Articles | Volume 13, issue 6
https://doi.org/10.5194/amt-13-3081-2020
https://doi.org/10.5194/amt-13-3081-2020
Research article
 | 
11 Jun 2020
Research article |  | 11 Jun 2020

Evaluation of the 15-year ROM SAF monthly mean GPS radio occultation climate data record

Hans Gleisner, Kent B. Lauritsen, Johannes K. Nielsen, and Stig Syndergaard

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Cited articles

Angerer, B., Ladstädter, F., Scherllin-Pirscher, B., Schwärz, M., Steiner, A. K., Foelsche, U., and Kirchengast, G.: Quality aspects of the Wegener Center multi-satellite GPS radio occultation record OPSv5.6, Atmos. Meas. Tech., 10, 4845–4863, https://doi.org/10.5194/amt-10-4845-2017, 2017. a, b, c
Anthes, R. A.: Exploring Earth's atmosphere with radio occultation: contributions to weather, climate and space weather, Atmos. Meas. Tech., 4, 1077–1103, https://doi.org/10.5194/amt-4-1077-2011, 2011. a
Anthes, R. A., Bernhardt, P. A., Chen, Y., Cucurull, L., Dymond, K. F., Ector, D., Healy, S. B., Ho, S.-P., Hunt, D. C., Kuo, Y.-H., Liu, H., Manning, K., McCormick, C., Meehan, T. K., Randel, W. J., Rocken, C., Schreiner, W. S., Sokolovskiy, S. V., Syndergaard, S., Thompson, D. C., Trenberth, K. E., Wee, T.-K., Yen, N. L., and Zeng, Z.: The COSMIC/FORMOSAT-3 mission: Early results, B. Am. Meteorol. Soc., 89, 313–333, https://doi.org/10.1175/BAMS-89-3-313, 2008. a
Ao, C. O., Jiang, J. H., Mannucci, A. J., Su, H., Verkhoglyadova, O., Zhai, C., Cole, J., Donner, L., Iversen, T., Morcrette, C., Rotstayn, L., Watanabe, M., and Yukimoto, S.: Evaluation of CMIP5 upper troposphere and lower stratosphere geopotential height with GPS radio occultation observations, J. Geophys. Res., 120, 1678–1689, https://doi.org/10.1002/2014JD022239, 2015. a
Beyerle, G., Schmidt, T., Michalak, G., Heise, S., Wickert, J., and Reigber, C.: GPS radio occultation with GRACE: Atmospheric profiling utilizing the zero difference technique, Geophys. Res. Lett., 32, L13806, https://doi.org/10.1029/2005GL023109, 2005. a
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Short summary
Data from GPS radio occultation (RO) instruments aboard a series of satellites have been reprocessed by the ROM SAF. We describe the monthly mean RO climate data records (CDRs) and the methods for removing sampling errors. The quality of the CDRs is evaluated, with a focus on systematic differences between satellite missions. Between 8 and 30 km, the data quality and the inter-mission differences are small enough to allow the generation of combined multi-mission data records starting in 2001.