This study simulated FY-2 D satellite infrared brightness images based on the WRF and RTTOV models. The effects of prediction errors in WRF micro-and macroscale cloud variables on FY-2 D infrared brightness temperatur...This study simulated FY-2 D satellite infrared brightness images based on the WRF and RTTOV models. The effects of prediction errors in WRF micro-and macroscale cloud variables on FY-2 D infrared brightness temperature accuracy were analyzed. The principle findings were as follows. In the T+0–48 h simulation time, the root mean square errors of the simulated brightness temperatures were within the range 10–27 K, i.e., better than the range of 20–40 K achieved previously. In the T+0–24 h simulation time, the correlation coefficients between the simulated and measured brightness temperatures for all four channels were >0.5. The simulation performance of water channel IR3 was stable and the best. The four types of cloud microphysical scheme considered all showed that the simulated values of brightness temperature in clouds were too high and that the distributions of cloud systems were incomplete, especially in typhoon areas. The performance of the THOM scheme was considered best, followed in descending order by the WSM6, WDM6, and LIN schemes. Compared with observed values, the maximum deviation appeared in the range 253–273 K for all schemes. On the microscale, the snow water mixing ratio of the THOM scheme was much bigger than that of the other schemes. Improving the production efficiency or increasing the availability of solid water in the cloud microphysical scheme would provide slight benefit for brightness temperature simulations. On the macroscale, the cloud amount obtained by the scheme used in this study was small. Improving the diagnostic scheme for cloud amount, especially high-level cloud, could improve the accuracy of brightness temperature simulations. These results could provide an intuitive reference for forecasters and constitute technical support for the creation of simulated brightness temperature images for the FY-4 satellite.展开更多
The Microwave Land Surface Emissivity(MLSE)atlas and instantaneous simulation of all-sky/all-surface MLSE are important prerequisites for satellite data assimilation.A ten-day/month synthesized FengYun-3D MLSE atlas(N...The Microwave Land Surface Emissivity(MLSE)atlas and instantaneous simulation of all-sky/all-surface MLSE are important prerequisites for satellite data assimilation.A ten-day/month synthesized FengYun-3D MLSE atlas(New_FY3D)was constructed by the two global MLSE daily product datasets,clear-sky(FY-3D1)and clear/cloudy(FY-3D2),which were retrieved from the same FY-3D MicroWave Radiation Imager(MWRI)Level-1 brightness temperature(BT)data from 2021 to 2022,respectively.Then,a set of global MLSE label samples based on the New_FY3D,including 14 surface geophysical parameters,was obtained for an instantaneous global MLSE simulation at a 0.10°spatial resolution by adopting the extreme gradient boosting(XGBoost)machine learning method.Finally,the FengYun-3F(FY-3F)MWRI-II BT simulations using the Advanced Radiative Transfer Modeling System(ARMS)based on the above different MLSE products were evaluated.The results show that the New_FY3D atlas performs well,and the BT simulation at the top of atmosphere is better than that of FY-3D1,FY-3D2,and the international mainstream TELSEM2(Version 2.0 for a Tool to Estimate Land Surface Emissivities in the Microwaves)atlas.Surface roughness,vegetation coverage,land cover type,and snow cover are vital parameters for MLSE simulation.The XGBoost model can accurately simulate all-sky/all-surface MLSE instantaneously over the frequency range 10.65–89.0 GHz.The average simulation determination coefficients(R^(2))under clear-sky and cloud-sky conditions are 0.925 and 0.901,respectively,and the average root-mean-square errors(RMSEs)are 0.018 and 0.021,respectively.Large simulation errors occur in permanent wetland,ice and snow,and urban and built-up areas.With a standard deviation of 6.6 K,the BT simulation based on an XGBoost simulated MLSE is better than those based on New_FY3D and TELSEM2.展开更多
Earth observation technologies are important for obtaining geospatial information on the Earth’s surface and are used widely in many disciplines,such as resource surveying,environmental monitoring,and evolutionary st...Earth observation technologies are important for obtaining geospatial information on the Earth’s surface and are used widely in many disciplines,such as resource surveying,environmental monitoring,and evolutionary studies.However,it is a challenge for existing Earth observation platforms to acquire this type of data rapidly on a global scale due to limitations in orbital altitude and field of view;thus development of an advanced platform for Earth observation is desirable.As a natural satellite of the Earth,placement of various sensors on the Moon could possibly facilitate comprehensive,continuous,and longterm observations of the Earth.This is a relatively new concept and the study is still at the preliminary stage with no actual Moon-based Earth observation data available at this time.To understand the characteristics of Moon-based microwave radiation,several physical factors that potentially influence microwave radiation imaging,e.g.,time zone correction,relative movement of the Earth-Moon,atmospheric radiative transfer,and the effect of the ionosphere,were examined.Based on comprehensive analysis of these factors,the Moon-based microwave brightness temperature images were simulated using spaceborne temperature data.The results show that time zone correction ensures that the simulation images may be obtained at Coordinated Universal Time(UTC)and that the relative movement of the Earth-Moon affects the positions of the nadir and Moon-based imaging.The effect of the atmosphere on Moon-based observation is dependent on various parameters,such as atmospheric pressure,temperature,humidity,water vapor,carbon dioxide,oxygen,the viewing zenith angle and microwave frequency.These factors have an effect on atmospheric transmittance and propagation of upward and downward radiation.When microwaves propagate through the ionosphere,the attenuation is related to frequency and viewing zenith angle.Based on initial studies,the simulation results suggest Moon-based microwave radiation imaging is realistic and viable.展开更多
基金supported jointly by the Major Special Projects of the Information System Bureau,the Special Proget of Earth Observation with High Resolution(Grant No.GFZX0402180102)the National Natural Science Foundation of China(Grant No.U1533131)
文摘This study simulated FY-2 D satellite infrared brightness images based on the WRF and RTTOV models. The effects of prediction errors in WRF micro-and macroscale cloud variables on FY-2 D infrared brightness temperature accuracy were analyzed. The principle findings were as follows. In the T+0–48 h simulation time, the root mean square errors of the simulated brightness temperatures were within the range 10–27 K, i.e., better than the range of 20–40 K achieved previously. In the T+0–24 h simulation time, the correlation coefficients between the simulated and measured brightness temperatures for all four channels were >0.5. The simulation performance of water channel IR3 was stable and the best. The four types of cloud microphysical scheme considered all showed that the simulated values of brightness temperature in clouds were too high and that the distributions of cloud systems were incomplete, especially in typhoon areas. The performance of the THOM scheme was considered best, followed in descending order by the WSM6, WDM6, and LIN schemes. Compared with observed values, the maximum deviation appeared in the range 253–273 K for all schemes. On the microscale, the snow water mixing ratio of the THOM scheme was much bigger than that of the other schemes. Improving the production efficiency or increasing the availability of solid water in the cloud microphysical scheme would provide slight benefit for brightness temperature simulations. On the macroscale, the cloud amount obtained by the scheme used in this study was small. Improving the diagnostic scheme for cloud amount, especially high-level cloud, could improve the accuracy of brightness temperature simulations. These results could provide an intuitive reference for forecasters and constitute technical support for the creation of simulated brightness temperature images for the FY-4 satellite.
基金supported by the National Natural Science Foundation of China(Grant No.U2242211)the Hunan Provincial Natural Science Foundation Major Project(Grant No.2021JC0009).
文摘The Microwave Land Surface Emissivity(MLSE)atlas and instantaneous simulation of all-sky/all-surface MLSE are important prerequisites for satellite data assimilation.A ten-day/month synthesized FengYun-3D MLSE atlas(New_FY3D)was constructed by the two global MLSE daily product datasets,clear-sky(FY-3D1)and clear/cloudy(FY-3D2),which were retrieved from the same FY-3D MicroWave Radiation Imager(MWRI)Level-1 brightness temperature(BT)data from 2021 to 2022,respectively.Then,a set of global MLSE label samples based on the New_FY3D,including 14 surface geophysical parameters,was obtained for an instantaneous global MLSE simulation at a 0.10°spatial resolution by adopting the extreme gradient boosting(XGBoost)machine learning method.Finally,the FengYun-3F(FY-3F)MWRI-II BT simulations using the Advanced Radiative Transfer Modeling System(ARMS)based on the above different MLSE products were evaluated.The results show that the New_FY3D atlas performs well,and the BT simulation at the top of atmosphere is better than that of FY-3D1,FY-3D2,and the international mainstream TELSEM2(Version 2.0 for a Tool to Estimate Land Surface Emissivities in the Microwaves)atlas.Surface roughness,vegetation coverage,land cover type,and snow cover are vital parameters for MLSE simulation.The XGBoost model can accurately simulate all-sky/all-surface MLSE instantaneously over the frequency range 10.65–89.0 GHz.The average simulation determination coefficients(R^(2))under clear-sky and cloud-sky conditions are 0.925 and 0.901,respectively,and the average root-mean-square errors(RMSEs)are 0.018 and 0.021,respectively.Large simulation errors occur in permanent wetland,ice and snow,and urban and built-up areas.With a standard deviation of 6.6 K,the BT simulation based on an XGBoost simulated MLSE is better than those based on New_FY3D and TELSEM2.
基金This work was supported by the National Natural Science Foundation of China(Grant No.41590855)the Key Research Project in Frontier Science of the Chinese Academy of Sciences(No.QYZDY-SSW-DQC026).
文摘Earth observation technologies are important for obtaining geospatial information on the Earth’s surface and are used widely in many disciplines,such as resource surveying,environmental monitoring,and evolutionary studies.However,it is a challenge for existing Earth observation platforms to acquire this type of data rapidly on a global scale due to limitations in orbital altitude and field of view;thus development of an advanced platform for Earth observation is desirable.As a natural satellite of the Earth,placement of various sensors on the Moon could possibly facilitate comprehensive,continuous,and longterm observations of the Earth.This is a relatively new concept and the study is still at the preliminary stage with no actual Moon-based Earth observation data available at this time.To understand the characteristics of Moon-based microwave radiation,several physical factors that potentially influence microwave radiation imaging,e.g.,time zone correction,relative movement of the Earth-Moon,atmospheric radiative transfer,and the effect of the ionosphere,were examined.Based on comprehensive analysis of these factors,the Moon-based microwave brightness temperature images were simulated using spaceborne temperature data.The results show that time zone correction ensures that the simulation images may be obtained at Coordinated Universal Time(UTC)and that the relative movement of the Earth-Moon affects the positions of the nadir and Moon-based imaging.The effect of the atmosphere on Moon-based observation is dependent on various parameters,such as atmospheric pressure,temperature,humidity,water vapor,carbon dioxide,oxygen,the viewing zenith angle and microwave frequency.These factors have an effect on atmospheric transmittance and propagation of upward and downward radiation.When microwaves propagate through the ionosphere,the attenuation is related to frequency and viewing zenith angle.Based on initial studies,the simulation results suggest Moon-based microwave radiation imaging is realistic and viable.
