We compare the precipitable water vapor (PWV) determined using a domestic ground-based microwave radiometer (MWR PWV) with PWV measurements from radiosondes (RS PWV), the Global Navigation Satellite System (GNSS PWV), and reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) (EC PWV). The MWR PWV is affected by precipitation, and thus it differs greatly from the other three observations. The correlation coefficient between the MWR PWV and RS PWV (EC PWV) is 0.934 (0.933), and the root mean square error (RMSE) is 17.19 mm (16.05 mm), whereas the correlation coefficient between the GNSS PWV and RS PWV (EC PWV) is 0.989 (0.986), and the RMSE is 17.04 mm (15.83 mm). The scatter distributions of the MWR PWV and the other observations show a systematic deviation that is negatively correlated with the surface air temperature. After polynomial fitting and corrections are applied, the correlation coefficients between the MWR PWV and the RS PWV and EC PWV increase to 0.993 and 0.99, and the RMSEs decrease to 14.13 and 15.86 mm, respectively. The temperature and water vapor density profiles are retrieved from the bright temperature and can reflect the quality of the bright temperature. Because the PWV retrieved from the ground-based MWR has a linear relationship with the brightness temperature, the accuracy of the PWV can be analyzed in terms of the quality of the brightness temperature. We found that the differences in the temperature profile below 2000 m are smaller, whereas those in the water vapor density profile below 2000 m show the largest difference. This finding reflects the differences in the brightness temperature, which may be the cause of the inaccurate PWV observations. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
In collaboration with 12 other institutions, the Meteorological Observation Center of the China Meteorological Administration undertook a comprehensive marine observation experiment in the South China Sea using the Yilong-10 high-altitude large unmanned aerial vehicle (UAV). The Yilong-10 UAV carried a self-developed dropsonde system and a millimeter-wave cloud radar system. In addition, a solar-powered unmanned surface vessel and two drifting buoys were used. The experiment was further supported by an intelligent, reciprocating horizontal drifting radiosonde system that was deployed from the Sansha Meteorological Observing Station, with the intent of producing a stereoscopic observation over the South China Sea. Comprehensive three-dimensional observations were collected using the system from 31 July to 2 August, 2020. This information was used to investigate the formation and development processes of Typhoon Sinlaku (2020). The data contain measurements of 21 oceanic and meteorological parameters acquired by the five devices, along with video footage from the UAV. The data proved very helpful in determining the actual location and intensity of Typhoon Sinlaku (2020). The experiment demonstrates the feasibility of using a high-altitude, large UAV to fill in the gaps between operational meteorological observations of marine areas and typhoons near China, and marks a milestone for the use of such data for analyzing the structure and impact of a typhoon in the South China Sea. It also demonstrates the potential for establishing operational UAV meteorological observing systems in the future, and the assimilation of such data into numerical weather prediction models.
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