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A variational data assimilation system for ground‐based GPS slant delays
Author(s) -
Järvinen Heikki,
Eresmaa Reima,
Vedel Henrik,
Salonen Kirsti,
Niemelä Sami,
de Vries John
Publication year - 2007
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.79
Subject(s) - data assimilation , global positioning system , geodetic datum , remote sensing , numerical weather prediction , computer science , troposphere , meteorology , geodesy , environmental science , algorithm , geology , geography , telecommunications
Tropospheric delay affects the propagation of the microwave signals broadcast by the Global Positioning System (GPS) satellites. Geodetic processing software enable estimation of this effect on the slanted signal paths connecting the satellites with the ground‐based receivers. These estimates are called slant delay (SD) observations and they are potentially of benefit in numerical weather prediction. The three‐dimensional variational data assimilation system of the High‐Resolution Limited‐Area Model (HIRLAM 3D‐Var) has been modified for data assimilation of the SD observations. This article describes the ground‐based GPS observing system, the SD observation operator, the estimation of the observation‐ and background‐error standard deviations, the methodology of accounting for the observation‐error correlation, and the tuning of the background quality control for this observation type. The SD data assimilation scheme is evaluated with experiments utilizing hypothetical observations from a single receiver station, as well as a single‐case experiment utilizing real observations from a regional GPS receiver network. The ability of the data assimilation system to extract the asymmetric information from the SD observations is confirmed. In terms of analysis increment structure and magnitude, SD observations are found to be comparable with other observation types currently in use, provided that the observation‐error correlation is taken into account. Copyright © 2007 Royal Meteorological Society