Comparative Analysis of Microwave Brightness Temperature Data in Northeast China Using AMSR-E and MWRI Products

With such significant advantages as all-day observation, penetrability and all-weather coverage, passive mi-crowave remote sensing technique has been widely applied in the research of global environmental change. As the sat-ellite-based passive microwave remote sensor, the Advanced Microwave Scanning Radiometer-Earth Observing Sys-tem (AMSR-E) loaded on NASA's (National Aeronautics and Space Administration of USA) Aqua satellite has been popularly used in the field of microwave observation. The Microwave Radiation Imager (MWRI) loaded on the Chi-nese FengYun-3A (FY-3A) satellite is an AMSR-E-like conical scanning microwave sensor, but there are few reports about MWRI data. This paper firstly proposed an optimal spatial position matching algorithm from rough to exact for the position matching between AMSR-E and MWRI data, then taking Northeast China as an example, comparatively analyzed the microwave brightness temperature data derived from AMSR-E and MWRI. The results show that when the antenna footprints of the two sensors are filled with either full water, or full land, or mixed land and water with ap-proximate proportion, the errors of brightness temperature between AMSR-E and MWRI are usually in the range from -10 K to +10 K. In general, the residual values of brightness temperature between the two microwave sensors with the same spatial resolution are in the range of ±3 K. Because the spatial resolution of AMSR-E is three times as high as that of MWRI, the results indicate that the quality of MWRI data is better. The research can provide useful information for the MWRI data application and microwave unmixing method in the future.

Evaluation of AMSR-E——Derived Soil Moisture over Northern China

In this study,the authors evaluated two re-motely sensed surface soil moisture datasets derived from the Advanced Microwave Scanning Radiometer of the Earth Observing System (AMSR-E) over northern China.The soil moisture datasets were derived from algorithms developed by the National Snow and Ice Data Center (NSIDC) and jointly developed by the Vrije Universiteit Amsterdam and NASA Goddard Space Flight Center (VUA-NASA).The NSIDC and VUA-NASA products were compared to in situ soil moisture data from nine enhanced coordinated observation stations.The VUA-NASA dataset presented a strong correlation with top layer in situ soil moisture observations,and the correla-tion coefficients ranged from 0.34 to 0.73 (p<0.01).The correlation coefficients decreased as the observed soil layer depth increased.The correlation coefficients be-tween the NSIDC retrievals and the top layer in situ ob-servations were between 0.10 and 0.62 (p<0.01).Fur-thermore,VUA-NASA soil moisture variations agreed well with in situ soil moisture dynamics and responded sensitively to precipitation events.In contrast,the NSIDC dataset failed to capture signals of soil moisture dynamics.The analyses demonstrated that the VUA-NASA product was capable of representing soil moisture conditions over northern China.

Validation of Land Surface Temperature Derived from 37-GHz AMSR-E over Northern China

A validation study of land surface temperature (LST) obtained from the Ka band (37 GHz) vertically polarized brightness temperature over northern China is presented.The remotely sensed LST derived jointly by the Vrije Universiteit Amsterdam and the NASA Goddard Space Flight Center (VUA-NASA) from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) were compared to the daily in-situ top soil temperature/infrared surface temperature observations from eleven/three Enhanced Coordinated Observation stations in arid and semi-arid regions of northern China.The VUA-NASA LST from the descending path exhibited a stronger correspondence to the in-situ infrared surface temperature than soil temperature observations,whereas correlations (R 2) of the latter ranged from 0.41 to 0.86.Meanwhile,the ascending overpass LST was generally warmer than the in-situ soil temperature observations at all stations,and the correlation (R 2) was between 0.07 and 0.72.Furthermore,the correlation of the descending path was generally greater than that of the ascending path at the same station.The descending path VUA-NASA LST was sensitive to precipitation and presented good agreement with ground temperature dynamics.The analyses demonstrated that the descending overpass LST was reliable to reflect reasonable patterns of temperature dynamics for land surface temperature in the region.