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I would like to generate a spatially resolved solar seasonality factor based on raster datasets from the Global Solar Atlas (https://globalsolaratlas.info/map) in QGIS. The data basis are average global horizontal irradiation GHI per month as twelve raster data sets for a specific country. Now I want to divide the irradiance of the highest month by the irradiance of the lowest month for each raster cell to get a seasonality factor.

However, this does not seem to be possible within the raster calculator. What is the best way to perform such an operation with multiple raster datasets in QGIS? Do I have to convert them into vector datasets and perform spatial joins or is there an easier direct way for raster files?

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    Checking the link you provided, I did not see monthly GHI, only yearly averages. The only parameter that I found that was supplied at monthly resolution was PVOUT, the potential photovoltaic output. Can you add some details where to get the monthly GHI?
    – Micha
    Commented Nov 24, 2022 at 10:35
  • @Micha is correct, on global scale you have only PVOUT monthly data layers available. GHI monthly is available for some selected countries (Nepal, Zambia, Pakistan, etc). PVOUT seasonality data layer should be available to download from PV country study.
    – jurajb
    Commented Nov 25, 2022 at 16:20

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It seems that in QGIS this is a 3-step job:

  • use Cell statistics from Processing toolbar to calculate MINIMUM from 12 monthly raster layers (see screenshot of the tool below) enter image description here
  • analogically MAXIMUM from 12 monthly raster layers
  • finally in raster calculator MAXIMUM / MINIMUM gives you seasonality index

Maybe there is some workaround to do it in one step in raster calculator, but I cannot find it. Definitely there are many other possibilities to do this in a single step, e.g. in GRASS GIS r.mapcalc or with a bit of python programming in NUMPY.

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