Abstract
Accurate precipitation detection is one of the most important factors in satellite data assimilation, due to the large uncertainties associated with precipitation properties in radiative transfer models and numerical weather prediction (NWP) models. In this paper, a method to achieve remote sensing of precipitation and classify its intensity over land using a co-located ground-based radar network is described. This method is intended to characterize the O−B biases for the microwave humidity sounder -2 (MWHS-2) under four categories of precipitation: precipitation-free (0–5 dBZ), light precipitation (5–20 dBZ), moderate precipitation (20–35 dBZ), and intense precipitation (>35 dBZ). Additionally, O represents the observed brightness temperature (TB) of the satellite and B is the simulated TB from the model background field using the radiative transfer model. Thresholds for the brightness temperature differences between channels, as well as the order relation between the differences, exhibited a good estimation of precipitation. It is demonstrated that differences between observations and simulations were predominantly due to the cases in which radar reflectivity was above 15 dBZ. For most channels, the biases and standard deviations of O−B increased with precipitation intensity. Specifically, it is noted that for channel 11 (183.31 ± 1 GHz), the standard deviations of O−B under moderate and intense precipitation were even smaller than those under light precipitation and precipitation-free conditions. Likewise, abnormal results can also be seen for channel 4 (118.75 ± 0.3 GHz).
Highlights
Polar-orbiting satellite observations in the visible, infrared, and microwave spectra provide a great deal of information on clouds and precipitation, as well as atmospheric water vapor and temperature [1,2,3]
It was pointed out that the brightness temperature at 118.75 GHz was much lower than that at 50–57 GHz, due to its strong frequency dependence on ice particle scattering in convective areas from the National Polar-Orbiting Operational Environmental Satellite System (NPOESS) aircraft sounder testbed-microwave (NAST-M) [33]
The characteristics of O−B biases for microwave humidity sounder -2 (MWHS-2) over land were estimated under different intensities of precipitation conditions aided by a ground-based radar network
Summary
Polar-orbiting satellite observations in the visible, infrared, and microwave spectra provide a great deal of information on clouds and precipitation, as well as atmospheric water vapor and temperature [1,2,3]. In operational numerical weather prediction (NWP) models, microwave and infrared radiances from polar-orbiting satellite instruments are routinely assimilated to improve the accuracy of short-range and medium-range forecasts [4,5,6]. Since satellite data assimilation is based on the underlying assumption that both observation (O) and simulation (B) are unbiased and that Gaussian error statistics and a linear relationship exist between them [9,10]. Any bias related to the instrument and model simulations needs to be quantified, removed, in satellite data assimilation. It is necessary to estimate the biases of the instrument and the model before assimilating the satellite data
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