5 ms·
What do you mean by data fidelity, you mean about how to represent the data so that it is comparable? I can imagine it is a problem especially since your scale
by igrekel 16y ago
What do you mean by data fidelity, you mean about how to represent the data so that it is comparable? I can imagine it is a problem especially since your scale can change. I know I am not showing accumulations graphically for a number of reasons myself. For a while I was showing snow accumulation on a graph where it would literally accumulate.
Or something about your data sources? I work with data from Environment Canada and the only annoying thing with the data was making meaningful unit conversions when the nature of the accumulation is snow.
- jrd79 16y agoHi, by "data fidelity" we mean that there are a lot of errors and irregularities in the liquid-equivalent precipitation measurements reported by the stations. Some stations don't report it at all, or not reliably, and some report it but with internal inconsistencies. For example, stations may report in 1-hour, 6-hour, or 12-hour intervals, but they frequently report 1-hour measurements that don't even come close to adding up to the 6-hour measurements. We just want to make sure we take some time to understand these issues with the data feeds before we start publishing them. The snow depth feed is also a really cool graph. We have it more or less ready, but it is perhaps the least reliable measurement. For example, during that recent snow storm in Chicago it reported some pretty crazy big snow depth numbers for a couple reports and then without correcting the old reports just dropped the snow depth by more than a meter in the next report. This is fine if you have a human reading the report, but it makes the graph look really weird.