On the turbulent heat fluxes: A comparison among satellite-based estimates, atmospheric reanalyses, and in-situ observations during the winter climate over Arctic sea ice

• Published in: Advances in Climate Change Research
• Main Authors: Zhi-Lun Zhang, Feng-Ming Hui, Timo Vihma, Mats A. Granskog, Bin Cheng, Zhuo-Qi Chen, Xiao Cheng
• Format: Article in Journal/Newspaper
• Language: English
• Published: KeAi Communications Co., Ltd. 2023
• Subjects: Arctic sea ice; Surface energy budget; Turbulent heat flux; Satellite observation; Reanalysis; Bulk-aerodynamic formula; Meteorology. Climatology; QC851-999; Social sciences (General); H1-99; Arctic; Svalbard; Sea ice
• Online Access: https://doi.org/10.1016/j.accre.2023.04.004; https://doaj.org/article/95db13ce6f674e00be75306529f43db6

The surface energy budget is crucial for Arctic sea ice mass balance calculation and climate systems, among which turbulent heat fluxes significantly affect the air–sea exchanges of heat and moisture in the atmospheric boundary layer. Satellite observations (e.g. CERES and APP-X) and atmospheric reanalyses (e.g., ERA5) are often used to represent components of the energy budget at regional and pan-Arctic scales. However, the uncertainties of the satellite-based turbulent heat fluxes are largely unknown, and cross-comparisons with reanalysis data and in-situ observations are limited. In this study, satellite-based turbulent heat fluxes were assessed against in-situ observations from the N-ICE2015 drifting ice station (north of Svalbard, January–June 2015) and ERA5 reanalysis. The turbulent heat fluxes were calculated by two approaches using the satellite-based ice surface temperature and radiative fluxes, surface atmospheric parameters from ERA5, and snow/sea ice thickness from the pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS). We found that the bulk-aerodynamic formula based results could better capture the variations of turbulent heat fluxes, while the maximum entropy production based estimates are comparable with ERA5 in terms of root-mean-square error (RMSE). CERES-based estimates outperform the APP-X-based ones but ERA5 performs the best in all seasons (RMSE of 18 and 7 W m−2 for sensible and latent heat flux, respectively). The air–ice temperature/humidity differences and the surface radiation budget were found the primary driving factors in the bulk-formula method and maximum entropy production (MEP) method, respectively. Furthermore, errors in the surface and near-surface temperature and humidity explain almost 50% of the uncertainties in the estimates based on the bulk-formula, whereas errors in the net radiative fluxes explain more than 50% of the uncertainties in the MEP-based results.