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Four regional climate models (RCMs) nested within global climate models (GCMs) were used to run future simulations.
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This encompasses the use of regional climate models (RCM), nested into global climate models (GCM) for an area of interest as well as employing empirical statistical downscaling methods (ESD).
A broadly-applicable, control-relevant system identification methodology for nonlinear restricted complexity models (RCMs) is presented.
These studies typically use the output from global (GCMs) and regional climate models (RCMs).
Regional Climate Models (RCMs) generate past and future climate simulations that serve as input for subsequent modelling of impact projections.
One strategy to accomplish this is to link GCM outputs with regional climate models (RCMs).
Daily climate projections from regional climate models (RCMs) were also applied to climate mortality studies.
The subcells' constitutive models are nested through a numerical stress-update algorithm.
New tensor models, called nested Tucker models and block PARALIND/CONFAC models, are also introduced.
All these models were nested.
It is considered the state-of-the-art for reanalysis-driven simulations of Regional Climate Models (RCM).
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