The infrared imager onboard the Geostationary Operational Environmental Satellite 15 (GOES-15) pro- vides temporally continuous observations over a limited spatial domain. To quantify bias of the GOES-15 imager, obs...The infrared imager onboard the Geostationary Operational Environmental Satellite 15 (GOES-15) pro- vides temporally continuous observations over a limited spatial domain. To quantify bias of the GOES-15 imager, observations from four infrared channels (2, 3, 4, and 6) are compared with simulations from the numerical weather prediction model and radiative transfer model. One-day clear-sky infrared observations from the GOES-15 imager over an oceanic domain during nighttime are selected. Two datasets, Global Forecast System (GFS) analysis and ERA- Interim reanalysis, are used as inputs to the radiative transfer model. The results show that magnitudes of biases for the GOES-15 surface channels are approximately 1 K using two datasets, whereas the magnitude of bias for the GOES-15 water vapor channel can reach 5.5 K using the GFS dataset and 2.5 K using the ERA dataset. The GOES- 15 surface channels show positive dependencies on scene temperature, whereas the water vapor channel has a weak dependence on scene temperature. The strong dependence of bias on sensor zenith angle for the GOES-15 water vapor channel using GFS analysis implies large biases might exist in GFS water vapor profiles.展开更多
首次将MSG-2(Meteosat Second Generation-2)卫星上的旋转增强可见光及红外成像仪(Spinning Enhanced Visible and Infrared Imager,SEVIRI)的观测资料同化到美国国家环境预报中心(National Centers for Environmental Prediction,NCEP...首次将MSG-2(Meteosat Second Generation-2)卫星上的旋转增强可见光及红外成像仪(Spinning Enhanced Visible and Infrared Imager,SEVIRI)的观测资料同化到美国国家环境预报中心(National Centers for Environmental Prediction,NCEP)全球资料同化系统(global data assimilation system,GDAS)中。对当前的地球静止业务环境卫星(Geostationary Operational Environmental Satellite,GOES)成像仪资料的同化问题也进行了进一步探讨。利用CRTM(The Community Radiative Transfer Model)模式,对SEVIRI辐射率观测资料进行了模拟。为了对红外辐射率资料进行模拟,CRTM模式中的几个关键部分得到改进,例如:动态更新地面发射率资料以及采用了快速精确的气体吸收模块。为了改进对SEVIRI和GOES成像仪辐射率资料的模拟效果,采用了GSICS(The Global Space-Based Inter-Calibration System)标定订正。初步研究结果表明,包含对SEVIRI辐射率资料的水汽通道(6.25和7.35μm)和二氧化碳通道(13.40μm)的同化对GFS(Global Forecast System)6d预报具有显著的正影响;而对其他5个SEVIRI红外窗口通道资料的同化则减小了这种正影响。通过应用GSICS标定算法,订正了SEVIRI和GOES-12成像仪观测资料的偏差,提高了对GFS预报的影响。此外,还需作进一步研究来提高对SEVIRI红外窗口通道辐射率资料同化的有效性。展开更多
文摘The infrared imager onboard the Geostationary Operational Environmental Satellite 15 (GOES-15) pro- vides temporally continuous observations over a limited spatial domain. To quantify bias of the GOES-15 imager, observations from four infrared channels (2, 3, 4, and 6) are compared with simulations from the numerical weather prediction model and radiative transfer model. One-day clear-sky infrared observations from the GOES-15 imager over an oceanic domain during nighttime are selected. Two datasets, Global Forecast System (GFS) analysis and ERA- Interim reanalysis, are used as inputs to the radiative transfer model. The results show that magnitudes of biases for the GOES-15 surface channels are approximately 1 K using two datasets, whereas the magnitude of bias for the GOES-15 water vapor channel can reach 5.5 K using the GFS dataset and 2.5 K using the ERA dataset. The GOES- 15 surface channels show positive dependencies on scene temperature, whereas the water vapor channel has a weak dependence on scene temperature. The strong dependence of bias on sensor zenith angle for the GOES-15 water vapor channel using GFS analysis implies large biases might exist in GFS water vapor profiles.
基金美国NOAA和NASA GOES-R Algorithm Working Group和GOES-R Risk Reduction关于地球静止卫星资料模拟和同化项目
文摘首次将MSG-2(Meteosat Second Generation-2)卫星上的旋转增强可见光及红外成像仪(Spinning Enhanced Visible and Infrared Imager,SEVIRI)的观测资料同化到美国国家环境预报中心(National Centers for Environmental Prediction,NCEP)全球资料同化系统(global data assimilation system,GDAS)中。对当前的地球静止业务环境卫星(Geostationary Operational Environmental Satellite,GOES)成像仪资料的同化问题也进行了进一步探讨。利用CRTM(The Community Radiative Transfer Model)模式,对SEVIRI辐射率观测资料进行了模拟。为了对红外辐射率资料进行模拟,CRTM模式中的几个关键部分得到改进,例如:动态更新地面发射率资料以及采用了快速精确的气体吸收模块。为了改进对SEVIRI和GOES成像仪辐射率资料的模拟效果,采用了GSICS(The Global Space-Based Inter-Calibration System)标定订正。初步研究结果表明,包含对SEVIRI辐射率资料的水汽通道(6.25和7.35μm)和二氧化碳通道(13.40μm)的同化对GFS(Global Forecast System)6d预报具有显著的正影响;而对其他5个SEVIRI红外窗口通道资料的同化则减小了这种正影响。通过应用GSICS标定算法,订正了SEVIRI和GOES-12成像仪观测资料的偏差,提高了对GFS预报的影响。此外,还需作进一步研究来提高对SEVIRI红外窗口通道辐射率资料同化的有效性。