I have 15 raster layers. Each one shows accumulated precipitation (rainfalls) for the month of April for the same US state during a given year. So, I cover the period from 1997 to 2012. I would like to have an idea of the variability of precipitation during the last 15 years.
I would like for example to calculate the standard deviation at each pixel across the 15 layers. I am guessing I can do it through the raster calculator using sums, subtractions and divisions. But the final formula would pretty long. Is there a more efficient way to achieve my goal? (So far, I am only a QGis user and I don't know Python...but I can start learning if necessary).