You might find this as a useful resource:

Pagé et al, dsclim: A software package to downscale climate scenarios at regional scale using a weather-typing based statistical methodology

Available at:

http://www.cerfacs.fr/~page/dsclim/dsclim_doc-latest.pdf

You can also use the scan function in R. If you've not used the package before it will take a bit of getting used to, but it is then a really powerful opensource package.

If you download R

run it and type: ?scan

it will give you an outline of the function.

This function basically lets you write a new file, but you can skip values etc..

use SDSM developed by Wilby

Either SDSM or ClimPact in R statistics only describing the methodology, many of the young researcher who not much expertise and experience doesn't know about what exactly the manuals describing and confusing with commends given. If subject expert explains the methodology with case study along with R scripts step-by-step it will be helpful in interpreting results also.

Please check the SDSM mannual, that is too good. Otherwise google for IPCC guidelines of statistical downscaling.

Dear Nimra,

If you want AR4 models for downscaling you can use LARS-WG5.5 or SDSM or ASD. But if you'll want downscaling AR5 you can't use these models. For downscaling CIMP5 models I am searching about  2 months. I think you can't use SDSM because it's for AR4 models.You can't use http://www.cerfacs.fr/~page/dsclim/dsclim_doc-latest.pdf  because it's for AR4 too.

you should use other methods for this aim. Now I am working on many different ways for spatial downscaling. When I'll choose the best one, I'll send you as soon as possible.

Regards,

Nasrin.

 I'm looking for that, too. After a week's research, I still doing that. There is seems not a easy way to do statistical downscaling expect the SDSM software, but it's not open source. You can't know how to implement it... Anyway, good luck to us!

For CMIP3 models, SDSM can be regarded as one of the easiest methods. However for CMIP5 models adopted in IPCC AR5, you cannot use that. 

For CMIP3 models, SDSM can be regarded as one of the easiest methods. However for CMIP5 models adopted in IPCC AR5, you cannot use that. 

For CMIP3 models, SDSM can be regarded as one of the easiest methods. However for CMIP5 models adopted in IPCC AR5, you cannot use that. 

spdownscale

An R package

This paper on "Representative general circulation models selection and downscaling of climate data" might be helpful:

https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/joc.6447