ALBERT

Description: Based on the large success of GRACE and GRACE-FO and their contributions to climate change research, there is a large interest in Germany to continue mass change measurements. Since 2020 GFZ and the German Space Agency at DLR have investigated a mission concept together with NASA based on a GRACE-like concept with a fully redundant Laser Ranging Interferometer (LRI). A Phase A study was successfully performed in 2022 with significant support of JPL. In October 2022 the German Parliament secured funds for the German mission elements Launcher, LRI optical components, Mission Operations and Science Data System (SDS). MPG and GFZ will additionally provide significant funding for LRI development and testing, SDS and Mission Operations after launch. To realize the GRACE-FO successor with launch not later than 2028 DLR is currently in close contact with NASA for the implementation of the next joint US/German Gravity mission. The GRACE-FO successor could be the first pair (P1) of a hybrid “Bender” constellation if combined with a second inclined pair (P2). The realization of this Mass-change And Geoscience International Constellation is currently discussed between ESA and NASA. P2 will fly lower than P1 and will be based on advanced instrumentation. Therefore, Phase A also investigated the option to add adapted MicroStar accelerometers to the baseline GRACE-FO like accelerometer on each P1 satellite as technology demonstrator for P2. We will present the current P1 mission status from a German view and discuss further steps towards realization.

Description: The GRACE and GRACE-FO missions have been fundamental in establishing a near-continuous time series of global mass transport since 2002. However, gravity field recovery using these mission data includes errors limiting the spatial and temporal resolution of gravity field solutions. The primary error contributions arise from instrument noise, temporal aliasing errors, uncertainties in the de-aliasing models, and imperfect ocean tide models. Particularly the latter will remain a limiting factor in determining high-resolution gravity fields from Next-Generation Gravity Missions.The topic has been investigated within the DFG research unit NEROGRAV and ESA´s Third Party Mission Program. One of the projects concerns stochastic modeling of ocean tide background models utilizing covariance information for eight major tidal constituents. The repeatable pattern of the tidal signal enables the extraction of uncertainty information by an ensemble of different ocean tide models. This information is introduced into the gravity field recovery process as a covariance matrix while expanding the parameter space by additional tidal parameters.An overview is provided of the recovered monthly gravity fields from GRACE/GRACE-FO when applying this covariance information. Additionally, realistic simulations have been performed for GRACE-like and MAGIC constellations to assess the impact that covariance information has on tidal errors and tidal constituents which have been co-estimated over one year and used to generate an improved ocean tide model for gravity field recovery. It is shown that the application of ocean tide covariance information contributes to the reduction of temporal aliasing caused by the mismodeling of ocean tide background models.

Description: In this study, basic interpolation and machine learning data augmentation were applied to scarce data used in Water Quality Analysis Simulation Programme (WASP) and Continuous Stirred Tank Reactor (CSTR) that were applied to nitrogenous compound degradation modelling in a river reach. Model outputs were assessed for statistically significant differences. Furthermore, artificial data gaps were introduced into the input data to study the limitations of each augmentation method. The Python Data Analysis Library (Pandas) was used to perform the deterministic interpolation. In addition, the effect of missing data at local maxima was investigated. The results showed little statistical difference between deterministic interpolation methods for data augmentation but larger differences when the input data were infilled specifically at locations where extrema occurred.

Description: Being part of the GRACE/GRACE-FO Science Data System, the GFZ German Research Centre for Geosciences is one of the official Level-2 processing centers routinely providing monthly gravity models. These models are used by a wide variety of geoscientists to infer mass changes mainly at the Earth’s surface. Currently, the operationally processed monthly gravity fields are still based on release 6 (RL06) standards, but developments in view of a reprocessed and improved GFZ RL07 time series are already ongoing. Most of these improvements have been developed within the Research Unit “New Refined Observations of Climate Change from Spaceborne Gravity Missions” (NEROGRAV) funded by the German Research Foundation DFG. After a successful first phase, the second three years phase of NEROGRAV has started at the beginning of this year. Regarding an advanced gravity field processing strategy for RL07, the main focus is on an optimized stochastic modelling of: (1) instrument errors for the main observations (K-band/LRI ranging, GPS, and accelerometer), and (2) background model errors for ocean tides and non-tidal atmosphere and ocean de-aliasing (AOD), making use of respective variance-covariance matrices. This presentation provides an overview of the main outcomes of the advanced processing strategies. Details on the applied stochastic modelling approaches will be discussed. Preliminary monthly gravity field results will be presented and compared to current GFZ RL06 solutions.

Description: 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.

Description: Monthly gravity field recovery using data from the GRACE and GRACE Follow-On missions includes errors limiting the spatial and temporal resolution of the estimated gravity fields. The major error contributions, besides the noise of the accelerometer instruments, arise from temporal aliasing errors due to imperfections in the non-tidal atmospheric and oceanic de-aliasing models and ocean tide models. We derive uncertainty information for the eight major tidal constituents from five different ocean tide models and introduce it into the gravity field recovery process in terms of a constrained normal equation system while expanding the parameter space by additional tidal parameters to be adjusted. We prove the effectiveness of the ocean tide variance-covariance information through realistic simulations and we assess its potential based on microwave and laser interferometer observations from the GRACE Follow-On mission. We show that errors are reduced by more than 20% ocean wRMS for a Gaussian filter radius of 300 km if uncertainty information for ocean tides is considered and stochastic modeling of instrument errors is applied, compared to the latest GFZ release 6.1. Our results also show the limited visibility of the effectiveness of the ocean tide variance-covariance information due to the dominating error contribution of non-tidal atmospheric and oceanic mass variations. Additionally, we investigate the option of estimating ocean tide parameters over a 1-year period while including ocean tide uncertainty information in order to improve ocean tide background modeling.