Results 1 to 10 of about 1,321 (143)
Three Microwave Radiation Imagers (MWRI) were carried onboard the FengYun-3B/C/D satellites and have collected more than 10 years of data since 2010. To create a robust climate quality of data, MWRI level one data were reprocessed with new calibration ...
Chuanwen Wei +4 more
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A global daily soil moisture dataset derived from Chinese FengYun Microwave Radiation Imager (MWRI)(2010–2019) [PDF]
Surface soil moisture (SSM) is an important variable in drought monitoring, floods predicting, weather forecasting, etc. and plays a critical role in water and heat exchanges between land and atmosphere. SSM products from L-band observations, such as the
Panpan Yao +9 more
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Surface Properties of Global Land Surface Microwave Emissivity Derived from FY-3D/MWRI Measurements [PDF]
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
Ronghan Xu +4 more
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Spatial Resolution Enhancement of Microwave Radiation Imager (MWRI) Data
A spaceborne microwave radiometer has a low spatial resolution limited by its antenna size. Enhancing the spatial resolution of data acquired by such sensors can improve the quality of subsequent applications.
Yihong Bai +5 more
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This study presents a correction algorithm to remove the backlobe intrusion from the hot-load reflector of microwave radiation imager (MWRI) on-board China FengYun-3C (FY-3C) meteorological satellite.
Xinxin Xie +4 more
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Estimation of IFOV Inter-Channel Deviation for Microwave Radiation Imager Onboard FY-3G Satellite
The Microwave Radiation Imager (MWRI) onboard the FengYun satellite plays a crucial role in global change monitoring and numerical weather prediction. Estimating and correcting geolocation errors are important to retrieving accurate geophysical variables.
Pengjuan Yao +6 more
doaj +3 more sources
Accurate information on microwave land surface emissivity (MLSE) is important for satellite data assimilation. In this article, a new random forest (RF) algorithm is developed for retrieving MLSE under all-sky conditions.
Yonghong Liu +7 more
doaj +2 more sources
A Multivariable Approach for Estimating Soil Moisture from Microwave Radiation Imager (MWRI)
Accurate measurements of soil moisture are beneficial to our understanding of hydrological processes in the earth system. A multivariable approach using the random forest (RF) machine learning technique is proposed to estimate the soil moisture from Microwave Radiation Imager (MWRI) onboard Fengyun-3C satellite. In this study, Soil Moisture Operational
Fuzhong Weng
exaly +3 more sources
Microwave radiometers are vital for global ocean observations, yet they are prone to errors from radio frequency interference, sun glint, and other contamination.
Qiumeng Xue +3 more
doaj +3 more sources
The microwave radiation imager (MWRI) onboard the Fengyun-3D satellite can provide valuable observation data in many fields such as meteorological research and weather forecasting. However, its coarse spatial resolution limits data application. Recently,
Zhou Zhang, Zhenzhan Wang, Xiaolin Tong
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