Impact of Model Structure & Dynamics, part of the "NWP Training Series: Effective Use of NWP in the Forecast Process", explains how a model forecast, and thus interpretation of that forecast, is affected by the basic design of the model. Topics include how meteorological variables are represented in grid point and spectral models, fundamental differences between hydrostatic and nonhydrostatic models, horizontal resolution of orographic and free-atmosphere features, vertical coordinate systems and how they affect the vertical resolution of features in the model forecast, and the forecast impact of lower, upper, and lateral boundary conditions, including nesting of high-resolution domains.
Back in 2000, the subject matter expert for this module was Dr. Ralph Petersen of the National Centers for Environmental Prediction, Environmental Modeling Center (NCEP/EMC). Revisions to the module were made in 2009 by Drs. Bill Bua and Stephen Jascourt, from the NWP team at UCAR/COMET.
After completing this module, students should be able to:
State the minimum size feature a gridpoint model can predict well (how many grid boxes wide)
List 4 types of weather features which a hydrostatic model of sufficient resolution is capable of properly predicting and 4 types of features which a hydrostatic model even of sufficient resolution will not be able to predict properly because the phenomena are nonhydrostatic in character
State 2 sources of error for a model forecast if the model had perfect initial conditions and perfect representation of physical processes such as radiation, surface energy exchange, microphysics, etc.
Describe the difference between how a grid point model and a spectral model lose information about unresolved features
State the primary source of error present in a limited-domain model but not present in a global model, and describe the time evolution of where in the limited-domain model the error appears
List 2 advantages and 2 limitations of models which use a sigma vertical coordinate or a hybrid which includes sigma coordinates at the bottom of the model
State 2 types of forecast errors other than temperature errors which occur in complex terrain when the terrain is not adequately resolved, even in a model with a grid spacing of 5 km
Describe a scenario in which the forecast from a nested model will be different if the model nesting has 2-way interaction than if it only has 1-way interaction, and describe what and where the forecast difference will be
Describe how the model prediction of boundary layer evolution can be affected by horizontal resolution in an area without complex terrain
model structure, model dynamics, model type, horizontal resolution, vertical resolution, vertical coordinate system, domain, boundary conditions, sigma coordinate, hybrid coordinate, gridpoint, spectral, hydrostatic, nonhydrostatic
December 2020 - The lesson was updated to current internet standards (mp4/html5), with no changes to content.
July 2014: Version 2 of the NWP course is still valid throughout. The most recent data assimilation system used in NCEP models, the Hybrid-EnKF, is not included. This data assimilation system combines 3D-VAR and EnKF into a single system and gets advantages from both. More discussion of the Hybrid-EnKF system can be found in the GFS May 2012 "splash' announcement at http://www.meted.ucar.edu/nwp/pcu2/GFS_20120522_HybEnKF3DVAR.htm.
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