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And on Friday afternoon at #EGU26 we have this series of posters from colleagues from the University of Reading and @ucl.ac.uk We hope you have all had a fantastic week in Vienna and wish you a safe journey home! 🙂

Find out more on Joe's presentation: cpom.org.uk/cpomegu26-bl...

🛰️ Coming up on Friday morning at #EGU26, CPOM's Dr Rosemary Willatt will present on progress of the PoSARA concept - a novel satellite instrument concept using polarimetric capability to estimate snow depth on sea ice, land ice and land from space. Read more 👇 🔗 cpom.org.uk/cpom-egu26-b...

Tomorrow afternoon (Friday) at #EGU26 🛰️ Dr Karla Boxall (Lancaster University) will present on a framework for evaluating altimetry uncertainty estimates. 🖥️ Dr Joe Phillips (Lancaster University) on extracting swath elevation information using probabilistic deep learning. Links in comments 👇

Find out more on Karla's presentation: cpom.org.uk/cpomegu26-cp...

Dr Joe Phillips (Lancaster University) will present this science as part of Session CR6.5 on Friday, 08 May, 14:45–14:55 (CEST) in Room L2. Radar altimetry satellites can measure the elevation of ice sheets by firing radio waves at the surface and timing how long the echo takes to return. However, with only a single antenna, these systems cannot tell exactly where on the surface each echo originated from. Current approaches work around this by making simplifying assumptions that reduce each echo to a single elevation estimate, discarding most of the information the waveform contains. This work takes a fundamentally different approach. Rather than throwing away that ambiguity, a probabilistic deep learning framework was trained to extract the full range of plausible surface elevations encoded within each echo. An ensemble of 16 deep learning models was trained on 600,000 radar echoes collected by CryoSat-2 over Antarctica between 2012 and 2021, using the Reference Elevation Model of Antarctica (REMA) as ground truth. The framework was tested over Pine Island Glacier – a region kept entirely separate from training – where it successfully reproduced well-established patterns of ice thinning of 2–3 metres per year. Encouragingly, results closely matched those from CryoSat-2’s interferometric products, which rely on additional information from a second antenna that many satellites do not carry. This matters because elevation change underpins almost everything we calculate about ice sheets: how much ice is being lost, how much seas are rising, and how reliable our future projections are. Extracting more information from each satellite echo – including from historical missions and future satellites that lack a second antenna – could meaningfully improve all of these estimates. Find out more by reading the abstract and attending his presentation online or in-person at EGU26. Feature image credit: ESA Header image credit: Professor Alison Banwell

Coming up tomorrow (Wednesday) at #EGU26 We have a CPOM poster presented by Karla Boxall (Lancaster University) on Cryo-TEMPO, an @esaearth.esa.int CryoSat-2 thematic product over land ice! If you're at the conference, do have a chat with Karla and find out more about Cryo-TEMPO🛰️

Coming up tomorrow (Thursday) at #EGU26 CPOM science highlights for Thursday include posters from Emily Glen and Diego Moral Pombo (Lancaster University), and Luca Bianchi (Cardiff University) ⭐ CPOM highlights for the week listed here 👇 🔗 cpom.org.uk/cpom-egu-2026/

✨We are proud to share that Professor Daniel Feltham (University of Reading) and CPOM Principal Investigator for Sea Ice Modelling, has been awarded the Seligman Crystal by the International Glaciological Society - one of the society's highest honours! 🔗 www.igsoc.org/about/awards...

Dr Karla Boxall (Lancaster University) will present this science as part of Session CR6.5 on Friday, 08 May, 14:35–14:45 (CEST) in Room L2. Satellite missions such as CryoSat-2, ICESat-2 and Sentinel-3 provide invaluable data for measuring and monitoring ice sheet elevation change and any associated contributions to sea level. To capitalise fully on the immense value of satellite altimetry, the uncertainty associated with its measurements must be considered. Despite this, there is currently no standardised approach towards estimating uncertainty nor is there a method to assess how well existing uncertainties perform. Karla, and colleagues from Lancaster University, University College London and Earthwave Ltd., have produced the first framework for evaluating methods of uncertainty generation to find that uncertainties based on the complexity of the landscape as well as the quality of the waveform itself are most robust. The production of reliable uncertainties in this way is important because failing to incorporate uncertainties into downstream applications of satellite altimetry, such as in ice sheet models, can result in unconstrained estimates of ice mass balance, and ultimately, inaccurate predictions of global sea level change. Satellite altimetry provides us with crucial data on the Cryosphere. Continuing to refine and improve the way we process that data, including identifying and formalising how we deal with uncertainties, is integral to ensuring the effective use of satellite altimetry data. As the Earth warms, and ice melts, this data will help us plan for, and adapt to, the impacts of a changing climate. Find out more by reading the abstract and attending her presentation online or in-person at EGU26. This work is also available as a preprint in The Cryosphere. Feature image credit: ESA Header image credit: Professor Alison Banwell

The ice Izzy models is thousands of miles away. Her CPOM / @northumbriauni.bsky.social PhD has got her closer to it than most. 🧊 2 minutes on what a CPOM polar science PhD can really involve - from running MONARCHS simulations to fieldwork in Ny-Ålesund with @bas.ac.uk 👇 📹 youtu.be/VGX_kwPb_8Q

YouTube video by Centre for Polar Observation and Modelling (CPOM)

UK Centre for Polar Observation and Modelling