Abstract ID: 204

Aplication of GPS Radio Occultation Data to Retrieve Atmospheric Profiles Using Artificial Neural Network

The availability of GPS (Global Positioning System) radio signals has introduced a new promising remote sensing technique for the Earth’s atmosphere. GPS-based radio occultation (RO) exploits GPS signals received onboard a Low Earth Orbiting (LEO) satellite for atmospheric limb sounding. Temperature and water vapor profiles with high accuracy and vertical resolution can be derived from these measurements. The GPS radio-occultation technique requires no calibration, is not affected by clouds, aerosols or precipitation, and the occultation are almost uniformly distributed over the globe. A method based on Artificial Neural Network (ANN) to retrieve temperature and humidity profiles is presented. This technique establishes a non-linear relationship with the meteorological variables. The bending angle and refractivity index from RO were chosen as the input vectors and temperature and vapor pressure as the output vector. The radio occultation data from German CHAMP (CHAllenging Minisatellite Payload) was from December 17 (2002) up to February 15 (2003) for a South America Region (35S to 5S and 80W to 50W), at southeast. Amazonian. These retrievals were compared with the corresponding ones from the CHAMP-ISCD (CHAMP Geoscientific Research and Application), and shows that ANN is convenient and an accurate tool to get profiles. Comparisons between ANN atmospheric profiles and radiosonde data from SALLJEX (South American Low Level Jet Experiment) project, located mainly in Peru and south Brazilian Amazonia are made and its results can be provided as the guess for the iterative methods or the non-linear optimal estimation inverse method. RO can play an important role in the sounding of the Earth’s atmosphere. Due to the unique combination of high accuracy, global coverage, high vertical resolution, long-term stability and weather independent capability the technique has a wide spectrum of applications in climate monitoring, weather forecast and atmospheric research (Melbourne et al., 1994; Kursinski et al., 1997; Anthes et al., 2000; Hajj et al., 2002).

Session:  Biodiversity - Data/metadata integration and information dissemination: PPBio challenges and solutions.

Presentation Type:  Poster