We will present our atmospheric physics contribution to the New Refined Observations of Climate Change from Spaceborne Gravity Missions (NEROGRAV) research group, which is funded by the German Research Foundation (DFG). The goal of NEROGRAV is to develop new analysis methods and modeling approaches to improve the current data analysis of the GRACE and GRACE-FO missions. Our contribution to this research unit is to is to (re)analyze data fields on horizontal grid sizes below 10 km from non-hydrostatic regional atmospheric models: the 1995-2019 COSMO-REA6 regional reanalysis and the July 2021 ICON-EU/D2 analyses. From these models, the mass densities of dry air and all water phases (gaseous, liquid clouds and rain, icy snow, sleet, and hail) are available in each of the 40-50 vertical layers, so that the total local and column-by-column atmospheric mass density can be calculated without using the hydrostatic assumption.
Current non-hydrostatic, high-resolution atmospheric models run under some idealizations (e.g., assumption of a perfect sphere, spatially constant gravitational acceleration, approximation of a flat atmosphere) that are inconsistent with the real measurements of the GRACE/GRACE-FO missions. Furthermore, high-resolution atmospheric model data are currently only available within the CORDEX-EU domain, which covers the North Atlantic-European region, or an even smaller domain. The results to be presented will answer the following questions: (1) Do the model idealizations cause discrepancies with respect to the GRACE/GRACE-FO measurements that are larger than the sum of the actual measurement uncertainties and the uncertainties resulting from the remaining dealiasing models? (2) Can the idealizations be corrected to achieve better agreement with the GRACE/GRACE-FO data without sacrificing the underlying model dynamics, e.g. by introducing additional gradients in the models? (3) Do extreme weather events, such as heavy rainfall observed in the Ruhr/Ahr/Erft/Maas basin in July 2021, cause mass variations that exceeds typical GRACE/GRACE-FO uncertainties? And finally, (4) does high-resolution but regional atmospheric mass variability leave a statistically significant fingerprint in the global loading coefficients?
How to cite: Friederichs, P., Dixit, S., Kracheletz, M., Springer, A., Mielke, C., Kusche, J., and Hense, A.: Atmospheric mass variations from high-resolution, non-hydrostatic atmospheric models and their influence on dealiasing of GRACE/GRACE-FO data sets, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-456, https://doi.org/10.5194/ems2022-456, 2022.
