From: NIPS.cc/2018/Workshop/Spatiotemporal/Paper46/AnonReviewer3
evaluation: This paper addresses the problem of global precipitation nowcasting by spatio-temporally fusing radar and satellite observations. Specifically,  to temporally fuse radar and satellite images together, this paper uses optical flow algorithm to synthetically generate satellite images at the same time resolution as that of radar. To spatially fuse two types of data, this paper proposes alpha blending with special modification in inpainting algorithm with a soft mask. The modification offers the advantage that algorithm incorporates some useful information from the corrupted part of the image and successfully fills larger regions. 
Overall, the writing is clear in that the meaning is easy to understand. The scientific nature of approach is presented clearly and directly. The title of the paper is directly explanatory of the topic area. The underpinning work cited in section 2,  is sufficient to justify the experimental part of the research. The results have been analysed both quantitatively and qualitatively. I found no substantial faults/comments in the paper. However, I found little relevance of this paper to the workshop domain. The reason is that, the main focus of the paper is spatial fusion of satellite and radar data. The temporal fusion is done just to get the satellite and radar images at the same time intervals.  I do not see any other part being played by temporal fusion.

From: NIPS.cc/2018/Workshop/Spatiotemporal/Paper46/AnonReviewer3
relevance: 3: borderline
impact: 4: high
novelty: 4: high