According to information brought by WorldClim the new CMIP6 spatial data on temperature and precipitation should contain 12 layers per each downloadable file (1 layer per month) and the bio-climatic variables should have 19 layers in total.
However, when downloading the files from the page: https://www.worldclim.org/data/cmip6/cmip6_clim2.5m.html each file comes as a zip-file apparently only containing one geotiff-file. I don't know if each *.tif file could be layered, but haven't heard about it being possible? (Not like NetCDF).
I have used the WinRar for decompressing the zip-files and Surfer v. 15 for processing the *.tif files.
Thanks!
I have been on this quest recently too. My understanding is that the page you are linking to provides a 20 year average for one variable. I used R to open the file and found only one geotiff-file also. This page: https://worldclim.org/data/cmip6weather.html 'provides' monthly variables, or it should if there wasn't a 404 not found/loading error for every resolution variable. I've emailed and haven't received any corresponding email.
Tayler A Schillerberg thank you for your prompt reply. However, the huge differences in file sizes still indicates that several datasets somehow still might be linked to to each coordinate point. Typically, the WorldClim CMIP6 BIO-climate data files are more that 5 times bigger than the corresponding tn, tx and pr data files, which is hard to explain for single datasets.
Anyway, I'm now looking for global high-res alternatives to the WorldClim data and will reply here if I find something useful. If somebody should have any information on such datasets, please reply!
Hi Sune,
I'm not sure if this is what you want, but you can save the files as raster to make spatial analyses. You can do it in R after downloading the .tiff files as follows:
library(raster)
library(sp)
library(rgdal)
my_files
First, tif files can be layered (in different bands). You can read the tif file using Pyhton's GDAL library, read the entire TIF file as a multi-dimensional array (or multi-dimensional matrix), and then write the array as a .nc file (using the netCDF4 library in Python), or just process and analyze the matrix.
Secondly, maybe you can try the "Raster to netCDF4" function in Arcgis, and read the newly generated .nc file in Python using xarray or netCDF4 library to check the mapping relationship between variables and dimensions.
Zhengyang Li thanks it worked great! In my case I executed GDAL via QGIS v. 3.20 with the Orfeo Toolbox (OTB) plugin installed (OTB/Image Manipulation/Split Image). Also the WorldClim data were complete as expected and had 12 layers for the precip, tmax and tmin parameters.
For download and installation of the OTB the following links have been useful:
https://www.orfeo-toolbox.org/download/
http://wiki.awf.forst.uni-goettingen.de/wiki/index.php/OTB_Plugin_installation
I have read the post of your:“How to open the new WorldClim CMIP6 "future climate data" as layers?”,because I was a newcomer，so can you give me WorldClim CMIP6 data already dealt with（bio-1.。。。。。bio19）thanks a lot
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