Closed hpoulos closed 7 years ago
I don't know how hard it is to make each of these, but having all of them could be helpful for the niche modeling from the get go.
Not hard. I am assuming those are all annual values. The ones that only need either daily tmin or tmax within a year would be easy, the ones that need both would be trickier since that would require some code reorganization (run tmin prediction on 1 year, then run tmax prediction, calculate 11 bioclim variables and then discard the dailies.
I'd just write 11 functions that each took a year of daily tmins and tmaxes as arguments.
That would reduce the current landscape time series data to be 11 values per year rather than 365, so more like 5-10 GB per mtn range total which is not bad for storage.
I think this sounds good. This will work for historical and future projected. I'll try to block a day soon to implement this as it will take a bit of reorganization.
Here are the worldclim bioclim data layers that are related to temperature. These microclimate modeling layers can be found here: http://www.worldclim.org/bioclim
BIO1 = Annual Mean Temperature BIO2 = Mean Diurnal Range (Mean of monthly (max temp - min temp)) BIO3 = Isothermality (BIO2/BIO7) (* 100) BIO4 = Temperature Seasonality (standard deviation *100) BIO5 = Max Temperature of Warmest Month BIO6 = Min Temperature of Coldest Month BIO7 = Temperature Annual Range (BIO5-BIO6) BIO8 = Mean Temperature of Wettest Quarter BIO9 = Mean Temperature of Driest Quarter BIO10 = Mean Temperature of Warmest Quarter BIO11 = Mean Temperature of Coldest Quarter