Rmarkdown underline3/19/2023 I tried to code it for one layer (when I use data frames instead of raster it gives an error): ![]() Is there a way to model this? Or a better way to do so instead of linear regression. I wanted to do a pixel-wise multivariable regression to do so, but it seems like the format did not work out. The monthly values were averages over 20-year periods (2021-2040).Īs I do not have solar irradiance I would like to estimate solar irradiation for the time period 2021-2040. Monthly values of minimum temperature, maximum temperature, and precipitation were processed for 23 global climate models (GCMs), and I want to work with two Shared Socio-economic Pathways (SSPs): 245 and 585. The downscaling and calibration (bias correction) was done with WorldClim v2.1 as the baseline climate. Further, I want to work with the data available from CMIP6 downscaled future climate projections. ![]() Each download is a “zip” file containing 12 GeoTiff (.tif) files, one for each month of the year (January is 1 December is 12). I used the data with 2.5 minutes spatial resolutions. There are also 19 “bioclimatic” variables, which I do not use. There are monthly climate data for minimum, mean, and maximum temperature, precipitation, solar radiation, wind speed, water vapor pressure, and for total precipitation. ![]() This version was released in January 2020. I have WorldClim version 2.1 climate data for 1970-2000. Jaey Asks: How do I do a pixel-wise regression between the independent variables tmax, tmin, prec and the depending variable srad after they are clipped in R?
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