👋We’re saying goodbye to X. From now on, you can find us on BlueSky ➡️ https://t.co/miUxKoRD0i Follow us there to stay updated with our latest news and research! 🌍✨

Most of the #EurIPS workshops now have their websites online 🙌 A lot of them have active call for participation and/or papers, so if you see something relevant to your field of research please consider submitting! Links for workshops are available at: https://t.co/IJtQVm7Iph

👥 This week we welcomed Tobias Braun, from the Institute for Earth System Science & Remote Sensing (Leipzig University). 🌏 Today he discussed the potential of complexity science to bridge the gap between synoptic processes and planetary-scale dynamics. 🙌Thanks for the visit!

🤝 A research in collaboration with @CamUniGeography @fzj_ibg3 @CREAF_ecologia @UniJena @DLRdatascience @INAR_fin @MPI_BGC

✍ The findings offer essential insights for enhancing drought prediction and ecosystem management—calling for integrated models that account for both soil moisture and atmospheric demand across diverse climates.

🌍 By comparing field observations with datasets like GLEAM, SEVIRI and ERA5-Land, the study validates key mechanisms controlling ET—pointing to the need for models that respond dynamically to both land and atmospheric drivers.

📊 Declines in ET during dry spells can be up to 50%, mirroring substantial reductions in soil moisture. These dramatic shifts underscore how sensitive water exchange is to drought stress.

☔ In contrast, during wet or non-limited periods, ET is more controlled by atmospheric demand (i.e. VPD) than soil moisture, highlighting a shift in dominant drivers across conditions.

🌱 Using remote sensing, models and in-situ flux tower data, the authors show that during drought years ET dramatically decreases due to dropping soil moisture (SM) and rising vapor pressure deficit (VPD).

🆕🔍 New paper out dissecting evapotranspiration (ET) dynamics across Central Europe under varying moisture conditions to better understand how drought impacts plant–atmosphere water fluxes. 🔗 Read it here: https://t.co/QbsOejXFMB #ClimateScience #Drought

🤝 A research in collab with @iitbombay @INRAE_France @MittiLabs, Southwest Jiaotong University, and Chinese Academy of Sciences.

➡️ By decoupling roughness from vegetation effects, the new framework provides a stronger geophysical basis for SMOS products and offers a transferable approach for future missions such as SMAP and the upcoming Copernicus CIMR.

🌱 This calibration improves the accuracy of soil moisture estimates when evaluated against ground networks and model simulations (ECMWF), while also enhancing the spatial and temporal consistency of vegetation optical depth (L-VOD) with reference biomass and vegetation indices.

📊 The study replaces empirical approximations with a machine learning model trained on soil and terrain properties, producing a physically based global map of roughness that better captures surface heterogeneity.

🆕 🗞️ New paper presenting a new global calibration of soil surface roughness for the SMOS-IC algorithm, which retrieves soil moisture and vegetation optical depth from passive L-band microwave satellite observations. 🔗 Read it here: https://t.co/qAMYcFyr1o #RemoteSensing

🚀Next month our colleague Jorge Vicent will take part in the #ECMLPKDD2025 with a special session dedicated to the AMLEC Challenge! 🗓️ Tuesday, September 16th 🔗 About this activity ➡️ https://t.co/xXFm6Hwrgc #DiscoveryChallenge2025 #ML @ECMLPKDD @elias_project @magellium

🧠 Some of our colleagues presented their work at #CCN2025 this month! 👥 This event brings together researchers in cognitive science, neuroscience, and AI to explore the computations behind complex behaviour. 🥳 Proud to see our team contributing to these conversations! 🧵

🔹Nuria Alabau-Bosque sharing her work on "Hues and Cues: Human vs. CLIP" 🔗 https://t.co/gxnzdHXs1q #CCN2025

🔹Paula Daudén-Oliver with her poster "Response to Affine Transforms of Image Distance Metrics and Humans" 🔗 https://t.co/TT0M1Pimee #CCN2025

🔹 "Contrast Sensitivity Function of Multimodal Vision-Language Models" (Alexandra Gomez-Villa) 🔗 https://t.co/sTGEcmXtpA #CCN2025