Remote Sensing Of Atmospheric Water Vapor Field With Tomography Using Multi Sensor Data

Remote Sensing of Atmospheric Water Vapor Field with Tomography Using Multi-sensor Data

To assess the quality of water vapor data from various observation systems, an intercomparison study was conducted for water vapor data derived from GPS, radiosonde, water vapor radiometer (WVR), non-hydrostatic model (NHM), and European Center for Medium-Range Weather Forecasts (ECMWF). For ZWD comparison with radiosonde data, ECMWF achieves the highest accuracy of 17.73 mm (~2.87 mm in precipitable water vapor (PWV)). GPS, WVR, and NHM have RMS errors of 18.06 mm (~2.93 mm in PWV), 18.15 mm (~2.94 mm in PWV), and 29.53 mm (~4.78 mm in PWV), respectively. Slant wet delays (SWD) estimated by GPS were assessed by SWDs derived from ECMWF, an overall accuracy of 36.44 mm (~5.90 mm in slant PWV) is yielded. Water vapor tomographic experiments were carried out using multiple data from GPS, radiosonde, WVR, NHM, sunphototmeter, and synoptic observations in Hong Kong. Experimental results have revealed that the best vertical constraint scheme is using average radiosonde profiles observed during the three days prior to the tomographic epoch. In the evaluation by radiosonde observations, the multi-sensor tomographic wet refractivity fields achieved an overall accuracy of 7.13 mm/km. In the vertical direction, RMS errors generally decrease with altitude from 11.44 mm/km at the lowest layer (0 to 0.4 km) to 3.30 mm/km at the uppermost layer (7.5 to 8.5 km). The tomographic results obtain RMS errors in the range of 6~9 mm/km at the horizontal grids when compared with ECMWF data. An important goal of water vapor tomography is to benefit the extreme weather prediction and thus to mitigate ensuing hazards. Due to the transfer of energy in the atmospheric processes, atmospheric water vapor has a strong influence on formation and lifecycle of severe weathers. Three heavy precipitation events that occurred in Hong Kong were investigated to examine the potential of water vapor tomography in extreme weather prediction. Several positive findings demonstrated the ability of tomography in forecasting heavy rains as it can detect atmospheric instability before the events.

Microwave Radiometry and Remote Sensing of The Environment

This volume contains a collection of refereed papers which were presented at the Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment, 14--17 February 1994, Rome, Italy. The last decade has marked a period of steady advancement and new developments in the observation of the terrestrial environment by passive microwave sensors. Both ground-based and satellite-borne systems have improved their accuracy, stability and spatial resolution and are providing a wealth of quantitative data, which are increasingly being employed in application-oriented projects. The contributions in this volume cover different fields of applications of microwave radiometry, the various observation and retrieval techniques and the recent technological developments. The articles are divided into four sections: measurement of atmospheric water vapor and cloud liquid, measurement of rain, observation of the surface, and new radiometric systems.

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