Abstract
In this study, global (50°S–50°N) distribution of water vapor is investigated using COSMIC GPS RO measurements. Detailed comparisons have been made between COSMIC and high resolution GPS radiosonde measurements across 13 tropical stations and model outputs (ERA-Interim, NCEP, and JRA-25 reanalyses data sets). In comparison with independent techniques like radiosonde (Väisälä), it is found that COSMIC GPS RO wet profiles are accurate up to 7–8 km (assuming radiosonde as standard technique). In general, comparisons with corresponding seasonal means of model outputs are qualitatively in good agreement, although they differ quantitatively especially over convective regions of South America, Africa, and Indonesia. In tropical latitudes, the COSMIC specific humidity values are higher than the model outputs. Among various model outputs, ERA-Interim data set show near realistic features to that observed by COSMIC GPS RO measurements. Large asymmetry in the specific humidity distribution is observed between northern and southern hemispheres.
Highlights
Water vapor is the most important greenhouse gas in the Earth’s atmosphere, inducing about two third of the natural greenhouse effect
We mainly focus on the tropical latitudes as much of the variability is noticed in these regions
COSMIC specific humidity profile refers to 0.241N, 102.281E observed at 13 UT which corresponds to the nearest pass from Singapore
Summary
Water vapor is the most important greenhouse gas in the Earth’s atmosphere, inducing about two third of the natural greenhouse effect. Radio occultation (RO) data using Global Navigation Satellite System (GNSS) signals emerged as powerful tool while overcoming problems of traditional data sources due to their encouraging combination of high accuracy and vertical resolution, long-term stability due to intrinsic self calibration, all weather capability and global coverage of obtaining atmospheric density, pressure, temperature and water vapor profiles in the troposphere and lower stratosphere. Though we mention global distribution we restrict our discussion to topical and mid-latitudes (501S–501N), unless we mention explicitly, due to more complexities in these data set over Polar latitudes We use this data to better understand the variability of specific humidity in the troposphere on various temporal and spatial scales. We compare the variability with National Centers for Environmental Prediction-Reanalysis (NCEP-reanalysis), the Japanese 25-year reanalysis (JRA-25), and ERA-Interim reanalysis (ERA) data sets
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