Elisa Fagiolini

Using Atmospheric Uncertainties for GRACE De-aliasing: First Results

In standard gravity field processing, short-term mass variations in the atmosphere and the ocean are eliminated in the so-called de-aliasing step. Up to now the background models used for de-aliasing have been assumed to be error-free. As the accuracy assessed prior to launch could not yet be achieved in the analysis of real GRACE data, the de-aliasing process and related geophysical model uncertainties have to be considered as potential error sources in GRACE gravity field determination. The goal of this study is to identify the impact of atmospheric uncertainties on the de-aliasing products and on the resulting GRACE gravity field models. The paper summarizes the standard GRACE de-aliasing process and studies the effect of uncertainties in the atmospheric (temperature, surface pressure, specific humidity, geopotential) input parameters on the gravity field potential coefficients. Finally, the impact of alternative de-aliasing products (with and without atmospheric model errors) on a GRACE gravity field solution is investigated on the level of K-band range-rate residuals. The results indicate that atmospheric model uncertainties are small in terms of the associated spherical harmonic coefficients. The effect in terms of K-band observation residuals is negligible compared to other modeling errors.

Gravity Field Mapping from GRACE: Different Approaches—Same Results?

GFZ as part of the GRACE Science Data System (SDS) is routinely processing time-variable global gravity field models on monthly and weekly basis throughout the whole GRACE mission period. These operational products consist of spherical harmonic coefficients which are calculated based on the so-called dynamic method, i.e. integration of variational equations. As a matter of fact, these coefficients are imperfect due to different error sources such as inaccurate background models, instrument noise and inhomogeneous sampling and thus have to be filtered during post-processing in an appropriate way. Nevertheless, the current release named GFZ RL05 shows significant improvements compared to its precursors with an average error level of only about a factor of 6 above the pre-launch estimated baseline accuracy.

Earth's surface mass transport derived from GRACE, evaluated by GPS, ICESat, hydrological modeling and altimetry satellite orbits

The authors discuss a novel method based on radial basis functions for recovery of the global Earth’s gravity field from GRACE inter-satellite range-rate data. To test its performance, they authors use four independent datasets and using various metrics they compare results of the new method with respect to three global geopotential models derived from GRACE data. Obtained numerical results demonstrate that the new method can be used for global gravity field modelling as an alternative to classical spherical (spheroidal) harmonic models.

A Non-tidal Atmospheric Loading Model: On Its Quality and Impacts on Orbit Determination and C20 from SLR

Based on European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim data we model displacements of global station coordinates due to non-tidal atmospheric loading based on Farrel’s theory. We compare these displacements to publicly available external displacements. We apply our displacements to Satellite Laser Ranging (SLR) data processing over a recent 6 years period of the LAGEOS, LARES, AJISAI, STARLETTE and STELLA geodetic satellites. We assess the impact of the loading model on the orbital fits of these missions. Indeed a tiny improvement shows up. We also quantify the impact of the non-tidal loading model on the large scale figure of the Earth expressed in terms of weekly C(2,0) harmonics. It turns out that here no effect is visible.

Impact of Numerical Weather Models on Gravity Field Analysis

Atmospheric pressure variations are one of the major sources of gravity perturbations. Due to the high variability of the atmospheric masses and the sparse sampling of these by GRACE the signals alias into the observations taken by the satellites. The determination of accurate atmospheric gravity field coefficients (AGC) is indispensable for the elimination of these signals. For the determination of AGC it is state of the art to use high resolution Numerical Weather Prediction (NWP) models which take into account the time-variable three-dimensional distribution of the atmospheric mass. By subtracting the gravity spherical harmonics of a long term atmospheric mean field from the ones of the instantaneous atmosphere, the residual gravity spherical harmonic series is obtained. It describes the deviation of the actual gravity field from the mean gravity field due to atmospheric mass variations. NWP models are not perfect as they can show significant differences to in situ measurements. Further these models evolve and change throughout time, which can lead to changes in the pressure data and therefore in the AGC. In this study several aspects of NWP models are investigated, and the influence they have on the determination of the AGC is discussed. We present a strategy that was developed for dealing with changes in the NWP models, and compare our products to those of the GRACE Atmosphere and Ocean Dealiasing level-1B products and those provided by the Groupe de Recherche de Geodesie Spatiale (GRGS).

Grace time variable gravity field for monitoring natural hazards

The US/German twin satellite mission GRACE (Gravity Recovery and Climate Experiment) [1] celebrated its 10th anniversary March 17, 2012. The prime objective of GRACE is to provide detailed measurements of the static and, for the first time, also of the time-variable gravity field of the Earth. Today, GRACE delivers the most accurate map to date of the Earths long wavelength gravity field. In view of global warming it can deliver substantial information about current and future trends concerning the global hydrology cycle, ocean currents and sea level rise and help to predict their impact on human live.