Slayt 1 - RTC, Regional Training Centre - Turkey

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How Models Solve the ForecastEquations Numerical models solve the forecast equations using one of two basicmodel formulations: grid point or spectral. Grid point models solve the forecast equations at regularly spaced gridpoints. The forecast variables are specified on a set of grid points(illustrated below). Derivatives are approximated at each grid point using a variety ofarithmetic techniques called finite differences, as illustrated below. Thechoice of finite difference method affects both the computational errorand amount of computer time required to run the model.
How Models Solve the ForecastEquationsSpectral models are also based on the primitive equations, but their mathematicalformulation and numerical solutions are quite different from grid point models for some ofthe forecast variables. Spectral techniques were developed as a means of increasing thespeed and therefore enhancing the resolution of global models. Although thesetechniques can be adapted to limited-area (regional) forecast problems, they are mostsuited to global forecasting. However, as the resolution of global models increases overthe next decade, the advantages of using spectral techniques may lessen and more globalmodels may begin using grid point formulations.
Page 1 and 2:
ATMOSPHERIC MODELINGNUMERICAL WEATH
Page 3 and 4:
MTO477Brief History of Meteorology
Page 5:
Excerpts from Aristotle’sMeteorol
Page 72:
The Forces of a Parcel of Air
Page 84 and 85: Atmospheric Model Aerosol processes
Page 86 and 87: Highlights 1955 - First Operational
Page 88 and 89: Highlights 1996 - AVN/MRF changed t
Page 90 and 91: Highlights2001 (November) - Major c
Page 92 and 93: Equivalent-Barotropic Atmosphere Co
Page 94 and 95: Thermal Wind (Remember?)The thermal
Page 96 and 97: Written in general form:tAiA i = de
Page 98 and 99: Example of a diagnostic equation:Co
Page 100 and 101: NUMERICAL WEATHER PREDICTIONLECTURE
Page 102 and 103: Model ComponentsForecast:This repre
Page 104 and 105: Model ComponentsDynamics:In NWP, dy
Page 106 and 107: Parameterized Processes and Paramet
Page 108 and 109: Parameterizing Sub Grid-Scale Proce
Page 110 and 111: Accounting for the Effects of Physi
Page 112 and 113: Outlook As computer power increases
Page 114 and 115: DiscussionThe correct choices are (
Page 116 and 117: 1- NWP EquationsIn NWP, future valu
Page 118 and 119: 2-The Primitive Equations
Page 120 and 121: Horizontal advection of west-to-eas
Page 122 and 123: Additional Information: Coriolis Fo
Page 124 and 125: Additional Information: Coriolis Fo
Page 126 and 127: Temperature Forecast EquationTime c
Page 128 and 129: Hydrostatic or Vertical MomentumEqu
Page 130 and 131: Physical ProcessesAll of the foreca
Page 134 and 135: Representing the Forecast Variables
Page 136 and 137: 3-Grid Point: Data RepresentationGr
Page 138 and 139: 4-Grid Point ModelsIn the real atmo
Page 140 and 141: 5- SPECTRAL MODELHow Data are Repre
Page 142 and 143: Use of Grid Point Methods in Spectr
Page 144 and 145: Impacts of Grid Point Physics Calcu
Page 146 and 147: 7- Hydrostatic Models Most grid poi
Page 148 and 149: Non-Hydrostatic Models In addition,
Page 151 and 152: HYDROSTATIC MODELS Characteristics
Page 153 and 154: References Carr, F.H., 1988: Introd
Page 155 and 156: The dependent variables in this set
Page 157 and 158: Problems in finding suitable latera
Page 159 and 160: Conditions whichOnemakeBIGthe primi
Page 161 and 162: Courant-Friederichs-Lewy criteria C
Page 163 and 164: Setting up a Numerical Model Grid p
Page 165 and 166: Horizontal resolution Horizontal re
Page 167 and 168: Sigma Coordinate System (σ)p• De
Page 169 and 170: Convective ParameterizationSchemes
Page 171: «Computations indicate that a perf
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Slayt 1 - RTC, Regional Training Centre - Turkey

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