The visible infrared radiometer(VIRR)is the first instrument with longest measurements equipped on the Fengyun(FY)polar-orbiting satellites.Through re-processing of the historic VIRR measurements,long-term(over 20 yr)...The visible infrared radiometer(VIRR)is the first instrument with longest measurements equipped on the Fengyun(FY)polar-orbiting satellites.Through re-processing of the historic VIRR measurements,long-term(over 20 yr)global data can be integrated from multiple participating VIRRs on a consistent radiometric scale,which are valuable to climate and climate change studies.Due to lack of an onboard calibration system for VIRR,the reflective solar bands must be vicariously calibrated.This study applied the multi-site vicarious approach for consistent calibration of the VIRR visible(VIS)and near-infrared(NIR)data,and produced calibration coefficients for five VIRRs on FY-1 C/D and FY-3 A/B/C.The data quality was then evaluated with observations.The reflectance predicted by using the radiative transfer model over multiple invariant desert and ocean targets was used to derive the calibration slope via a weighted fitting scheme,in which the weights are the inverse of the variance from a radiative transfer simulation evaluated with reference to Aqua moderate resolution imaging spectroradiometer(MODIS).The sensor-specific calibration coefficients were derived on a daily basis by using piecewise polynomials.The calibration reference of the VIRR solar band record was further traced to the Aqua MODIS Collection 6.1 reference calibration with a systematic correction derived from the Libya4 desert.The VIRR record was compared with the Aqua MODIS C6.1 calibration over the polar region based on simultaneous nadir overpass observations.The lifetime relative difference for each sensor are within 3.3%and 4.5%for channels 1 and 2.Invariant deserts were also employed to evaluate the stability and consistency of the VIRR record.In general,the means of the directional and spectral corrected reflectance for each sensor are within 1%of the 20-yr average,implying that the VIRR reflectance of the invariant targets is consistent to within 1%among the sensors for channels 1 and 2.The VIRR data thus derived are reliable.展开更多
Chinese meteorological satellite FY-1D can obtain global data from four spectral channels which include visible channel(0.58-0.68 μm) and infrared channels(0.84-0.89 μm,10.3-11.3 μm,11.5-12.5 μm).2366 snow and ice...Chinese meteorological satellite FY-1D can obtain global data from four spectral channels which include visible channel(0.58-0.68 μm) and infrared channels(0.84-0.89 μm,10.3-11.3 μm,11.5-12.5 μm).2366 snow and ice samples,2024 cloud samples,1602 land samples and 1648 water samples were selected randomly from Arctic imageries.Land and water can be detected by spectral features.Snow-ice and cloud can be classified by textural features.The classifier is Bayes classifier.By synthesizing five d ays classifying result of Arctic snow and ice cover area,complete Arctic snow and ice cover area can be obtained.The result agrees with NOAA/NESDIS IMS products up to 70%.展开更多
FY-1D is the second national operation meteorological satellite of China, and is much better compared to monitoring fog. However, research on monitoring fog using FY-1D is very few. In this paper, based on the typical...FY-1D is the second national operation meteorological satellite of China, and is much better compared to monitoring fog. However, research on monitoring fog using FY-1D is very few. In this paper, based on the typical FY-1D data, a fog＇s spectral characteristics in the different channels are analyzed using the histogram analysis method, and a method of monitoring fog using FY-1D is suggested. The results indicate that the 1st and 4th channels are the representative channels of FY-1D for the identification of fog. In the 1st channel, the fog is with uniform veins, smooth top, and clear-cut boundary, and its albedo is 20%-48%. In the 4th channel, the fog＇s brightness and temperature is 272-289K, and the difference value between the fog＇s and the ground surface＇s is not more than 6K.展开更多
基金Supported by the National Key Research and Development Program of China(2018YFB0504905 and 2018YFB0504900)。
文摘The visible infrared radiometer(VIRR)is the first instrument with longest measurements equipped on the Fengyun(FY)polar-orbiting satellites.Through re-processing of the historic VIRR measurements,long-term(over 20 yr)global data can be integrated from multiple participating VIRRs on a consistent radiometric scale,which are valuable to climate and climate change studies.Due to lack of an onboard calibration system for VIRR,the reflective solar bands must be vicariously calibrated.This study applied the multi-site vicarious approach for consistent calibration of the VIRR visible(VIS)and near-infrared(NIR)data,and produced calibration coefficients for five VIRRs on FY-1 C/D and FY-3 A/B/C.The data quality was then evaluated with observations.The reflectance predicted by using the radiative transfer model over multiple invariant desert and ocean targets was used to derive the calibration slope via a weighted fitting scheme,in which the weights are the inverse of the variance from a radiative transfer simulation evaluated with reference to Aqua moderate resolution imaging spectroradiometer(MODIS).The sensor-specific calibration coefficients were derived on a daily basis by using piecewise polynomials.The calibration reference of the VIRR solar band record was further traced to the Aqua MODIS Collection 6.1 reference calibration with a systematic correction derived from the Libya4 desert.The VIRR record was compared with the Aqua MODIS C6.1 calibration over the polar region based on simultaneous nadir overpass observations.The lifetime relative difference for each sensor are within 3.3%and 4.5%for channels 1 and 2.Invariant deserts were also employed to evaluate the stability and consistency of the VIRR record.In general,the means of the directional and spectral corrected reflectance for each sensor are within 1%of the 20-yr average,implying that the VIRR reflectance of the invariant targets is consistent to within 1%among the sensors for channels 1 and 2.The VIRR data thus derived are reliable.
文摘Chinese meteorological satellite FY-1D can obtain global data from four spectral channels which include visible channel(0.58-0.68 μm) and infrared channels(0.84-0.89 μm,10.3-11.3 μm,11.5-12.5 μm).2366 snow and ice samples,2024 cloud samples,1602 land samples and 1648 water samples were selected randomly from Arctic imageries.Land and water can be detected by spectral features.Snow-ice and cloud can be classified by textural features.The classifier is Bayes classifier.By synthesizing five d ays classifying result of Arctic snow and ice cover area,complete Arctic snow and ice cover area can be obtained.The result agrees with NOAA/NESDIS IMS products up to 70%.
基金FY Meteorology Satellite Remote Sensing Developing and Application Demonstration (No.FiDAF-2-01)
文摘FY-1D is the second national operation meteorological satellite of China, and is much better compared to monitoring fog. However, research on monitoring fog using FY-1D is very few. In this paper, based on the typical FY-1D data, a fog＇s spectral characteristics in the different channels are analyzed using the histogram analysis method, and a method of monitoring fog using FY-1D is suggested. The results indicate that the 1st and 4th channels are the representative channels of FY-1D for the identification of fog. In the 1st channel, the fog is with uniform veins, smooth top, and clear-cut boundary, and its albedo is 20%-48%. In the 4th channel, the fog＇s brightness and temperature is 272-289K, and the difference value between the fog＇s and the ground surface＇s is not more than 6K.
