Fengyun-3 D(FY-3 D) satellite is the latest polar-orbiting meteorological satellite launched by China and carries 10 instruments onboard. Its microwave temperature sounder(MWTS) and microwave humidity sounder(MWHS) ca...Fengyun-3 D(FY-3 D) satellite is the latest polar-orbiting meteorological satellite launched by China and carries 10 instruments onboard. Its microwave temperature sounder(MWTS) and microwave humidity sounder(MWHS) can acquire a total of 28 channels of brightness temperatures, providing rich information for profiling atmospheric temperature and moisture. However, due to a lack of two important frequencies at 23.8 and 31.4 GHz, it is difficult to retrieve the total precipitable water vapor(TPW) and cloud liquid water path(CLW) from FY-3 D microwave sounder data as commonly done for other microwave sounding instruments. Using the channel similarity between Suomi National Polar-orbiting Partnership(NPP) advanced technology microwave sounder(ATMS) and FY-3 D microwave sounding instruments, a machine learning(ML) technique is used to generate the two missing low-frequency channels of MWTS and MWHS. Then, a new dataset named as combined microwave sounder(CMWS) is obtained,which has the same channel setting as ATMS but the spatial resolution is consistent with MWTS. A statistical inversion method is adopted to retrieve TPW and CLW over oceans from the FY-3 D CMWS. The intercomparison between different satellites shows that the inversion products of FY-3 D CMWS and Suomi NPP ATMS have good consistency in magnitude and distribution. The correlation coefficients of retrieved TPW and CLW between CMWS and ATMS can reach 0.95 and 0.85, respectively.展开更多
With the launch of the first civilian early-morning orbit satellite Fengyun-3E(FY-3E),higher demands are placed on the accuracy of radiative transfer simulations for hyperspectral infrared data.Therefore,several key i...With the launch of the first civilian early-morning orbit satellite Fengyun-3E(FY-3E),higher demands are placed on the accuracy of radiative transfer simulations for hyperspectral infrared data.Therefore,several key issues are investigated in the paper.First,the accuracy of the fast atmospheric transmittance model implemented in the Advanced Research and Modeling System(ARMS)has been evaluated with both the line-by-line radiative transfer model(LBLRTM)and the actual satellite observations.The results indicate that the biases are generally less than 0.25 K when compared to the LBLRTM,while below 1.0 K for the majority of the channels when compared to the observations.However,during both comparisons,significant biases are observed in certain channels.The accuracy of Hyperspectral Infrared Atmospheric Sounder-II(HIRAS-II)onboard FY-3E is comparable to,and even superior to that of the Cross-track Infrared Sounder(CrIS)onboard NOAA-20.Furthermore,apodization is a crucial step in the processing of hyperspectral data in that the apodization function is utilized as the instrument channel spectral response function to produce the satellite channel-averaged transmittance.To further explore the difference between the apodized and unapodized simulations,Sinc function is adopted in the fast transmittance model.It is found that the use of Sinc function can make the simulations fit the original satellite observations better.When simulating with apodized observations,the use of Sinc function exhibits larger deviations compared to the Hamming function.Moreover,a correction module is applied to minimize the impact of Non-Local Thermodynamic Equilibrium(NLTE)in the shortwave infrared band.It is verified that the implementation of the NLTE correction model leads to a significant reduction in the bias between the simulation and observation for this band.展开更多
基金the National Key Research and Development Program of China (2018YFC1506500)National Natural Science Foundation of China (41675030 and 41675027)National Satellite Meteorological Center [FY3 (02P)-MAS-1803]。
文摘Fengyun-3 D(FY-3 D) satellite is the latest polar-orbiting meteorological satellite launched by China and carries 10 instruments onboard. Its microwave temperature sounder(MWTS) and microwave humidity sounder(MWHS) can acquire a total of 28 channels of brightness temperatures, providing rich information for profiling atmospheric temperature and moisture. However, due to a lack of two important frequencies at 23.8 and 31.4 GHz, it is difficult to retrieve the total precipitable water vapor(TPW) and cloud liquid water path(CLW) from FY-3 D microwave sounder data as commonly done for other microwave sounding instruments. Using the channel similarity between Suomi National Polar-orbiting Partnership(NPP) advanced technology microwave sounder(ATMS) and FY-3 D microwave sounding instruments, a machine learning(ML) technique is used to generate the two missing low-frequency channels of MWTS and MWHS. Then, a new dataset named as combined microwave sounder(CMWS) is obtained,which has the same channel setting as ATMS but the spatial resolution is consistent with MWTS. A statistical inversion method is adopted to retrieve TPW and CLW over oceans from the FY-3 D CMWS. The intercomparison between different satellites shows that the inversion products of FY-3 D CMWS and Suomi NPP ATMS have good consistency in magnitude and distribution. The correlation coefficients of retrieved TPW and CLW between CMWS and ATMS can reach 0.95 and 0.85, respectively.
基金Supported by the Startup Project of Donghai Laboratory(DH-2023QD0002)National Key Research and Development Program of China(2021YFB3900400)Hunan Provincial Natural Science Foundation of China(2021JC0009)。
文摘With the launch of the first civilian early-morning orbit satellite Fengyun-3E(FY-3E),higher demands are placed on the accuracy of radiative transfer simulations for hyperspectral infrared data.Therefore,several key issues are investigated in the paper.First,the accuracy of the fast atmospheric transmittance model implemented in the Advanced Research and Modeling System(ARMS)has been evaluated with both the line-by-line radiative transfer model(LBLRTM)and the actual satellite observations.The results indicate that the biases are generally less than 0.25 K when compared to the LBLRTM,while below 1.0 K for the majority of the channels when compared to the observations.However,during both comparisons,significant biases are observed in certain channels.The accuracy of Hyperspectral Infrared Atmospheric Sounder-II(HIRAS-II)onboard FY-3E is comparable to,and even superior to that of the Cross-track Infrared Sounder(CrIS)onboard NOAA-20.Furthermore,apodization is a crucial step in the processing of hyperspectral data in that the apodization function is utilized as the instrument channel spectral response function to produce the satellite channel-averaged transmittance.To further explore the difference between the apodized and unapodized simulations,Sinc function is adopted in the fast transmittance model.It is found that the use of Sinc function can make the simulations fit the original satellite observations better.When simulating with apodized observations,the use of Sinc function exhibits larger deviations compared to the Hamming function.Moreover,a correction module is applied to minimize the impact of Non-Local Thermodynamic Equilibrium(NLTE)in the shortwave infrared band.It is verified that the implementation of the NLTE correction model leads to a significant reduction in the bias between the simulation and observation for this band.
