Model<\/a><\/p>\n\n\n\n

“What the paper suggests is that in the future it could be important to examine the possibility that gaps in the science of coupling can be addressed by developing what are called hybrid physics-AI approaches, where, for example, numerical models and partial differential equation based systems can be at least partly connected via machine learning,” Ganguly says<\/p>\n\n\n\n

Improving information flows<\/h2>\n\n\n\n

Dy, who is director of experiential AI postdoc education, says Northeastern’s Institute for Experiential AI plans to work on developing “generalizable and trustworthy solutions” combining global climate models with customized machine learning<\/p>\n\n\n\n

Being able to predict information about river flows from sea surface temperature maps may appear to be a niche solution, says Ganguly, a Northeastern College of Engineering distinguished professor<\/p>\n\n\n\n

“However, it allows incredible opportunities to open up,” he says<\/p>\n\n\n\n

The research shows how data-driven methods can enable improved climate-informed water resources projections, says Duffy, who recently stepped down as a NASA scientist to launch her own startup in AI-based satellite remote sensing with a NASA SBIR grant<\/p>\n\n\n\n

The intriguing possibility, according to Ganguly and Dy, is that this opens up the development of hybrid-AI systems for more effective coupling of model components within earth systems and global climate models<\/p>\n\n\n\n

Provided by\u00a0Northeastern University<\/a><\/p>","protected":false},"excerpt":{"rendered":"

For centuries, fishermen in Peru have noticed a connection between warmer than usual ocean waters\u2014what is now known as the El Ni\u00f1o phenomenon\u2014and droughts and floods on land But making accurate hydrologic predictions about El Ni\u00f1o’s impact on regional weather patterns\u2014and even understanding the complex El Ni\u00f1o phenomenon itself\u2014has stymied\u00a0climate scientists\u00a0for decades It was believed […]<\/p>\n","protected":false},"author":9,"featured_media":15760,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"jnews-multi-image_gallery":[],"jnews_single_post":{"subtitle":"","format":"standard","video":"","gallery":"","source_name":"","source_url":"","via_name":"","via_url":"","override_template":"0","override":[{"template":"1","single_blog_custom":"","parallax":"1","fullscreen":"1","layout":"right-sidebar","sidebar":"default-sidebar","second_sidebar":"default-sidebar","sticky_sidebar":"1","share_position":"topbottom","share_float_style":"share-monocrhome","show_share_counter":"1","show_view_counter":"1","show_featured":"1","show_post_meta":"1","show_post_author":"1","show_post_author_image":"1","show_post_date":"1","post_date_format":"default","post_date_format_custom":"Y\/m\/d","show_post_category":"1","show_post_reading_time":"0","post_reading_time_wpm":"300","show_zoom_button":"0","zoom_button_out_step":"2","zoom_button_in_step":"3","show_post_tag":"1","show_prev_next_post":"1","show_popup_post":"1","number_popup_post":"1","show_author_box":"1","show_post_related":"0","show_inline_post_related":"0"}],"override_image_size":"0","image_override":[{"single_post_thumbnail_size":"crop-500","single_post_gallery_size":"crop-500"}],"trending_post":"0","trending_post_position":"meta","trending_post_label":"Trending","sponsored_post":"0","sponsored_post_label":"Sponsored 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