Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China.
Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing 100081, China.
Sensors (Basel). 2023 Jun 13;23(12):5534. doi: 10.3390/s23125534.
Land surface microwave emissivity is crucial to the accurate retrieval of surface and atmospheric parameters and the assimilation of microwave data into numerical models over land. The microwave radiation imager (MWRI) sensors aboard on Chinese FengYun-3 (FY-3) series satellites provide valuable measurements for the derivation of global microwave physical parameters. In this study, an approximated microwave radiation transfer equation was used to estimate land surface emissivity from MWRI by using brightness temperature observations along with corresponding land and atmospheric properties obtained from ERA-Interim reanalysis data. Surface microwave emissivity at the 10.65, 18.7, 23.8, 36.5, and 89 GHz vertical and horizontal polarizations was derived. Then, the global spatial distribution and spectrum characteristics of emissivity over different land cover types were investigated. The seasonal variations of emissivity for different surface properties were presented. Furthermore, the error source was also discussed in our emissivity derivation. The results showed that the estimated emissivity was able to capture the major large-scale features and contains a wealth of information regarding soil moisture and vegetation density. The emissivity increased with the increase in frequency. The smaller surface roughness and increased scattering effect may result in low emissivity. Desert regions showed high emissivity microwave polarization difference index (MPDI) values, which suggested the high contrast between vertical and horizontal microwave signals in this region. The emissivity of the deciduous needleleaf forest in summer was almost the greatest among different land cover types. There was a sharp decrease in the emissivity at 89 GHz in the winter, possibly due to the influence of deciduous leaves and snowfall. The land surface temperature, the radio-frequency interference, and the high-frequency channel under cloudy conditions may be the main error sources in this retrieval. This work showed the potential capabilities of providing continuous and comprehensive global surface microwave emissivity from FY-3 series satellites for a better understanding of its spatiotemporal variability and underlying processes.
地表微波发射率对于准确反演地表和大气参数以及将微波数据同化到陆地上的数值模型中至关重要。中国风云三号（FY-3）系列卫星上的微波辐射成像仪（MWRI）传感器为全球微波物理参数的推导提供了有价值的测量。在本研究中，使用近似微波辐射传输方程，通过利用亮度温度观测值以及从 ERA-Interim 再分析数据中获得的相应陆地和大气属性，从 MWRI 估算地表发射率。推导了 10.65、18.7、23.8、36.5 和 89 GHz 垂直和水平极化的地表微波发射率。然后，研究了不同土地覆盖类型的全球空间分布和发射率的光谱特征。展示了不同地表特性的发射率季节性变化。此外，还讨论了发射率推导中的误差源。结果表明，估算的发射率能够捕捉到主要的大尺度特征，并包含有关土壤湿度和植被密度的丰富信息。发射率随频率的增加而增加。较小的表面粗糙度和增加的散射效应可能导致低发射率。沙漠地区表现出高的微波极化差异指数（MPDI）值，这表明该地区垂直和水平微波信号之间存在高对比度。落叶针阔混交林在夏季的发射率几乎是所有土地覆盖类型中最大的。在冬季，89 GHz 的发射率急剧下降，可能是由于落叶和降雪的影响。该反演中的主要误差源可能是地表温度、射频干扰和云层条件下的高频通道。这项工作展示了 FY-3 系列卫星提供连续和全面的全球地表微波发射率的潜力，有助于更好地了解其时空变化和潜在过程。
