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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>
[[File:Spatial scales of cloud models.png|thumb|A comparison of different types of atmospheric models by spatial ___domain and model grid size.|alt=A plot of model ___domain size versus model grid size with several different types of numerical models arranged diagonally.|left]]
The vertical coordinate is handled in various ways. Lewis Fry Richardson's 1922 model used geometric height (<math>z</math>) as the vertical coordinate. Later models substituted the geometric <math>z</math> coordinate with a pressure coordinate system, in which the [[geopotential height]]s of constant-pressure surfaces become [[dependent variable]]s, greatly simplifying the primitive equations.<ref name="Lynch Ch2">{{cite book|last=Lynch|first=Peter|title=The Emergence of Numerical Weather Prediction|url=https://archive.org/details/emergencenumeric00lync|url-access=limited|year=2006|publisher=[[Cambridge University Press]]|isbn=978-0-521-85729-1|pages=[https://archive.org/details/emergencenumeric00lync/page/n55 45]–46|chapter=The Fundamental Equations}}</ref> This correlation between coordinate systems can be made since pressure decreases with height through the [[Earth's atmosphere]].<ref>{{cite book|author=Ahrens, C. Donald|page=10|isbn=978-0-495-11558-8|year=2008|publisher=Cengage Learning|title=Essentials of meteorology: an invitation to the atmosphere|url=https://books.google.com/books?id=2Yn29IFukbgC&pg=PA244}}</ref> The first model used for operational forecasts, the single-layer barotropic model, used a single pressure coordinate at the 500-millibar (about {{convert|5500|m|ft|abbr=on}}) level,<ref name="Charney 1950">{{cite journal|last1=Charney|first1=Jule|last2=Fjørtoft|first2=Ragnar|last3=von Neumann|first3=John|title=Numerical Integration of the Barotropic Vorticity Equation|journal=Tellus|date=November 1950|volume=2|issue=4|bibcode=1950Tell....2..237C |doi=10.3402/tellusa.v2i4.8607|author-link1=Jule Charney|author-link2=Ragnar Fjørtoft|author-link3=John von Neumann|pages=237|doi-access=free}}</ref> and thus was essentially two-dimensional. High-resolution models—also called ''mesoscale models''—such as the [[Weather Research and Forecasting model]] tend to use normalized pressure coordinates referred to as [[sigma coordinates]].<ref>{{cite web|last=Janjic |first=Zavisa |title=Scientific Documentation for the NMM Solver |url=http://nldr.library.ucar.edu/collections/technotes/asset-000-000-000-845.pdf |publisher=[[National Center for Atmospheric Research]] |access-date=2011-01-03 |author2=Gall, Robert |author3=Pyle, Matthew E. |pages=12–13 |date=February 2010 |url-status=dead |archive-url=https://web.archive.org/web/20110823082059/http://nldr.library.ucar.edu/collections/technotes/asset-000-000-000-845.pdf |archive-date=2011-08-23 }}</ref> This coordinate system receives its name from the [[independent variable]] <math>\sigma</math> used to [[nondimensionalization|scale]] atmospheric pressures with respect to the pressure at the surface, and in some cases also with the pressure at the top of the ___domain.<ref>{{cite book|last=Pielke|first=Roger A.|title=Mesoscale Meteorological Modeling|url=https://archive.org/details/mesoscalemeteoro00srro|url-access=limited|year=2002|publisher=[[Academic Press]]|isbn=978-0-12-554766-6|pages=[https://archive.org/details/mesoscalemeteoro00srro/page/n147 131]–132}}</ref>
==Model output statistics==
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