EVALUATING CRYORAD PERFORMANCE REQUIREMENTS THROUGH 0.4–2 GHZ BRIGHTNESS TEMPERATURE SIMULATIONS WITH OCEAN–SEA ICE MODELS

L. Kaleschke¹, L. Bertino², M. Brogioni³, P. Browne⁴, M. Drusch⁵, S. Hendricks¹, K. Jezek⁶, J. Johnson⁷, M. Leduc-Leballeur³, G. Macelloni³, G. Picard⁸, R. T. Tonboe⁹, X. Tian-Kunze¹

¹Sea ice physics, Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany, ²Nansen Environmental and Remote Sensing Center, Bergen, Norway, ³National Research Council Institute for Applied Physics “Nello Carrara”, Sesto Fiorentino, Italy, ⁴European Centre for Medium-Range Weather Forecasts, Reading, UK, ⁵Earth Surfaces and Interior Section (EOP-SME), Earth and Mission Science Division, European Space Agency/ESTEC, Noordwijk, The Netherlands, ⁶Byrd Polar and Climate Research Center, School of Earth Sciences of The Ohio State University, Ohio, USA, ⁷ElectroScience Laboratory, The Ohio State University, Ohio, USA, ⁸ Institut des Géosciences de l’Environnement (IGE), CNRS/UGA, Grenoble, France, ⁹Technical University of Denmark, 2800 Kgs. Lyngby, Denmark

CryoRad is a candidate satellite mission concept equipped with a broadband low-frequency microwave radiometer operating between 0.4 and 2 GHz with continuous frequency scanning. Its primary objective is to advance cryosphere science by delivering new geophysical variables critical for ocean and climate studies. CryoRad will provide temperature profiles of the Antarctic and Greenland ice sheets from surface to bedrock, previously accessible only through sparse borehole observations, and will address long-standing limitations of L-band radiometers in retrieving sea surface salinity (SSS) in cold waters. Furthermore, the mission aims to significantly improve estimates of sea ice thickness, volume, and salinity, thereby enabling a more comprehensive characterization of the polar ocean–sea ice system.

To quantify the scientific return and define radiometer performance requirements, we combine forward modeling and retrieval experiments with data from the ECMWF ORAS6 ocean reanalysis. ORAS6 includes a multicategory sea ice model with prognostic salinity, providing spatially and temporally consistent fields of sea ice concentration, thickness, volume, temperature, and salinity. These parameters serve as a physically consistent baseline for simulating CryoRad brightness temperatures using simplified one-layer emissivity models as well as more advanced retrieval frameworks. Sensitivity analyses reveal the frequency-dependent impact of ice thickness, salinity, and ocean surface properties on measured brightness temperatures, and allow us to define thresholds, breakthrough, and goal levels for uncertainty in line with WMO requirements for sea ice climate data records. Initial results show that CryoRad retrievals of sea ice thickness and volume are able to meet or surpass uncertainty requirements, whereas the retrieval of ice salinity remains more challenging and may require additional constraints.

As an outlook, we are extending these investigations with a new simulation framework using the Snow Microwave Radiative Transfer (SMRT) model in combination with the CICE sea ice model to generate brightness temperatures that are then resampled to the satellite swath geometry. This approach will deliver a synthetic dataset including both physical and satellite parameters, providing a testbed for further algorithm development and sensor performance evaluation.