# Comparison of SEVIRI-Derived Cloud Occurrence Frequency and Cloud-Top Height with A-Train Data
## 4 Discussion
### Cloud-Top Height  
The CTH comparison results in this study are in line with those from previous research. [PERSON] et al. (2006) compared AIRS and MODIS CTH retrievals with CALIOP and CPR products using the data on 22 July 2006 when the scenes include various cloud types. They found the CTH retrieved from AIRS and MODIS agree well in general, and these retrievals are closer to the values obtained by CPR than the ones obtained by CALIOP. They also noted that the ability to retrieve CTH of optically thin cirrus clouds and very low clouds is limited due to the nature of infrared measurements. [PERSON] et al. (2006) investigated the difference between MODIS and CALIOP CTH for the months of August 2006 and February 2007. They found that the MODIS CTH was 2.6 \(\pm\) 3.9 km lower than the CALIOP products. The mean differences were larger than 4 km for optically thin high clouds. The large CTH differences were observed mainly for high thin cirrus clouds in the equatorial region. They noted that CTH bias depended on the CALIOP product resolution used in the comparison. The 5-km CALIOP averaged product (same resolution as we used in this study) is more sensitive to optically thin clouds than the 1-km product because the signal-to-noise ratio increases through horizontal averaging of CALIOP LiDAR shots. Hence, the higher clouds are detected in the 5-km CALIOP product and the CTH difference to the data from infrared passive sensor becomes larger. [PERSON] et al. (2006) compared ten SEVIRI CTH data sets retrieved from Meteosat-9 satellite observations from ten retrieval algorithms of different institutes in Europe and the USA and validated them with products from CALIOP and CPR by using the five golden day datasets in 2008. In their research, the correlations of the SEVIRI datasets with CALIOP and CPR measurements were between 0.77 and 0.90, and the mean SEVIRI CTHs were 1.1 to 2.5 km lower than the CALIOP measurement, as CALIOP is more sensitive to optically thin clouds. The differences between the SEVIRI and the CPR CTHs ranged from \(-0.8\) to 0.6 km. They also validated CTH retrievals for three different cloud regimes: optically thick and thin single layer clouds and multi-layer clouds. They found that the correlation coefficients were generally above 0.95 and the biases were on the order of a few hundred metres, but the retrieval uncertainties for optically thin clouds and multi-layer clouds became greater.  
In this study, we investigated the CTH accuracy derived from SEVIRI measurements on board Meteosat-10 in the UK Met Office for a longer time period (one year). We found that the SEVIRI CTH products showed similar characteristics to the products from CALIOP and CPR measurements. The overall statistics showed a bias of \(-1.61\) km and a standard deviation of 3.24 km compared to CALIOP CTH, and a bias of \(-0.20\) km and a standard deviation of 1.67 km compared to CPR products. The difference of these statistics from those in [PERSON] (2006)'s study is within the acceptable limits considering the difference in the study period, satellites (Meteosat-9 and Meteosat-10), and the filters used. The visual inspection of comparison plots for many different times and locations suggests that the bias tends to be larger for optically thin clouds and multi-layer clouds than for well-defined single-layer clouds. The reason is that the UK Met Office SEVIRI algorithm assumes a single layer cloud when retrieving CTH similar to many other CTH algorithms for passive infrared measurements. To improve the CTH retrieval for these cloud situations, further research is needed in multi-layer approaches suggested by [PERSON] and [PERSON] (2011), [PERSON] et al. (2013), and recently by [PERSON] et al. (2014) for SEVIRI retrievals. In this study, we also found that CTH derived from SEVIRI measurements depended on the CO\({}_{2}\) channel bias correction increment used in the algorithm. Therefore, careful treatment of the bias correction values is required.