Update of the corrective model for Jason-1 DORIS data in relation to the South Atlantic Anomaly and a corrective model for SPOT-5

Abstract After recalling the principle of the Jason-1 data corrective model in relation to the South Atlantic Anomaly (SAA) developed by Lemoine and Capdeville (2006), we present a model update which takes into account the orbit changes and the recent DORIS data. We propose also here a method to the International DORIS Service (IDS) Analysis Centers (ACs) in their contribution to the ITRF2014 for adding DORIS Jason-1 data into their solutions. When the Jason-1 satellite is added to the multi-satellite solution (orbit of inclination of 66° complements the polar-orbiting satellites), the stability of the geocenter Z-translation is improved (standard deviation of 11.5 mm against 16.5 mm). In a second part we take advantage of a high-energy particles dosimeter (CARMEN) on-board Jason-2 to improve the corrective model of Jason-1. We completed a correlation study showing that the CARMEN >87 MeV integrated proton flux map averaged over the period 2009–2011 is the energy band of the CARMEN maps which are the most coherent with the one obtained from Jason-1 DORIS measurements. The model based on the Jason-1 map and the one based on the CARMEN map are then compared in terms of orbit determination and station position estimation. We derive and validate a SPOT-5 data corrective model. We determine the SAA grid at the altitude of SPOT-5 from the frequency time derivative of the on-board frequency offsets and estimated the model parameters. We demonstrate the impact of the SPOT-5 data corrective model on the Precise Orbit Determination and the station position estimation from the weekly solutions, based on two individual Analysis Centers solutions, GOP (Geodetic Observatory Pecny) and GRG ( Groupe de Recherche de Geodesie Spatiale ). The SPOT-5 data corrective model significantly improves the Precise Orbit Determination (reduction of 1.4% in 2013 of RMS of the fit, reduction of 25% in normal direction of arc overlap RMS) and the overall statistics of the station position estimation (reduction of 2% of repeatability RMS, reduction of 3–7% of geocenter variations). Moreover, the application of the data corrective model strongly reduces the individual station bias in the North component for all the SAA-affected stations and the height bias for the most affected SAA stations. The East bias is, however, not reduced by this data corrective model.