Forecast impact studies of zenith total delay data from European near real‐time GPS stations in Météo France 4DVAR

Abstract

Several networks of Global Positioning System receiving stations over Europe send their data to several processing centers to generate atmospheric Zenith Total Delay (ZTD) observations. Thanks to the efforts of the Targeting Optimal Use of Global Positioning System Humidity measurements in meteorology project, these observations combining surface pressure and total precipitable water information in the atmosphere have been delivered to the operational meteorological centers in near real‐time since 2004. This paper presents forecast impact trials of such ZTD observations in a global Four‐Dimensional Variational (4DVAR) assimilation and forecasting system. The implementation of the ZTD assimilation in the 4DVAR system is described, including a preprocessing developed specifically for the ZTD data. The preprocessing involves a time averaging procedure of the observations in order to ensure consistency with the resolution of the 4DVAR, a bias correction, and a station selection based on χ2 tests of the normality of the observation minus first‐guess differences. Three forecast trials were conducted: winter, spring, and summer 2005. These trials cover various meteorological conditions and a total of about 10 weeks of assimilation. All three trials suggest a positive impact of the ZTD data in helping constrain the synoptic circulation in 1 to 4 day forecasts. In the spring and the summer trials, the impact of the ZTD data also shows positively on the prediction of precipitation patterns as indicated by improved Quantitative Precipitation Forecast scores for total precipitation forecasts over France between +12 and +36 hours. We also assess in this paper ZTD observation and background errors.

An observing‐system experiment with ground‐based GPS zenith total delay data using HIRLAM 3D‐Var in the absence of satellite data

“…Receiver-station-dependent observation biases have been reported to characterize the GPS ZTD observing system (Gustafsson, 2002;Poli, et al, 2007). The source of the biases is unknown, and the role of geodetic pre-processing cannot be excluded.…”

“…Retrieval of ZTD from geodetic GPS data processing makes use of fewer assumptions than the retrieval of PW; in fact, the retrieval of PW from GPS measurements requires the estimation of ZTD as an intermediate step. Therefore, significant attention has been placed on the data assimilation of ZTD observations, instead of PW, during the past decade (De Pondeca and Zou, 2001;Gustafsson, 2002;Vedel and Huang, 2004;Poli, et al, 2007;Macpherson, et al, 2008;Yan, et al, 2009). These studies differ from each other in terms of NWP system implementation, grid spacing, domain size and experiment time period.…”

“…It is possible to estimate ZTD at each receiver station with a temporal resolution of the order of a few minutes. These observations are nowadays assimilated in operational numerical weather prediction (NWP) systems at several meteorological institutes (Poli, et al, 2007;Yan, et al, 2009). The new observation type is considered welcome by the meteorological community, because of the limitations of traditional observing systems for atmospheric water vapour.…”

“…The source of the biases is unknown, and the role of geodetic pre-processing cannot be excluded. In most impact studies, the ZTD observation biases are corrected by relatively simple algorithms, such as using a three-or ten-day running mean of ZTD observation minus background as an estimate of the bias at each receiver station (Gustafsson, 2002;Macpherson, et al, 2008), or applying a static bias correction at each receiver station (Poli, et al, 2007;Yan, et al, 2009). Air-massdependent bias-correction algorithms have also been tested (R. Randriamampianina, personal communication).…”

Retrieving high‐resolution tropospheric gradients from multiconstellation GNSS observations

“…The zenith total delay (ZTD), which is closely related to the integrated water vapor above the station, is the basic observable in GPS meteorology [Bevis et al, 1992]. Currently, the GPS-derived ZTD data are assimilated operationally at several weather agencies worldwide [e.g., Poli et al, 2007]. These centers have shown the benefit of GPS ZTD for short-term severe precipitation forecast [Karabatic et al, 2011;Dousa and Vaclavovic, 2014].…”