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A methodology to compute GPS slant total delays in a numerical weather model

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Zus,  Florian
1.1 GPS/GALILEO Earth Observation, 1.0 Geodesy and Remote Sensing, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/bender

Bender,  Michael
1.1 GPS/GALILEO Earth Observation, 1.0 Geodesy and Remote Sensing, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/deng

Deng,  Zhiguo
Deutsches GeoForschungsZentrum;

/persons/resource/dick

Dick,  Galina
1.1 GPS/GALILEO Earth Observation, 1.0 Geodesy and Remote Sensing, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/heise

Heise,  Stefan
1.1 GPS/GALILEO Earth Observation, 1.0 Geodesy and Remote Sensing, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Shangguan,  M.
External Organizations;

/persons/resource/wickert

Wickert,  Jens
1.1 GPS/GALILEO Earth Observation, 1.0 Geodesy and Remote Sensing, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

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Zitation

Zus, F., Bender, M., Deng, Z., Dick, G., Heise, S., Shangguan, M., Wickert, J. (2012): A methodology to compute GPS slant total delays in a numerical weather model. - Radio Science, 47, 2, RS2018.
https://doi.org/10.1029/2011RS004853


https://gfzpublic.gfz-potsdam.de/pubman/item/item_245382
Zusammenfassung
A numerical algorithm based on Fermat's Principle was developed to simulate the propagation of Global Positioning System (GPS) radio signals in the refractivity field of a numerical weather model. The unique in the proposed algorithm is that the ray-trajectory automatically involves the location of the ground-based receiver and the satellite, i.e. the posed two-point boundary value problem is solved by an implicit finite difference scheme. This feature of the algorithm allows the fast and accurate computation of the signal travel-time delay, referred to as Slant Total Delay (STD), between a satellite and a ground-based receiver. We provide a technical description of the algorithm and estimate the uncertainty of STDs due to simplifying assumptions in the algorithm and due to the uncertainty of the refractivity field. In a first application, we compare STDs retrieved from GPS phase-observations at the German Research Centre for Geosciences Potsdam (GFZ STDs) with STDs derived from the European Center for Medium-Range Weather Forecasts analyses (ECMWF STDs). The statistical comparison for one month (August 2007) for a large and continuously operating network of ground-based receivers in Germany indicates good agreement between GFZ STDs and ECMWF STDs; the standard deviation is 0.5% and the mean deviation is 0.1%.