the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
HUST-Grace2024: a new GRACE-only gravity field time series based on more than 20 years satellite geodesy data and a hybrid processing chain
Abstract. To improve the accuracy of monthly temporal gravity field models for Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) mission, a new series named HUST-Grace2024 is determined based on the updated L1B dataset (GRACE L1B RL03 & GRACE-FO L1B RL04) and the newest atmosphere and ocean de-aliasing product (AOD1B RL07). Compared to the previous HUST temporal gravity field model releases, we made some improvements on both updating background models and processing chain as follows. (1) During the satellite onboard events, the intersatellite pointing angles are calculated to pinpoint the outliers in K-band range rates (KBRRs) and accelerometer observations. To exclude outliers, the advisable threshold is respectively 50 mrad for KBRRs and 20 mrad for accelerations. (2) To relieve the impacts of KBRR noise in different frequencies, a hybrid data weighting method is proposed. Kinematic empirical parameters are used to reduce the low frequency noise, while a stochastic model is designed to relieve the impacts of random noise above 10 mHz. (3) a fully-populated scale factor matrix is used to improve the quality of accelerometer calibration. Analysis in spectral and spatial domain is then implemented, which demonstrates that HUST-Grace2024 has a noticeable reduction of 10 % to 30 % in noise level and remains consistent amplitudes over 48 basins in singal content compared with the official GRACE and GRACE-FO solutions. These evaluations confirm that our aforementioned efforts lead to a better temporal gravity field series.
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Status: open (until 15 May 2024)
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CC1: 'Comment on essd-2024-39', Shuang Yi, 03 Apr 2024
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The improvement relative to official gravity solutions is impressive. The improvement may come from 1) new accelerometer product, 2) new AOD1B product, 3) algorithm in the manuscript. I would like to see how much of the improvement comes from the new products, and how much comes from the algorithm, thus consolidating the contribution of this work. I suggest the authors add such a controlled variable experiment.
Fig. 8, the HUST result is better over the CSR result globally, with the exception in western Pacific. Is there a reason for this?
Page 13, L18, a typo in ‘shown’
Citation: https://doi.org/10.5194/essd-2024-39-CC1
Data sets
HUST-Grace2024: GRACE and GRACE Follow-On monthly gravity field solution Hao Zhou et al. https://dataservices.gfz-potsdam.de/panmetaworks/review/d8ed23eb2f84c503cf70494fc827800197693e1100b3a4b8976e9f9a1eb0d323-icgem/
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