The SUMTIME system builders believe deviating from corpus frequency in such cases makes SUMTIME texts better from the reader's perspective, and it does appear to increase human ratings of the system; but deviating from the corpus in such a way decreases the system's score under corpus-similarity metrics.
the SUMTIME corpus contains both the inputs (numerical weather predictions) and the outputs (forecast texts) of the forecast-generation process.