{"id":26050,"date":"2026-10-17T00:04:51","date_gmt":"2026-10-16T21:04:51","guid":{"rendered":"https:\/\/trialoog.taltech.ee\/?p=26050"},"modified":"2026-10-19T13:36:58","modified_gmt":"2026-10-19T10:36:58","slug":"researchers-help-detect-dangerous-rises-in-sea-level-earlier","status":"publish","type":"post","link":"https:\/\/trialoog.taltech.ee\/en\/researchers-help-detect-dangerous-rises-in-sea-level-earlier\/","title":{"rendered":"Researchers help detect dangerous rises in sea level earlier"},"content":{"rendered":"","protected":false},"excerpt":{"rendered":"

When a severe storm drives up coastal water levels, every hour counts: the earlier the danger is detected, the more time ports and shipping operators have to prepare or respond. As part of Europe\u2019s Destination Earth initiative, TalTech\u2019s Department of Marine Systems was tasked with developing a solution to identify such rises early, assess their possible extent and, where necessary, produce a much more detailed forecast for the area.<\/p>\n","protected":false},"author":8,"featured_media":25859,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[251],"tags":[391,890,889,641],"class_list":["post-26050","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-science","tag-artificial-intelligence","tag-climate","tag-forecasting","tag-marine-systems"],"acf":{"postbuilder":[{"acf_fc_layout":"text","type":"text","text":"A sudden, short-lived rise in sea level caused by strong winds is known as a storm surge. Researchers at TalTech\u2019s Department of Marine Systems<\/a>, working with the Slovenian meteorological service ARSO<\/a>, developed a deep-learning forecasting system that helps assess possible changes in water level and the confidence of the forecast.\r\n\r\nThe work formed part of the On-Demand Extremes Digital Twin project<\/a> within Europe\u2019s Destination Earth initiative. The project is developing a system that can run very-high-resolution numerical weather models for selected areas when weather hazards arise, using them to produce more detailed impact and marine forecasts. Its aim was to connect the detection of extreme weather, detailed forecasting and assessment of potential impacts into a single workflow.\r\n\r\nAccording to project coordinator Theo Schoebel at France\u2019s national meteorological service, M\u00e9t\u00e9o-France<\/a>, TalTech was invited because of its experience in marine forecasting and storm surge modelling. \u201cTalTech had two main development roles. First, the team tested how high-resolution weather forecasts could improve predictions of sea levels and storm surges. Secondly, TalTech applied a storm surge detection and forecasting model within the project,\u201d Schoebel explained.\r\n

Computing power where the danger arises<\/strong><\/h4>\r\nModern global weather forecasts cover the entire planet and therefore cannot describe every island or coastal inlet in equal detail. Rivo Uiboupin<\/a>, Director of TalTech\u2019s Department of Marine Systems, says large-scale weather forecasts have limited detail, describing conditions at a resolution of around nine kilometres. Along coasts and around islands, that is insufficient.\r\n\r\nWhen danger arises, Destination Earth allows forecasts to focus on a smaller area and describe an extreme weather event there in much greater detail. Islands, coastlines and terrain can then be represented more accurately. In Estonia, this matters around small islands, among other places, where local conditions can influence wind, rainfall and thunderstorms.\r\n\r\nContinuously calculating ultra-high-resolution forecasts for all of Europe would be impractical. On-demand modelling therefore directs additional computing power towards areas where a potential hazard has been identified. \u201cIf a potential extreme event is detected in an area, such as very high or low water levels, a much more detailed meteorological model can be run for that region,\u201d Uiboupin explained.\r\n\r\nHigh-resolution models are not limited to predicting sea levels. They can also improve forecasts of heavy showers and associated flooding. \u201cFor example, the high-resolution model developed within the European weather forecasting project DEODE refined rainfall forecasts several times this summer and also indicated a flood risk during the flooding in P\u00e4rnu in early September,\u201d Uiboupin said.\r\n

\u201cFor example, the high-resolution model developed within the European weather forecasting project DEODE refined rainfall forecasts several times this summer and also indicated a flood risk during the flooding in P\u00e4rnu in early September.\u201d<\/p><\/blockquote>","image":null,"align":""},{"acf_fc_layout":"image","image":25855},{"acf_fc_layout":"text","type":"text","text":"

AI provides a rapid initial assessment of flood risk<\/strong><\/h4>\r\nMarine forecasts currently rely mainly on physical models, which calculate currents, temperature and salinity as well as water levels. They provide extensive information, but require substantial computing power for each forecast.\r\n\r\nThe deep-learning model used by TalTech was trained on historical water-level measurements from coastal stations and weather forecasts to predict water-level changes over six days. Once trained, it can produce new forecasts at much lower computational cost.\r\n\r\nAI does not replace a physical ocean model. One of its roles is to provide a rapid initial assessment: detecting potential danger and helping determine where to run a far more detailed and computationally intensive model. \u201cA rapid AI-based forecast helps identify a possible storm surge early, assess its likelihood and activate a more detailed forecasting system where necessary,\u201d Uiboupin explained.\r\n\r\nBy the end of the project\u2019s second phase, the solution was operating in the Adriatic Sea and at selected stations along Estonia\u2019s coast. Each morning, the extremes-detection workflow downloads new ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) and the latest coastal measurements from the Copernicus Marine Service\u2019s observation database. It then produces fifty possible water-level trajectories for the following six days. This allows not only the most likely outcome but also the risk of extreme water levels to be assessed.\r\n\r\nWeather forecasting is not the end of the chain. \u201cThe resulting data can also feed into impact models that assess risks such as flooding, wildfires, frost damage to crops, or risks affecting wind and solar power generation,\u201d explained Ilja Maljutenko<\/a>, Senior Researcher at the department. TalTech tested the forecasts in Estonia\u2019s coastal waters to predict storm surges and high and low water levels.\r\n

Estonian marine expertise becomes part of a European system<\/strong><\/h4>\r\nTalTech\u2019s contribution extended beyond technical development of storm surge forecasting. France\u2019s national meteorological service also highlighted the researchers\u2019 initiative and engagement with potential users. \u201cWe particularly valued our TalTech colleagues\u2019 proactive approach, both in developing technical solutions and in demonstrating what the data could offer at different stages of the project,\u201d Schoebel said.\r\n\r\nIn Schoebel\u2019s view, the collaboration also demonstrated Estonian researchers\u2019 ability to contribute to major European developments. \u201cWhen the application need is clearly defined, Estonian researchers can bring specialist knowledge, flexibility and a strong practical focus to a project,\u201d he said.\r\n\r\nThe collaboration also benefited TalTech. Researchers gained access to Destination Earth data, tools under development, new data-transfer solutions and other forecasts of extreme weather. This enables TalTech to test new European solutions early, connect them to its own marine forecasting models and bring proven technologies to Estonian users more quickly.\r\n

\u201cA rapid AI-based forecast helps identify a possible storm surge early, assess its likelihood and activate a more detailed forecasting system where necessary.\u201d<\/p><\/blockquote>","image":null,"align":""},{"acf_fc_layout":"image","image":25865},{"acf_fc_layout":"text","type":"text","text":"

Forecasts must inform decisions<\/strong><\/h4>\r\nThe project\u2019s second development phase ended in spring 2026, but work continues in a third phase. The focus is now on improving reliability and extending the solution tested along the Estonian and Slovenian coasts to other European coastal regions.\r\n\r\nOne next step is to introduce simulations of what-if scenarios. These could assess, for example, how high the sea might rise during a severe present-day storm surge if the projected increase in mean sea level by 2100 were added. Such information would help ports, local authorities, rescue services and critical infrastructure operators assess the situations they must prepare for.\r\n\r\nMaljutenko says marine forecasts also have considerable untapped potential to support everyday maritime decisions. Last winter, TalTech provided operational ice-drift forecasts. Feedback from ports and shipping operators indicated that these could help plan shipping routes, icebreaking and other marine operations. Even within maritime sectors, he noted, it is not yet widely known that water levels, currents, waves and ice movements can already be predicted fairly accurately several days ahead.\r\n\r\nThe obstacle is therefore not always a lack of data. High-quality regional forecasts often exist, but potential users do not know about them, or the information is not presented in a suitable form. \u201cDeveloping an accurate model alone is therefore not enough. Model forecasts must be translated into decision-relevant information for a specific sector,\u201d Maljutenko said.\r\n\r\nA ship\u2019s master may need the direction and speed of ice movement, while a port may need a forecast of critical water levels. High-resolution weather forecasts are also useful on land, for example by helping electricity network operators assess the likelihood of strong winds and thunderstorms.\r\n\r\nUiboupin sees further untapped opportunities for cooperation between businesses, public authorities and researchers. \u201cBusinesses and organisations should be more willing to approach researchers with specific problems and ask whether existing marine, weather or climate data could be used to create the forecast or risk indicator they need.\u201d\r\n\r\nThe department\u2019s expertise extends beyond running forecasting models, Uiboupin says. Researchers can combine observations, forecasts and AI to develop a specific service. In his view, this final step \u2014 from high-quality scientific data to an everyday decision-making tool \u2014 remains underused.\r\n

\u201cBusinesses and organisations should be more willing to approach researchers with specific problems and ask whether existing marine, weather or climate data could be used to create the forecast or risk indicator they need.\u201d<\/p><\/blockquote>","image":null,"align":""}],"related_authors":[{"author":7990,"position":"Editor of Trialoog"}]},"yoast_head":"\nResearchers help detect dangerous rises in sea level earlier - Trialoog<\/title>\n<meta name=\"description\" content=\"When a severe storm drives up coastal water levels, every hour counts: the earlier the danger is detected, the more time ports and shipping operators have to prepare or respond. 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