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An Analysis Study of FORMOSAT-7/COSMIC-2 Radio Occultation Data in the Troposphere.
- Source :
- Remote Sensing; 2/15/2021, Vol. 13 Issue 4, p717-717, 1p
- Publication Year :
- 2021
-
Abstract
- This study investigates the Global Navigation Satellite System (GNSS) radio occultation (RO) data from FORMOSAT-7/COSMIC-2 (FS7/C2), which provides considerably more and deeper profiles at lower latitudes than those from the former FORMOSAT-3/COSMIC (FS3/C). The statistical analysis of six-month RO data shows that the rate of penetration depth below 1 km height within ±45° latitudes can reach 80% for FS7/C2, significantly higher than 40% for FS3/C. For verification, FS7/C2 RO data are compared with the observations from chartered missions that provided aircraft dropsondes and on-board radiosondes, with closer observation times and distances from the oceanic RO occultation over the South China Sea and near a typhoon circulation region. The collocated comparisons indicate that FS7/C2 RO data are reliable, with small deviations from the ground-truth observations. The RO profiles are compared with collocated radiosondes, RO data from other missions, global analyses of ERA5 and National Centers for Environmental Prediction (NCEP) final (FNL), and satellite retrievals of NOAA Unique Combined Atmospheric Processing System (NCAPS). The comparisons exhibit consistent vertical variations, showing absolute mean differences and standard deviations of temperature profiles less than 0.5 °C and 1.5 °C, respectively, and deviations of water vapor pressure within 2 hPa in the lower troposphere. From the latitudinal distributions of mean difference and standard deviation (STD), the intertropical convergence zone (ITCZ) is evidentially shown in the comparisons, especially for the NUCAPS, which shows a larger deviation in moisture when compared to FS7/C2 RO data. The sensitivity of data collocation in time departure and spatial distance among different datasets are presented in this study as well. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 13
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 149772357
- Full Text :
- https://doi.org/10.3390/rs13040717