{"id":12690,"date":"2025-07-21T09:26:38","date_gmt":"2025-07-21T14:26:38","guid":{"rendered":"https:\/\/www.wisconsin.edu\/all-in-wisconsin-new\/?post_type=campus_story&p=12690"},"modified":"2025-07-21T09:26:38","modified_gmt":"2025-07-21T14:26:38","slug":"can-extreme-weather-be-predicted-uwl-researcher-uses-artificial-intelligence-to-help-protect-vulnerable-communities-from-the-worlds-most-dangerous-storms","status":"publish","type":"campus_story","link":"https:\/\/www.wisconsin.edu\/all-in-wisconsin\/story\/can-extreme-weather-be-predicted-uwl-researcher-uses-artificial-intelligence-to-help-protect-vulnerable-communities-from-the-worlds-most-dangerous-storms\/","title":{"rendered":"Can extreme weather be predicted? UWL researcher uses artificial intelligence to help protect vulnerable communities from the world\u2019s most dangerous storms"},"content":{"rendered":"
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\"Photo<\/a>
Rupsa Bhowmick uses artificial intelligence\u2014specifically machine learning techniques such as decision trees, random forests, and XGBoost with explainable AI (XAI) approaches\u2014to improve classification and prediction of rapidly intensifying cyclones. Her models analyze environmental factors such as ocean temperature, wind patterns, and humidity to improve early warning systems.<\/figcaption><\/figure>\n

When extreme weather strikes, it can change lives in an instant. That\u2019s why Rupsa Bhowmick, assistant professor of\u00a0Geography and Environmental Science at UW-La Crosse<\/a>, is using artificial intelligence (AI) to make forecasting faster, smarter, and more accurate \u2014 especially for communities most at risk.<\/p>\n

Bhowmick\u2019s research focuses on predicting tropical cyclones in the Southwest Pacific, a region where island nations like Fiji, Vanuatu, and New Caledonia are increasingly vulnerable to destructive storms fueled by warming oceans. She\u2019s also applying these methods to the U.S. Midwest, where extreme weather like floods, blizzards and tornadoes pose growing threats.<\/p>\n

Whether across the globe or close to home, Bhowmick\u2019s mission is clear: improve forecasts to save lives.<\/p>\n

\u201cExtreme weather events can turn our lives upside down in seconds,\u201d Bhowmick says. \u201cThrough research, we can improve forecasting, better communicate risk, and design infrastructure that\u2019s ready for what\u2019s coming.\u201d<\/p>\n

A personal drive: From India\u2019s Bay of Bengal to global forecasting<\/h3>\n

Bhowmick\u2019s passion for weather research began with personal experience. Growing up near the Bay of Bengal in India, she witnessed firsthand the devastating impact of cyclones and flooding.<\/p>\n

In her community, outcomes often depend on economic status. Families with means could recover quickly. Those living in low-income or slum districts faced far greater challenges\u2014including displacement and permanent loss of homes.<\/p>\n

\u201cEven as a child, I wondered why the impact of the same storm could vary so much from one region to the next,\u201d she recalls. \u201cThat\u2019s what led me to study geography and weather\u2014to find answers that could help people.\u201d<\/p>\n

As a graduate student, Bhowmick turned her attention to the Southwest Pacific, a cyclone-prone region where many communities lack the resources to recover after disasters. Her work focuses on developing machine learning methods to classify and predict cyclone intensity evolution\u2014especially before landfall\u2014by integrating supervised learning with geospatial diagnostics. This work resulted in a scalable and interpretable framework for probabilistic intensity forecasting, aimed at supporting climate-resilient hazard planning in vulnerable regions.<\/p>\n

She also studies extreme cyclone risk estimation, helping map where extreme cyclones – Category 4 and beyond \u2013 are likely to strike, carrying catastrophic impacts. Additionally, she studies how warmer ocean temperatures are making these extreme storms stronger and more frequent.<\/p>\n

AI for cyclone forecasting<\/h3>\n

A major breakthrough in Bhowmick\u2019s research is her use of machine learning\u2014a subset of AI\u2014to improve cyclone prediction, especially for rapidly intensifying (RI) cyclones.<\/p>\n

These storms strengthen dramatically in a short time, often catching communities off guard. Traditional weather models struggle to predict RI events because they involve complex interactions between multiple environmental factors.<\/p>\n

Bhowmick\u2019s machine learning models\u2014such as decision trees, random forests, and XGBoost\u2014analyze massive datasets of cyclone behavior alongside environmental conditions like ocean heat, humidity, and wind patterns. The goal: spot patterns and correctly identify RI events earlier, giving people more time to prepare.<\/p>\n

\u201cMachine learning can process many interacting variables at once, helping to avoid issues like multicollinearity while uncovering complex, non-linear patterns in the data\u201d she explains. \u201cThat\u2019s what makes it so powerful for predicting rapid intensification, which is still one of the biggest challenges in weather forecasting.\u201d<\/p>\n<\/div>\n

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Bringing research home: extreme weather in the Midwest<\/h3>\n

While her early work focused on tropical regions, Bhowmick is now applying her expertise to the Midwestern U.S., where communities face a different kind of storm: extra-tropical cyclones.<\/p>\n

These storms do not form over warm ocean waters like tropical cyclones, but rather from the interaction of contrasting air masses along the jet stream, particularly between October and March. They can bring intense winds, heavy snow, thunderstorms, and even dangerous waves on the Great Lakes. Some evolve into ‘bomb cyclones,’ rapidly intensifying within 24 hours and producing intense winds and blizzard conditions.<\/p>\n

Bhowmick is using machine learning to study these storms\u2019 behavior, including their intensity, speed, frequency, and how long-term oceanic-atmospheric trends may influence them.<\/p>\n

\u201cWhether it\u2019s a tropical or extra-tropical cyclone, the impact can be devastating if people aren\u2019t warned in time,\u201d she says. \u201cMy research aims to give communities the tools they need to stay safe.\u201d<\/p>\n

Teaching the next generation<\/h3>\n

In addition to her research, Bhowmick teaches physical geography and climatology courses at UWL and is actively working to involve students in her projects. She sees education as a critical part of the solution\u2014training the next generation to use data and technology to improve public safety.<\/p>\n

\u201cNow my training inspires me to translate this knowledge into action,\u201d she says. \u201cI want students to learn how to build these models, analyze extreme weather, and apply their skills to help communities prepare for the worst.\u201d<\/p>\n

So \u2014 can extreme weather be predicted?<\/h3>\n

The answer is yes, though it\u2019s not easy.<\/p>\n

Predicting extreme weather remains one of science\u2019s toughest challenges. But thanks to advances in high-resolution data, machine learning, and deep learning-based forecasting and prediction techniques, researchers like Bhowmick are making real progress.<\/p>\n

\u201cThis research is all about people,\u201d she says. \u201cWith better forecasts and more resilient infrastructure, we can reduce loss\u2014of property and, more importantly, of life.\u201d<\/p>\n<\/div>\n

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Written by UW-La Crosse<\/p>\n

Link to original story: https:\/\/www.uwlax.edu\/news\/posts\/can-extreme-weather-be-predicted\/<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

When extreme weather strikes, it can change lives in an instant. That\u2019s why Rupsa Bhowmick, assistant professor of\u00a0Geography and Environmental Science at UW-La Crosse, is using artificial intelligence (AI) to make forecasting faster, smarter, and more accurate \u2014 especially for communities most at risk. Bhowmick\u2019s research focuses on predicting tropical cyclones in the Southwest Pacific, […]<\/p>\n","protected":false},"author":15,"featured_media":12695,"comment_status":"closed","ping_status":"closed","template":"","institution":[104],"story_category":[],"class_list":["post-12690","campus_story","type-campus_story","status-publish","has-post-thumbnail","hentry","institution-uw-la-crosse"],"_links":{"self":[{"href":"https:\/\/www.wisconsin.edu\/all-in-wisconsin\/wp-json\/wp\/v2\/campus_story\/12690","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.wisconsin.edu\/all-in-wisconsin\/wp-json\/wp\/v2\/campus_story"}],"about":[{"href":"https:\/\/www.wisconsin.edu\/all-in-wisconsin\/wp-json\/wp\/v2\/types\/campus_story"}],"author":[{"embeddable":true,"href":"https:\/\/www.wisconsin.edu\/all-in-wisconsin\/wp-json\/wp\/v2\/users\/15"}],"replies":[{"embeddable":true,"href":"https:\/\/www.wisconsin.edu\/all-in-wisconsin\/wp-json\/wp\/v2\/comments?post=12690"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.wisconsin.edu\/all-in-wisconsin\/wp-json\/wp\/v2\/media\/12695"}],"wp:attachment":[{"href":"https:\/\/www.wisconsin.edu\/all-in-wisconsin\/wp-json\/wp\/v2\/media?parent=12690"}],"wp:term":[{"taxonomy":"institution","embeddable":true,"href":"https:\/\/www.wisconsin.edu\/all-in-wisconsin\/wp-json\/wp\/v2\/institution?post=12690"},{"taxonomy":"story_category","embeddable":true,"href":"https:\/\/www.wisconsin.edu\/all-in-wisconsin\/wp-json\/wp\/v2\/story_category?post=12690"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}