ITSG-Grace2018 is a new series of GRACE-only gravity field solutions based on reprocessed GRACE observation data (L1B RL03) and the latest atmosphere and ocean dealiasing product (AOD1B RL06). It includes unconstrained monthly and constrained daily solutions, as well as a high-resolution static gravity field. Compared to the previous ITSG release, we implemented a number of improvements within the processing chain and use updated background models. In an effort to better model all known error sources, we propagate synthetic orientation uncertainties of the star camera assembly to the antenna offset correction for intersatellite ranging observations. This enables the disentanglement of the stationary noise of the K-Band system and the nonstationary noise of the antenna offset correction. We further incorporated uncertainties of the atmosphere and ocean dealiasing product to reduce temporal aliasing effects. To mitigate errors in the applied ocean tide model, we used constrained GRACE estimates of selected tidal constituents as an additional background model. Variability over quiet ocean areas suggests a 27% to 46% lower noise level compared to the current spherical harmonic solutions of the official processing centers (300 km Gaussian filter applied). To ensure that the low noise floor is not accompanied by signal loss, we examined drainage basin averages, which showed consistent amplitudes with the official GRACE time series. These evaluations lead to the conclusion that ITSG-Grace2018 is a state-of-the-art GRACE time series which exhibits an excellent signal-to-noise ratio.

For further improvements of gravity field models based on Gravity Recovery and Climate Experiment (GRACE) observations, it is necessary to identify the error sources within the recovery process. Observation residuals obtained during the gravity field recovery contain most of the measurement and modeling errors and thus can be considered a realization of actual errors. In this work, we investigate the ability of wavelets to help in identifying specific error sources in GRACE range-rate residuals. The multiresolution analysis (MRA) using discrete wavelet transform (DWT) is applied to decompose the residual signal into different scales with corresponding frequency bands. Temporal, spatial, and orbit-related features of each scale are then extracted for further investigations. The wavelet analysis has proven to be a practical tool to find the main error contributors. Besides the previously known sources such as K-band ranging (KBR) system noise and systematic attitude variations, this method clearly shows effects which the classic spectral analysis is hardly able or unable to represent. These effects include long-term signatures due to satellite eclipse crossings and dominant ocean tide errors.

For missions such as GRACE, precise knowledge of the satellite's attitude is a fundamental requirement for the realization of the intersatellite ranging principle. It is not only essential for the realization of the precise in-orbit intersatellite pointing but also for the recovery of accurate temporal gravity field models. Here, we present a comparative study of two attitude datasets. One of them is the standard SCA1B RL02 datasets provided by JPL NASA, and another is a fused attitude dataset computed at TU Graz, based on the combination of ACC1B angular accelerations and SCA1B quaternions. Furthermore, we also present the impact of the attitude datasets on the intersatellite range measurements by analyzing their residuals. Our analysis reveals the significant improvement in the attitude due to the reprocessed product and reduced value of residuals computed from the reprocessed attitude.

The Gravity Recovery And Climate Experiment (GRACE) mission has enabled the study of the Earth’s timevariable gravity field with unprecedented accuracy. Its successor, the GRACE-FO mission, is scheduled for launch in spring 2018. GRACE-FO is a quasi-replica of GRACE, and pursues the primary objectives of GRACE. For this purpose, evolved versions of the GRACE instruments (KBR, GPS, ACC) will be used and the attitude determination will be based on three star camera (SCA) heads instead of two. Additionally, GRACE-FO will serve as a technology demonstrator, implementing the first Laser Ranging Interferometer (LRI) between two satellites in orbit.

For more than 14 years, the Gravity Recovery and Climate Experiment (GRACE) mission has provided information about Earth's gravity field with unprecedented accuracy. The twin satellites GRACE-A and GRACE-B are both equipped with a three-axis electrostatic accelerometer, measuring the non-gravitational forces acting on the spacecraft. In order to make use of the uncalibrated Level-1B accelerometer (ACC1B) data during gravity field recovery, bias and scale parameters have to be estimated.The proposed calibration method is a two-step approach and makes use of modeled non-conservative accelerations. The simulated non-conservative accelerations serve as reference for the a priori accelerometer calibration, i.e. for the ACC1B data. During gravity field recovery the calibration parameters are re-estimated. Several calibration parameters for the GRACE accelerometers using different methods have already been published. The aim of our study was primarily to analyze the temperature-dependent behavior of the accelerometer scale factors and biases, and the impact of the parametrization of scale factors and biases on the recovered gravity field solutions; but not to obtain calibrated accelerometer data.Within the ITSG-Grace2016 release, the accelerometer biases are estimated daily using uniform cubic basis splines (UCBS), the scale factors are also estimated daily using a fully-populated scale factor matrix. Therefore, not only the scale factors in along-track, cross track, and radial direction are estimated, but also the non-orthogonality of the accelerometer axes (cross-talk) and the misalignment between the Accelerometer Frame (AF) and Science Reference Frame (SRF) are taken into account. The time evolution of the estimated calibration parameters over the whole GRACE period (2002-04 to 2016-01) shows a clear temperature-dependency for both scale factors and biases. Using this new approach, the estimates of the C20 coefficient significantly improve, with results now comparable to Satellite Laser Ranging (SLR) solutions. Based on the achieved results, we suggest the presence of a clear temperature-dependent behavior and the presence of off-diagonal elements in the accelerometer scale factor matrix. (C) 2016 COSPAR. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.

The project European Gravity Service for Improved Emergency Management (EGSIEM) of the Horizon 2020 Framework Programme for Research and Innovation of the European Commission has started in January 2015. EGSIEM shall demonstrate that observations of the redistribution of water and ice mass derived from the current GRACE mission, the future GRACE-FO mission, and additional data provide critical and complementary information to more traditional Earth Observation products and open the door for innovative approaches to flood and drought monitoring and forecasting. We give an overview of the current status of the project and present the latest results from the three key objectives that EGSIEM shall address: 1) to establish a scientific combination service to deliver the best gravity products for applications in Earth and environmental science research based on the unified knowledge of the European GRACE community, 2) to establish a near real-time and regional service to reduce the latency and increase the temporal resolution of the mass redistribution products, and 3) to establish a hydrological and early warning service to develop gravity-based indicators for extreme hydrological events and to demonstrate their value for flood and drought forecasting and monitoring services. All of these services are tailored to the various needs of the respective communities.

The project GRAZIL addresses the highly accurate recovery of the lunar gravity field using intersatellite Ka-band ranging (KBR) measurements collected by the Lunar Gravity Ranging System (LGRS) of the Gravity Recovery And Interior Laboratory (GRAIL) mission. Dynamic precise orbit determination is an indispensable task in order to recover the lunar gravity field based on LGRS measurements. The concept of variational equations is adopted to determine the orbit of the two GRAIL satellites based on radio science data. In this contribution we focus on the S-band two-way Doppler data collected by the Deep Space Network.