Hi everyone
I'm currently working on predicting the climate change impacts with LARS-WG statistical downscaling model. LARS-WG supports existing models of CMIP5. Given that, the GCM models are very diverse. I should compare the historical period of the model with the observation period of my area. To see which model is suitable for my area. I saw this in some articles. My problem is that I do not know where I can get historical data about GCMs. The data I need is the maximum and minimum temperature, precipitation, sunshine and solar radiation.
Thank you so much for advising me.
Hi Amin,
You can get the data here: https://esgf-node.llnl.gov/projects/cmip5/. You need to create an account and specify which variables/models you want. It will be on netcdf format. Hope this helps!
ESGF is good, but you can also try https://climate4impact.eu/impactportal/general/index.jsp
do not try to choose a GCM but use multiple GCMs. There is no good GCM but the use of ensemble average of the GCMs is recommended in several research studies
Dear Dr. Philbert Modest Luhunga
Many thanks for your suggestion
Can you introduce me a sample of these articles?
Check this node for CMIP5 dataset
https://esgf-node.llnl.gov/projects/esgf-llnl/
you can use this Canadian database :
http://climate-scenarios.canada.ca/?page=sdi-cmip5intro
Saber Aradpour, I would like to help but I don't know how. The data from climate models normally are expressed per second. You can convert them by multiplying them by 24*60*60 to make them per day, then you can convert them per month, or per year. Then you can compare with your observation to try to choose the models that perform better in your location.
Dear Ahmad you can downscale your data using Lars WG or SDSM, these models are very popular.
Which RCP in Marksim will provide accurate climate data of 2017? 2.6 or 4.2?
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