Markus Hauk

Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences

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Roland Pail

Technical University of Munich

Frank Flechtner

Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences

Michael Murböck

Technische Universität Berlin

Christoph Dahle

Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences

Josefine Wilms

Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences

Natalia Panafidina

Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences

A. Purkhauser

Technical University of Munich

Vitali Müller

Leibniz University Hannover

Petro Abrykosov

Technical University of Munich

Karl-Hans Neumayer

Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences

Cooperative Institutions

Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences

Institute of Geodesy and Geophysics

Technical University of Munich

Leibniz University Hannover

Max Planck Institute for Gravitational Physics

Chinese Academy of Sciences

Wuhan University

Huazhong University of Science and Technology

Technische Universität Berlin

University of Stuttgart

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Gravity Field Recovery Using High-Precision, High–Low Inter-Satellite Links

Remote Sensing (2019)

Markus Hauk Roland Pail

Past temporal gravity field solutions from the Gravity Recovery and Climate Experiment (GRACE), as well as current solutions from GRACE Follow-On, suffer from temporal aliasing errors due to undersampling of the signal to be recovered (e.g., hydrology), which arise in terms of stripes caused by the north–south observation direction. In this paper, we investigate the potential of the proposed mass variation observing system by high–low inter-satellite links (MOBILE) mission. We quantify the impact of instrument errors of the main sensors (inter-satellite link and accelerometer) and high-frequency tidal and non-tidal gravity signals on achievable performance of the temporal gravity field retrieval. The multi-directional observation geometry of the MOBILE concept with a strong dominance of the radial component result in a close-to-isotropic error behavior, and the retrieved gravity field solutions show reduced temporal aliasing errors of at least 30% for non-tidal, as well as tidal, mass variation signals compared to a low–low satellite pair configuration. The quality of the MOBILE range observations enables the application of extended alternative processing methods leading to further reduction of temporal aliasing errors. The results demonstrate that such a mission can help to get an improved understanding of different components of the Earth system.

Aliasing

10.3390/rs11050537

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Advanced processing strategies regarding an improved GFZ GRACE/GRACE-FO RL07 time series

Markus Hauk Christoph Dahle Josefine Wilms Murböck Michael Natalia Panafidina

GFZ, as part of the GRACE/GRACE-FO Science Data System, 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&#8217;s surface. While the current release 6 (RL06) is still operationally processed, plans and internal tests for a reprocessed GFZ RL07 time series are already in progress. In this context, advanced processing strategies are developed within the Research Unit (RU) NEROGRAV (New Refined Observations of Climate Change from Spaceborne Gravity Missions) funded by the German Research Foundation DFG. The main focus is on an improved stochastic modeling regarding both instrument data (accelerometer and inter-satellite ranging observations) as well as background models (e.g. by the utilization of covariance information for these models). At the same time, the solved-for parameter space, in particular regarding empirical accelerations, has been revised. Finally, also the potential benefit by adding observations of the laser-ranging interferometer (LRI) onboard GRACE-FO has been investigated. This poster provides an overview of the developed advanced processing strategies, and their individual and combined impact on GFZ&#8217;s Level-2 products compared to current GFZ RL06 solutions.

Ranging

10.5194/gstm2022-15

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New Methods for Linking Science Objectives to Remote Sensing Observations: A Concept Study Using Single‐ and Dual‐Pair Satellite Gravimetry Architectures

Earth and Space Science (2020)

Markus Hauk D. N. Wiese

Abstract In this manuscript, we present a new analysis tool, called space‐time‐accuracy grid (STAG) analysis, to simultaneously assess the performance of an observing system architecture across space and time. Such an analysis tool is useful to directly link science objectives (typically expressed via a targeted spatial resolution, temporal resolution, and accuracy) to the expected performance of the observing system architecture. As a proof of concept, we apply STAG analysis to analyze three potential future observing systems for mass change in the Earth system: a single pair of polar orbiting satellites (heritage Gravity Recovery and Climate Experiment and Gravity Recovery and Climate Experiment Follow‐On), two polar pairs of satellites, and a polar pair of satellites coupled with an inclined (70°) pair of satellites. Here, we demonstrate the use of STAG analysis to quantify the relative performance of each architecture across space (200–1,800 km) and time (1–30 days), offering a significantly more comprehensive assessment of performance than previous studies. Results show that the polar pair coupled with the inclined pair reduces errors (after state‐of‐the‐art post‐processing for each architecture is accounted for) relative to the single pair of satellites by 40–60% in medium spatial scales (500–1,200 km), with the greatest benefit being for longer solution (monthly) timespans. Overall, the results from this case study highlight the importance of increasing the isotropy of the observable over simply increasing the sampling frequency. Some demonstrated benefits of STAG analysis include the ability to incorporate state‐of‐the‐art post‐processing methods into the analysis and also tailor the analysis to specific geographic regions to address targeted scientific objectives.

10.1029/2019ea000922

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New Versions of the AEI-derived LRI1B dataset

Laura Müller Vitali Müller Malte Misfeldt Henry Wegener Yihao Yan

The inter-satellite distance changes of the GRACE Follow-On spacecraft are measured by the main science instrument, the K-Band Ranging (KBR) system, and by the new Laser Ranging Interferometer (LRI), which exhibits a higher precision. The official ranging data is provided by the Science Data System (SDS) in the so-called KBR1B and LRI1B data products, which are available in the latest version v04. However, the Albert Einstein Institute (AEI) in Hannover is deriving alternative LRI1B data products (v50+v52). These data sets allow us to investigate different processing strategies that might improve the quality of the ranging data.We will present the most important processing steps for the AEI-derived data products and compare them to the official SDS v04 data. The main differences in the processing regard<ul><li>the deglitching algorithm, which is essential to remove disturbances induced by thruster activations or by single event upsets</li> <li>transformation of LRI time-tags to GPS time using a smooth and at day-bounds continuous correction formed by CLK1B, TIM1B, datation reports and empirical offsets obtained by daily cross-correlating KBR and LRI (only v50)</li> <li>conversion of phase-to-range using a novel formula that was published recently and that can utilize a time-depend laser frequency (scale factor)</li> <li>light-time-correction using alternative formulas that are expected to be more precise</li> <li>tilt-to-length (TTL) coupling correction, which is similar to the antenna offset correction (AOC) in KBR1B but missing in LRI1B v04 so far.</li> </ul>Furthermore, we have implemented a quality flag to indicate special events such as sun-blinding periods or momentum transfer events that might reduce the quality of the ranging data. This allows to down-weight affected segments during gravity field recovery. By comparing LRI1B v04 and AEI-derived LRI1B data, a verification and validation of the official dataset is possible. We will conclude with some examples where the LRI1B data quality can be improved compared to the v04 results.Our LRI1B datasets are available at:&#160; https://www.aei.mpg.de/grace-fo-ranging-datasets

Ranging

10.5194/gstm2022-38

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Gravity field recovery by high-precision high-low inter-satellite links

Markus Hauk Roland Pail

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Determination of Temporal Changes in the Earth's Gravitational Field using optical Two- way Links between GALILEO and LEO Satellites

Markus Hauk Michael Murböck Roland Pail Anja Schlicht

Galileo (satellite navigation)

Earth observation

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Using stochastic information on geophysical processes for daily GRACE Kalman filter solutions

Natalia Panafidina Michael Murböck Christoph Dahle Markus Hauk Josefine Wilms

The Research Unit (RU) New Refined Observations of Climate Change from Spaceborne Gravity Missions (NEROGRAV) aims at improving the understanding and providing new information about sensor data, background models and the processing strategies for the GRACE and GRACE-FO data. The achieved improvements in the standard GRACE data processing create a possibility for improvements in the computation of gravity fields with a high temporal resolution. In the current contribution we focus on the studying the potential of daily gravity filed solutions obtained by Kalman filtering. We use in particular the NEROGRAV results on stochastic modeling of the observations and background models used in the GRACE data processing, as well as the provided stochastic information on the geophysical processes governing the variations of the gravity field on sub-monthly time scales. While the standard GRACE gravity field solutions are obtained using one month of observational data, there are on-going attempts to obtain high-quality gravity fields with a higher temporal resolution. Unlike the monthly solutions, which are computed fully independent of each other, the computation of the daily gravity fields requires taking into account the temporal correlations between the subsequent solutions. The assessment of this timely correlation is based on the knowledge of the stochastic properties of the underlying geophysical processes. In this contribution we study how the daily Kalman solutions are influenced by the stochastic information on the two main geophysical processes causing high-frequency variations in the gravity field: non-tidal atmospheric and oceanic variations and hydrology. We present results for daily gravity field solutions for several test months in the spectral and spatial domain.

10.5194/gstm2024-80

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Treatment of ocean tide aliasing in the context of a next generation gravity field mission

EGUGA (2014)

Roland Pail Markus Hauk Ilias Daras Michael Murböck A. Purkhauser

Aliasing

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Reduction of ocean tide aliasing errors in GRACE, GRACE-FO, and future mission gravity field recovery

Josefine Wilms Natalia Panafidina Markus Hauk Christoph Dahle Roman Sulzbach

The GRACE and GRACE-FO missions have been fundamental in establishing a near-continuous time series of global mass transport since 2002. However, monthly gravity field recovery using these mission data includes errors limiting the spatial and temporal resolution of the estimated gravity field solutions. Besides the noise of the accelerometer instruments, the primary error contributions arise from temporal aliasing errors due to undersampling of signals to be recovered (e.g., hydrology), uncertainties in the de-aliasing models (e.g., non-tidal atmosphere and ocean), and imperfect ocean tide models. Especially the latter will also remain one of the most limiting factors in determining high-resolution temporal gravity fields from Next-Generation Gravity Missions (NGGM).In this context, recent further developments have been made within the research unit, NEROGRAV (New Refined Observations of Climate Change from Spaceborne Gravity Missions), funded by the German Research Foundation (DFG). One of the NEROGRAV projects deals with 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 can be introduced into the gravity field recovery process as a covariance matrix while expanding the parameter space by additional tidal parameters to be estimated.This presentation provides an overview of the recovered monthly gravity fields from GRACE/GRACE-FO when applying covariance information of ocean tide errors. In addition, realistic simulations have been performed to assess the pure effect of the covariance information on ocean tide errors and the potential of co-estimating ocean tides over a longer period while considering tidal covariance information is addressed. 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.

Aliasing

Tide gauge

10.5194/egusphere-egu23-6551

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Gravity field recovery in the framework of a Geodesy and Time Reference in Space (GETRIS)

Advances in Space Research (2017)

Markus Hauk Anja Schlicht Roland Pail Michael Murböck

10.1016/j.asr.2017.01.028

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Citations (9)