Model Deficiencies of ERA5 Atmospheric Reanalysis Over Arctic Sea-Ice - Analysis of the Winter Surface Radiative Energy Budget by Using MOSAiC and Satellite Observations.

• Main Author: Herrmannsdörfer, Lia Francisca
• Format: Master Thesis
• Language: English
• Published: 2022
• Subjects: ERA5; AMSR-E/2; Ice Thickness; AMSR/AVHRR; MODIS; Snow Depth; MOSAiC; Surface Temperature; CryoSat-2/SMOS; Reanalysis; Long Wave Radiation; Surface Energy Budget; Arctic; Climate change; Sea ice
• Online Access: http://hdl.handle.net/10852/94237; http://urn.nb.no/URN:NBN:no-96787

As part of the global climate change the Arctic is warming rapidly. The surface energy budget is a central aspect of the Arctic system with sea ice growth and melt. However, the representation of the surface energy budget and its components has large errors in atmospheric reanalyses, which are often used for climate model comparisons, forcing of ocean and sea ice models and initialisation of climate predictions. Since observations of the Arctic surface energy budget are sparse, expeditions like MOSAiC (2019/2020) are crucial to understand the components of the Arctic system and to validate global and regional earth system and forecasting models. In order to analyse deficiencies of the surface radiative energy budget over Arctic sea ice in clear sky conditions and possible error sources, the ERA5 global atmospheric reanalysis is compared to the MOSAiC campaign data from December 2019 to February 2020 and to the pan-Arctic MODIS ice surface temperature remote sensing product. The analysis shows a surface temperature warm bias of 4 ◦ C to 6 ◦ C in clear sky conditions. Furthermore, ERA5 is not able to distinguish the observed radiative Arctic winter states, but simulates the timing of clear sky periods sufficiently. The sensitivity analysis of possible error sources, by including satellite products of snow depth and sea ice thickness, shows that the main errors are caused by insufficient ice thickness and snow depth representation in the reanalysis system.