the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
AIUB-GRACE gravity field solutions for G3P: processing strategies and instrument parametrization
Neda Darbeheshti
Martin Lasser
Ulrich Meyer
Daniel Arnold
Adrian Jaeggi
Abstract. This paper discusses strategies to improve the GRACE monthly solutions computed at the Astronomical Institute of the University of Bern (AIUB) which are contributing to the Horizon 2020 project G3P - Global Gravity-based Groundwater Product. To improve the AIUB-GRACE gravity field solutions, we updated the use of the Level-1B observations and adapted the background models, and improved the processing strategies in terms of instrument screening and parametrization. We used the latest Release 3 K-Band product (KBR) and star camera data (L1B RL03), and adopted the latest Release 6 of the Atmospheric and Ocean De-aliasing (AOD1B RL06) product. For the accelerometer parametrization, we used arc-wise full scale factor matrix and arc-wise third-order polynomial biases. The new accelerometer parametrization is effective to reduce noise over the oceans in gravity field solutions especially for the late years of the GRACE mission when the thermal control was switched off. In this paper, we show that the outliers in KBR antenna offset correction (AOC) are projected into the range-rate residuals; therefore, we used the KBR AOC as the main source for outlier detection and eliminated the AOC above a threshold for all data before the gravity field processing.
- Preprint
(3109 KB) - Metadata XML
- BibTeX
- EndNote
Neda Darbeheshti et al.
Status: open (until 18 Oct 2023)
-
RC1: 'Review of essd-2023-72', Henryk Dobslaw, 04 Jul 2023
reply
The manuscript „AIUB-GRACE gravity field solutions for G3P: processing strategies and instrument parametrizations“ summarizes the analysis decisions taken at the Astronomical Institute of University of Bern (AIUB) for deriving monthly-mean gravity fields from sensor data collected by the GRACE and GRACE-FO satellite missions. Calculating gravity fields is a complex task involving the careful consideration of data from a range of different sensors (i.e., range-rate tracking, accelerometers, star cameras, GNSS navigation signals, etc.). Besides common standards & conventions, a number of choices are available to the processing centers like AIUB for individual aspects of the data pre-processing, screening, and integration. Documenting those choices as done in the current manuscript is important to foster international collaboration in order to identify the most promising ways to calculate GRACE-based gravity fields. The manuscript is generally well written and certainly fits the scope of the journal. Nevertheless, a number of comments might be considered before eventually accepting the article.
More details are needed on the outlier handling (P6L3). It seems to me that complete daily arcs are flagged and ignored, is that true at this point already? Do you have an idea about how much (potentially valid) data is removed by this step? What about options to calculate arcs that span over shorter periods of time, or that are shifted by 6 (or 12) hours?Â
The question above is also related to your statements on p10, where the elimination of whole days is described as the last stage of data screening. From the text, it is not immediately clear which approach exactly is taken for the most recent G3P release from AIUB. AIUB-RL01 does not need to be discussed again at this stage. If there are no changes with respect to AIUB-RL02, this should be stated so.Â
Results presented in Figure 7 need further analysis, in particular with respect to the months that appear to be worse than in previous releases. I suggest to explicitly map (i) the monthly-mean background model, (ii) the mean from Peter et al. (2022) and the residual obtained with both AIUB releases leading to the RMS values presented in the time-series for those months in question. Please exclude continental signals and choose a color range & spatial smoothing that amplifies signals in the oceans.
P1L5: RL06 is not the latest release of AOD1B anymore, since release 07 is already available (https://doi.org/10.1093/gji/ggad119). I suggest to skip the word „latest“ and mention only that RL06 is now incorporated instead of RL05, which makes this processing choice consistent with the RL06 gravity fields of both the SDS and many other contributors to Cost-G.Â
P3L1: „non-unit“ diagonal elements sounds odd. Please revise.
P4L1: we can not see the star camera data in eq. 1 -> star camera data is not explicitly identified in eq. 1
P21L1: Author contributions of AJ and UM might be elaborated a little further in view of, e.g., software heritage used for this work.
Citation: https://doi.org/10.5194/essd-2023-72-RC1
Neda Darbeheshti et al.
Data sets
AIUB-G3P GRACE monthly gravity field solutions Neda Darbeheshti, Martin Lasser, Ulrich Meyer, Daniel Arnold, and Adrian Jäggi https://doi.org/10.5880/icgem.2023.001
Neda Darbeheshti et al.
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
273 | 55 | 14 | 342 | 7 | 8 |
- HTML: 273
- PDF: 55
- XML: 14
- Total: 342
- BibTeX: 7
- EndNote: 8
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1