## 4 Difference between Climate Normals and Climatologies  
### Total and Low Cloud Fraction  
Figure 1 shows the absolute values of climate normal of total cloud fraction for the month of January following the strict WMO data completeness guidelines (i.e., CN_WMO) together with the differences between CN_WMO and the other versions of climate normal and climatologies, as explained in Section 3 above. It can be seen that, in the case of total cloud fraction, the CN_WMO, CN_MB and Clim30 are exactly identical. This means that the conventional 30-year climatology can fully represent climate normal for this variable in question. This is possible mainly due to the fact that the total cloud fraction is retrieved under all circumstances wherein the quality controlled data are available, which has predominantly been the case during the 1991-2020 period. This is evident in Figure 2, which shows the total number of longitude grid points failing either the D5 or the D11 condition in the latitude-time domain. In 1995, a brief data loss occurred during the change from NOAA-11 to NOAA-14 satellite platform. The availability of NOAA-12 during this time was not enough at the higher latitudes in the northern hemisphere to cover the data loss due to the change of satellite platform and the data loss due to solar contamination of thermal channels [50; 51]. However, in all other years, the valid daily means are available continuously and uniformly, thus allowing the computation of CN_WMO globally. Figure 1: The absolute values of CN_WMO for the total cloud fraction (in %) together with the differences (also in %) between CN_WMO and the monthly based climate normal (CN_MB) and the two climatologies (Clim30 and Clim40). The numbers in the titles of subplots show the global mean differences. The spatial resolution of the equal angle lat-lon grid is 0.25 degrees. When the total cloud fraction is sub-divided into contributions from low, middle, and high clouds, CN_WMO, CN_MB and Clim30 are also exactly identical. This is shown in Figure 3 in the case of low cloud fraction. This shows that all valid outcomes of cloud detection lead to the successful classification into low, middle, or high cloud types. This data completeness further enables the successful computation of CN_WMO. Similar results were also found for the middle and high clouds (not shown here). The differences between CN_WMO and Clim40 shown in Figures 1 and 3 for the total and low cloud fraction, respectively, are noteworthy. Previous studies have shown that the global cloud cover is generally decreasing when the trends are computed over the  
Figure 3: Same as in Figure 1, but for the low-level clouds. Figure 2: Latitude–time histograms showing the number of longitude grids failing either the D5 or the D11 condition when computing climate normals of total cloud fraction. Maximum number of longitudes grids can be 1440 since the spatial resolution in 0.25 degrees. The resolution on the \(Y\)-axis (latitude) is also 0.25 degrees. last forty years [21; 23; 25; 26; 48]. The decrease has mainly occurred over the sub-tropical to mid-latitudes in both hemispheres. It is, however, worth pointing out that this decrease has not been continuous throughout the 40-year period (1981-2020). For example, although the global cloudiness is decreasing when all forty years considered, when we focus only on the last twenty years, we see that this long-term decreasing trend in global cloudiness is either stabilising or even slightly reversing. Since Clim40 includes an extra 10 years of data from the decade before the latest normal period (1991-2020) when the cloud cover was higher, the global mean differences between CN_WMO and Clim40 are still negative. There are, however, some regions where these differences are positive due to increasing trends in cloudiness, for example, the stratocumulus regions in the southeast Pacific off the northwestern coast of South America and also the stratocumulus region in the southeast Atlantic.