📢 One week left - Call for Abstracts hashtag#EGU26, Vienna (3-8 May 2026) 🚨

🌳 We warmly invite you to submit an abstract. Let’s shape the next generation of plant hydraulic science together!

🌱 We’re happy to convene a session at #EGU26 on plant hydraulics #FromLeafToLandscape 🌳

🛰️ We welcome studies on VWC: satellite-based, in-situ or DA/ML methods, retrievals and findings 💻🔬

📍 Join us in Vienna!
🗓️ Abstract deadline: 15 Jan 2026
🔗 meetingorganizer.copernicus.org/EGU26/sessio...

Too little training data for deep learning? 🚫📉 Not with transfer learning! 🔁💡
Our latest paper by E. Bueechi and @wouterdorigo.bsky.social shows how transfer learning enables accurate field-scale crop yield forecasts using @copernicusecmwf.bsky.social / @esa.int data 🛰️🌾
doi.org/10.1016/j.at...

🏆 Congrats to @ruxizotta.bsky.social for the Best Paper Award 2024 from the Faculty of Mathematics and Geoinformation!

🛰️Her VODCA v2 paper advances global vegetation monitoring using multi-sensor microwave data. 🌿
🔗 doi.org/10.5194/essd...

👏 A well-deserved recognition of this impactful work

Ruxandra Zotta, Wouter Dorigo and Nicolas Bader at the FAIR site with Georg Wohlfahrt of University of Innsbruck

Autumn in Tyrol

🍂🏔️ What better place to exchange ideas than the Tyrolean mountains in early autumn?

We visited the Dept. of Ecology at Uni Innsbruck, sharing research, exploring synergies, and learning about the impressive FAIR site. 🌿🌲

Thanks @biomet.bsky.social for the warm welcome and the tour!

Emanuel Bueechi

Nirajan Luintel

👨‍🏫 Our teammates Nirajan Luintel & Emanuel Bueechi helped train the next generation of Earth Observation scientists at ESA’s 14th Advanced Course on Land Remote Sensing for Agriculture 🚜

🌾 They shared insights on drought monitoring & crop yield forecasting 💻

🛰️ Great to engage with EO enthusiasts! 🌍

A Practical Introduction to Utilising Uncertainty Information in the Analysis of Essential Climate Variables - Surveys in Geophysics An estimate of uncertainty is essential to understanding what information is conveyed by data and how it relates to the wider context of what one intended to measure. It can be difficult to know how t...

🛠️ Turning uncertainty into a tool for better climate data 🛰️📊

Our colleague Alexander Gruber, with Adam Povey & Claire Bulgin, co-authored a new Surveys in Geophysics paper on how to make the best use of uncertainty in essential climate variables.

🔗 link.springer.com/article/10.1...

ESA CCI Soil Moisture GAPFILLED: an independent global gap-free satellite climate data record with uncertainty estimates Abstract. The ESA CCI Soil Moisture multi-satellite climate data record is a widely used dataset for large-scale hydrological and climatological applications and studies. However, data gaps in the rec...

📢 New publication 💧

Wolfgang Preimesberger, Pietro Stradiotti & @wouterdorigo.bsky.social present the @esa.int CCI Soil Moisture GAPFILLED record 🌍🛰️ (1991–2023), based on 19 satellites w/ uncertainty estimates & validation.

🔗 Paper: doi.org/10.5194/essd...
🔗 Dataset: doi.org/10.48436/hcm...

🧑‍🏫Ukrainian STEM talents visited us to learn how #AI aids #ClimateChange adaptation🌳lecture by @wouterdorigo.bsky.social & Emanuel Büechi
Great to engage with these motivated students🧠
Thanks to @aithyra.bsky.social, MmF & Dmytro Rzhemovskyi for the neat organization👏
mmf.univie.ac.at/ai-science-s...

Making Sense of Uncertainties: Ask the Right Question - Surveys in Geophysics Earth observation data should inform decision making, but good decisions can only be made if the uncertainties in the data are taken into account. Making sense of uncertainty information can be diffic...

🚨📄 Paper alert!
Our latest paper in Surveys in Geophysics provokes a paradigm shift for the way we think about remote sensing data uncertainties. Our innovative approach can help decision-makers to make better-informed decisions based on Earth observation data.
doi.org/10.1007/s107...

🚨📄 Paper alert!
Our new paper in Science of Remote Sensing introduces a seasonal uncertainty estimation approach to merging multi-satellite data, significantly improving uncertainty estimates in the ESA CCI soil moisture climate data records.
doi.org/10.1016/j.sr...
#RemoteSensing #ESACCI

🌿🛰️ Our team joined the MAC1 Conference at @inrae-france.bsky.social Bordeaux

🛰️ @ruxizotta.bsky.social presented improvements to microwave-based VOD estimates using optimised LPRM settings.
📡 @nicolasfbader.bsky.social showed how GNSS signals help track canopy water in beech forests.

#GNSST #VOD

🌍 Our team took part in NHCC 2025 in Szeged!
🎉 Johanna Lems won Best Presentation (Young Researchers) for her work on @esa.int CCI Soil Moisture & droughts.
📊 Nirajan Luintel presented on drought monitoring in Central Europe @interregeurope.bsky.social
🔗 nathaz.eu
#NHCC2025 #ClimateScience #CLIMERS

Frontiers | Analyzing satellite and airborne Ka-band passive microwave observations over land for temperature and vegetation monitoring

🚨📄 Paper alert!
🎉 Congrats to long-term collaborator Richard de Jeu on his new paper unlocking Ka-band microwave for land-surface temp & vegetation monitoring. 🌍📡 @wouterdorigo.bsky.social @ruxizotta.bsky.social
🔗 doi.org/10.3389/frsen.2025.1574072
#RemoteSensing #KaBand #VOD

🌡️ Increasing drought, heatwave, and wildfire events require more attention. In the project Clim4Cast, we develop new forecasting systems for Central Europe and find solutions to tackle these disasters.

📢 We discussed these results and identified potential improvements with stakeholders last week.

🌲🍃 It's #WorldForestDay 2025 🍂🌳

📉 Forests are changing fast. This animation shows deforestation in Brazil, using Landsat and VODCA2GPP.

🌍 Long-term satellite data help us understand climate impacts and ecosystem change.

🛰️ Based on the work of @ruxizotta.bsky.social
🔗 doi.org/10.5194/essd...

📣🎓PhD Defense: 7 Mar 2025, 16:00 CET 🌍🛰️

Zdenko Heyvaert (KU Leuven & @tuwien.bsky.social, @geodepartment.bsky.social) will defend his PhD on

📖“Continental assimilation of satellite-based soil moisture & vegetation in land-atmosphere coupling.”

📍 livestream.kuleuven.be?pin=940064

#Climers #PhD

🚀🛰️TU Wien's @geodepartment.bsky.social is hiring for the Women4GEO position, supporting and advancing female students in geospatial sciences! 🌍 Join a dynamic research environment in Vienna.

🔗 Details & Application: jobs.tuwien.ac.at/Job/247895

💡✨ #WomenInSTEM #GeospatialScience #Hiring

Summer student job in climate and environmental remote sensing Open position

Our @climers.bsky.social group is looking to fill two summer positions for students: www.tuwien.at/en/mg/geo/ne... www.tuwien.at/en/mg/geo/ne...

Great paper by our former @climers.bsky.social team member Matthias!

New upgrade to the ESA CCI Soil Moisture Dataset (version 09.1) Explore ESA's latest and ground-breaking global soil moisture dataset, spanning 40 years (1978-2023). Developed by the CCI Soil Moisture team, this trusted dataset is cited by the IPCC's 6th Assessmen...

Our latest dataset just released: global soil moisture from 1978-2024: climate.esa.int/en/news-even...

@esaclimate.bsky.social @climers.bsky.social

🚀 Excited to share our latest publication on estimating uncertainties in satellite-derived soil moisture at a global scale, led by our colleagues at @CesbioLab: https://doi.org/10.1016/j.srs.2024.100147 🌍📡 #SoilMoisture #RemoteSensing #EarthObservation @esa @ESA_EO

Our Quality Assurance for Soil Moisture (QA4SM) framework is in the ESA headlines 🥳Try it yourself!
earth.esa.int/eogateway/news/workshop-...

CLIMERS auf der EGU 2024 Termine der Beiträge von CLIMERS

#EGU2024 day 3 is starting🗣️
9⃣ contributions from our side done✅
5⃣ more to come📢
Check them out on www.tuwien.at/mg/geo/climers/aktuelles...

Women4Geo summer job in climate and environmental remote sensing Open position

🚨Job alert🚨 We are offering a Women4Geo summer job to a female student who is interested in remote sensing. Deadline for applications: 30.04. Spread the word📢www.tuwien.at/en/mg/geo/news/news-deta...

Very productive workshop organized by @esa and @EU_Commission bringing together scientists and decision makers 🗣️ With two @CLIMERS_GEO presentations about #drought monitoring and crop yield forecasting using #satellite data🛰️

Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations Abstract. Soil moisture is a key variable in monitoring climate and an important component of the hydrological, carbon, and energy cycles. Satellite products ameliorate the sparsity of field measurements but are inherently limited to observing the near-surface layer, while water available in the unobserved root-zone controls critical processes like plant water uptake and evapotranspiration. A variety of approaches exist for modelling root-zone soil moisture (RZSM), including approximating it from surface layer observations. While the number of available RZSM datasets is growing, they usually do not contain estimates of their uncertainty. In this paper we derive a long-term RZSM dataset (2002–2020) from the Copernicus Climate Change Service (C3S) surface soil moisture (SSM) COMBINED product via the exponential filter (EF) method. We identify the optimal value of the method's model parameter T, which controls the level of smoothing and delaying applied to the surface observations, by maximizing the correlation of RZSM estimates with field measurements from the International Soil Moisture Network (ISMN). Optimized T-parameter values were calculated for four soil depth layers (0–10, 10–40, 40–100, and 100–200 cm) and used to calculate a global RZSM dataset. The quality of this dataset is then globally evaluated against RZSM estimates of the ERA5-Land reanalysis. Results of the product comparison show satisfactory skill in all four layers, with the median Pearson correlation ranging from 0.54 in the topmost to 0.28 in the deepest soil layer. Temporally dynamic product uncertainties for each of the RZSM product layers are estimated by applying standard uncertainty propagation to SSM input data and by estimating structural uncertainties in the EF method from ISMN ground reference measurements taken at the surface and at varying depths. Uncertainty estimates were found to exhibit both realistic absolute magnitudes and temporal variations. The product described here is, to the best of our knowledge, the first global, long-term, uncertainty-characterized, and purely observation-based product for RZSM estimates up to 2 m depth.

📢Paper Alert📷Check out our latest publication about an error-characterized global long-term root-zone soil moisture product created from @copernicus C3S soil moisture data: https://t.co/dAWnEImhcH%E2%80%A6 funded by
@H2020Projects

🚨Paper Alert📢 Interested to learn how #remotesensing 🛰️and meteorological data can be used to forecast the drying-out of salt pans? Check out our latest publication: https://www.mdpi.com/2072-4292/15/19/4659
#Landsat #MachineLearning @NP_Austria @wouterdorigo @HenriSchauer

Soil Moisture 💧🌎from ESA CCI SM @esaclimate @CAlbergel captured well the triple-dip La Niña patterns, with some remarkable drought events. (2/3)

🚨#StateofClimate2022
Check out our contributions to this year's climate report on soil moisture 💧 and vegetation optical depth🍃. @wouterdorigo @RuxandraZotta @esaclimate
(1/3)🧵 https://x.com/NOAA/status/1699410219233841263