The production of true color images requires observational data in the red,green,and blue(RGB)bands.The Advanced Geostationary Radiation Imager(AGRI)onboard China’s Fengyun-4(FY-4)series of geostationary satellites o...The production of true color images requires observational data in the red,green,and blue(RGB)bands.The Advanced Geostationary Radiation Imager(AGRI)onboard China’s Fengyun-4(FY-4)series of geostationary satellites only has blue and red bands,and we therefore have to synthesize a green band to produce RGB true color images.We used random forest regression and conditional generative adversarial networks to train the green band model using Himawari-8 Advanced Himawari Imager data.The model was then used to simulate the green channel reflectance of the FY-4 AGRI.A single-scattering radiative transfer model was used to eliminate the contribution of Rayleigh scattering from the atmosphere and a logarithmic enhancement was applied to process the true color image.The conditional generative adversarial network model was better than random forest regression for the green band model in terms of statistical significance(e.g.,a higher determination coefficient,peak signal-to-noise ratio,and structural similarity index).The sharpness of the images was significantly improved after applying a correction for Rayleigh scattering,and the images were able to show natural phenomena more vividly.The AGRI true color images could be used to monitor dust storms,forest fires,typhoons,volcanic eruptions,and other natural events.展开更多
风云四号A星(FY-4A)上搭载的干涉式红外探测仪(GIIRS)是首个地球静止轨道上的红外高光谱大气探测仪,它可以提供连续的三维大气温度和水汽的观测,通过追踪水汽的移动可以反演得到不同高度的大气水平风场。本研究利用台风玛丽亚(2018年)期...风云四号A星(FY-4A)上搭载的干涉式红外探测仪(GIIRS)是首个地球静止轨道上的红外高光谱大气探测仪,它可以提供连续的三维大气温度和水汽的观测,通过追踪水汽的移动可以反演得到不同高度的大气水平风场。本研究利用台风玛丽亚(2018年)期间FY-4A加密观测(15分钟间隔)的GIIRS数据开展晴空和部分云区的三维水平风场算法研究,重点研究如何联合同一卫星平台的多光谱成像仪(AGRI)改进GIIRS部分云视场区的三维风场反演结果。利用ERA5独立测试集、CRA40再分析和空投探空数据开展对晴空和云区的三维风场反演结果的检验,基于该个例的反演结果表明:(1)基于GIIRS亮温信息反演得到对流层水平风场,在晴空区均方根误差小于1.5 m s^(-1),方向绝对差基本在15°左右,在部分云视场区,均方根误差为1.5~1.7 m s^(-1),方向绝对差基本在20°左右。与光流法相比,基于GIIRS亮温的直接反演表现出更好的优势,其均方根误差和方向绝对差明显小于光流法的结果。(2)按云量和云顶高度分类后,表现出云量越多、云顶高度越高则RMSE(Root Mean Square Error)越大。在部分云视场区,进一步在反演模型输入中加入来自同平台上成像仪(AGRI)云量和云高信息后,RMSE有所减小,表明更高空间分辨率的AGRI产品可以改进GIIRS部分云覆盖区的风场反演精度。(3)基于GIIRS亮温信息反演的风廓线与CRA40再分析、空投探测风廓线有较好的一致性,表明利用静止卫星红外高光谱大气探测仪观测亮温反演风场的合理性和可行性。展开更多
基金Supported by the National Key Research and Development Program of China(2018YFC150650)National Satellite Meteorological Center Mountain Flood Geological Disaster Prevention Meteorological Guarantee Project 2020 Construction Project(IN_JS_202004)。
文摘The production of true color images requires observational data in the red,green,and blue(RGB)bands.The Advanced Geostationary Radiation Imager(AGRI)onboard China’s Fengyun-4(FY-4)series of geostationary satellites only has blue and red bands,and we therefore have to synthesize a green band to produce RGB true color images.We used random forest regression and conditional generative adversarial networks to train the green band model using Himawari-8 Advanced Himawari Imager data.The model was then used to simulate the green channel reflectance of the FY-4 AGRI.A single-scattering radiative transfer model was used to eliminate the contribution of Rayleigh scattering from the atmosphere and a logarithmic enhancement was applied to process the true color image.The conditional generative adversarial network model was better than random forest regression for the green band model in terms of statistical significance(e.g.,a higher determination coefficient,peak signal-to-noise ratio,and structural similarity index).The sharpness of the images was significantly improved after applying a correction for Rayleigh scattering,and the images were able to show natural phenomena more vividly.The AGRI true color images could be used to monitor dust storms,forest fires,typhoons,volcanic eruptions,and other natural events.
文摘风云四号A星(FY-4A)上搭载的干涉式红外探测仪(GIIRS)是首个地球静止轨道上的红外高光谱大气探测仪,它可以提供连续的三维大气温度和水汽的观测,通过追踪水汽的移动可以反演得到不同高度的大气水平风场。本研究利用台风玛丽亚(2018年)期间FY-4A加密观测(15分钟间隔)的GIIRS数据开展晴空和部分云区的三维水平风场算法研究,重点研究如何联合同一卫星平台的多光谱成像仪(AGRI)改进GIIRS部分云视场区的三维风场反演结果。利用ERA5独立测试集、CRA40再分析和空投探空数据开展对晴空和云区的三维风场反演结果的检验,基于该个例的反演结果表明:(1)基于GIIRS亮温信息反演得到对流层水平风场,在晴空区均方根误差小于1.5 m s^(-1),方向绝对差基本在15°左右,在部分云视场区,均方根误差为1.5~1.7 m s^(-1),方向绝对差基本在20°左右。与光流法相比,基于GIIRS亮温的直接反演表现出更好的优势,其均方根误差和方向绝对差明显小于光流法的结果。(2)按云量和云顶高度分类后,表现出云量越多、云顶高度越高则RMSE(Root Mean Square Error)越大。在部分云视场区,进一步在反演模型输入中加入来自同平台上成像仪(AGRI)云量和云高信息后,RMSE有所减小,表明更高空间分辨率的AGRI产品可以改进GIIRS部分云覆盖区的风场反演精度。(3)基于GIIRS亮温信息反演的风廓线与CRA40再分析、空投探测风廓线有较好的一致性,表明利用静止卫星红外高光谱大气探测仪观测亮温反演风场的合理性和可行性。
