Refining DORIS atmospheric drag estimation in preparation of ITRF2008

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• 作者：Marie-Line Gobinddass ; Pascal Willis ; Michel Menvielle ; Michel Diament
• 关键词：DORIS ; Geodesy ; Atmospheric drag ; Halloween geomagnetic storm ; Polar motion
• 刊名：Advances in Space Research
• 出版年：2010
• 出版时间：15 December 2010
• 年：2010
• 卷：46
• 期：12
• 页码：1566-1577
• 全文大小：1295 K

文摘

In preparation of ITRF2008, all geodetic technique services (VLBI, SLR, GPS and DORIS) are generating new solutions based on combination of individual analysis centers solutions. These data reprocessing are based on a selection of models, parameterization and estimation strategy unique to each analysis center and to each technique. While a good agreement can be found for models between groups, thanks to the existence of the IERS conventions, a great diversity still exist for parameter estimation, allowing possible future improvements in this direction. The goal of this study is to focus on the atmospheric drag estimation used to generate the new DORIS/IGN ignwd08 time series prepared for ITRF2008. We develop here a method to inter-compare different processing strategies. In a first step, by analyzing single-satellite solutions for a few weeks of data but for a large number of possible analysis strategies, we demonstrate that estimating drag coefficient more frequently (typically every 1–2 h instead of previously every 4–8 h) for the lowest DORIS satellites (SPOTs and Envisat) provides better geodetic results for station coordinates and polar motion. This new processing strategy also solved earlier problem found when processing DORIS data during intense geomagnetic events, such as geomagnetic storms. Differences between drag estimation strategies can mostly be found during these few specific periods of extreme geomagnetic activity (few days per year). In such a case, when drag coefficient is only estimated every 6 h or less often for single-satellite solution, a significant degradation in station coordinate accuracy can be observed (120 mm vs. 20 mm) and significant biases arose in polar motion estimation (5 mas vs. 0.3 mas). In a second step, we reprocessed a full year of DORIS data (2003) in a standard multi-satellite mode. We were able to provide statistics on a more reliable data set and to strengthen these conclusions. Our proposed DORIS analysis is easy to implement in all software packages and is now already used by several analysis centers of the International DORIS Service (IDS) when submitting reprocessed solutions for ITRF2008.