Anticipating help for worldclim data downscaling

[Babu Ram Paudel]

Dear all,

Greetings from Nepal.

I am working on the distribution modelling of a native plant in Nepal. Given the high landscape heterogeneity in mountainous countries such as Nepal, I feel that the highest resolution data (1 km * 1 km) available in the world clim database is still coarse. So, I want to downscale the worldclim data to a finer resolution such as  100 m*100 m. I tried using ArcGIS on my own but could not complete it. So, I request your kind help (possibly R codes or any manual) in this regard. Indeed your contribution will be duly acknowledged in future publication.

Thank you for your understanding and support in advance. I am looking forward to hearing back from you.

Sincerely yours

[Bede-Fazekas Ákos]

Hello Babu,
WorldClim is already downscaled, and downscaling a downscaled dataset is generally not recommended. If you have homogenized weather station data, then it is much more suitable input for your downscaling process than the 1-km-resolution WorldClim data. Or a homogenized and gridded but not downscaled dataset, like E-OBS.
I suggest the following steps:
- calculate the mean and standard deviation of the raw monthy climate variables (Pres01, Prec02, ..., Tmax01) of the coarse-resolution grid (E-OBS, WorldClim, whatever)
- standardize the variables: (x-mean)/sd
- extract the altitude from a DEM for each point of the coarse-resolution grid
- create the fine-resolution (e.g. 100×100 m) grid
- extract the altitude from a DEM for each point of the fine-resolution grid
- using for(), lapply() or future_lapply(), iterate through the 48 monthly climate variables, and do regression kriging with altitude, latitude and longitude as auxiliary variables, using package "gstat"
- destudentize the kriged, fine-resolution monthly variables using the previously stored means and standard deviations: x*sd + mean
- finally, calculate the bioclimatic variables from the monthly climate variables. (I do not suggest downscaling the bioclimatic variables, instead, downscale the raw monthly variables)

Hope this helps,
Ákos
_____________
Ákos Bede-Fazekas
Centre for Ecological Research, Hungary

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[Marcelo Lima]

Hi Babu, 

I have come across a similar issue, and I came across these resources:

https://sites.ualberta.ca/~ahamann/data.html
https://www.sdsm.org.uk/

I have successfully used the  Climate AF software and exchanged emails with Dr Andreas Hamann, who was very helpful. 

Good luck and please report back on your work!

Marcelo

To view this discussion visit https://groups.google.com/d/msgid/maxent/a13d43cf-7611-42a6-8a9e-40d9e2a1691f%40gmail.com.

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Dr Marcelo Gonçalves de Lima

(views are mine)

Research Fellow - Center for Large Landscape Conservation

Cambridge Conservation Forum - Connectivity Conservation Work Group Chair

IUCN - WCPA member/Connectivity Conservation Specialist Group - UK and Brazil Lead

IUCN - CEM member

Biologist, PhD in Ecology

https://www.linkedin.com/in/marcelo-gon%C3%A7alves-de-lima-35b3ba20/