Using a convective-cloud differential (CCD) method, developed in-house and applied to retrievals of total ozone and cloud data from three European satellite instruments (viz. GOME/ERS-2, 1995–2003; SCIAMACHY/Envisat, 2002–2012 and GOME-2/MetOp-A, 2007–2015), monthly mean tropical tropospheric columns of ozone (TTCO) have been retrieved, which are in good agreement with ozonesondes (biases less than 6 DU). As small differences in TTCO between the individual instruments were evident, it was necessary to develop a scheme to harmonise the three datasets into one consistent time series starting from 1996 until 2015. Correction offsets (biases) between the instruments using SCIAMACHY as intermediate reference have been calculated and six different harmonisation or merging scenarios have been evaluated. Depending on the merging approach, the magnitude, pattern and uncertainty in the trends strongly vary. The harmonisation or merging represents an additional source of uncertainty in the trends (2 DU decade−1 on average, in most of the cases exceeding the uncertainty from the regression). For studying further details on tropospheric ozone trends on various spatial scales in the tropics, we stick with one preferred merged dataset that shows best agreement with ozonesondes. In this merged dataset, no correction was applied for GOME, and mean biases with respect to SCIAMACHY in the overlapping period (2007–2012) were calculated and applied for GOME-2 in each grid box (2.5° × 5°). In contrast with other studies we found that the tropospheric trend averaged over the tropics (−15° S to 15° N) is not statistically significant. The mean tropospheric ozone trend equals −0.2 ± 0.6 DU decade−1 (2σ). Regionally, tropospheric ozone has a statistically significant increase of ∼ 3 DU decade−1 over southern Africa ( ∼ 1.5 % yr−1), the southern tropical Atlantic ( ∼ 1.5 % yr−1), southeastern tropical Pacific Ocean ( ∼ 1 % yr−1), and central Oceania ( ∼ 2 % yr−1) and by ∼ 2 DU decade−1 over central Africa (2–2.5 % yr−1) and south India ( ∼ 1.5 % yr−1). On the other hand, tropospheric O3 decreases by ∼ 3 DU decade−1 over the Caribbean Sea and parts of the North Pacific Ocean ( ∼ 2 % yr−1), and by less than 2 DU decade−1 over some regions of the southern Pacific and Indian oceans ( ∼ 0.5–1 % yr−1).

The authors present in the paper a detailed trend analysis of tropospheric ozone over the tropics, using a long term homogenized data set based on satellite measurements using the Convective Clouds Differential method. This method and its application on individual satellite sensors has already been presented in various studies including a publication from the same group in AMT (Leventidou et al. 2016). In this paper they homogenize the data from three sensors and examine the variability and the trends over regions and mega cities within the tropics. The paper is well written and structured but there are many significant issues that should be considered before being accepted for publication in ACP.

Tropical tropospheric ozone columns are retrieved with the convective cloud differential (CCD) technique using total ozone columns and cloud parameters from different European satellite instruments. Monthly-mean tropospheric column amounts [DU] are calculated by subtracting the above-cloud ozone column from the total column. A CCD algorithm (CCD_IUP) has been developed as part of the verification algorithm developed for TROPOspheric Monitoring Instrument (TROPOMI) on Sentinel 5-precursor (S5p) mission, which was applied to GOME/ERS-2 (1995–2003), SCIAMACHY/Envisat (2002–2012), and GOME-2/MetOp-A (2007–2012) measurements. Thus a unique long-term record of monthly-mean tropical tropospheric ozone columns (20° S–20° N) from 1996 to 2012 is now available. An uncertainty estimation has been performed, resulting in a tropospheric ozone column uncertainty less than 2 DU ( < 10 %) for all instruments. The dataset has not been yet harmonised into one consistent; however, comparison between the three separate datasets (GOME/SCIAMACHY/GOME-2) shows that GOME-2 overestimates the tropical tropospheric ozone columns by about 8 DU, while SCIAMACHY and GOME are in good agreement. Validation with Southern Hemisphere ADditional OZonesondes (SHADOZ) data shows that tropospheric ozone columns from the CCD_IUP technique and collocated integrated ozonesonde profiles from the surface up to 200 hPa are in good agreement with respect to range, interannual variations, and variances. Biases within ±5 DU and root-mean-square (RMS) deviation of less than 10 DU are found for all instruments. CCD comparisons using SCIAMACHY data with tropospheric ozone columns derived from limb/nadir matching have shown that the bias and RMS deviation are within the range of the CCD_IUP comparison with the ozonesondes. The 17-year dataset can be helpful for evaluating chemistry models and performing climate change studies.

The aim of this study is to propose an evaluation methodology of CALIPSO retrievals of the planetary boundary layer (PBL) height using the analyses of the operational early-delivery assimilation system of the European Centre for Medium-Range Weather Forecast (ECMWF) and Radiosonde observations. The investigation is performed over Thessaloniki, Greece, for a period of almost 5 years between 2006 and 2011. Low correlations between CALIPSO and ECMWF are found when CALIPSO aerosol classification scheme reveals dust presence over Thessaloniki. When eliminating cases of dust advection, the correlation between CALIPSO and ECMWF improves considerably, reaching a value of 0.82, while the correlation between CALIPSO and radiosondes reaches 0.74. The proposed methodology for evaluation shows a good potential for future work when more stations will be considered. Taking into account the aforementioned limitations due to the presence of advected dust layers for the Mediterranean site investigated here, the CALIPSO PBL height could be considered a valuable satellite product for investigating the atmospheric boundary layer processes and for evaluating global and regional atmospheric models.