Abstract
AbstractPointwise GPS measurements of tropospheric zenith total delay can be interpolated to provide high‐resolution water vapor maps which may be used for correcting synthetic aperture radar images, for numeral weather prediction, and for correcting Network Real‐time Kinematic GPS observations. Several previous studies have addressed the importance of the elevation dependency of water vapor, but it is often a challenge to separate elevation‐dependent tropospheric delays from turbulent components. In this paper, we present an iterative tropospheric decomposition interpolation model that decouples the elevation and turbulent tropospheric delay components. For a 150 km × 150 km California study region, we estimate real‐time mode zenith total delays at 41 GPS stations over 1 year by using the precise point positioning technique and demonstrate that the decoupled interpolation model generates improved high‐resolution tropospheric delay maps compared with previous tropospheric turbulence‐ and elevation‐dependent models. Cross validation of the GPS zenith total delays yields an RMS error of 4.6 mm with the decoupled interpolation model, compared with 8.4 mm with the previous model. On converting the GPS zenith wet delays to precipitable water vapor and interpolating to 1 km grid cells across the region, validations with the Moderate Resolution Imaging Spectroradiometer near‐IR water vapor product show 1.7 mm RMS differences by using the decoupled model, compared with 2.0 mm for the previous interpolation model. Such results are obtained without differencing the tropospheric delays or water vapor estimates in time or space, while the errors are similar over flat and mountainous terrains, as well as for both inland and coastal areas.
Highlights
Time-varying two-dimensional precipitable water vapor (PWV) fields are used in meteorological nowcasting, including the identification of events dominated by horizontal advection [Benevides et al, 2015], for assessing moisture transport in the lower troposphere [e.g., Mengistu Tsidu et al, 2015], for relating humidity fields to precipitation events [e.g., Boniface et al, 2009], for assessing the severity of tropical cyclones [e.g., Shoji et al, 2011], and for assessing the impact of new assimilated observations for forecasting precipitation [e.g., Yan et al, 2009]
P177 is near the ocean, while S300 and P230 are in mountainous areas with elevations of ~500 m and ~700 m, respectively
An iterative tropospheric decomposition model has been developed for the generation of highresolution regional tropospheric PWV fields from the interpolation of pointwise GPS zenith total delay (ZTD), without any data differencing
Summary
Time-varying two-dimensional precipitable water vapor (PWV) fields (maps) are used in meteorological nowcasting, including the identification of events dominated by horizontal advection [Benevides et al, 2015], for assessing moisture transport in the lower troposphere [e.g., Mengistu Tsidu et al, 2015], for relating humidity fields to precipitation events [e.g., Boniface et al, 2009], for assessing the severity of tropical cyclones [e.g., Shoji et al, 2011], and for assessing the impact of new assimilated observations for forecasting precipitation [e.g., Yan et al, 2009] Such maps are essential for correcting synthetic aperture radar (SAR) images for atmospheric effects to enable small (and long wavelength) geophysical signals to be measured, including interseismic strain accumulation and postseismic motion, observations of which give insight into the mechanics of a fault and play key roles in estimating the likelihood of future earthquakes [Wright et al, 2004; Gourmelen and Amelung, 2005; Fialko, 2006; Walters et al, 2013; Wen et al, 2012; Li et al, 2009a]. They provide global coverage every 1– 2 days with observations in 36 spectral bands at moderate resolution (250–1000 m), five of which (nearinfrared (IR)) are used for remote sensing of water vapor with 1 km spatial resolution over clear land areas, YU ET AL
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