|Abstract:||Accurate estimation of the Precipitable Water Vapour (PWV) is hence crucial for weather forecast and climate studies. The Global Navigation Satellite System (GNSS) data is generally used for continuous, accurate, all-weather and realtime PWV. For this, one has to compute the mean tropospheric temperature which is generally modelled as a linear function depending on the air surface temperature. The parameters for a mean tropospheric temperature model are usually derived using radiosonde data which is expensive and covers only a small area. In this work, we propose to use temperature and water vapour profiles from satellite data to derive parameters of the mean tropospheric temperature models using the Extended Kalman Filter (EKF) supposing that the air surface temperature is periodic. The satellite data is obtained from the Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU) board on NASA Aqua satellite and available for free. The satellite has also global coverage and passes over a specific region on Earth twice a day and hence appropriate for local and global mean tropospheric temperature model derivation. We also show that the mean error of the derived PWV is reduced when the derived local model is used compared to when a global model is used for PWV estimation in Bangkok from January to November 2015. Keywords—Precipitable Water Vapour (PWV), Global Navigation Satellite System (GNSS), Mean atmospheric temperature, Atmospheric Infrared Sounder (AIRS), Advanced Microwave Sounding Unit (AMSU), Atmosphere modelling using satellite data|
Proceedings of the 29th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2016)
September 12 - 16, 2016
Oregon Convention Center
|Pages:||1642 - 1648|
|Cite this article:||
Suwantong, Rata, Satirapod, Chalermchon, Srestasathiern, Panu, Kitpracha, Chaiyaporn, "Deriving the Mean Tropospheric Temperature Model using AIRS and AMSU for GNSS Precipitable Water Vapour Estimation," Proceedings of the 29th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2016), Portland, Oregon, September 2016, pp. 1642-1648.
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