Results 51 to 60 of about 1,456,367 (121)
Abstract The FY‐3G Precipitation Measurement Radar (PMR), the world's second dual‐frequency satellite precipitation radar (SR), provides three‐dimensional precipitation structure data in mid‐ and low‐latitude regions, with performance comparable to Global Precipitation Measurement Dual‐frequency PR (GPM DPR).
Peng Chen +4 more
wiley +1 more source
Abstract A factor of 2 difference is found between microwave brightness temperature (TB) observations and simulations from vector radiative transfer models. A physical explanation of this difference is related to the calibration process. In principle, for the calibration of polarimetric instruments of a total power radiometer, the radiation should be ...
Ziqiang Zhu, Fuzhong Weng
wiley +1 more source
Experiments assimilating horizontal line‐of‐sight winds from the European Space Agency's Aeolus satellite at the Met Office has shown numerous benefits to global weather forecasts. Improvements are seen across a broad range of forecast variables, and the impacts are comparable to assimilation of surface winds from scatterometers.
Gemma Halloran, Mary Forsythe
wiley +1 more source
Global Surface Soil Moisture from the Microwave Radiation Imager onboard the Fengyun-3B satellite
Soil moisture retrievals from China’s recently launched meteorological Fengyun-3B satellite are presented. An established retrieval algorithm – the Land Parameter Retrieval Model (LPRM) – was applied to observations of the Microwave Radiation Imager ...
Liu, Y.Y. +7 more
core +1 more source
Sea‐ice concentration and state parameters are retrieved at the locations of microwave imager observations within an atmospheric data assimilation system. This allows the assimilation of microwave observations with strong surface sensitivities over sea ice and possible sea‐ice surfaces, with direct benefits to atmospheric forecasts.
Alan J. Geer
wiley +1 more source
Reconstruction of 3D DPR Observations Using GMI Radiances
Abstract Three‐dimensional global precipitation observation is crucial for understanding climate and weather dynamics. While spaceborne precipitation radars provide precise but limited observations, passive microwave imagers are available much more frequently.
Yunfan Yang +4 more
wiley +1 more source
Precipitation Retrieval From Fengyun-3D MWHTS and MWRI Data Using Deep Learning
In this article, two multitask deep learning models, multilayer perceptron (MLP) and convolutional neural networks (CNNs) are constructed to detect precipitation flags and retrieve precipitation rates simultaneously over the Northwest Pacific area.
Kangwen Liu, Jieying He, Haonan Chen
doaj +1 more source
Satellite microwave radiometer data is affected by many degradation factors during the imaging process, such as the sampling interval, antenna pattern and scan mode, etc., leading to spatial resolution reduction.
Weidong Hu +5 more
doaj +1 more source
Spatial Resolution Matching of Microwave Radiometer Data with Convolutional Neural Network
Passive multi-frequency microwave remote sensing is often plagued with the problems of low- and non-uniform spatial resolution. In order to adaptively enhance and match the spatial resolution, an accommodative spatial resolution matching (ASRM) framework,
Yade Li +6 more
doaj +1 more source
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 ...
Fuzhong Weng +4 more
core +1 more source

