EGU25-8060, updated on 14 Mar 2025
https://doi.org/10.5194/egusphere-egu25-8060
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Wednesday, 30 Apr, 08:35–08:45 (CEST)
 
Room L2
Estimating Antarctic surface melt rates using passive microwave data calibrated with weather station observations.
Valeria Di Biase1, Peter Kuipers Munneke1, Bert Wouters2, Michiel van den Broeke1, and Maurice van Tiggelen1
Valeria Di Biase et al.
  • 1Utrecht University, IMAU, Utrecht, Netherlands (valedibiase@gmail.com)
  • 2Department of Geoscience & Remote Sensing, Delft University of Technology, Delft, the Netherlands

Surface melt is a critical boundary condition for the hydrological system of the Antarctic Ice Sheet, impacting processes such as mass balance and ice shelf stability. However, its quantification remains challenging due to the scarcity of in-situ measurements and the spatial variability of melt processes. While remote sensing offers extensive coverage, estimating melt rates - beyond binary melt detection - is complicated by the nature of satellite measurements, which detect the presence of liquid water rather than the physical process of melting.

This study explores a novel method for estimating surface melt rates across Antarctica by calibrating passive microwave data from the Special Sensor Microwave Imager/Sounder (SSMIS) with in-situ observations of surface melt collected by Automatic Weather Stations (AWS).

Binary melt days were identified using SSMIS 19GHz brightness temperature thresholds carefully calibrated against AWS data from diverse Antarctic regions, including the Larsen C, Baudouin, and Ekström ice shelves. A quantitative relationship was established to link the number of melt days to the melt quantities measured at AWS sites, offering a first approximation of annual melt rates. The methodology emphasizes spatial coherence and compatibility across datasets and offers insights into regional variations in melt processes.

We suggest that this approach has the potential to improve the detection of melt days and provide estimates of melt rates from space rather than merely identifying melt occurrence. The study underscores the significance of AWS calibration, while also acknowledging the uncertainties in both the data and the methodology. This framework represents a step forward in understanding melt dynamics in Antarctica and contributes to the development of tools for long-term operational monitoring of surface melt, as well as offering an independent estimate of surface melt over the past 45 years since the onset of the satellite era.

How to cite: Di Biase, V., Kuipers Munneke, P., Wouters, B., van den Broeke, M., and van Tiggelen, M.: Estimating Antarctic surface melt rates using passive microwave data calibrated with weather station observations., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8060, https://doi.org/10.5194/egusphere-egu25-8060, 2025.