Zhou Bingxue, Zhu Langfeng, Wu Hao, et al. Accuracy of atmospheric profiles retrieved from microwave radiometer and its application to precipitation forecast. J Appl Meteor Sci, 2023, 34(6): 717-728. DOI: 10.11898/1001-7313.20230607.
Citation: Zhou Bingxue, Zhu Langfeng, Wu Hao, et al. Accuracy of atmospheric profiles retrieved from microwave radiometer and its application to precipitation forecast. J Appl Meteor Sci, 2023, 34(6): 717-728. DOI: 10.11898/1001-7313.20230607.

Accuracy of Atmospheric Profiles Retrieved from Microwave Radiometer and Its Application to Precipitation Forecast

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  • Real-time and effective detection of atmospheric profiles is of great significance in understanding the evolution of climate system. Ground-based microwave radiometers can provide atmospheric temperature and humidity profiles with extremely high temporal and spatial resolution. Domestic MWP967KV microwave radiometer has effectively made up for problems of imported microwave radiometers, but there are relatively few studies on the performance evaluation and application of this microwave radiometer. In order to better apply data and products of MWP967KV microwave radiometer, inversion data from June 2018 to July 2021 at Jinghe Station of Xi'an are compared with L-band radiosonde observation. The accuracy of atmospheric temperature, relative humidity and vapor density retrieved from microwave radiometer under clear skies and different cloudy skies (classified as low cloud, middle cloud and high cloud, respectively) are analyzed, and the applicability of the related products in precipitation is further explored. Results show that correlation coefficients of temperature between microwave radiometer and radiosonde are 0.99, correlation coefficients of vapor density are 0.97, and correlation coefficients of relative humidity are less than 0.50 under clear skies and cloudy skies, all passing 0.01 significant test. The difference of temperature between clear and cloudy skies is small, but root mean square error of relative humidity in cloudy skies is more than 25%, which is significantly larger than that in clear skies. It indicates that the presence of clouds reduces the accuracy of the humidity inversion, causing large errors, and the inversion accuracy is higher near the ground. Under different cloud types, the temperature difference is small, while root mean square error and bias of relative humidity in low cloud are the largest, which are 26.85% and 9.51%, respectively. In addition, a case analysis shows that relative humidity, liquid water content, atmospheric precipitable water vapor and liquid water path increase significantly before the occurrence of precipitation, which can be used as indicators of the possible occurrence of precipitation. Statistic results show that the atmospheric precipitable water vapor reaches 4 cm and liquid water path reaches 0.2 mm during several precipitation cases, and these indexes can be used as the reference threshold for judging the precipitation of Xi'an.
  • Fig  1.   Scatter density of temperature, relative humidity and vapor density of microwave radiometer and radiosonde for clear and cloudy sky

    Fig  2.   Profiles of correlation coefficient, bias and root mean square error of temperature, relative humidity and vapor density between microwave radiometer and radiosonde for clear and cloudy sky

    Fig  3.   Scatter density of temperature, relative humidity and vapor density of microwave radiometer and radiosonde for low, middle and high cloud

    Fig  4.   Profiles of correlation coefficient, bias and root mean square error of temperature, relative humidity and vapor density between microwave radiometer and radiosonde for low, middle and high cloud

    Fig  5.   Relative humidity (the shaded), liquid water content (the shaded), atmospheric precipitable water vapor (the red line), liquid water path (the blue line) and rainfall (the grey column) from 1800 BT 20 Aug to 1800 BT 22 Aug in 2018

    Fig  6.   Box plots of atmospheric precipitable water vapor and liquid water path for non-precipitation days and 1 hour before light rain, moderate rain and heavy rain from Jun to Sep in 2018-2019

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    Article views468 PDF downloads160 Cited by: 9
    • Received : 2023-07-15
    • Accepted : 2023-09-24
    • Published : 2023-11-26

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