In this paper,the latest progress,major achievements and future plans of Chinese meteorological satellites and the core data processing techniques are discussed.First,the latest three FengYun(FY)meteorological satelli...In this paper,the latest progress,major achievements and future plans of Chinese meteorological satellites and the core data processing techniques are discussed.First,the latest three FengYun(FY)meteorological satellites(FY-2H,FY-3D,and FY-4A)and their primary objectives are introduced Second,the core image navigation techniques and accuracies of the FY meteorological satellites are elaborated,including the latest geostationary(FY-2/4)and polar-orbit(FY-3)satellites.Third,the radiometric calibration techniques and accuracies of reflective solar bands,thermal infrared bands,and passive microwave bands for FY meteorological satellites are discussed.It also illustrates the latest progress of real-time calibration with the onboard calibration system and validation with different methods,including the vicarious China radiance calibration site calibration,pseudo invariant calibration site calibration,deep convective clouds calibration,and lunar calibration.Fourth,recent progress of meteorological satellite data assimilation applications and quantitative science produce are summarized at length.The main progress is in meteorological satellite data assimilation by using microwave and hyper-spectral infrared sensors in global and regional numerical weather prediction models.Lastly,the latest progress in radiative transfer,absorption and scattering calculations for satellite remote sensing is summarized,and some important research using a new radiative transfer model are illustrated.展开更多
SWAT(Soil and Water Assessment Tool)模型是对大尺度复杂流域进行长时期水文模拟的重要工具,在水文循环、土壤侵蚀、污染物负荷、气候变化与土地利用变化的影响等方面得到广泛应用。SWAT模型在国内外流域模拟中取得良好的模拟效果,但...SWAT(Soil and Water Assessment Tool)模型是对大尺度复杂流域进行长时期水文模拟的重要工具,在水文循环、土壤侵蚀、污染物负荷、气候变化与土地利用变化的影响等方面得到广泛应用。SWAT模型在国内外流域模拟中取得良好的模拟效果,但不确定性问题普遍存在。从模型使用者的视角,针对输入数据的准备、子流域划分和输入数据尺度转换、模型参数校准3个SWAT模型应用的重要步骤,讨论了其主要不确定性来源。模型输入数据精度不足以准确反映其空间差异,模拟单元划分粗略导致输入数据向模拟单元尺度转换时参数集总程度过高,模型参数校准过程中观测数据和评价指标的不合理选择以及异参同效现象。对此,总结提出了降低不确定性、提高模拟精度的主要措施:提高输入数据的分辨率和模拟单元划分精度至理想阈值,对模型的关键参数和部分计算方法进行本地化,采用多重评价指标、自动校准与人工校准相结合以及多要素、多站点的参数校准方法。把握模型应用主要步骤中可能的不确定性来源,并结合具体研究区特征和研究目标采取相应的措施降低不确定性,是提高SWAT模型模拟结果可信度的必要途径。展开更多
A C-band mobile polarimetric radar with simultaneous horizontal and vertical transmission was built in the State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences. It was used in heavy rainf...A C-band mobile polarimetric radar with simultaneous horizontal and vertical transmission was built in the State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences. It was used in heavy rainfall and typhoon observations in 2008. It is well-known that radar calibration is essential and critical to high quality radar data and products. In this paper, the test and weather signals were used in calibration of reflectivity ZH, differential reflectivity ZDR and differential phase ФDP. Noise effects on correlation coefficient ρHV at low signal-noise-ratio （SNR） were analyzed. The polarimetric radar data for a heavy rain and a snow event were inspected to evaluate the performance of the calibration method and radar data quality, and S-band Doppler radar data were used to validate the refiectivity data quality collected by the polarimetric radar. The results show that the polarimetric and S-band Doppler radars have observed comparable reflectivity values and a similar structure of a heavy rainfall case at middle and low levels. The mismatch of two receivers produce obvious ZDR biases, which were verified by the radar data observed at vertical incidence. The ZDR correction improved the radar data quality. The usage range for PHV was defined. Application of the calibration method introduced in this paper can reduce the system biases caused by the difference of horizontal （H） and vertical （V） channels. After the calibration and correction, the polarimetric parameters observed by the polarimetric radar could be used in further relevant researches.展开更多
The launching of CBERS-01(China Brazil Earth Resource Satellite)in 1999,China’s first land observation satellite,signifies an unprecedented milestone in Chinese satellite remote sensing history.Since then,a large num...The launching of CBERS-01(China Brazil Earth Resource Satellite)in 1999,China’s first land observation satellite,signifies an unprecedented milestone in Chinese satellite remote sensing history.Since then,a large number of applications have been developed that drew upon solely CBERS-01 and other Chinese land observation satellites.The application development evolves from one satellite to multiple satellites,from one series of satellites to multiple series,from scientific research to industrial applications.Six aspects of the Chinese land observation satellite program are discussed in this paper:development status,data sharing and distribution,satellite calibration,industrial data applications,future prospects,and conclusion.展开更多
基金funded by the National Key R&D Program of China(Grant Nos.2018YFB0504900 and 2015AA123700)
文摘In this paper,the latest progress,major achievements and future plans of Chinese meteorological satellites and the core data processing techniques are discussed.First,the latest three FengYun(FY)meteorological satellites(FY-2H,FY-3D,and FY-4A)and their primary objectives are introduced Second,the core image navigation techniques and accuracies of the FY meteorological satellites are elaborated,including the latest geostationary(FY-2/4)and polar-orbit(FY-3)satellites.Third,the radiometric calibration techniques and accuracies of reflective solar bands,thermal infrared bands,and passive microwave bands for FY meteorological satellites are discussed.It also illustrates the latest progress of real-time calibration with the onboard calibration system and validation with different methods,including the vicarious China radiance calibration site calibration,pseudo invariant calibration site calibration,deep convective clouds calibration,and lunar calibration.Fourth,recent progress of meteorological satellite data assimilation applications and quantitative science produce are summarized at length.The main progress is in meteorological satellite data assimilation by using microwave and hyper-spectral infrared sensors in global and regional numerical weather prediction models.Lastly,the latest progress in radiative transfer,absorption and scattering calculations for satellite remote sensing is summarized,and some important research using a new radiative transfer model are illustrated.
文摘SWAT(Soil and Water Assessment Tool)模型是对大尺度复杂流域进行长时期水文模拟的重要工具,在水文循环、土壤侵蚀、污染物负荷、气候变化与土地利用变化的影响等方面得到广泛应用。SWAT模型在国内外流域模拟中取得良好的模拟效果,但不确定性问题普遍存在。从模型使用者的视角,针对输入数据的准备、子流域划分和输入数据尺度转换、模型参数校准3个SWAT模型应用的重要步骤,讨论了其主要不确定性来源。模型输入数据精度不足以准确反映其空间差异,模拟单元划分粗略导致输入数据向模拟单元尺度转换时参数集总程度过高,模型参数校准过程中观测数据和评价指标的不合理选择以及异参同效现象。对此,总结提出了降低不确定性、提高模拟精度的主要措施:提高输入数据的分辨率和模拟单元划分精度至理想阈值,对模型的关键参数和部分计算方法进行本地化,采用多重评价指标、自动校准与人工校准相结合以及多要素、多站点的参数校准方法。把握模型应用主要步骤中可能的不确定性来源,并结合具体研究区特征和研究目标采取相应的措施降低不确定性,是提高SWAT模型模拟结果可信度的必要途径。
基金the National Natural Science Foundation of China under Grant No.40775021the National"863"Project"Research on Application System of the Airborne Radar"+1 种基金the China Meteorological Administration Project"Tropical West Pacific Ocean Observation and Predictability"the National Key Basic Research and Development Program of China under Grant No.2004CB418305.
文摘A C-band mobile polarimetric radar with simultaneous horizontal and vertical transmission was built in the State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences. It was used in heavy rainfall and typhoon observations in 2008. It is well-known that radar calibration is essential and critical to high quality radar data and products. In this paper, the test and weather signals were used in calibration of reflectivity ZH, differential reflectivity ZDR and differential phase ФDP. Noise effects on correlation coefficient ρHV at low signal-noise-ratio （SNR） were analyzed. The polarimetric radar data for a heavy rain and a snow event were inspected to evaluate the performance of the calibration method and radar data quality, and S-band Doppler radar data were used to validate the refiectivity data quality collected by the polarimetric radar. The results show that the polarimetric and S-band Doppler radars have observed comparable reflectivity values and a similar structure of a heavy rainfall case at middle and low levels. The mismatch of two receivers produce obvious ZDR biases, which were verified by the radar data observed at vertical incidence. The ZDR correction improved the radar data quality. The usage range for PHV was defined. Application of the calibration method introduced in this paper can reduce the system biases caused by the difference of horizontal （H） and vertical （V） channels. After the calibration and correction, the polarimetric parameters observed by the polarimetric radar could be used in further relevant researches.
基金supported in part by the National Basic Research Program of China(973 Program,Nos.2014CB744201 and 2012CB719902)the Program for New Century Excellent Talents in University+2 种基金the National High Technology Research and Development Program of China(No.2011AA120203)the National Natural Science Foundation of China(No.41371430)the Program for Changjiang Scholars and Innovative Research Team in University under Grant IRT1278.
文摘The launching of CBERS-01(China Brazil Earth Resource Satellite)in 1999,China’s first land observation satellite,signifies an unprecedented milestone in Chinese satellite remote sensing history.Since then,a large number of applications have been developed that drew upon solely CBERS-01 and other Chinese land observation satellites.The application development evolves from one satellite to multiple satellites,from one series of satellites to multiple series,from scientific research to industrial applications.Six aspects of the Chinese land observation satellite program are discussed in this paper:development status,data sharing and distribution,satellite calibration,industrial data applications,future prospects,and conclusion.
