This article proposed a statistical spatio-temporal kriging-based approach that is able to interpolate/predict from the dataset and provide uncertainties. The topic is of interest to the readership of this journal, this study is well planned, and the mathematics appears correct and keeps at an appropriate level. However, this paper still need to be improved with moderate revisions:

1. Kriging methods have been widely used in spatial and temporal interpolation for meteorological elements, in the meantime, many improved kriging methods have been proposed, such as Universal Kriging, Co-Kriging, Disjunctive Kriging and so on. Therefore, this paper should give a brief overview of these improved methods, and highlight the advance of this paper method compared with the existing methods.
2. The experimental section is lack of adequate contrast experiments with other existing interpolation methods (especially the representative improved kriging methods).

In this article, the authors use a kriging method to interpolate measurements and predict cloud properties of LWC from CloudSat satellite retrievals. Because of the polar orbit and the fixed-nadir radar measurement, CloudSat provides the most spatiotemporally coarse measurements of any satellite cloud radar. This is a frequent impediment for users of CloudSat for climatologies, and many prior studies have dealt with this issue with comparatively simple methods, such as gaussian means and standard deviations. There is a clear benefit in an advanced statistical method that could provide well-described (that is, with numerical uncertainties) predictions of unsampled regions based off of neighboring retrievals, so I recommend this paper for publication. 

The majority of this paper discusses the kriging method, application, and resulting optimal estimation. I do not have much of a background in Kriging, but it seems like the other reviewer has already gone in-depth with recommendations on this matter, so I will not add anything else. I do not find any other issues with the results.