Quality aspects of the Wegener Center multi-satellite GPS radio occultation record OPSv5.6

Abstract

Abstract. The demand for high-quality atmospheric data records, which are applicable in climate studies, is undisputed. Using such records requires knowledge of the quality and the specific characteristics of all contained data sources. The latest version of the Wegener Center (WEGC) multi-satellite Global Positioning System (GPS) radio occultation (RO) record, OPSv5.6, provides globally distributed upper-air satellite data of high quality, usable for climate and other high-accuracy applications. The GPS RO technique has been deployed in several satellite missions since 2001. Consistency among data from these missions is essential to create a homogeneous long-term multi-satellite climate record. In order to enable a qualified usage of the WEGC OPSv5.6 data set we performed a detailed analysis of satellite-dependent quality aspects from 2001 to 2017. We present the impact of the OPSv5.6 quality control on the processed data and reveal time-dependent and satellite-specific quality characteristics. The highest quality data are found for MetOp (Meteorological Operational satellite) and GRACE (Gravity Recovery and Climate Experiment). Data from FORMOSAT-3/COSMIC (Formosa Satellite mission-3/Constellation Observing System for Meteorology, Ionosphere, and Climate) are also of high quality. However, comparatively large day-to-day variations and satellite-dependent irregularities need to be taken into account when using these data. We validate the consistency among the various satellite missions by calculating monthly mean temperature deviations from the multi-satellite mean, including a correction for the different sampling characteristics. The results are highly consistent in the altitude range from 8 to 25 km, with mean temperature deviations less than 0.1 K. At higher altitudes the OPSv5.6 RO temperature record is increasingly influenced by the characteristics of the bending angle initialization, with the amount of impact depending on the receiver quality.

Precise Orbit Determination for Climate Applications of GNSS Radio Occultation including Uncertainty Estimation

“…As secondary mission goal RO instrumentation was tested on both GRACE satellites for shorter periods before continuous activation of RO measurements on 22 May, 2006 on GRACE-A [27]. The majority of measurements were obtained by GRACE-A intermitted by shorter periods of occultations by GRACE-B (Jul-Dec 2014, Jun-Oct 2015, Apr-Sep 2016) when swapping maneuvers took place, making GRACE-B the trailing satellite [16]. Therefore, we limit the evaluations in this paper to the quality assessment of GRACE-A, seen as representative for both flight models.…”

“…While the quality and high accuracy of RO in the upper-troposphere and lower-stratosphere regions is well-acknowledged (e.g., [14][15][16]) and high consistency has been assessed between different RO retrievals of leading international processing centers [10,17,18], a rigorous uncertainty estimation and propagation throughout the entire RO retrieval remains an important but incomplete task. In addition, the former occultation processing system at WEGC [16] lacks this utility since the retrieval starts from external excess phase data and thus does not tie to the raw measurements and the physical unit of time. The new Reference Occultation Processing System (rOPS) [19,20] developed at WEGC, on the contrary, aims to establish such a fully traceable processing comprising all retrieval steps [19,21,22].…”

Tropical convection regimes in climate models: evaluation with satellite observations

“…RO data from different missions are highly consistent and agree within 0.2 K between 4 and 35 km for temperature (Scherllin-Pirscher et al, 2011a). The data, from bending angle to temperature, can be merged without intercalibration or homogenization if the same processing system is used (Schreiner et al, 2007;Foelsche et al, 2011;Angerer et al, 2017). Available RO data products include individual profiles and gridded climatologies (e.g., Ho et al, 2012;Steiner et al, 2013).…”

“…We used RO temperature and specific humidity profiles processed by the Wegener Center for Climate and Global Change (WEGC) with the Occultation Processing System (OPS) version 5.6 (Schwärz et al, 2016;Angerer et al, 2017), based on excess phase and orbit data (versions 2009.2650 and 2010.2640) from the University Corporation for Atmospheric Research (UCAR). In the OPS retrieval, bending angle is initialized at high altitudes with background data from the European Centre for MediumRange Weather Forecasts (ECMWF) short-range forecasts.…”

Integrating uncertainty propagation in GNSS radio occultation retrieval: from excess phase to atmospheric bending angle profiles

“…For CHAMP and COSMIC we set u s Lr,1 = 0.2 mm and u s Lr,2 = 0.4 mm, to roughly reflect the fact that these RO receivers are lower-cost instruments with lower gain, and thus somewhat lower tracking performance, than the RO receiver on MetOp (e.g., Luntama et al, 2008;Angerer et al, 2017).…”