Accounting for residual errors in atmosphere–ocean background models applied in satellite gravimetry

verfasst von: Linus Shihora, Zhijun Liu, Kyriakos Balidakis, Josefine Wilms, Christoph Dahle, Frank Flechtner, Robert Dill, Henryk Dobslaw
Abstract: The Atmosphere and Ocean non-tidal De-aliasing Level-1B (AOD1B) product is widely used in precise orbit determination and satellite gravimetry to correct for transient effects of atmosphere–ocean mass variability that would otherwise alias into monthly mean global gravity fields. The most recent release is based on the global ERA5 reanalysis and ECMWF operational data together with simulations from the general ocean circulation model MPIOM consistently forced with fields from the corresponding atmospheric dataset. As background models are inevitably imperfect, residual errors will consequently propagate into the resulting geodetic products. Accounting for uncertainties of the background model data in a statistical sense, however, has been shown before to be a useful approach to mitigate the impact of residual errors leading to temporal aliasing artefacts. In light of the changes made in the new release RL07 of AOD1B, previous uncertainty assessments are deemed too pessimistic and thus need to be revisited. We here present an analysis of the residual errors in AOD1B RL07 based on ensemble statistics derived from different atmospheric reanalyses, including ERA5, MERRA2 and JRA55. For the oceans, we investigate the impact of both the forced and intrinsic variability through differences in MPIOM simulation experiments. The atmospheric and oceanic information is then combined to produce a new time-series of true errors, called AOe07, which is applicable in combination with AOD1B RL07. AOe07 is further complemented by a new spatial error variance–covariance matrix. Results from gravity field recovery simulation experiments for the planned Mass-Change and Geosciences International Constellation (MAGIC) based on GFZ’s EPOS software demonstrate improvements that can be expected from rigorously implementing the newly available stochastic information from AOD1B RL07 into the gravity field estimation process.
Organisationseinheit(en): SFB 1464: Relativistische und quanten-basierte Geodäsie (TerraQ)
Externe Organisation(en): Helmholtz-Zentrum Potsdam Deutsches GeoForschungsZentrum
Max-Planck-Institut für Meteorologie
Technische Universität Berlin
Typ: Artikel
Journal: Journal of geodesy
Band: 98
ISSN: 0949-7714
Publikationsdatum: 04.2024
Publikationsstatus: Veröffentlicht
Peer-reviewed: Ja
ASJC Scopus Sachgebiete: Geophysik, Geochemie und Petrologie, Computer in den Geowissenschaften
Elektronische Version(en): https://doi.org/10.1007/s00190-024-01832-7 (Zugang: Offen)

BibTeX

@article{008f5fe6e6f44df69eebe160e5f581f9,
title = "Accounting for residual errors in atmosphere–ocean background models applied in satellite gravimetry",
abstract = "The Atmosphere and Ocean non-tidal De-aliasing Level-1B (AOD1B) product is widely used in precise orbit determination and satellite gravimetry to correct for transient effects of atmosphere–ocean mass variability that would otherwise alias into monthly mean global gravity fields. The most recent release is based on the global ERA5 reanalysis and ECMWF operational data together with simulations from the general ocean circulation model MPIOM consistently forced with fields from the corresponding atmospheric dataset. As background models are inevitably imperfect, residual errors will consequently propagate into the resulting geodetic products. Accounting for uncertainties of the background model data in a statistical sense, however, has been shown before to be a useful approach to mitigate the impact of residual errors leading to temporal aliasing artefacts. In light of the changes made in the new release RL07 of AOD1B, previous uncertainty assessments are deemed too pessimistic and thus need to be revisited. We here present an analysis of the residual errors in AOD1B RL07 based on ensemble statistics derived from different atmospheric reanalyses, including ERA5, MERRA2 and JRA55. For the oceans, we investigate the impact of both the forced and intrinsic variability through differences in MPIOM simulation experiments. The atmospheric and oceanic information is then combined to produce a new time-series of true errors, called AOe07, which is applicable in combination with AOD1B RL07. AOe07 is further complemented by a new spatial error variance–covariance matrix. Results from gravity field recovery simulation experiments for the planned Mass-Change and Geosciences International Constellation (MAGIC) based on GFZ{\textquoteright}s EPOS software demonstrate improvements that can be expected from rigorously implementing the newly available stochastic information from AOD1B RL07 into the gravity field estimation process.",
keywords = "Atmosphere–ocean mass variability, Satellite gravimetry, Stochastic modelling",
author = "Linus Shihora and Zhijun Liu and Kyriakos Balidakis and Josefine Wilms and Christoph Dahle and Frank Flechtner and Robert Dill and Henryk Dobslaw",
note = "Funding Information: This work has been supported by the ESA under contract No. 4000135530 as well as the German Research Foundation (Grant No. DO 1311/4-2) as part of the research group NEROGRAV (FOR 2736). KB is funded by the DFG via the Collaborative Research Cluster TerraQ (SFB 1464, Project-ID 434617780). Deutscher Wetterdienst (Offenbach, Germany) and the European Centre for Medium-range Weather Forecasts (Reading, U.K.) are acknowledged for granting access to ECMWF operational data. Numerical analyses were performed at Deutsches Klimarechenzentrum (DKRZ) in Hamburg (Germany) under Project-ID 0499. Calculations carried out herein were facilitated by using the Climate Data Operators software suite (Schulzweida ). We also thank J. Bonin for the constructive feedback and review ",
year = "2024",
month = apr,
doi = "10.1007/s00190-024-01832-7",
language = "English",
volume = "98",
journal = "Journal of geodesy",
issn = "0949-7714",
publisher = "Springer Verlag",
number = "4",
}