Numerical weather prediction: Difference between revisions

Revision as of 17:37, 19 April 2025

Revision as of 04:16, 20 April 2025

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==Domains==

[[File:Sigma-z-coordinates.svg|thumb|280px|A cross-section of the atmosphere over terrain with a [[Sigma coordinate system|sigma- coordinate representation]] shown. Mesoscale models divide the atmosphere vertically using representations similar to the one shown here.|alt=A sigma coordinate systemrepresentation is shown. The lines of equal sigma values follow the terrain at the bottom, and gradually smoothen towards the top of the atmosphere.]]

The horizontal [[Domain of a function|___domain of a model]] is either ''global'', covering the entire Earth, or ''regional'', covering only part of the Earth. Regional models (also known as ''limited-area'' models, or LAMs) allow for the use of finer grid spacing than global models because the available computational resources are focused on a specific area instead of being spread over the globe. This allows regional models to resolve explicitly smaller-scale meteorological phenomena that cannot be represented on the coarser grid of a global model. Regional models use a global model to specify conditions at the edge of their ___domain ([[boundary condition]]s) in order to allow systems from outside the regional model ___domain to move into its area. Uncertainty and errors within regional models are introduced by the global model used for the boundary conditions of the edge of the regional model, as well as errors attributable to the regional model itself.<ref>{{cite book|url=https://books.google.com/books?id=6RQ3dnjE8lgC&pg=PA261|title=Numerical Weather and Climate Prediction|author=Warner, Thomas Tomkins |publisher=[[Cambridge University Press]]|year=2010|isbn=978-0-521-51389-0|page=259}}</ref>