Environmental Data Science
@envdatascience.bsky.social
Environmental Data Science is an #OpenAccess journal @cambridgeup.bsky.social dedicated to the use of data science & AI to enhance our understanding of the environment.
New article!
Uncertainty quantification for deep learning
👉 https://bit.ly/49MlJpa
✍️ Peter Jan van Leeuwen, Jui-Yuan Christine Chiu & Chen-Kuang Kevin Yang (@csuatmossci.bsky.social)
Proposes a framework to improve consistency for #uncertaintyquantification in #deeplearning
#machinelearning
Uncertainty quantification for deep learning
👉 https://bit.ly/49MlJpa
✍️ Peter Jan van Leeuwen, Jui-Yuan Christine Chiu & Chen-Kuang Kevin Yang (@csuatmossci.bsky.social)
Proposes a framework to improve consistency for #uncertaintyquantification in #deeplearning
#machinelearning
January 12, 2026 at 11:02 AM
New article!
Uncertainty quantification for deep learning
👉 https://bit.ly/49MlJpa
✍️ Peter Jan van Leeuwen, Jui-Yuan Christine Chiu & Chen-Kuang Kevin Yang (@csuatmossci.bsky.social)
Proposes a framework to improve consistency for #uncertaintyquantification in #deeplearning
#machinelearning
Uncertainty quantification for deep learning
👉 https://bit.ly/49MlJpa
✍️ Peter Jan van Leeuwen, Jui-Yuan Christine Chiu & Chen-Kuang Kevin Yang (@csuatmossci.bsky.social)
Proposes a framework to improve consistency for #uncertaintyquantification in #deeplearning
#machinelearning
New article!
Language models for the analysis of and interaction with climate change documents
👉 https://bit.ly/48RjC1W
✍️ Elena Volkanovska (@tuda.bsky.social)
Part of the Tackling Climate Change with Machine Learning special issue
#climatechange #MachineLearning
Language models for the analysis of and interaction with climate change documents
👉 https://bit.ly/48RjC1W
✍️ Elena Volkanovska (@tuda.bsky.social)
Part of the Tackling Climate Change with Machine Learning special issue
#climatechange #MachineLearning
December 19, 2025 at 11:01 AM
New article!
Language models for the analysis of and interaction with climate change documents
👉 https://bit.ly/48RjC1W
✍️ Elena Volkanovska (@tuda.bsky.social)
Part of the Tackling Climate Change with Machine Learning special issue
#climatechange #MachineLearning
Language models for the analysis of and interaction with climate change documents
👉 https://bit.ly/48RjC1W
✍️ Elena Volkanovska (@tuda.bsky.social)
Part of the Tackling Climate Change with Machine Learning special issue
#climatechange #MachineLearning
Calling all @britishecologicalsociety.org #BES2025 attendees!
Visit @universitypress.cambridge.org at booth L15 in the Lennox Suite, floor -2, to find out more about Environmental Data Science journal & how to publish your research #openaccess!
Have a great conference!
#ecology #environment #data
Visit @universitypress.cambridge.org at booth L15 in the Lennox Suite, floor -2, to find out more about Environmental Data Science journal & how to publish your research #openaccess!
Have a great conference!
#ecology #environment #data
December 16, 2025 at 1:31 PM
Calling all @britishecologicalsociety.org #BES2025 attendees!
Visit @universitypress.cambridge.org at booth L15 in the Lennox Suite, floor -2, to find out more about Environmental Data Science journal & how to publish your research #openaccess!
Have a great conference!
#ecology #environment #data
Visit @universitypress.cambridge.org at booth L15 in the Lennox Suite, floor -2, to find out more about Environmental Data Science journal & how to publish your research #openaccess!
Have a great conference!
#ecology #environment #data
New article!
Using Gaussian processes for spatial prediction of PM2.5 concentration based on calibrated data from distributed low-cost sensor networks
👉 https://bit.ly/496Ty42
✍️Lillian Muyama, Richard Sserunjogi, Deo Okure & Engineer Bainomugisha (
@airqo.bsky.social)
#airquality #airpollution
Using Gaussian processes for spatial prediction of PM2.5 concentration based on calibrated data from distributed low-cost sensor networks
👉 https://bit.ly/496Ty42
✍️Lillian Muyama, Richard Sserunjogi, Deo Okure & Engineer Bainomugisha (
@airqo.bsky.social)
#airquality #airpollution
December 15, 2025 at 11:03 AM
New article!
Using Gaussian processes for spatial prediction of PM2.5 concentration based on calibrated data from distributed low-cost sensor networks
👉 https://bit.ly/496Ty42
✍️Lillian Muyama, Richard Sserunjogi, Deo Okure & Engineer Bainomugisha (
@airqo.bsky.social)
#airquality #airpollution
Using Gaussian processes for spatial prediction of PM2.5 concentration based on calibrated data from distributed low-cost sensor networks
👉 https://bit.ly/496Ty42
✍️Lillian Muyama, Richard Sserunjogi, Deo Okure & Engineer Bainomugisha (
@airqo.bsky.social)
#airquality #airpollution
Exploring the Impact of 2025 @climformatics.bsky.social in the Global South - by @rblourenco.bsky.social
#CI2025 #ClimateInformatics #DataScience
www.cambridge.org/core/blog/20...
#CI2025 #ClimateInformatics #DataScience
www.cambridge.org/core/blog/20...
Climate Informatics 2025: Exploring Climate Science and Data Science in the Global South « Earth & Environmental Science# « Cambridge Core Blog
As many readers will know, COP30, the UN climate conference, got underway in Belém, Brazil this month. In this blog post, we’re pleased to report on another conference that was successfully held in Br...
www.cambridge.org
December 3, 2025 at 1:20 PM
Exploring the Impact of 2025 @climformatics.bsky.social in the Global South - by @rblourenco.bsky.social
#CI2025 #ClimateInformatics #DataScience
www.cambridge.org/core/blog/20...
#CI2025 #ClimateInformatics #DataScience
www.cambridge.org/core/blog/20...
New article!
Prediction and uncertainty quantification of drought in North Benin
👉https://bit.ly/3Xhrrsc
Part of the Tackling #ClimateChange with #MachineLearning special issue.
Study underscoreing the importance of uncertainty quantification in #drought #forecasting.
Prediction and uncertainty quantification of drought in North Benin
👉https://bit.ly/3Xhrrsc
Part of the Tackling #ClimateChange with #MachineLearning special issue.
Study underscoreing the importance of uncertainty quantification in #drought #forecasting.
November 26, 2025 at 11:02 AM
New article!
Prediction and uncertainty quantification of drought in North Benin
👉https://bit.ly/3Xhrrsc
Part of the Tackling #ClimateChange with #MachineLearning special issue.
Study underscoreing the importance of uncertainty quantification in #drought #forecasting.
Prediction and uncertainty quantification of drought in North Benin
👉https://bit.ly/3Xhrrsc
Part of the Tackling #ClimateChange with #MachineLearning special issue.
Study underscoreing the importance of uncertainty quantification in #drought #forecasting.
📢 CALL FOR PAPERS!
Solution-Based #DataScience for #Environmental #Biology Challenges
A special collection with @cu-esiil.bsky.social to advance data-intensive approaches to better understand today's environmental challenges
🗓️1 March-31 May 2026
ℹ️https://bit.ly/4q0b68m
#TippingPoints
Solution-Based #DataScience for #Environmental #Biology Challenges
A special collection with @cu-esiil.bsky.social to advance data-intensive approaches to better understand today's environmental challenges
🗓️1 March-31 May 2026
ℹ️https://bit.ly/4q0b68m
#TippingPoints
November 14, 2025 at 11:03 AM
📢 CALL FOR PAPERS!
Solution-Based #DataScience for #Environmental #Biology Challenges
A special collection with @cu-esiil.bsky.social to advance data-intensive approaches to better understand today's environmental challenges
🗓️1 March-31 May 2026
ℹ️https://bit.ly/4q0b68m
#TippingPoints
Solution-Based #DataScience for #Environmental #Biology Challenges
A special collection with @cu-esiil.bsky.social to advance data-intensive approaches to better understand today's environmental challenges
🗓️1 March-31 May 2026
ℹ️https://bit.ly/4q0b68m
#TippingPoints
New article!
From winter storm thermodynamics to wind gust extremes: discovering interpretable equations from data
👉 https://bit.ly/4oPzZSN
✍️ Frederick Iat-Hin Tam, Fabien Augsburger, Tom Beucler (@fgse-unil.bsky.social, @unil.bsky.social )
@climformatics.bsky.social #CI2025 #thermodynamics #wind
From winter storm thermodynamics to wind gust extremes: discovering interpretable equations from data
👉 https://bit.ly/4oPzZSN
✍️ Frederick Iat-Hin Tam, Fabien Augsburger, Tom Beucler (@fgse-unil.bsky.social, @unil.bsky.social )
@climformatics.bsky.social #CI2025 #thermodynamics #wind
November 5, 2025 at 11:02 AM
New article!
From winter storm thermodynamics to wind gust extremes: discovering interpretable equations from data
👉 https://bit.ly/4oPzZSN
✍️ Frederick Iat-Hin Tam, Fabien Augsburger, Tom Beucler (@fgse-unil.bsky.social, @unil.bsky.social )
@climformatics.bsky.social #CI2025 #thermodynamics #wind
From winter storm thermodynamics to wind gust extremes: discovering interpretable equations from data
👉 https://bit.ly/4oPzZSN
✍️ Frederick Iat-Hin Tam, Fabien Augsburger, Tom Beucler (@fgse-unil.bsky.social, @unil.bsky.social )
@climformatics.bsky.social #CI2025 #thermodynamics #wind
📢 CALL FOR PAPERS: FINAL 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 https://bit.ly/4k09cBu
#climate #AI #forecasting
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 https://bit.ly/4k09cBu
#climate #AI #forecasting
October 31, 2025 at 11:01 AM
📢 CALL FOR PAPERS: FINAL 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 https://bit.ly/4k09cBu
#climate #AI #forecasting
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 https://bit.ly/4k09cBu
#climate #AI #forecasting
Reposted by Environmental Data Science
We are Climate.us, a nonprofit successor to Climate(.)gov.
Our goal is to build an enduring, independent, and scientifically rigorous platform that the world can rely on for climate communication, education, and engagement. Stay up to date: #updatesmate.us/#updates" class="hover:underline text-blue-600 dark:text-sky-400 no-card-link" target="_blank" rel="noopener" data-link="bsky">Climate.us/#updates
Our goal is to build an enduring, independent, and scientifically rigorous platform that the world can rely on for climate communication, education, and engagement. Stay up to date: #updatesmate.us/#updates" class="hover:underline text-blue-600 dark:text-sky-400 no-card-link" target="_blank" rel="noopener" data-link="bsky">Climate.us/#updates
October 22, 2025 at 10:17 PM
We are Climate.us, a nonprofit successor to Climate(.)gov.
Our goal is to build an enduring, independent, and scientifically rigorous platform that the world can rely on for climate communication, education, and engagement. Stay up to date: #updatesmate.us/#updates" class="hover:underline text-blue-600 dark:text-sky-400 no-card-link" target="_blank" rel="noopener" data-link="bsky">Climate.us/#updates
Our goal is to build an enduring, independent, and scientifically rigorous platform that the world can rely on for climate communication, education, and engagement. Stay up to date: #updatesmate.us/#updates" class="hover:underline text-blue-600 dark:text-sky-400 no-card-link" target="_blank" rel="noopener" data-link="bsky">Climate.us/#updates
📢 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 https://bit.ly/4k09cBu
#climate #AI #forecasting
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 https://bit.ly/4k09cBu
#climate #AI #forecasting
October 17, 2025 at 10:01 AM
📢 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 https://bit.ly/4k09cBu
#climate #AI #forecasting
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 https://bit.ly/4k09cBu
#climate #AI #forecasting
New article!
Graph neural networks for hourly precipitation projections at the convection permitting scale with a novel hybrid imperfect framework
👉https://bit.ly/46RPjIF
✍️Valentina Blasone,
@erikacoppola.bsky.social, Guido Sanguinetti, Viplove Arora, Serafina Di Gioia & Luca Bortolussi
Graph neural networks for hourly precipitation projections at the convection permitting scale with a novel hybrid imperfect framework
👉https://bit.ly/46RPjIF
✍️Valentina Blasone,
@erikacoppola.bsky.social, Guido Sanguinetti, Viplove Arora, Serafina Di Gioia & Luca Bortolussi
October 15, 2025 at 10:02 AM
New article!
Graph neural networks for hourly precipitation projections at the convection permitting scale with a novel hybrid imperfect framework
👉https://bit.ly/46RPjIF
✍️Valentina Blasone,
@erikacoppola.bsky.social, Guido Sanguinetti, Viplove Arora, Serafina Di Gioia & Luca Bortolussi
Graph neural networks for hourly precipitation projections at the convection permitting scale with a novel hybrid imperfect framework
👉https://bit.ly/46RPjIF
✍️Valentina Blasone,
@erikacoppola.bsky.social, Guido Sanguinetti, Viplove Arora, Serafina Di Gioia & Luca Bortolussi
📢 Solution-Based #DataScience for #Environmental #Biology Challenges
Announcing a new Call for Papers with @cu-esiil.bsky.social to advance data-intensive approaches to better understand today's environmental challenges:
ℹ️https://bit.ly/4q0b68m
📅 31 May 2026
#TippingPoints #Resilience #Adaptation
Announcing a new Call for Papers with @cu-esiil.bsky.social to advance data-intensive approaches to better understand today's environmental challenges:
ℹ️https://bit.ly/4q0b68m
📅 31 May 2026
#TippingPoints #Resilience #Adaptation
October 14, 2025 at 10:40 AM
📢 Solution-Based #DataScience for #Environmental #Biology Challenges
Announcing a new Call for Papers with @cu-esiil.bsky.social to advance data-intensive approaches to better understand today's environmental challenges:
ℹ️https://bit.ly/4q0b68m
📅 31 May 2026
#TippingPoints #Resilience #Adaptation
Announcing a new Call for Papers with @cu-esiil.bsky.social to advance data-intensive approaches to better understand today's environmental challenges:
ℹ️https://bit.ly/4q0b68m
📅 31 May 2026
#TippingPoints #Resilience #Adaptation
Reposted by Environmental Data Science
We have exciting news! #CI2026 will be hosted by the École Polytechnique Fédérale de Lausanne (EPFL), in the period of April 27-30, 2026. More information in Tom Beucler's post:
www.linkedin.com/posts/tom-be...
www.linkedin.com/posts/tom-be...
Save the date! 🌍
Climate Informatics will convene researchers at the intersection of weather & climate science, statistics, and machine learning, April 27-30, 2026 on our beautiful UNIL/EPFL… | ...
Save the date! 🌍
Climate Informatics will convene researchers at the intersection of weather & climate science, statistics, and machine learning, April 27-30, 2026 on our beautiful UNIL/EPFL campus ...
www.linkedin.com
October 1, 2025 at 6:35 PM
We have exciting news! #CI2026 will be hosted by the École Polytechnique Fédérale de Lausanne (EPFL), in the period of April 27-30, 2026. More information in Tom Beucler's post:
www.linkedin.com/posts/tom-be...
www.linkedin.com/posts/tom-be...
📢 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 https://bit.ly/4k09cBu
#climate #AI #forecasting
Only 1 month left to submit to this special collection building upon a workshop at #EGU25.
ℹ️ https://bit.ly/4k09cBu
#climate #AI #forecasting
September 30, 2025 at 10:02 AM
📢 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 https://bit.ly/4k09cBu
#climate #AI #forecasting
Only 1 month left to submit to this special collection building upon a workshop at #EGU25.
ℹ️ https://bit.ly/4k09cBu
#climate #AI #forecasting
Recently published!
Precipitation prediction over the upper Indus Basin from large-scale circulation patterns using Gaussian processes
👉 https://bit.ly/4nojwoo
✍️ @kenzatazi.bsky.social , Andrew Orr, @scotthosking.bsky.social & Richard E. Turner
@theturing.bsky.social
@bas.ac.uk
#precipitation
Precipitation prediction over the upper Indus Basin from large-scale circulation patterns using Gaussian processes
👉 https://bit.ly/4nojwoo
✍️ @kenzatazi.bsky.social , Andrew Orr, @scotthosking.bsky.social & Richard E. Turner
@theturing.bsky.social
@bas.ac.uk
#precipitation
September 29, 2025 at 10:02 AM
Recently published!
Precipitation prediction over the upper Indus Basin from large-scale circulation patterns using Gaussian processes
👉 https://bit.ly/4nojwoo
✍️ @kenzatazi.bsky.social , Andrew Orr, @scotthosking.bsky.social & Richard E. Turner
@theturing.bsky.social
@bas.ac.uk
#precipitation
Precipitation prediction over the upper Indus Basin from large-scale circulation patterns using Gaussian processes
👉 https://bit.ly/4nojwoo
✍️ @kenzatazi.bsky.social , Andrew Orr, @scotthosking.bsky.social & Richard E. Turner
@theturing.bsky.social
@bas.ac.uk
#precipitation
New article!
Toward accurate forecasting of renewable energy: Building datasets and benchmarking machine learning models for solar and wind power in France
👉 https://bit.ly/4mCtrWj
✍️ Eloi Lindas, Yannig Goude & Philippe Ciais (@lsce-ipsl.bsky.social)
#climate #MachineLearning #forecasting
Toward accurate forecasting of renewable energy: Building datasets and benchmarking machine learning models for solar and wind power in France
👉 https://bit.ly/4mCtrWj
✍️ Eloi Lindas, Yannig Goude & Philippe Ciais (@lsce-ipsl.bsky.social)
#climate #MachineLearning #forecasting
September 25, 2025 at 10:02 AM
New article!
Toward accurate forecasting of renewable energy: Building datasets and benchmarking machine learning models for solar and wind power in France
👉 https://bit.ly/4mCtrWj
✍️ Eloi Lindas, Yannig Goude & Philippe Ciais (@lsce-ipsl.bsky.social)
#climate #MachineLearning #forecasting
Toward accurate forecasting of renewable energy: Building datasets and benchmarking machine learning models for solar and wind power in France
👉 https://bit.ly/4mCtrWj
✍️ Eloi Lindas, Yannig Goude & Philippe Ciais (@lsce-ipsl.bsky.social)
#climate #MachineLearning #forecasting
New article!
Air quality prediction from images in Indonesia: enhancing model explainability through visual explanation with AQI-net and grad-CAM
👉 https://bit.ly/4g434qD
✍️ Muhammad Labib Alauddin, Novanto Yudistira & Muhammad Arif Rahman
@climformatics.bsky.social #CI2025 #airquality
Air quality prediction from images in Indonesia: enhancing model explainability through visual explanation with AQI-net and grad-CAM
👉 https://bit.ly/4g434qD
✍️ Muhammad Labib Alauddin, Novanto Yudistira & Muhammad Arif Rahman
@climformatics.bsky.social #CI2025 #airquality
September 3, 2025 at 10:02 AM
New article!
Air quality prediction from images in Indonesia: enhancing model explainability through visual explanation with AQI-net and grad-CAM
👉 https://bit.ly/4g434qD
✍️ Muhammad Labib Alauddin, Novanto Yudistira & Muhammad Arif Rahman
@climformatics.bsky.social #CI2025 #airquality
Air quality prediction from images in Indonesia: enhancing model explainability through visual explanation with AQI-net and grad-CAM
👉 https://bit.ly/4g434qD
✍️ Muhammad Labib Alauddin, Novanto Yudistira & Muhammad Arif Rahman
@climformatics.bsky.social #CI2025 #airquality
Recently published! 🌍
Crafting desirable climate trajectories with reinforcement learning explored socio-environmental simulations
👉 https://bit.ly/4oVbLre
✍️James Rudd-Jones, Fiona Thendean & María Pérez-Ortiz (@ucl.ac.uk)
#ClimateChange #ClimatePolicy
Crafting desirable climate trajectories with reinforcement learning explored socio-environmental simulations
👉 https://bit.ly/4oVbLre
✍️James Rudd-Jones, Fiona Thendean & María Pérez-Ortiz (@ucl.ac.uk)
#ClimateChange #ClimatePolicy
August 29, 2025 at 10:02 AM
Recently published! 🌍
Crafting desirable climate trajectories with reinforcement learning explored socio-environmental simulations
👉 https://bit.ly/4oVbLre
✍️James Rudd-Jones, Fiona Thendean & María Pérez-Ortiz (@ucl.ac.uk)
#ClimateChange #ClimatePolicy
Crafting desirable climate trajectories with reinforcement learning explored socio-environmental simulations
👉 https://bit.ly/4oVbLre
✍️James Rudd-Jones, Fiona Thendean & María Pérez-Ortiz (@ucl.ac.uk)
#ClimateChange #ClimatePolicy
New article! 🌍🛰️
Discrete variational autoencoders for synthetic nighttime visible satellite imagery
👉 https://bit.ly/4oVjTb5
✍️ Mickell D. Als, David Tomarov & @steve.fediscience.org.ap.brid.gy (@uoftcompsci.bsky.social)
Part of the @climformatics.bsky.social #CI2025 collection
#DeepLearning
Discrete variational autoencoders for synthetic nighttime visible satellite imagery
👉 https://bit.ly/4oVjTb5
✍️ Mickell D. Als, David Tomarov & @steve.fediscience.org.ap.brid.gy (@uoftcompsci.bsky.social)
Part of the @climformatics.bsky.social #CI2025 collection
#DeepLearning
August 27, 2025 at 10:04 AM
New article! 🌍🛰️
Discrete variational autoencoders for synthetic nighttime visible satellite imagery
👉 https://bit.ly/4oVjTb5
✍️ Mickell D. Als, David Tomarov & @steve.fediscience.org.ap.brid.gy (@uoftcompsci.bsky.social)
Part of the @climformatics.bsky.social #CI2025 collection
#DeepLearning
Discrete variational autoencoders for synthetic nighttime visible satellite imagery
👉 https://bit.ly/4oVjTb5
✍️ Mickell D. Als, David Tomarov & @steve.fediscience.org.ap.brid.gy (@uoftcompsci.bsky.social)
Part of the @climformatics.bsky.social #CI2025 collection
#DeepLearning
New article!🌍💨💡
Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6
👉 doi.org/10.1017/eds....
✍️ Nina Effenberger & @nnludwig.bsky.social
This uses a global #climate model and shows #wind as a reliable #energy source with turbine location essential for projections.
Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6
👉 doi.org/10.1017/eds....
✍️ Nina Effenberger & @nnludwig.bsky.social
This uses a global #climate model and shows #wind as a reliable #energy source with turbine location essential for projections.
August 22, 2025 at 7:51 AM
New article!🌍💨💡
Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6
👉 doi.org/10.1017/eds....
✍️ Nina Effenberger & @nnludwig.bsky.social
This uses a global #climate model and shows #wind as a reliable #energy source with turbine location essential for projections.
Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6
👉 doi.org/10.1017/eds....
✍️ Nina Effenberger & @nnludwig.bsky.social
This uses a global #climate model and shows #wind as a reliable #energy source with turbine location essential for projections.
Recent article! 🌳🌍
Tree semantic segmentation from aerial image time series
👉 doi.org/10.1017/eds....
✍️ Venkatesh Ramesh @arthurouaknine.bsky.social & @drolnick.bsky.social
Research that advances #forest monitoring using #deeplearning on aerial imagery time series.
Tree semantic segmentation from aerial image time series
👉 doi.org/10.1017/eds....
✍️ Venkatesh Ramesh @arthurouaknine.bsky.social & @drolnick.bsky.social
Research that advances #forest monitoring using #deeplearning on aerial imagery time series.
August 21, 2025 at 10:13 PM
Recent article! 🌳🌍
Tree semantic segmentation from aerial image time series
👉 doi.org/10.1017/eds....
✍️ Venkatesh Ramesh @arthurouaknine.bsky.social & @drolnick.bsky.social
Research that advances #forest monitoring using #deeplearning on aerial imagery time series.
Tree semantic segmentation from aerial image time series
👉 doi.org/10.1017/eds....
✍️ Venkatesh Ramesh @arthurouaknine.bsky.social & @drolnick.bsky.social
Research that advances #forest monitoring using #deeplearning on aerial imagery time series.
📢 CALL FOR PAPERS REMINDER!
Connecting #Data-Driven and Physical Approaches: Application to #Climate #Modeling and #Earth System Observation
Submit your work to this special collection in EDS (@universitypress.cambridge.org)
🗓️ 31st Oct 2025
ℹ️ bit.ly/4k09cBu
@brajard.bsky.social #AI #ML #Weather
Connecting #Data-Driven and Physical Approaches: Application to #Climate #Modeling and #Earth System Observation
Submit your work to this special collection in EDS (@universitypress.cambridge.org)
🗓️ 31st Oct 2025
ℹ️ bit.ly/4k09cBu
@brajard.bsky.social #AI #ML #Weather
August 20, 2025 at 11:09 AM
📢 CALL FOR PAPERS REMINDER!
Connecting #Data-Driven and Physical Approaches: Application to #Climate #Modeling and #Earth System Observation
Submit your work to this special collection in EDS (@universitypress.cambridge.org)
🗓️ 31st Oct 2025
ℹ️ bit.ly/4k09cBu
@brajard.bsky.social #AI #ML #Weather
Connecting #Data-Driven and Physical Approaches: Application to #Climate #Modeling and #Earth System Observation
Submit your work to this special collection in EDS (@universitypress.cambridge.org)
🗓️ 31st Oct 2025
ℹ️ bit.ly/4k09cBu
@brajard.bsky.social #AI #ML #Weather
Article!
MoTiF: a self-supervised model for multi-source #forecasting with application to #tropical #cyclones 🌀🌍
✍️Clément Dauvilliers & Claire Monteleoni (INRIA & colorado.edu)
�� https://doi.org/10.1017/eds.2025.1000014
Presents #deeplearninga#AIng #AI method for foreca#extremeweathereather.
MoTiF: a self-supervised model for multi-source #forecasting with application to #tropical #cyclones 🌀🌍
✍️Clément Dauvilliers & Claire Monteleoni (INRIA & colorado.edu)
�� https://doi.org/10.1017/eds.2025.1000014
Presents #deeplearninga#AIng #AI method for foreca#extremeweathereather.
August 20, 2025 at 10:46 AM
Article!
MoTiF: a self-supervised model for multi-source #forecasting with application to #tropical #cyclones 🌀🌍
✍️Clément Dauvilliers & Claire Monteleoni (INRIA & colorado.edu)
�� https://doi.org/10.1017/eds.2025.1000014
Presents #deeplearninga#AIng #AI method for foreca#extremeweathereather.
MoTiF: a self-supervised model for multi-source #forecasting with application to #tropical #cyclones 🌀🌍
✍️Clément Dauvilliers & Claire Monteleoni (INRIA & colorado.edu)
�� https://doi.org/10.1017/eds.2025.1000014
Presents #deeplearninga#AIng #AI method for foreca#extremeweathereather.