Aerodynamic Roughness Retrieval at Typical Antarctic Stations Based on Multi-Source Remote Sensing

Antarctica’s aerodynamic roughness length (z0m) is crucial for surface energy exchange and atmospheric modeling, but its remote sensing estimation remains challenging due to complex ice-surface conditions and limited observations. To address these challenges, this study establishes a z0m retrieval framework derived from the Raupach model using Unmanned Aerial Vehicle (UAV), Reference Elevation Model of Antarctica (REMA), and Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) datasets at three representative Antarctic sites. The results show that UAV benchmarks yield mean z0m values of 0.009795, 0.011597, and 0.005203 m at Zhongshan Station, Great Wall Station, and Qinling Station, respectively. In experiments with ICESat-2 data, z0m derived from ATL06 demonstrates accuracy comparable to that from ATL03 (RMSE = 7.45 × 10−6 m), with the best performance obtained at a 2 km window. Spatially, the agreement with UAV-derived z0m decreases in the order: REMA > ICESat-2 (IDW-interpolated). The accuracy of REMA and ICESat-2 decreased with terrain complexity, from ice-free zones to the ice-shelf front and finally to the steep ice sheet margin. The elevation and slope variations emerge as dominant controls of z0m spatial patterns. This study demonstrates the complementary strengths of UAV, REMA, and ICESat-2 datasets in Antarctic aerodynamic roughness estimation, providing practical guidance for data selection and methodology optimization. This study develops an improved z0m retrieval method for Antarctica, clarifies the applicability and limitations of UAV, REMA, and ICESat-2 data, and provides methodological and data support for simulations of near-surface atmospheric parameters in Antarctica region.