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Content archived on 2024-05-14

Climate and environmental Monitoring with GPS Atmospheric Profiling.

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

A prototype system processing all intermediate steps between the extraction of raw data into international data formats orbit determination and derivation of atmospheric profiles of pressure temperature and humidity has been developed. Data from the Oorsted satellite and to some extent data from GPS/MET has been used for the processing and the validation of the developed software. Validation of products has been performed and tools for assimilation of the profiles into the regional numerical weather prediction models has been developed. Analysis of the impact of GPS profiles on the weather prediction has been done. Space based occultation measurements have the advantage of a global distribution which, with a sufficient number of measurements, are expected to improve numerical weather predictions and Climate Monitoring. A semi automatic “end-to-end” radio occultation processing chain has been developed, processing all steps from data retrieval , orbit calculation ,filtering, derivation of bending angles, refractivity index etc. to density, temperature and humidity profiles. Development of new techniques to process observational data ( The single frequency technique ) in order to be able to use data fro the Oorsteed satellite which was degraded to only one frequency. Although the GPS profiles are just a small addition to the existing observing systems used by the HIRLAM OI, they are able to contribute significantly to the analysis increments as shown by our results. The results from CLIMAP show that the impact on forecasts is neutral, however, with significant daily variations. This is despite the limitations in our approach: 1) Error due to the selection of ECMWF analysis and forecast as “truth” in the calculation of error statistics needed for observational errors in the analysis. 2) Errors in representation due to the short period of available data. Thus, there is hope that a significantly enhanced number of GPS RO data could contribute positively to the data assimilation system.

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