Abstract. We present the CHORA (Cloud Height Ozone Reference Algorithm) algorithm for retrieving tropospheric ozone columns from S5P/TROPOMI. The method uses a local cloud reference sector (CLC, CHORA Local Cloud) to determine the stratospheric (above cloud) column, which is subtracted from the total column in clear-sky scenes in the same zonal band to retrieve the tropospheric column. The standard CCD (Convective Cloud Differential) approach uses cloud data from the Pacific region (CPC, CHORA Pacific Cloud) instead. An important assumption for the standard method is the zonal invariance of stratospheric ozone. The local cloud approach is the first step to diminish this constraint in order to extend the CCD method to middle latitudes, where stratospheric ozone variability is 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 between ±5° and ±50° and latitudinally by ±1°. The optimised CLCT (CHORA-Local Cloud Theil-Sen algorithm) algorithm, a follow-up from CLC, employs a homogeneity criterion for total ozone from the cloud reference sector in order to overcome the inhomogeneities in stratospheric ozone. It directly estimates the above cloud column ozone for a common reference altitude of 270 hPa using the Theil-Sen regression. The latter allows combining the CCD method with the cloud slicing algorithm that retrieves upper tropospheric ozone volume mixing ratios. Monthly averaged Tropospheric Column Ozone (TCO) 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 2022. The accuracy of the various methods was investigated by comparisons with collocated NASA/GSFC SHADOZ ozonesonde measurements and the ESA TROPOMI Level 2 tropospheric ozone product. At eleven out of twelve stations, tropospheric ozone columns using CLCT yield better agreement with ozonesondes than CPC. The overall statistical dispersion is effectively reduced from 4 DU (CPC) to 2 DU (CLCT). In the tropical region (20° S–20° N), CLCT shows a significantly lower overall mean bias and dispersion of -1±8 %, outperforming both CPC (12±9 %) and CCD-ESA (22±10 %). CLCT surpasses the ESA operational product, providing more accurate tropospheric ozone retrievals at eight out of nine stations in the tropics. For the Hilo station, with a larger stratospheric ozone variability due to its proximity to the subtropics, the bias of +25 % (CPC) is effectively reduced to -12 % (CLCT). Similarly, in the subtropics (Reunion, Irene, and Hanoi), the CLCT algorithm provides an improved overall bias and scatter (-11±8 %) compared to CPC (-17±13 %) with respect to sondes but the bias remains negative. The CLCT effectively reduces the impact of stratospheric ozone inhomogeneity, typically at higher latitudes. These results demonstrate the advantage of the local cloud reference sector in the subtropics. The algorithm, thereby, is an important basis for subsequent systematic applications in current and future missions of geostationary satellites, like GEMS (Geostationary Environment Monitoring Spectrometer, Korea), ESA Sentinel-4, and NASA TEMPO (Tropospheric Emissions: Monitoring of POllution) covering predominantly middle latitudes.