1. Are there regional variations in utilizing climate change assessment models in regional climate models and global climate models?
2. Can a distinction be made between regional climate models and global climate models? What is the scope of utilizing these models, what are their similarities and differences?
3. As developing countries are worst hit by climate change and impacts, what strategies can be utilized to use these climate change models using climate data?
I need Climate change scientists and experts to share their views. Shalom
General Circulation Models (GCMs), also called Global Climate Models, which simulate the physics of the climate itself. This means they capture the flows of air and water in the atmosphere and/or the oceans, as well as the transfer of heat.
There are also Regional Climate Models (“RCMs”) which do a similar job as GCMs, but for a limited area of the Earth. Because they cover a smaller area, RCMs can generally be run more quickly and at a higher resolution than GCMs. A model with a high resolution has smaller grid cells and therefore can produce climate information in greater detail for a specific area.
RCMs are one way of “downscaling” global climate information to a local scale. This means taking information provided by a GCM or coarse-scale observations and applying it to a specific area or region.
Hi Charles,
GCM is the climate model for the whole globe in which past and future climate conditions can be modelled. This GCM is typically with 1-2.5⁰ horizontal resolution which may coarser for local climate studies. Thus, dynamical and statistical downscaling techniques are used to scale down GCM results to finer resolutions.
The dynamic downscaling is performed via RCM using boundary conditions from GCM. RCM resolution varies from 20-60km in general. The statistical downscaling y boundary conditions from a GCM to derive smaller-scale information uses empirical relationships between large-scale climate predictors from GCMs and local-scale predictands. Both downscaling techniques equally capable in downscaling and come along with advantages and disadvantages. There are many studies in literature you can refer to. The statistical downscaling approach is widely used because of its easy implementation and low computational effort.
V. Daksiya
Many thanks, Rajesh Kumar Mall Your explanations are well understood. And to @Velautham Daksiya I also appreciate you. thanks
The difference is when running climate change simulations via GCMs there is just initial conditions and no boundary conditions to run the models. hence GCMs are designed in a way that they run for the entire globe (thus the name global), they follow a periodic boundary condition approach where if the entire earth is taken into simulations there are no boundaries as the earth is spherical.
Whereas RCMs are always dependent on reanalysis outputs for historical simulation and GCMs output for climate change simulations and they run over smaller scale thus "Regional: because fo which they always have a boundary ( as the earth is the rectangular plane at regional level)
GCMs are used to understand the large-scale changes in circulation because of climate change whereas RCMs uses GCMs as input to see how these large scale changes in GCMs have an impact on a regional level.
Hope this helps
Dr Saurabh SIngh
PhD NTU Singapore
CTO, Intensel Limited
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