Downscaling simulated data on CDO
Added by ibrahim erkol over 3 years ago
Have a nice day everyone,
I need to downscale my simulated GCM data using Quantile mapping method.
Is there anyway I can conduct this process on CDO and if not, I'd be so glad if you shared with me a way that doesn't require code writing so much for performing quantile mapping downscaling/bias correction.
I have two nc files. One of them is observation data extending from 1980 to 2018 and the other one is simulated data extending from 1980 to 2100.
Thanks in advance
Best of luck
Replies (6)
RE: Downscaling simulated data on CDO - Added by Ralf Mueller over 3 years ago
Hi Ibrahim!
As far as I know, quantile mapping is not implemented in CDO, sorry.
cheers + a good weekend!
ralf
RE: Downscaling simulated data on CDO - Added by ibrahim erkol over 3 years ago
Hi Ralf,
Thanks for your kind return and everything.
Can you suggest any different way for performing Quantile Mapping downscaling which will not require me to write some lines of code from scratch.
Thanks in advance
Best of weekends
Ibrahim Erkol
RE: Downscaling simulated data on CDO - Added by Ralf Mueller over 3 years ago
sorry - the mapping technique is completely new to me. The method seems to related to histograms.
From what I understood so far it takes values and maps them into some classes, which are set up to cover certain value ranges.
So my first guess would be to analyze the histogram of the data set to come up with a useful classification, or setting of reasonable bins
(using histogram vocabulary). Them I would
- (a) mask out the data for each range using
gtc
andltc
operators with the corresponding values of the each class - (a) multiply these mask with a certain number uniq for each class
- (a) use
add
for addition of all masks - by setting everything else to zero this should leave all classes intact (X-checks needed for validation)
or
- (b) use the
expr
operator and come up with a very long ternary-statement, that covers all classes and - (b) sets the class identifiers right away
here is the docu about it.
hth
ralf
RE: Downscaling simulated data on CDO - Added by Brendan DeTracey over 3 years ago
ibraham. R has a toolbox for quantile mapping(a statistical downscaling method). Python probably does too if you google it. But there will be some coding involved...
edit: https://cran.r-project.org/web/packages/qmap/qmap.pdf
https://www.google.com/search?q=python+quantile+mapping -->
https://www.researchgate.net/post/Does-anyone-know-about-bias-correction-and-quantile-mapping-in-PYTHON
https://www.mdpi.com/2073-4441/11/5/1102/pdf
https://core.ac.uk/download/pdf/207879397.pdf
https://figshare.com/articles/presentation/Scikit-downscale_an_open_source_Python_package_for_scalable_climate_downscaling/12506648/1
RE: Downscaling simulated data on CDO - Added by ibrahim erkol over 3 years ago
Thanks for the resource suggestions but this "there will be some coding involved" issue is a big deal for me. That's why I was looking another way around. Still, thanks a lot for the resources
Best regards
RE: Downscaling simulated data on CDO - Added by Brendan DeTracey over 3 years ago
Yes, but one of the above resources has a TK toolkit i.e. a GUI. I have not tried it but maybe it will help you.
https://github.com/AgroClimaticTools/CDBC