Sea ice concentration(SIC)is one of the most important indicators when monitoring climate changes in the polar region.With the development of the Chinese satellite technology,the Feng Yun(FY)series has been applied to...Sea ice concentration(SIC)is one of the most important indicators when monitoring climate changes in the polar region.With the development of the Chinese satellite technology,the Feng Yun(FY)series has been applied to retrieve the sea ice parameters in the polar region.In this paper,to improve the SIC retrieval accuracy from the passive microwave(PM)data of the Microwave Radiation Imager(MWRI)aboard on the Feng Yun-3 B(FY-3 B)Satellite,the dynamic tie-point(DT)Arctic Radiation and Turbulence Interaction Study(ARTIST)Sea Ice(ASI)(DT-ASI)SIC retrieval algorithm is applied and obtained Arctic SIC data for nearly 10 a(from November 18,2010 to August 19,2019).Also,by applying a land spillover correction scheme,the erroneous sea ice along coastlines in melt season is removed.The results of FY-3 B/DT-ASI are obviously improved compared to that of FY-3 B/NT2(NASA-Team2)in both SIC and sea ice extent(SIE),and are highly consistent with the results of similar products of AMSR2(Advanced Microwave Scanning Radiometer 2)/ASI and AMSR2/DT-ASI.Compared with the annual average SIC of FY-3 B/NT2,our result is reduced by 2.31%.The annual average SIE difference between the two FY-3 Bs is 1.65×10^(6) km^(2),of which the DT-ASI algorithm contributes 87.9%and the land spillover method contributes12.1%.We further select 58 MODIS(Moderate-resolution Imaging Spectroradiometer)cloud-free samples in the Arctic region and use the tie-point method to retrieve SIC to verify the accuracy of these SIC products.The root mean square difference(RMSD)and mean absolute difference(MAD)of the FY-3 B/DT-ASI and MODIS results are 17.2%and 12.7%,which is close to those of two AMSR2 products with 6.25 km resolution and decreased 8%and 7.2%compared with FY-3 B/NT2.Further,FY-3 B/DT-ASI has the most significant improvement where the SIC is lower than 60%.A high-quality SIC product can be obtained by using the DT-ASI algorithm and our work will be beneficial to promote the application of Feng Yun Satellite.展开更多
Microwave Land Surface Emissivity(MLSE)over China under both clear and cloudy sky conditions was retrieved using measurements of recalibrated microwave brightness temperatures(Tbs)from Fengyun-3B Microwave Radiation I...Microwave Land Surface Emissivity(MLSE)over China under both clear and cloudy sky conditions was retrieved using measurements of recalibrated microwave brightness temperatures(Tbs)from Fengyun-3B Microwave Radiation Imager(FY-3B MWRI),combined with cloud properties derived from Himawari-8 Advanced Himawari Imager(AHI)observations.The contributions from cloud particles and atmospheric gases to the upwelling Tbs at the top of atmosphere were calculated and removed in radiative transfer.The MLSEs at horizontal polarizations at 10.65,18.7,and 36.5 GHz during 7 July 2015 to 30 June 2019 over China showed high values in the southeast vegetated area and low values in the northwest barren,or sparsely vegetated,area.The maximum values were found in the belt area of the Qinling-Taihang Mountains and the eastern edge of the Qinghai-Tibet Plateau,which is highly consistent with MLSEs derived from AMSR-E.It demonstrates that the measurements of FY-3B MWRI Tbs,including its calibration and validation,are reliable,and the retrieval algorithm developed in this study works well.Seasonal variations of MLSE in China are mainly driven by the combined effects of vegetation,rainfall,and snow cover.In tropical and southern forest regions,the seasonal variation of MLSE is small due to the enhancement from vegetation and the suppression from rainfall.In the boreal area,snow causes a significant decrease of MLSE at 36.5 GHz in winter.Meanwhile,the MLSE at lower frequencies experiences less suppression.In the desert region in Xinjiang,increases of MLSEs at all frequencies are observed with increasing snow cover.展开更多
This paper analyzes the sea surface backward thermal radiation data in the China Sea observed by the mmwave channel of FY3 MWRI, explains the reason for which the analysis method combined with multiple mmwave channels...This paper analyzes the sea surface backward thermal radiation data in the China Sea observed by the mmwave channel of FY3 MWRI, explains the reason for which the analysis method combined with multiple mmwave channels is conducive to wind inversion, uses the complex model of the two-scale randomly rough surface with foam scattering layer to calculate the backward heat emission, analyzes the different response characteristics of the thermal radiation characteristics of each channel with the change of the sea surface wind speed, and establishes the wind speed inversion model applying to the microwave radiometer, achieving better results than in previous studies. The sea surface medium-low wind speed precision standard deviation of new model reaches 1.2 m/s (0 - 15 m/s);the inversion strong wind data are consistent with the island fixed buoys data, and the global sea surface wind speed image schematic diagram is given.展开更多
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 t...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.展开更多
以青藏高原地区为研究区域,利用FY-3B/MWRI(Microwave Radiation Imager)一级亮温数据和NCEP(the National Centers for Environmental Prediction) FNL(Final)全球业务分析资料,通过简化的微波辐射传输方程反演了晴空大气条件下的地表...以青藏高原地区为研究区域,利用FY-3B/MWRI(Microwave Radiation Imager)一级亮温数据和NCEP(the National Centers for Environmental Prediction) FNL(Final)全球业务分析资料,通过简化的微波辐射传输方程反演了晴空大气条件下的地表微波发射率.进而根据IGBP(International Geosphere-Biosphere Program)陆表覆盖分类数据,进一步分析了青藏高原地区微波地表发射率的频谱和空间分布特征,并分析了反演误差的来源.结果表明:青藏高原地区微波地表发射率的空间分布、频谱特征都与地表覆盖类型分布特征高度吻合,呈现出西北部地表发射率极化差异大,东南部极化异差小的分布特征.本研究中地表发射率的反演误差主要来自降水像元判别方案、再分析资料的时空匹配.还需要进一步研究定量误差,以期提高反演精度,进而建立长时间序列的地表发射率数据库,为青藏高原地球物理参数的遥感反演提供数据支持.展开更多
基金supported by the National Key R&D Program of China[grant number 2022YFF0801301]the National Natural Science Foundation of China[grant number 41575033]+1 种基金the Fengyun Satellite Application Pioneer Project[grant number FY-APP-2022.0111]the Natural Science Foundation of Jiangsu Province[grant number BK20231148]。
基金The National Key Research and Development Program of China under contract No.2016YFC1402704the National Natural Science Foundation of China under contract Nos 41941012 and 42076228the Guangdong Basic and Applied Basic Research Foundation under contract No.2019A1515110295。
文摘Sea ice concentration(SIC)is one of the most important indicators when monitoring climate changes in the polar region.With the development of the Chinese satellite technology,the Feng Yun(FY)series has been applied to retrieve the sea ice parameters in the polar region.In this paper,to improve the SIC retrieval accuracy from the passive microwave(PM)data of the Microwave Radiation Imager(MWRI)aboard on the Feng Yun-3 B(FY-3 B)Satellite,the dynamic tie-point(DT)Arctic Radiation and Turbulence Interaction Study(ARTIST)Sea Ice(ASI)(DT-ASI)SIC retrieval algorithm is applied and obtained Arctic SIC data for nearly 10 a(from November 18,2010 to August 19,2019).Also,by applying a land spillover correction scheme,the erroneous sea ice along coastlines in melt season is removed.The results of FY-3 B/DT-ASI are obviously improved compared to that of FY-3 B/NT2(NASA-Team2)in both SIC and sea ice extent(SIE),and are highly consistent with the results of similar products of AMSR2(Advanced Microwave Scanning Radiometer 2)/ASI and AMSR2/DT-ASI.Compared with the annual average SIC of FY-3 B/NT2,our result is reduced by 2.31%.The annual average SIE difference between the two FY-3 Bs is 1.65×10^(6) km^(2),of which the DT-ASI algorithm contributes 87.9%and the land spillover method contributes12.1%.We further select 58 MODIS(Moderate-resolution Imaging Spectroradiometer)cloud-free samples in the Arctic region and use the tie-point method to retrieve SIC to verify the accuracy of these SIC products.The root mean square difference(RMSD)and mean absolute difference(MAD)of the FY-3 B/DT-ASI and MODIS results are 17.2%and 12.7%,which is close to those of two AMSR2 products with 6.25 km resolution and decreased 8%and 7.2%compared with FY-3 B/NT2.Further,FY-3 B/DT-ASI has the most significant improvement where the SIC is lower than 60%.A high-quality SIC product can be obtained by using the DT-ASI algorithm and our work will be beneficial to promote the application of Feng Yun Satellite.
基金the National Natural Science Foundation of China(Grant Nos.41830104,41661144007,41675022,and 41375148)Research and Development Program of China(Grant No.2017YFC1501402)the Jiangsu Provincial 2011 Program(Col-laborative Innovation Center of Climate Change).
文摘Microwave Land Surface Emissivity(MLSE)over China under both clear and cloudy sky conditions was retrieved using measurements of recalibrated microwave brightness temperatures(Tbs)from Fengyun-3B Microwave Radiation Imager(FY-3B MWRI),combined with cloud properties derived from Himawari-8 Advanced Himawari Imager(AHI)observations.The contributions from cloud particles and atmospheric gases to the upwelling Tbs at the top of atmosphere were calculated and removed in radiative transfer.The MLSEs at horizontal polarizations at 10.65,18.7,and 36.5 GHz during 7 July 2015 to 30 June 2019 over China showed high values in the southeast vegetated area and low values in the northwest barren,or sparsely vegetated,area.The maximum values were found in the belt area of the Qinling-Taihang Mountains and the eastern edge of the Qinghai-Tibet Plateau,which is highly consistent with MLSEs derived from AMSR-E.It demonstrates that the measurements of FY-3B MWRI Tbs,including its calibration and validation,are reliable,and the retrieval algorithm developed in this study works well.Seasonal variations of MLSE in China are mainly driven by the combined effects of vegetation,rainfall,and snow cover.In tropical and southern forest regions,the seasonal variation of MLSE is small due to the enhancement from vegetation and the suppression from rainfall.In the boreal area,snow causes a significant decrease of MLSE at 36.5 GHz in winter.Meanwhile,the MLSE at lower frequencies experiences less suppression.In the desert region in Xinjiang,increases of MLSEs at all frequencies are observed with increasing snow cover.
文摘This paper analyzes the sea surface backward thermal radiation data in the China Sea observed by the mmwave channel of FY3 MWRI, explains the reason for which the analysis method combined with multiple mmwave channels is conducive to wind inversion, uses the complex model of the two-scale randomly rough surface with foam scattering layer to calculate the backward heat emission, analyzes the different response characteristics of the thermal radiation characteristics of each channel with the change of the sea surface wind speed, and establishes the wind speed inversion model applying to the microwave radiometer, achieving better results than in previous studies. The sea surface medium-low wind speed precision standard deviation of new model reaches 1.2 m/s (0 - 15 m/s);the inversion strong wind data are consistent with the island fixed buoys data, and the global sea surface wind speed image schematic diagram is given.
基金Under the auspices of National Natural Science Foundation of China (No. 40971189)Knowledge Innovation Programs of Chinese Academy of Sciences (No. KZCX2-YW-340)China Postdoctoral Science Foundation (No. 20100471276)
文摘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.
文摘目前还没有基于国产卫星的1 km分辨率的全天候陆表温度(LST)产品,FY-3D卫星提供了中分辨率成像仪(MERSI)Ⅱ型1 km分辨率晴空LST产品与微波成像仪(MWRI)25 km全天候LST产品,因此可结合两者优势开展全天候1 km分辨率LST的融合研究。基于地理加权回归(GWR)方法,选择海拔、FY-3D归一化植被指数和归一化建筑指数等建立GWR模型对FY-3D/MWRI 25 km LST降尺度到1 km,并与MERSI 1 km LST进行融合;同时针对MWRI轨道间隙,利用前后1天融合后的云覆盖像元1 km LST进行补值,可以得到接近全天候下的1 km LST。基于以上融合算法,选择了中国区域多个典型日期FY-3D/MERSI和MWRI LST官网产品进行了融合试验,并利用公开发布的全天候1 km LST产品(TPDC LST)对FY-3D 1 km LST融合结果进行了评估。研究结果表明,基于GWR法的LST降尺度方法,可以有效避免传统微波LST降尺度方法中存在的“斑块”效应和局地温度偏低等问题;LST融合结果有值率从融合前的22.4%~36.9%可提高到融合后69.3%~80.7%,融合结果与TPDC LST的空间决定系数为0.503~0.787,均方根误差为3.6~5.8 K,其中晴空为2.6~4.9 K,云下为4.1~6.1 K;分析还表明目前官网产品FY-3D/MERSI和MWRI LST均存在缺值较多与精度偏低等问题,显示其存在较大改进潜力,这有利于进一步改进FY-3D LST融合质量。
