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Environmental Data Science @EnvDataScience

Environmental Data Science is an #OpenAccess @CambridgeUP journal dedicated to the use of data science & AI to enhance our understanding of the environment.

Joined September 2020
  • Tweets 1,110
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  • Followers 3,322
390 Photos and videos
New article! Correcting dry/wet classification bias in precipitation downscaling via generative adversarial networks 👉 cup.org/4ugXdUr ✍️Shivam Singh, @SimonPapalexiou, Hebatallah M. Abdelmoaty, @tom_hartvigsen & @AntoniosMamala2 #data #generativemodels #precipitation
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New article! Assessing the risk of future Dunkelflaute events for Germany using generative deep learning 👉cup.org/4nEHj4c ✍️ Felix Strnad, Jonathan Schmidt, Fabian Mockert, Philipp Hennig & @nnludwig (@uni_tue) #CMIP6 #renewableenergy #generativeAI #climate
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Recently published! How reliable are retrieval-augmented and standard ChatGPT models to support flood susceptibility mapping? 👉cup.org/4uoQb0F ✍️@pourzangbar and @Mario_J_Franca #ChatGPT #LLMs #floods #machinelearning

How reliable are retrieval-augmented and standard ChatGPT models to support flood susceptibility...

How reliable are retrieval-augmented and standard ChatGPT models to support flood susceptibility mapping? - Volume 5

cambridge.org
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Recently published! Data-driven discovery of meteotsunami patterns from sparse observations 👉 cup.org/4wcgN6l ✍️Ardiansyah Fauzi, Emiliano Renzi, @FredericDiasUCD, Daniel Santiago Pelaez-Zapata & @koksikt #data #meteotsunami #coastalhazard
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Recent article! Detecting unique wind field features in hurricane Sandy from topological data maps 👉 cup.org/3OEfL25 ✍️Justin Hoffmeier (@FLPolyU) Part of the Connecting Data-Driven and Physical Approaches special issue #weather #cyclones #wind #dataanalysis

Detecting unique wind field features in hurricane Sandy from topological data maps | Environmental...

Detecting unique wind field features in hurricane Sandy from topological data maps - Volume 5

cambridge.org
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New article! Language models for the analysis of and interaction with climate change documents 👉 bit.ly/48RjC1W ✍️ Elena Volkanovska (@linglitTUDA) Part of the Tackling Climate Change with Machine Learning special issue #climatechange #MachineLearning
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Calling all @BritishEcolSoc #BES2025 attendees! Visit @CambridgeUP at booth L15 in the Lennox Suite on floor -2 to find out more about Environmental Data Science journal and how to publish your research #openaccess! Have a great conference! #ecology #environment #data
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New article! Using Gaussian processes for spatial prediction of PM2.5 concentration based on calibrated data from distributed low-cost sensor networks 👉 bit.ly/496Ty42 ✍️Lillian Muyama, @sserurichx, @OkureDo & @iBaino #airquality #airpollution @AirQoProject
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New article! Prediction and uncertainty quantification of drought in North Benin 👉bit.ly/3Xhrrsc By authors from @UM6P_officiel, @IFDCGlobal & @uacbenin Part of the Tackling Climate Change with Machine Learning special issue #climatechange #drought #MachineLearning
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📢CALL FOR PAPERS! Solution-Based #DataScience for #Environmental #Biology Challenges A special collection with @CU_ESIIL to advance data-intensive approaches to better understand today's environmental challenges 🗓️1 March-31 May 2026 ℹ️bit.ly/4q0b68m #TippingPoints
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New article! From winter storm thermodynamics to wind gust extremes: discovering interpretable equations from data 👉 bit.ly/4oPzZSN ✍️ Frederick Iat-Hin Tam, Fabien Augsburger & Tom Beucler (@FGSE_UNIL) @Climformatics #CI2025 #thermodynamics #wind #windgusts
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📢 CALL FOR PAPERS: Last day to submit! Connecting Data-Driven and Physical Approaches: Application to Climate Modeling and Earth System Observation A special collection building upon a workshop at #EGU25. ⏰ 31 October 2025 ℹ️ bit.ly/4k09cBu @brajard #climate #AI
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📢 CALL FOR PAPERS: Closing soon! Connecting Data-Driven and Physical Approaches: Application to Climate Modeling and Earth System Observation A special collection building upon a workshop at #EGU25. ⏰ 31 October 2025 ℹ️ bit.ly/4k09cBu @brajard #climate #AI
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New article! Graph neural networks for hourly precipitation projections at the convection permitting scale with a novel hybrid imperfect framework 👉 bit.ly/46RPjIF ✍️ Valentina Blasone,@ErikaCoppolaE, Guido Sanguinetti, Viplove Arora, @SerafinaDiG & Luca Bortolussi
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📢Solution-Based #DataScience for #Environmental #Biology Challenges Announcing a new Call for Papers with @CU_ESIIL to advance data-intensive approaches to better understand today's environmental challenges: ℹ️bit.ly/4q0b68m #TippingPoints #Resilience #Adaptation
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📢 CALL FOR PAPERS: Connecting Data-Driven and Physical Approaches: Application to Climate Modeling and Earth System Observation Only 1 month left to submit to this special collection building upon a workshop at #EGU25. ℹ️ bit.ly/4k09cBu @brajard #climate #AI
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Recently published! Precipitation prediction over the upper Indus Basin from large-scale circulation patterns using Gaussian processes 👉 bit.ly/4nojwoo ✍️ @KenzaxTazi, Andrew Orr, J. Scott Hosking & Richard E. Turner (@BAS_News, @Cambridge_Uni, @turinginst)
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New article! Toward accurate forecasting of renewable energy: Building datasets and benchmarking machine learning models for solar and wind power in France 👉 bit.ly/4mCtrWj ✍️ Eloi Lindas, @YannigGoude & @ciais_philippe @LSCE_IPSL #climate #MachineLearning
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New article! Air quality prediction from images in Indonesia: enhancing model explainability through visual explanation with AQI-net and grad-CAM 👉 bit.ly/4g434qD ✍️ Muhammad Labib Alauddin, Novanto Yudistira & Muhammad Arif Rahman @Climformatics #CI2025 #airquality
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Recently published! 🌍 Crafting desirable climate trajectories with reinforcement learning explored socio-environmental simulations 👉 bit.ly/4oVbLre ✍️James Rudd-Jones, Fiona Thendean & @MPerezOrtiz_ (@ai_ucl, @uclcs) #ClimateChange #ClimatePolicy
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