Chenggege Fang, Peiming Dong, Yang Han, Wanlin Kan
{"title":"大气透射率和 NLTE 校正对 FY-3E 上高光谱红外大气探测仪模拟的影响","authors":"Chenggege Fang, Peiming Dong, Yang Han, Wanlin Kan","doi":"10.1007/s13351-024-3121-2","DOIUrl":null,"url":null,"abstract":"<p>With the launch of the first civilian early-morning orbit satellite <i>Fengyun-3E</i> (<i>FY-3E</i>), 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 <i>FY-3E</i> is comparable to, and even superior to that of the Cross-track Infrared Sounder (CrIS) onboard <i>NOAA-20</i>. 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.</p>","PeriodicalId":48796,"journal":{"name":"Journal of Meteorological Research","volume":"18 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Impact of Atmospheric Transmittance and NLTE Correction on Simulation of High Spectral Infrared Atmospheric Sounder onboard FY-3E\",\"authors\":\"Chenggege Fang, Peiming Dong, Yang Han, Wanlin Kan\",\"doi\":\"10.1007/s13351-024-3121-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>With the launch of the first civilian early-morning orbit satellite <i>Fengyun-3E</i> (<i>FY-3E</i>), 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 <i>FY-3E</i> is comparable to, and even superior to that of the Cross-track Infrared Sounder (CrIS) onboard <i>NOAA-20</i>. 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.</p>\",\"PeriodicalId\":48796,\"journal\":{\"name\":\"Journal of Meteorological Research\",\"volume\":\"18 1\",\"pages\":\"\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-05-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Meteorological Research\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1007/s13351-024-3121-2\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Meteorological Research","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s13351-024-3121-2","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
Impact of Atmospheric Transmittance and NLTE Correction on Simulation of High Spectral Infrared Atmospheric Sounder onboard FY-3E
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.
期刊介绍:
Journal of Meteorological Research (previously known as Acta Meteorologica Sinica) publishes the latest achievements and developments in the field of atmospheric sciences. Coverage is broad, including topics such as pure and applied meteorology; climatology and climate change; marine meteorology; atmospheric physics and chemistry; cloud physics and weather modification; numerical weather prediction; data assimilation; atmospheric sounding and remote sensing; atmospheric environment and air pollution; radar and satellite meteorology; agricultural and forest meteorology and more.