Cosmic Gps Radio Occultation: Neural Networks for Tropospheric Profiling over the Intertropical Ocean Area

Global Positioning System (GPS) radio-occultation (RO) is provided as a global sounding technique for obtaining atmospheric profiles by integrating them in global models for numerical weather prediction and for climate change studies. The radio occultation system employs GPS receivers placed on a Low-Earth Orbit (LEO) satellite to sound the Earth’s troposphere and ionosphere evaluating the additional delay affecting a radio signal when passing through the atmosphere due to the refractivity index magnitude and its variations (Gorbunov and Sokolovskiy 1993; Rius et al. 1998). GPS radio-occultations probe the atmosphere operating under all-weather conditions because the GPS signal wavelength do not scatter by clouds, aerosols, and precipitation, preserving a relatively high vertical resolution throughout the depth of the atmosphere associated with the limbviewing geometry. This technique is limited by the horizontal resolution due to the Fresnel diffractionlimited pencil-shaped sampling volume of each measurement: each one has a horizontal resolution of about 200 km in the direction along the occulted link and a resolution of 1 km or better in the cross-link and vertical directions (Kursinski et al. 1997). In this paper we have proposed a retrieval method based on neural networks to achieve atmospheric profiles from RO in wet conditions without using temperature profile at each GPS occultation from independent observations (i.e. radiosoundings or ECMWF data). We have trained three neural