While the CERES input aerosol optical depth and precipitable water data are continuously available, the same parameters derived from BSRN site measurements are available only intermittently. Cloudiness disrupts the aerosol optical depth (AOD) retrieval and precipitable water (w) observation sampling. Irregularly sampled records, such as these, can cause systematic biases if the averages of the continuous data are not sampled at the same times as the observed data, as shown by high biases in Fig. 10 in our original paper. This, however, does not suggest that the CERES input aerosol optical depth and precipitable water are systematically significantly higher than ground-based observations. In this addendum, we show that when the monthly means are computed from only those CERES hourly means that have a BSRN match, then the resulting monthly means differ from BSRN-derived parameters to a much lesser extent. To be precise, the biases in the original Fig. 10 decrease 82%, 69% and 52%, respectively; the magnitudes of slopes in the original Fig. 11 decrease by 69% and 65%, respectively. Imposing a cloud fraction less than or equal to 5% further reduces AOD and w mean values but not biases. Nevertheless, the flux bias reduces from -16.9 W m⁻² to -4.2 W m⁻² after imposing the cloud fraction restraint relative to the RADFlux clear-sky fluxes which appear to represent the driest and clearest conditions.

尽管CERES输入的气溶胶光学深度和可沉淀的水数据是连续可用的，但从BSRN站点测量中得出的相同参数只能间歇性地使用。浑浊破坏了气溶胶光学深度（AOD）的回收和可沉淀的水（w）观察抽样。如果不对连续数据的平均值与观测数据同时采样，则诸如此类的不规则采样记录可能会导致系统性偏差，如原始论文中图10中的高偏差所示。但是，这并不意味着CERES输入的气溶胶光学深度和可沉淀水在系统上显着高于地面观测。在此附录中，我们显示，当仅从那些具有BSRN匹配的CERES每小时均值中计算月均值时，则所得的每月均值与BSRN派生的参数的差异就小得多。准确地说，原始图10中的偏差分别降低了82％，69％和52％；原始图11中的斜率幅度分别降低了69％和65％。w是平均值，而不是偏差。然而，相对于RADFlux晴空通量（表现出最干燥和最清晰的条件）施加了云量限制之后，通量偏差从-16.9 W m ^-2减小到-4.2 W m ^-2。