Dear all,
I am working with daily time series of meteorological variables. This is an
example of the dataset:
library(raster)
# Create date sequence
idx <- seq(as.Date("1961/1/1"), as.Date("1990/12/31"), by = "day")
# Create raster stack and assign dates
r <- raster(ncol=20, nrow=20)
s <- stack(lapply(1:length(idx), function(x) setValues(r, runif(ncell(r)))))
s <- setZ(s, idx)
Now, let's assume those values represent daily precipitation. What I need to do
is to integrate daily to monthly values,
and then take a monthly climatology. Climatology in this case means multi-year
average of selected months, e.g., an average of the 30 Octobers from 1961 to
1990, an average of the 30 Novembers from 1961 to 1990 and etc.
On the other hand, let's assume the raster values represent daily temperature.
Integrating daily to monthly temperature doesn't make sense. Hence, instead of
integrating daily values, I need to take monthly means (e.g. mean value of all
days in every month), and then calculate the climatology.
What would be the best approach to achieve that using the raster package?
Greetings,
-- Thiago V. dos Santos
PhD student
Land and Atmospheric Science
University of Minnesota
_______________________________________________
R-sig-Geo mailing list
[email protected]
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
