Dimitrios Natsiopoulos

Validation of GOCE/GRACE Satellite Only and Combined Global Geopotential Models Over Greece in the Frame of the GOCESeaComb Project

The GOCESeaComb project, funded by ESA in the frame of the PRODEX program, aims to utilize GOCE data within combination schemes in order to achieve high-quality and accuracy predictions related to Earth’s gravity field, sea level and dynamic ocean topography. In this work the results from the detailed validation of the latest GOCE, GOCE/GRACE and combined global geopotential models are presented referring to the fourth release of the models and the various strategies (TIM, DIR, GOCO, EIGEN-S/c) employed for their determination. The validation is performed following two approaches. The first one refers to the evaluation of the GGMs signal and error in the form of the provided degree and error variances. The second refers to an external evaluation of the GGMs against local gravity, GPS/Leveling data and deflections of the vertical. In this validation step we follow a spectral enhancement approach of GOCE GGMs, where EGM08 is used to fill-in the medium and high-frequency content along with RTM effects for the high and ultra high part. From the evaluation with GPS/Levelling benchmarks, it is concluded that the GOCE/GRACE GGMs provide improved accuracies compared to EGM2008 by about 2 cm in the spectral range between d/o 120–230. Finally, GOCE/GRACE GGMs manage to provide the same, as EGM2008, level of reduction to the local gravity anomalies, with a standard deviation at the 6.1–6.2 mGal level and marginally better residuals, at the sub-arcsec level in the reduction of deflections of the vertical.

GOCE Variance and Covariance Contribution to Height System Unification

The definition and realization of vertical datum is a key concept in support of not only geodetic works but also for surveying and hydraulic studies to name a few. In the GOCE era, this is customarily done by estimating height and/or geopotential offsets with respect to a conventional reference geopotential value or to available GNSS/Leveling observations on trigonometric BMs and a GOCE-based geoid. This work investigates the influence of GOCE errors in the determination of the Hellenic Local Vertical Datum. This is facilitated through a least-squares adjustment of collocated GNSS/Leveling and GOCE geoid heights over a network of 1,542 BMs. TIM-R5, GOCO05s and GOCO05c Global Geopotential Models (GGMs) are used for representing the contribution of GOCE and GRACE to the Earth’s gravity field. First, a weighted adjustment is carried out employing the GGMs commission error as indicative of the geoid height variance for all stations. Then, full variance-covariance matrices of the GGMs are employed for utilizing realistic GOCE error information and investigating their influence on the adjustment results. Using the available GNSS/Leveling formal errors, a Variance Component Estimation (VCE) is performed to evaluate height (h, H, N) error matrices and assess the stochastic model for the corresponding observational noise. VCE is used to address the impact of a simplified uniform variance assumption for all geoid height data on the final prediction variances in contrast to using the full covariance matrices. Finally, zero-level geopotential values are estimated for the Greek mainland following weighting schemes as the ones described above.

SLA Determination in Coastal Areas Using Least-Squares Collocation and Cryosat-2 Data

Satellite altimetry has provided during the last 30 years an unprecedented amount of high-resolution and high-accuracy data for the state of the oceans. With the latest altimetric satellites utilizing the SAR and SAR-in modes, reliable sea surface heights close to the coastline can be determined more efficiently. The main purpose of this paper is to estimate Sea Level Anomalies (SLAs) close to the coastline and to areas where data are absent, while Least Squares Collocation (LSC) has been used to carry out the prediction. The selected study area is the entire Mediterranean Sea and the estimation of SLA values was carried out using raw Cryosat-2 observations. For LSC to be applied, empirical and analytical covariance function models are defined and evaluated for estimating SLAs within 10° block windows. In order to investigate the accuracy of the analytical covariance functions that provide the most accurate results, prediction has been carried out at a single point, randomly selected in the Greek region being close to the coastline. From the analysis carried out, three types of analytical covariance functions were deemed as the optimal ones, providing a mean prediction accuracy at the 3.7 cm level. These models were then used for the SLA estimation at the 10° windows, specifying local empirical and analytical covariance function models. The prediction accuracies achieved range between 3.7 cm and 12.5 cm depending on the presence of islands.