Enhancing Clear Radiance Generation for Geostationary Hyperspectral Infrared Sounder Using High Temporal Resolution Information
Abstract With high spatio‐temporal resolution geostationary hyperspectral infrared sounder (GeoHIS) observations, monitoring, and predicting rapidly changing weather events are expected to be improved with continuous information of 3D weather cube. However, due to the nature of radiation, clouds pre...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-01-01
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| Series: | Geophysical Research Letters |
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| Online Access: | https://doi.org/10.1029/2023GL107194 |
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| _version_ | 1849314210608054272 |
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| author | Di Di Jun Li Zhenglong Li Jing Zheng Xinya Gong |
| author_facet | Di Di Jun Li Zhenglong Li Jing Zheng Xinya Gong |
| author_sort | Di Di |
| collection | DOAJ |
| description | Abstract With high spatio‐temporal resolution geostationary hyperspectral infrared sounder (GeoHIS) observations, monitoring, and predicting rapidly changing weather events are expected to be improved with continuous information of 3D weather cube. However, due to the nature of radiation, clouds prevent an adequate retrieval of atmospheric thermodynamic information under clear‐sky conditions due to large uncertainties in the current radiative transfer model. Removing cloud effects from GeoHIS sub‐footprint is an alternative approach for enhancing clear radiance generation. Such cloud removal can be achieved through the optimal cloud‐clearing (OCC) method, which usually relies on the assumption of atmospheric spatial homogeneity. With high temporal resolution observations from GeoHIS, cloud removal can also be achieved through OCC but using the assumption of temporal homogeneity. This concept was demonstrated using 15‐min Geostationary Interferometric Infrared Sounder (GIIRS) observations. The longwave GIIRS clear radiances under partially cloud cover can be effectively produced with observation errors less than 0.02 ± 0.86 K and 0.04 ± 0.77 K for 11 and 12 μm, respectively. |
| format | Article |
| id | doaj-art-5a00cd571b8c40c18e7672d6ce3a34d7 |
| institution | Kabale University |
| issn | 0094-8276 1944-8007 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geophysical Research Letters |
| spelling | doaj-art-5a00cd571b8c40c18e7672d6ce3a34d72025-08-20T03:52:32ZengWileyGeophysical Research Letters0094-82761944-80072024-01-01512n/an/a10.1029/2023GL107194Enhancing Clear Radiance Generation for Geostationary Hyperspectral Infrared Sounder Using High Temporal Resolution InformationDi Di0Jun Li1Zhenglong Li2Jing Zheng3Xinya Gong4Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology Nanjing ChinaFYSIC National Satellite Meteorological Center China Meteorological Administration Beijing ChinaCooperative Institute for Meteorological Satellite Studies University of Wisconsin‐Madison Madison WI USAFYSIC National Satellite Meteorological Center China Meteorological Administration Beijing ChinaFYSIC National Satellite Meteorological Center China Meteorological Administration Beijing ChinaAbstract With high spatio‐temporal resolution geostationary hyperspectral infrared sounder (GeoHIS) observations, monitoring, and predicting rapidly changing weather events are expected to be improved with continuous information of 3D weather cube. However, due to the nature of radiation, clouds prevent an adequate retrieval of atmospheric thermodynamic information under clear‐sky conditions due to large uncertainties in the current radiative transfer model. Removing cloud effects from GeoHIS sub‐footprint is an alternative approach for enhancing clear radiance generation. Such cloud removal can be achieved through the optimal cloud‐clearing (OCC) method, which usually relies on the assumption of atmospheric spatial homogeneity. With high temporal resolution observations from GeoHIS, cloud removal can also be achieved through OCC but using the assumption of temporal homogeneity. This concept was demonstrated using 15‐min Geostationary Interferometric Infrared Sounder (GIIRS) observations. The longwave GIIRS clear radiances under partially cloud cover can be effectively produced with observation errors less than 0.02 ± 0.86 K and 0.04 ± 0.77 K for 11 and 12 μm, respectively.https://doi.org/10.1029/2023GL107194geostationaryhyperspectral infrared soundercloud‐clearing |
| spellingShingle | Di Di Jun Li Zhenglong Li Jing Zheng Xinya Gong Enhancing Clear Radiance Generation for Geostationary Hyperspectral Infrared Sounder Using High Temporal Resolution Information Geophysical Research Letters geostationary hyperspectral infrared sounder cloud‐clearing |
| title | Enhancing Clear Radiance Generation for Geostationary Hyperspectral Infrared Sounder Using High Temporal Resolution Information |
| title_full | Enhancing Clear Radiance Generation for Geostationary Hyperspectral Infrared Sounder Using High Temporal Resolution Information |
| title_fullStr | Enhancing Clear Radiance Generation for Geostationary Hyperspectral Infrared Sounder Using High Temporal Resolution Information |
| title_full_unstemmed | Enhancing Clear Radiance Generation for Geostationary Hyperspectral Infrared Sounder Using High Temporal Resolution Information |
| title_short | Enhancing Clear Radiance Generation for Geostationary Hyperspectral Infrared Sounder Using High Temporal Resolution Information |
| title_sort | enhancing clear radiance generation for geostationary hyperspectral infrared sounder using high temporal resolution information |
| topic | geostationary hyperspectral infrared sounder cloud‐clearing |
| url | https://doi.org/10.1029/2023GL107194 |
| work_keys_str_mv | AT didi enhancingclearradiancegenerationforgeostationaryhyperspectralinfraredsounderusinghightemporalresolutioninformation AT junli enhancingclearradiancegenerationforgeostationaryhyperspectralinfraredsounderusinghightemporalresolutioninformation AT zhenglongli enhancingclearradiancegenerationforgeostationaryhyperspectralinfraredsounderusinghightemporalresolutioninformation AT jingzheng enhancingclearradiancegenerationforgeostationaryhyperspectralinfraredsounderusinghightemporalresolutioninformation AT xinyagong enhancingclearradiancegenerationforgeostationaryhyperspectralinfraredsounderusinghightemporalresolutioninformation |