Validation of Using SWARM to Fill-in the GRACE/GRACE-FO Gap: Case Study in Africa

<p>The American/German missions Gravity Recovery and Climate Experiment (GRACE) and the GRACE Follow-On (GRACE-FO) and the European mission (Swarm) play an important role in study of the Earth's gravity field with unprecedented high-precision and high-resolution measurements. The aim of this study is to use Swarm data to fill-in the data-gap between GRACE and GRACE-FO missions from July 2017 to May 2018, and evaluate the new datasets in Africa. We used the available data from the triple GRACE processing centers CSR, GFZ and JPL, in addition to the Swarm TVGF data provided by the Czech Academy of Sciences (ASU) and the International Combination Service for Time-variable Gravity (COST-G). The GRCAE and Swarm date have been tested in the frequency and space domains. For the frequency domain, the data assessed in two different levels: the potential degree variances and the harmonic coefficients themselves. The results show consistency between GRACE/GRACE-FO and Swarm for all processing centers. In the space domain, a comparison between GRACE/GRACE-FO and Swarm for the TWS, gravity anomaly, and the potential/geoid have been carried out. For the TWS, an artificial gap (AG) - simulating the gap between GRACE and GRACE-FO – has been artificially made in the GRACE data from July 2015 to May 2016. The GRACE AG has been filled by the two sets of the Swarm data for CSR, GFZ and JPL. The results indicated that the best agreement has been achieved between GRACE-CSR and Swarm COST-G. For the gravity anomaly and the potential/geoid, a better agreement between GRACE and Swarm data has been concluded. Eventually, we chose Swarm COST-G data to fill-in the gap between GRACE and GRACE-FO CSR in order to be used, among others, to estimate the TWS in Africa for the period from April 2002 to October 2020. This study is supported by the National Natural Science Foundations of China (NSFC) under Grants Nos. 42030105, 41721003, 41804012, 41631072, and 41874023.</p>

Explicit Construction of the Modified Spherical Harmonic Series for the Gravity Gradients and Analysis of their Characteristics

Explicit Construction of the Modified Spherical Harmonic Series for the Gravity Gradients and Analysis of their CharacteristicsThe present paper complements the research carried out in PV2008 (Petrovskaya and Vershkov, 2008), concerning the expansion of the gravity gradients in the local north-oriented reference frame in orthogonal series of modified spherical harmonics. In PV2008 procedures are developed for recovering the orthogonal bases of these series. Then an idea is briefly described how the spectral relations can be obtained between the gravity gradients and the geopotential. However no explicit procedures are demonstrated for their derivation. In the present paper successive transformations are described for each derivative which convert the initial non-orthogonal expansion into the orthogonal series. The resulting spectral relations are applied for evaluating the harmonic coefficients of these series at different altitudes, on the basis of the geopotential model EGM2008. The corresponding degree variances are estimated. The new simple expressions for the gravity gradients are convenient for various applications. In the present paper they are implemented for constructing digital colored maps for Fennoscandia region which attracts much attention of geophysicists. These maps visually demonstrate an anomalous behavior of the gravity gradients in this area.

Wind and turbulence measurements by the Middle and Upper Atmosphere Radar (MUR): comparison of techniques

The structure-function-based method (referred to as UCAR-STARS), a technique for estimating mean horizontal winds, variances of three turbulent velocity components and horizontal momentum flux was applied to the Middle and Upper atmosphere Radar (MUR) operating in spaced antenna (SA) profiling mode. The method is discussed and compared with the Holloway and Doviak (HAD) correlation-function-based technique. Mean horizontal winds are estimated with the STARS and HAD techniques; the Doppler Beam Swinging (DBS) method is used as a reference for evaluating the SA techniques. Reasonable agreement between SA and DBS techniques is found at heights from 5km to approximately 11km, where signal-to-noise ratio was rather high. The STARS and HAD produced variances of vertical turbulent velocity are found to be in fair agreement. They are affected by beam-broadening in a different way than the DBS-produced spectral width, and to a much lesser degree. Variances of horizontal turbulent velocity components and horizontal momentum flux are estimated with the STARS method, and strong anisotropy of turbulence is found. These characteristics cannot be estimated with correlation-function-based SA methods, which could make UCAR-STARS a useful alternative to traditional SA techniques.

Globally covering a-priori regional gravity covariance models

Gravity anomaly data generated using Wenzel’s GPM98A model complete to degree 1800, from which OSU91A has been subtracted, have been used to estimate covariance functions for a set of globally covering equal-area blocks of size 22.5° × 22.5° at Equator, having a 2.5° overlap. For each block an analytic covariance function model was determined. The models are based on 4 parameters: the depth to the Bjerhammar sphere (determines correlation), the free-air gravity anomaly variance, a scale factor of the OSU91A error degree-variances and a maximal summation index, N, of the error degree-variances. The depth of Bjerhammar-sphere varies from -134km to nearly zero, N varies from 360 to 40, the scale factor from 0.03 to 38.0 and the gravity variance from 1081 to 24(10µms-2)2. The parameters are interpreted in terms of the quality of the data used to construct OSU91A and GPM98A and general conditions such as the occurrence of mountain chains. The variation of the parameters show that it is necessary to use regional covariance models in order to obtain a realistic signal to noise ratio in global applications.Key words. GOCE mission, Covariance function, Spacewise approach`