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Assimilation of MLS and OMI Ozone Data

Ivanka Štajner, K. Wargan, Li-Yen Chang, Hiroo Hayashi, Steven Pawson, L. Froidevaux, N. J. Livesey

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Abstract

Ozone data from Aura Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) were assimilated into the model at NASA's Global Modeling and Assimilation Office (GMAO). This assimilation produces fields that are superior to those from the operational GMAO assimilation of Solar Backscatter Ultraviolet (SBUV/2) instrument data. Assimilation of Aura data improves the representation of the ozone hole and the agreement with independent Stratospheric Aerosol and Gas Experiment (SAGE) III and sonde data. Ozone in the lower stratosphere is captured better: mean state, vertical gradients, spatial and temporal variability are all improved. Inclusion of OMI and MLS data together, or separately, in the assimilation system provides a way of checking how consistent OMI and MLS data are with each other, and with the model. We found that differences between OMI total column data and model forecasts decrease after MLS data are assimilated. This indicates that MLS stratospheric profiles are consistent with OMI total columns. The evaluation of error characteristics of OMI and MLS will continue as data from newer versions of retrievals becomes available. We report on the initial step in obtaining global assimilated fields that combine measurements from different Aura instruments, the model at the GMAO, and their respective error characteristics. We plan to use assimilated fields in estimation of tropospheric ozone. We also plan to investigate impacts of assimilated fields on numerical weather prediction through their use in radiative models and in the assimilation of infrared nadir radiance data from NASA's Advanced Infrared Sounder (AIRS).

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What this paper is about

Ozone data from Aura Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) were assimilated into the model at NASA's Global Modeling and Assimilation Office (GMAO). This assimilation produces fields that are superior to those from the operational GMAO assimilation of Solar Backscatter Ultraviolet (SBUV/2) instrument data. Assimilation of Aura data improves the representation of the ozone hole and the agreement with independent Stratospheric Aerosol and Gas Experiment (SAGE) III and sonde data. Ozone in the lower stratosphere is captured better: mean state, vertical gradients, spatial and temporal variability are all improved. Inclusion of OMI and MLS data together, or separately, in the assimilation system provides a way of checking how consistent OMI and MLS data are with each other, and with the model. We found that differences between OMI total column data and model forecasts decrease after MLS data are assimilated. This indicates that MLS stratospheric profiles are consistent with OMI total columns. The evaluation of error characteristics of OMI and MLS will continue as data from newer versions of retrievals becomes available. We report on the initial step in obtaining global assimilated fields that combine measurements from different Aura instruments, the model at the GMAO, and their respective error characteristics. We plan to use assimilated fields in estimation of tropospheric ozone. We also plan to investigate impacts of assimilated fields on numerical weather prediction through their use in radiative models and in the assimilation of infrared nadir radiance data from NASA's Advanced Infrared Sounder (AIRS).

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Available abstract

Ozone data from Aura Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) were assimilated into the model at NASA's Global Modeling and Assimilation Office (GMAO). This assimilation produces fields that are superior to those from the operational GMAO assimilation of Solar Backscatter Ultraviolet (SBUV/2) instrument data. Assimilation of Aura data improves the representation of the ozone hole and the agreement with independent Stratospheric Aerosol and Gas Experiment (SAGE) III and sonde data. Ozone in the lower stratosphere is captured better: mean state, vertical gradients, spatial and temporal variability are all improved. Inclusion of OMI and MLS data together, or separately, in the assimilation system provides a way of checking how consistent OMI and MLS data are with each other, and with the model. We found that differences between OMI total column data and model forecasts decrease after MLS data are assimilated. This indicates that MLS stratospheric profiles are consistent with OMI total columns. The evaluation of error characteristics of OMI and MLS will continue as data from newer versions of retrievals becomes available. We report on the initial step in obtaining global assimilated fields that combine measurements from different Aura instruments, the model at the GMAO, and their respective error characteristics. We plan to use assimilated fields in estimation of tropospheric ozone. We also plan to investigate impacts of assimilated fields on numerical weather prediction through their use in radiative models and in the assimilation of infrared nadir radiance data from NASA's Advanced Infrared Sounder (AIRS).

Key concepts: Microwave Limb Sounder, Ozone Monitoring Instrument, Data assimilation, Radiance, Environmental science, Meteorology, Stratosphere, Atmospheric Infrared Sounder

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