Wenfu Tang, Benjamin Gaubert, Louisa Emmons, Daniel Ziskin, Debbie Mao, David Edwards, Avelino Arellano, Kevin Raeder, Jeffrey Anderson, Helen Worden
{"title":"同化大气成分多光谱卫星反演的优势:利用MOPITT CO产品的演示","authors":"Wenfu Tang, Benjamin Gaubert, Louisa Emmons, Daniel Ziskin, Debbie Mao, David Edwards, Avelino Arellano, Kevin Raeder, Jeffrey Anderson, Helen Worden","doi":"10.5194/amt-2023-238","DOIUrl":null,"url":null,"abstract":"<strong>Abstract.</strong> The Measurements Of Pollution In The Troposphere (MOPITT) is an ideal instrument to understand the impact of (1) assimilating multispectral/joint retrievals versus single-spectral products, (2) assimilating satellite profile products versus column products, and (3) assimilating multispectral/joint retrievals versus assimilating individual products separately. We use the Community Atmosphere Model with chemistry with the Data Assimilation Research Testbed (CAM-chem+DART) to assimilate different MOPITT CO products to address these three questions. Both anthropogenic and fire CO emissions are optimized in the data assimilation experiments. The results are compared with independent CO observations from TROPOspheric Monitoring Instrument (TROPOMI), the Total Carbon Column Observing Network (TCCON), NOAA Carbon Cycle Greenhouse Gases (CCGG) sites, In-service Aircraft for a Global Observing System (IAGOS), and Western wildfire Experiment for Cloud chemistry, Aerosol absorption and Nitrogen (WE-CAN). We find that (1) assimilating the MOPITT joint (multispectral Near-IR and Thermal-IR) column product leads to better model-observation agreement at and near the surface than assimilating the MOPITT Thermal-IR-only column retrieval. (2) Assimilating column products has a larger impact and improvement for background and large-scale CO compared to assimilating profile products due to vertical localization in profile assimilation. However, profile assimilation can out-perform column assimilations in fire-impacted regions and near the surface. (3) Assimilating multispectral/joint products results in similar or slightly better agreement with observations compared to assimilating the single-spectral products separately.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"23 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advantages of assimilating multi-spectral satellite retrievals of atmospheric composition: A demonstration using MOPITT CO products\",\"authors\":\"Wenfu Tang, Benjamin Gaubert, Louisa Emmons, Daniel Ziskin, Debbie Mao, David Edwards, Avelino Arellano, Kevin Raeder, Jeffrey Anderson, Helen Worden\",\"doi\":\"10.5194/amt-2023-238\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Abstract.</strong> The Measurements Of Pollution In The Troposphere (MOPITT) is an ideal instrument to understand the impact of (1) assimilating multispectral/joint retrievals versus single-spectral products, (2) assimilating satellite profile products versus column products, and (3) assimilating multispectral/joint retrievals versus assimilating individual products separately. We use the Community Atmosphere Model with chemistry with the Data Assimilation Research Testbed (CAM-chem+DART) to assimilate different MOPITT CO products to address these three questions. Both anthropogenic and fire CO emissions are optimized in the data assimilation experiments. The results are compared with independent CO observations from TROPOspheric Monitoring Instrument (TROPOMI), the Total Carbon Column Observing Network (TCCON), NOAA Carbon Cycle Greenhouse Gases (CCGG) sites, In-service Aircraft for a Global Observing System (IAGOS), and Western wildfire Experiment for Cloud chemistry, Aerosol absorption and Nitrogen (WE-CAN). We find that (1) assimilating the MOPITT joint (multispectral Near-IR and Thermal-IR) column product leads to better model-observation agreement at and near the surface than assimilating the MOPITT Thermal-IR-only column retrieval. (2) Assimilating column products has a larger impact and improvement for background and large-scale CO compared to assimilating profile products due to vertical localization in profile assimilation. However, profile assimilation can out-perform column assimilations in fire-impacted regions and near the surface. 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Advantages of assimilating multi-spectral satellite retrievals of atmospheric composition: A demonstration using MOPITT CO products
Abstract. The Measurements Of Pollution In The Troposphere (MOPITT) is an ideal instrument to understand the impact of (1) assimilating multispectral/joint retrievals versus single-spectral products, (2) assimilating satellite profile products versus column products, and (3) assimilating multispectral/joint retrievals versus assimilating individual products separately. We use the Community Atmosphere Model with chemistry with the Data Assimilation Research Testbed (CAM-chem+DART) to assimilate different MOPITT CO products to address these three questions. Both anthropogenic and fire CO emissions are optimized in the data assimilation experiments. The results are compared with independent CO observations from TROPOspheric Monitoring Instrument (TROPOMI), the Total Carbon Column Observing Network (TCCON), NOAA Carbon Cycle Greenhouse Gases (CCGG) sites, In-service Aircraft for a Global Observing System (IAGOS), and Western wildfire Experiment for Cloud chemistry, Aerosol absorption and Nitrogen (WE-CAN). We find that (1) assimilating the MOPITT joint (multispectral Near-IR and Thermal-IR) column product leads to better model-observation agreement at and near the surface than assimilating the MOPITT Thermal-IR-only column retrieval. (2) Assimilating column products has a larger impact and improvement for background and large-scale CO compared to assimilating profile products due to vertical localization in profile assimilation. However, profile assimilation can out-perform column assimilations in fire-impacted regions and near the surface. (3) Assimilating multispectral/joint products results in similar or slightly better agreement with observations compared to assimilating the single-spectral products separately.
期刊介绍:
Atmospheric Measurement Techniques (AMT) is an international scientific journal dedicated to the publication and discussion of advances in remote sensing, in-situ and laboratory measurement techniques for the constituents and properties of the Earth’s atmosphere.
The main subject areas comprise the development, intercomparison and validation of measurement instruments and techniques of data processing and information retrieval for gases, aerosols, and clouds. The manuscript types considered for peer-reviewed publication are research articles, review articles, and commentaries.