You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Short description of the diagnostic
As part of the H2020 EUCP project one our deliverables for WP5 is a selection of case studies examining multiple lines of evidence for climate projections of areas of the EU. In practice, this involves comparing multi model ensembles to identify differences and put datasets with a narrow range of projections in the context of ensembles with wider ranges and more members, i.e. comparing RCMs with GCMs.
ESMValTool provides a way to perform this analysis using reproducible workflows that can easily* be modified for different regions and datasets.
I've developed a recipe to facilitate this along with a couple of diagnostic scripts that produce boxplots and spatial maps of the relevant data, branch and PR details below.
The recipe aims to allow replication of some of the analysis from:
Boé, J., Somot, S., Corre, L., & Nabat, P. (2020). Large discrepancies in summer climate change over Europe as projected by global and regional climate models: causes and consequences. Climate Dynamics, 54(5–6), 2981–3002. https://doi.org/10.1007/s00382-020-05153-1
and also:
Gutiérrez, C., Somot, S., Nabat, P., Mallet, M., Corre, L., Van Meijgaard, E., et al. (2020). Future evolution of surface solar radiation and photovoltaic potential in Europe: investigating the role of aerosols. Environmental Research Letters, 15(3). https://doi.org/10.1088/1748-9326/ab6666
as these papers form the basis of one of our initial case studies. (The goal though is to also include other datasets not examined as part of these papers, as well as look at other case studies that will involve different variables and datasets).
Short description of the diagnostic
As part of the H2020 EUCP project one our deliverables for WP5 is a selection of case studies examining multiple lines of evidence for climate projections of areas of the EU. In practice, this involves comparing multi model ensembles to identify differences and put datasets with a narrow range of projections in the context of ensembles with wider ranges and more members, i.e. comparing RCMs with GCMs.
ESMValTool provides a way to perform this analysis using reproducible workflows that can easily* be modified for different regions and datasets.
I've developed a recipe to facilitate this along with a couple of diagnostic scripts that produce boxplots and spatial maps of the relevant data, branch and PR details below.
The recipe aims to allow replication of some of the analysis from:
Boé, J., Somot, S., Corre, L., & Nabat, P. (2020). Large discrepancies in summer climate change over Europe as projected by global and regional climate models: causes and consequences. Climate Dynamics, 54(5–6), 2981–3002. https://doi.org/10.1007/s00382-020-05153-1
and also:
Gutiérrez, C., Somot, S., Nabat, P., Mallet, M., Corre, L., Van Meijgaard, E., et al. (2020). Future evolution of surface solar radiation and photovoltaic potential in Europe: investigating the role of aerosols. Environmental Research Letters, 15(3). https://doi.org/10.1088/1748-9326/ab6666
as these papers form the basis of one of our initial case studies. (The goal though is to also include other datasets not examined as part of these papers, as well as look at other case studies that will involve different variables and datasets).
This recipe requires use of CORDEX RCM data and as a result needs a number of open issues and PRs from ESMValCore to be resolved.
This includes: ESMValGroup/ESMValCore#865 ESMValGroup/ESMValCore#184 ESMValGroup/ESMValCore#1141 ESMValGroup/ESMValCore#1142 ESMValGroup/ESMValCore#1082 ESMValGroup/ESMValCore#1081 ESMValGroup/ESMValCore#1062 ESMValGroup/ESMValCore#1044 ESMValGroup/ESMValCore#772
There are more issues on my TODO list that I've not got around to opening issues for (mentioned in the comments of the recipe), and other issues are also likely to arise as I examine more of the CORDEX dataset as well as look into other data sources 😒
*Turns out not so easy depending on the dataset...
Branch and pull request
#2178
recipe_GCM_RCM
The text was updated successfully, but these errors were encountered: