Improved CCD tropospheric ozone from S5P/TROPOMI satellite data using local cloud fields

Tropospheric ozone is an important pollutant and greenhouse gas in the Earth’s atmosphere. Due to its short lifespan and dependence on sunlight and precursor emissions from natural and anthropogenic sources, tropospheric ozone exhibits a high spatio-temporal variability on seasonal, inter-annual and decadal time scales, which, in turn, poses a clear challenge to the satellite observing system. The Convective Cloud Differential (CCD) and Cloud Slicing Algorithms (CSA) are two standard tropospheric ozone retrieval methods limited to the tropical band (20◦S-20◦N). In particular, the CCD approach has been successfully applied to currently operating satellite sensors such as Aura OMI, MetOp GOME-2 and Sentinel-5 Precursor TROPOMI to derive tropical tropospheric column ozone (TTCO). In this study, we present the CHORA-CCD (Cloud Height Ozone Reference Algorithm-CCD) for retrieving TTCOs from TROPOMI. It uses a local cloud reference sector (CLC, CHORA-CCD Local Cloud) rather than the more common CCD approach using the Pacific region (CPC, CHORA-CCD Pacific Cloud) to determine the TTCO by subtracting the stratospheric (above cloud) column from the total column in clear-sky scenes in the same zonal band. An important assumption for this method is the zonal invariance of stratospheric ozone, which is only valid in the tropics. The local cloud approach is the first step to avoid this constraint and to extend the CCD method to middle latitudes, where stratospheric ozone variations are larger. An iterative approach has been developed for the automatic selection of an optimal local cloud reference sector around each retrieval grid box varying longitudinally from ±5◦ to a maximum of ±50◦. The CLC algorithm is further adapted and optimised in the CLCT algorithm by introducing a homogeneity criterion for total ozone to overcome the inhomogeneities in stratospheric ozone. An alternative method to directly estimate the above cloud column down to a reference altitude (270 hPa) is also introduced based on the Theil-Sen regression. The latter allows combining the CCD method with the CSA. Monthly averaged TTCOs using the Pacific cloud reference sector (CPC) and local cloud reference sector (CLC, CLCT) have been determined over the tropics and subtropics (26◦S-21◦N) from TROPOMI for the time period from 2018 to 2021. The accuracy of the various methods was investigated by comparisons with collocated NASA/GSFC SHADOZ ozonesonde retrievals. At eight out of twelve stations, TTCOs using CLC and CLCT yields better agreement with ozonesondes than CPC. In the tropics, the overall mean CLCT bias and dispersion of -6±8% is lower than the 11±12% of CPC. Similarly, in the subtropics, the CLCT algorithm significantly improves overall bias and scatter (-15±9%) compared to CPC (-25±19%). The overall statistical dispersion is effectively reduced to 2DU using CLCT from 5DU using CPC. In this presentation, a detailed validation of the new local CCD retrievals will be given. Our results demonstrate the advantage of using the local cloud reference sector in the subtropics, thereby providing an important basis for subsequent systematic applications in current and future missions of geostationary satellites, like ESA Sentinel 4, NASA Tempo, and GEMS covering only middle latitudes.