Retrieval of daytime mesospheric ozone using OSIRIS observations of O2 (a1Δg) emission

Journal article, 2020

This work is distributed under the Creative Commons Attribution 4.0 License. Improving knowledge of the ozone global distributions in the mesosphere-lower thermosphere (MLT) is a crucial step in understanding the behaviour of the middle atmosphere. However, the concentration of ozone under sunlit conditions in the MLT is often so low that its measurement requires instruments with very high sensitivity. Fortunately, the bright oxygen airglow can serve as a proxy to retrieve the daytime ozone density indirectly, due to the strong connection to ozone photolysis in the Hartley band. The OSIRIS IR imager (hereafter, IRI), one of the instruments on the Odin satellite, routinely measures the oxygen infrared atmospheric band (IRA band) at 1.27 μm. In this paper, we will primarily focus on the detailed description of the steps done for retrieving the calibrated IRA band limb radiance (with <10 % random error), the volume emission rate of O2 (a1i"g) (with <25 % random error) and finally the ozone number density (with <20 % random error). This retrieval technique is applied to a 1-year sample from the IRI dataset. The resulting product is a new ozone dataset with very tight along-track sampling distance (<20 km). The feasibility of the retrieval technique is demonstrated by a comparison of coincident ozone measurements from other instruments aboard the same spacecraft, as well as zonal mean and monthly average comparisons between Odin-OSIRIS (both spectrograph and IRI), Odin-SMR and Envisat-MIPAS. We find that IRI appears to have a positive bias of up to 25 % below 75 km, and up to 50 % in some regions above. We attribute these differences to uncertainty in the IRI calibration as well as uncertainties in the photochemical constants. However, the IRI ozone dataset is consistent with the compared dataset in terms of the overall atmospheric distribution of ozone between 50 and 100 km. If the origin of the bias can be identified before processing the entire dataset, this will be corrected and noted in the dataset description. The retrieval technique described in this paper can be further applied to all the measurements made throughout the 19 year mission, leading to a new, long-term high-resolution ozone dataset in the middle atmosphere.