[Webinar Series] <\/strong>Contrails in the climate system – enhancing NWP through cloud observation and AI<\/span><\/b><\/h2>\n<\/div>The CONTRAILS project aims to provide tools to monitor the impact of contrails on climate. As a joint work of the German Weather Service DWD (DE), Thal\u00e8s Research & Technology (FR), Reuniwatt SAS (FR) and Laboratoire atmosph\u00e8res, milieux, observations spatiales (FR), the goal of the subproject at DWD<\/abbr> was to develop assimilation and prediction methods for contrail and cirrus observations within the Numerical Weather Prediction (NWP) systems, using the ICON<\/abbr> model and its ensemble-variational data assimilation.<\/p>\nThis webinar will present contrails observation using all-sky imagers by Reuniwatt, as well as AI tools that have been developed to detect contrails in camera and satellite images, enabling the identification of contrail clusters. These clusters can be used to evaluate the representation of ice-supersaturated regions in the NWP model. Our speakers are happy to present the remarkable progress the team has achieved in the identification, representation, and data assimilation of contrails and high cirrus clouds.<\/p>\n
In our webinar, you will learn more about the methos for AI-based parameterizations for subgrid-scale cloud properties in the NWP model developed by DWD in collaboration with the other CONTRAILS project parterns. These AI parameterizations have been trained using satellite observations, allowing for a more realistic representation of cloud distributions compared to traditional purely physical parameterizations.<\/p>\n
Based on these parameterizations, an all-sky data assimilation method has been implemented and successfully tested for incorporating visible satellite images into global numerical weather prediction. This enables a more realistic representation of current humidity and cloud distributions in the atmosphere, leading to improved forecasts for these parameters.<\/p>\n
Prof. Roland Potthast<\/strong> is the Head of Numerical Weather Prediction (NWP) forecasts provided to millions of users every day. He will introduce the project’s objectives, scientific advances and implications for prediction systems and applications.<\/p>\nDr. Stefanie Hollborn<\/span><\/strong> will provide her expertise on how artificial intelligence methods results are automatically fed into the observation pool for the analyses of the numerical weather forecast, where they provide a significantly improved formation probability of contrails and climate-relevant clouds.<\/span><\/p>\nSarah Vadillo-Quesada\u00a0<\/strong>will present the different technologies leveraged within the project to observe contrails, and support the data assimilation and prediction of contrails.<\/span><\/p>\nThe webinar will be chaired by Dr. Teodora Petrisor<\/strong>, who will lead the audience through the webinar, and forward your questions on the observation, modelling and prediction of contrails to the panelists.<\/p>\n<\/div>After this webinar, you will have a better understanding of:<\/h3>\n<\/div><\/div><\/div><\/div><\/div>- <\/i><\/span>\n
Ground-based all-sky camera observations<\/strong> in combination with new satellite-based cloud observations<\/span><\/p>\n<\/div><\/li>- <\/i><\/span>\n
Trustworthy AI methods and physical models <\/strong>to improve the monitoring and characterisation of contrails<\/span><\/p>\n<\/div><\/li>- <\/i><\/span>\n
Get a better understanding of the entire physical process<\/strong> underlying the formation of contrails<\/span><\/p>\n<\/div><\/li>- <\/i><\/span>\n
Learn about the results of CONTRAILS and augmenting NWP models <\/strong>accordingly<\/span><\/p>\n<\/div><\/li><\/ul><\/div><\/div><\/div><\/div>About the speakers:<\/h3>\n<\/div>Dr. Teodora Petrisor <\/strong>is a senior research engineer in AI at CortAIx Labs, Thales, leading the AI algorithm validation roadmap. She holds a PhD in Signal and Image Processing from Telecom Paris. For the past couple of years she has been focusing on trustworthy AI algorithms with applications to green operations in avionics and more specifically to contrail detection and prediction. She is currently leading the French consortium in the BPI\/DLR CONTRAILS project.<\/span><\/p>\nProf. Roland Potthast<\/strong>, is Director for Meteorological Modeling and Analysis at the German Weather Service (Deutscher Wetterdienst, DWD)<\/span>, EUMETNET AI Programme Coordinator, and Professor for Applied Mathematics at the University of Reading, UK.<\/p>\nDr. Stefanie Hollborn<\/span><\/strong> is a scientist at DWD, and leads the Department of Observation Modeling and Verification. She holds a PhD in Numerical Mathematics with a specialization in Inverse Problems from the University of Mainz. Her research focuses on developing and implementing data assimilation methods to enhance Numerical Weather Prediction. Recently, her work has increasingly concentrated on the application of artificial intelligence in weather forecasting and weather and climate services.<\/span><\/p>\nSarah Vadillo-Quesada <\/strong>graduated with a dual degree in energy engineering and business administration, before developing an extensive background in public affairs by integrating the French Ministry of Ecological Transition and the Ministry of Foreign Affairs, where she contributed to developing research partnerships between French and American Universities. She joined Reuniwatt\u2019s Paris office in 2021 to develop collaborations with universities and projects in the PV sector.<\/p>\n<\/div><\/div><\/div>![](\"https:\/\/reuniwatt.com\/en\/wp-content\/uploads\/sites\/3\/2025\/02\/tp2021_2_small_square1.jpg\")
<\/span><\/div>Teodora Petrisor<\/span><\/p>\nModerator
\nSenior Research Engineer AI <\/span>@Thales<\/span><\/p>\n\u00a0<\/span><\/p>\n\u00a0<\/span><\/p>\n<\/div><\/div><\/div>![](\"https:\/\/reuniwatt.com\/en\/wp-content\/uploads\/sites\/3\/2021\/01\/rp.jpg\" "\\"Reuniwatt")
<\/span><\/div>Prof. Roland Potthast<\/span><\/p>\nSpeaker
\nHead of NWP (Numerical Weather Prediction) <\/span>@DWD<\/span><\/p>\n\u00a0<\/span><\/p>\n\u00a0<\/span><\/p>\n<\/div><\/div><\/div>![](\"https:\/\/reuniwatt.com\/en\/wp-content\/uploads\/sites\/3\/2025\/02\/stefaniehollborn_sq.jpg\")
<\/span><\/div>Stefanie Hollborn, PhD<\/span><\/p>\nSpeaker
\nHead of Observation Modelling and Verification NWP @DWD<\/span><\/p>\n\u00a0<\/span><\/p>\n<\/div><\/div><\/div>![](\"https:\/\/reuniwatt.com\/en\/wp-content\/uploads\/sites\/3\/2022\/08\/SarahVadillo_sq.jpg\")
<\/span><\/div>Sarah Vadillo-Quesada<\/span><\/p>\nSpeaker
\nBusiness Developer <\/span>@Reuniwatt<\/span><\/p>\n\u00a0<\/span><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/h2>\nThis webinar will take place on March 20, 2025 starting 3pm CET.<\/h2>\n<\/div><\/div><\/div><\/div><\/div>
The CONTRAILS project aims to provide tools to monitor the impact of contrails on climate. As a joint work of the German Weather Service DWD (DE), Thal\u00e8s Research & Technology (FR), Reuniwatt SAS (FR) and Laboratoire atmosph\u00e8res, milieux, observations spatiales (FR), the goal of the subproject at DWD<\/abbr> was to develop assimilation and prediction methods for contrail and cirrus observations within the Numerical Weather Prediction (NWP) systems, using the ICON<\/abbr> model and its ensemble-variational data assimilation.<\/p>\n This webinar will present contrails observation using all-sky imagers by Reuniwatt, as well as AI tools that have been developed to detect contrails in camera and satellite images, enabling the identification of contrail clusters. These clusters can be used to evaluate the representation of ice-supersaturated regions in the NWP model. Our speakers are happy to present the remarkable progress the team has achieved in the identification, representation, and data assimilation of contrails and high cirrus clouds.<\/p>\n In our webinar, you will learn more about the methos for AI-based parameterizations for subgrid-scale cloud properties in the NWP model developed by DWD in collaboration with the other CONTRAILS project parterns. These AI parameterizations have been trained using satellite observations, allowing for a more realistic representation of cloud distributions compared to traditional purely physical parameterizations.<\/p>\n Based on these parameterizations, an all-sky data assimilation method has been implemented and successfully tested for incorporating visible satellite images into global numerical weather prediction. This enables a more realistic representation of current humidity and cloud distributions in the atmosphere, leading to improved forecasts for these parameters.<\/p>\n Prof. Roland Potthast<\/strong> is the Head of Numerical Weather Prediction (NWP) forecasts provided to millions of users every day. He will introduce the project’s objectives, scientific advances and implications for prediction systems and applications.<\/p>\n Dr. Stefanie Hollborn<\/span><\/strong> will provide her expertise on how artificial intelligence methods results are automatically fed into the observation pool for the analyses of the numerical weather forecast, where they provide a significantly improved formation probability of contrails and climate-relevant clouds.<\/span><\/p>\n Sarah Vadillo-Quesada\u00a0<\/strong>will present the different technologies leveraged within the project to observe contrails, and support the data assimilation and prediction of contrails.<\/span><\/p>\n The webinar will be chaired by Dr. Teodora Petrisor<\/strong>, who will lead the audience through the webinar, and forward your questions on the observation, modelling and prediction of contrails to the panelists.<\/p>\n<\/div> Ground-based all-sky camera observations<\/strong> in combination with new satellite-based cloud observations<\/span><\/p>\n<\/div><\/li> Trustworthy AI methods and physical models <\/strong>to improve the monitoring and characterisation of contrails<\/span><\/p>\n<\/div><\/li> Get a better understanding of the entire physical process<\/strong> underlying the formation of contrails<\/span><\/p>\n<\/div><\/li> Learn about the results of CONTRAILS and augmenting NWP models <\/strong>accordingly<\/span><\/p>\n<\/div><\/li><\/ul><\/div><\/div> Dr. Teodora Petrisor <\/strong>is a senior research engineer in AI at CortAIx Labs, Thales, leading the AI algorithm validation roadmap. She holds a PhD in Signal and Image Processing from Telecom Paris. For the past couple of years she has been focusing on trustworthy AI algorithms with applications to green operations in avionics and more specifically to contrail detection and prediction. She is currently leading the French consortium in the BPI\/DLR CONTRAILS project.<\/span><\/p>\n Prof. Roland Potthast<\/strong>, is Director for Meteorological Modeling and Analysis at the German Weather Service (Deutscher Wetterdienst, DWD)<\/span>, EUMETNET AI Programme Coordinator, and Professor for Applied Mathematics at the University of Reading, UK.<\/p>\n Dr. Stefanie Hollborn<\/span><\/strong> is a scientist at DWD, and leads the Department of Observation Modeling and Verification. She holds a PhD in Numerical Mathematics with a specialization in Inverse Problems from the University of Mainz. Her research focuses on developing and implementing data assimilation methods to enhance Numerical Weather Prediction. Recently, her work has increasingly concentrated on the application of artificial intelligence in weather forecasting and weather and climate services.<\/span><\/p>\n Sarah Vadillo-Quesada <\/strong>graduated with a dual degree in energy engineering and business administration, before developing an extensive background in public affairs by integrating the French Ministry of Ecological Transition and the Ministry of Foreign Affairs, where she contributed to developing research partnerships between French and American Universities. She joined Reuniwatt\u2019s Paris office in 2021 to develop collaborations with universities and projects in the PV sector.<\/p>\n<\/div><\/div><\/div> Teodora Petrisor<\/span><\/p>\n Moderator \u00a0<\/span><\/p>\n \u00a0<\/span><\/p>\n<\/div><\/div><\/div> Prof. Roland Potthast<\/span><\/p>\n Speaker \u00a0<\/span><\/p>\n \u00a0<\/span><\/p>\n<\/div><\/div><\/div> Stefanie Hollborn, PhD<\/span><\/p>\n Speaker \u00a0<\/span><\/p>\n<\/div><\/div><\/div> Sarah Vadillo-Quesada<\/span><\/p>\n Speaker \u00a0<\/span><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div>After this webinar, you will have a better understanding of:<\/h3>\n<\/div><\/div><\/div>
About the speakers:<\/h3>\n<\/div>
<\/span><\/div>
\nSenior Research Engineer AI <\/span>@Thales<\/span><\/p>\n<\/span><\/div>
\nHead of NWP (Numerical Weather Prediction) <\/span>@DWD<\/span><\/p>\n<\/span><\/div>
\nHead of Observation Modelling and Verification NWP @DWD<\/span><\/p>\n<\/span><\/div>
\nBusiness Developer <\/span>@Reuniwatt<\/span><\/p>\n<\/h2>\n
This webinar will take place on March 20, 2025 starting 3pm CET.<\/h2>\n<\/div><\/div><\/div><\/div><\/div>
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This project is supported by the Digital Technologies for Business funding program: Artificial Intelligence Technologies for Risk Prevention, Crisis Management and Resilience, as well as BPI France.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":24,"featured_media":14261,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"content-type":"","_eb_attr":"","footnotes":""},"categories":[49,34],"tags":[],"class_list":["post-14255","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-evenements","category-actualites-reuniwatt"],"_links":{"self":[{"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/posts\/14255","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/users\/24"}],"replies":[{"embeddable":true,"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/comments?post=14255"}],"version-history":[{"count":7,"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/posts\/14255\/revisions"}],"predecessor-version":[{"id":14875,"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/posts\/14255\/revisions\/14875"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/media\/14261"}],"wp:attachment":[{"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/media?parent=14255"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/categories?post=14255"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/reuniwatt.com\/fr\/wp-json\/wp\/v2\/tags?post=14255"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}