# Comparison of SEVIRI-Derived Cloud Occurrence Frequency and Cloud-Top Height with A-Train Data
## 5 Summary and Conclusions  
This study investigated the characteristics of the UK Met Office SEVIRI products of COF and CTH conducting an inter-comparison of the cloud products from the CPR and the CALIOP on board the A-Train constellation. The evaluation was made on the basis of 329 CPR overpasses allowing for approximately 800,000 individual matchups among the CPR, CALIOP, and SEVIRI products for one year from May 2013 to April 2014. Due to the CPR data availability, only daytime products were compared in this study. The COFs showed good agreement in terms of spatial distribution and temporal variability despite systematic biases, which are expected due to the differences in observation and instrument characteristics of the three sensors. The distribution and variability of the SEVIRI COFs were also consistent with previous studies. CALIOP detected clouds most sensitively and widely, followed by SEVIRI, with a mean frequency difference of \(-\)3.90% in COF. The CPR showed less sensitivity with a COF 14.35% lower than that for SEVIRI. Particularly over the tropics, it is outstanding that the CALIOP COFs showed high frequency and were distributed over the large area near the ITCZ. This can be attributed to CALIOP's high sensitivity to clouds with small ice particles and low optical thickness, which are not enough to be sensed by other sensors. The seasonal variability of the three products showed a similar pattern of decline in summer and an increase in winter. These results suggest that SEVIRI COFs are reliable. However, SEVIRI detected clouds more strictly over oceans (with 64.32% of SEVIRI COF which is 17.28% and 0.67% higher than those from CPR and CALIOP products, respectively) with relatively less effectiveness over the land surface (44.74% of SEVIRI COF with 9.07% and \(-\)12.14% biases against CPR and CALIOP COFs, respectively), where accurate cloud retrievals from passive infrared measurement are challenging. This study also investigated the CTH retrievals by the UK Met Office SEVIRI algorithm compared to CALIOP and CPR products. Differences among the products in the CTH analysis were also noted. The high sensitivity to thin, high clouds of CALIOP was apparent, which generated a larger scatter in the plots of CTH retrieved by the SEVIRI algorithm against CALIOP measurements. The majority of the scatter points were on the lower right-hand side of the one-to-one line, meaning that the CTH retrieved by the SEVIRI algorithm was lower than the CALIOP CTH. Some points were retrieved by SEVIRI as lower clouds with around 1-2 km CTH while CALIOP retrieved them as mid- or high-level clouds. The mean SEVIRI CTHs were 1.61 km lower than CALIOP measurements with a correlation coefficient of 0.78. The average CTHs derived from SEVIRI were closer to CPR products with a correlation coefficient of 0.92 and a bias of \(-\)0.20 km. Thus, further analysis was conducted with the CPR products. Considering that the CO\({}_{2}\) channel BC used in the SEVIRI CTH retrieval algorithm was updated periodically through radiance monitoring, the effect of these BC changes was analysed. The results showed that the SEVIRI CTHs derived by the MR method were highly sensitive to CO\({}_{2}\) BC values. The correlation and STD did not change much, but the retrieved CTH changed noticeably with CO\({}_{2}\) BC updates with the bias ranging from \(-\)0.7 to 0.5 km. The first update of CO\({}_{2}\) BC value from \(-\)1.15 K to 0.85 K led to an increase in CTH values up to about 0.67 km in mean CTH values. Since the BC update in November 2013, SEVIRI has produced more stable CTHs compared with the CPR CTHs, with a correlation coefficient of 0.93, bias of \(-\)0.27 km, and standard deviation of 1.61 km. This study found that the bias correction values need to be carefully monitored and selected when the CTH algorithm is applied with simulated and observed radiance comparison. This study was performed through collaboration of the UK Met Office and Korea Meteorological Administration (KMA).