Using a microwave radiative transfer （MWRT） model with microwave brightness temperatures （TBs） observed from the Tropical Rainfall Measuring Mission （TRMM） Microwave Imager （TMI）, an indirect approach evaluate...Using a microwave radiative transfer （MWRT） model with microwave brightness temperatures （TBs） observed from the Tropical Rainfall Measuring Mission （TRMM） Microwave Imager （TMI）, an indirect approach evaluated hydrometeors generated from the Weather Research and Forecasting （WRY） model in the process of CHABA typhoon in August 2004. This study compares the simulated TBs generated from the microwave radioactive transfer model connected to the WRF model with the observed TBs derived from TMI and analyzes the differences between these TBs. The results indicate that the WRF model underestimates the amount and area of liquid and ice hydrometeors inside the typhoon center. The results also indicate relatively better agreement between the simulated and the observed TBs in the vertical polarization than in the horizontal polarization.展开更多
A type of wavelet neural network, in which the scale function isadopted only, is proposed in this paper for non-linear dynamicprocess modelling. Its network size is decreased significantly andthe weight coefficients c...A type of wavelet neural network, in which the scale function isadopted only, is proposed in this paper for non-linear dynamicprocess modelling. Its network size is decreased significantly andthe weight coefficients can be estimated by a linear algorithm. Thewavelet neural network holds some advantages superior to other typesof neural networks. First, its network structure is easy to specifybased on its theoretical analysis and intuition. Secondly, networktraining does not rely on stochastic gradient type techniques andavoids the problem of poor convergence or undesirable local minima.展开更多
The primary objective of this work is to develop an operational snow depth retrieval algorithm for the FengYun3B Microwave Radiation Imager(FY3B-MWRI)in China.Based on 7-year(2002–2009)observations of brightness temp...The primary objective of this work is to develop an operational snow depth retrieval algorithm for the FengYun3B Microwave Radiation Imager(FY3B-MWRI)in China.Based on 7-year(2002–2009)observations of brightness temperature by the Advanced Microwave Scanning Radiometer-EOS(AMSR-E)and snow depth from Chinese meteorological stations,we develop a semi-empirical snow depth retrieval algorithm.When its land cover fraction is larger than 85%,we regard a pixel as pure at the satellite passive microwave remote-sensing scale.A 1-km resolution land use/land cover(LULC)map from the Data Center for Resources and Environmental Sciences,Chinese Academy of Sciences,is used to determine fractions of four main land cover types(grass,farmland,bare soil,and forest).Land cover sensitivity snow depth retrieval algorithms are initially developed using AMSR-E brightness temperature data.Each grid-cell snow depth was estimated as the sum of snow depths from each land cover algorithm weighted by percentages of land cover types within each grid cell.Through evaluation of this algorithm using station measurements from 2006,the root mean square error(RMSE)of snow depth retrieval is about 5.6 cm.In forest regions,snow depth is underestimated relative to ground observation,because stem volume and canopy closure are ignored in current algorithms.In addition,comparison between snow cover derived from AMSR-E and FY3B-MWRI with Moderate-resolution Imaging Spectroradiometer(MODIS)snow cover products(MYD10C1)in January 2010 showed that algorithm accuracy in snow cover monitoring can reach 84%.Finally,we compared snow water equivalence(SWE)derived using FY3B-MWRI with AMSR-E SWE products in the Northern Hemisphere.The results show that AMSR-E overestimated SWE in China,which agrees with other validations.展开更多
基金supported by the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant Nos. KZCX2-YW-Q11-04 and KZCX2-EW-QN507)the National Basic Research Program of China (973 Program,Grant No. 2010CB428601)the National Natural Science Foundation of China (Grant Nos. 40730950 and 41075041)
文摘Using a microwave radiative transfer （MWRT） model with microwave brightness temperatures （TBs） observed from the Tropical Rainfall Measuring Mission （TRMM） Microwave Imager （TMI）, an indirect approach evaluated hydrometeors generated from the Weather Research and Forecasting （WRY） model in the process of CHABA typhoon in August 2004. This study compares the simulated TBs generated from the microwave radioactive transfer model connected to the WRF model with the observed TBs derived from TMI and analyzes the differences between these TBs. The results indicate that the WRF model underestimates the amount and area of liquid and ice hydrometeors inside the typhoon center. The results also indicate relatively better agreement between the simulated and the observed TBs in the vertical polarization than in the horizontal polarization.
基金Supported by the Eu Information Technologies Programme Project(No. 22416) and National High Tech R&D Project(863/Computer Integrated Manufacture System AA413130) of China.
文摘A type of wavelet neural network, in which the scale function isadopted only, is proposed in this paper for non-linear dynamicprocess modelling. Its network size is decreased significantly andthe weight coefficients can be estimated by a linear algorithm. Thewavelet neural network holds some advantages superior to other typesof neural networks. First, its network structure is easy to specifybased on its theoretical analysis and intuition. Secondly, networktraining does not rely on stochastic gradient type techniques andavoids the problem of poor convergence or undesirable local minima.
基金supported by the National Natural Science Foundation of China(Grant Nos.41171260&41030534)
文摘The primary objective of this work is to develop an operational snow depth retrieval algorithm for the FengYun3B Microwave Radiation Imager(FY3B-MWRI)in China.Based on 7-year(2002–2009)observations of brightness temperature by the Advanced Microwave Scanning Radiometer-EOS(AMSR-E)and snow depth from Chinese meteorological stations,we develop a semi-empirical snow depth retrieval algorithm.When its land cover fraction is larger than 85%,we regard a pixel as pure at the satellite passive microwave remote-sensing scale.A 1-km resolution land use/land cover(LULC)map from the Data Center for Resources and Environmental Sciences,Chinese Academy of Sciences,is used to determine fractions of four main land cover types(grass,farmland,bare soil,and forest).Land cover sensitivity snow depth retrieval algorithms are initially developed using AMSR-E brightness temperature data.Each grid-cell snow depth was estimated as the sum of snow depths from each land cover algorithm weighted by percentages of land cover types within each grid cell.Through evaluation of this algorithm using station measurements from 2006,the root mean square error(RMSE)of snow depth retrieval is about 5.6 cm.In forest regions,snow depth is underestimated relative to ground observation,because stem volume and canopy closure are ignored in current algorithms.In addition,comparison between snow cover derived from AMSR-E and FY3B-MWRI with Moderate-resolution Imaging Spectroradiometer(MODIS)snow cover products(MYD10C1)in January 2010 showed that algorithm accuracy in snow cover monitoring can reach 84%.Finally,we compared snow water equivalence(SWE)derived using FY3B-MWRI with AMSR-E SWE products in the Northern Hemisphere.The results show that AMSR-E overestimated SWE in China,which agrees with other validations.
