I have meteorology datasets of 30 meteorology stations from 1992-2022.
However, there are stations that are missing 20% of the sunshine time.
I have completed these using IDV with the help of Python. Is it an appropriate method?
Yes, using the IDV can contribute favorably to fill the missing data as an appropriate method, but to respond assertively, it depends on the use and applicability of such information. However, it is important to evaluate whether the filled data are reasonable and consistent with the climatic reality of the region. If such missing data cannot be obtained from other sources or databases, it is recommended that cross-validation be performed, which can be done with other data sources to verify the accuracy of the results obtained, or even reanalysis. It is also important that this limitation, if the data is to be published, be clearly described in the data filling method as any assumptions or limitations associated with the process.