rdale
EF5
No, not the Tyra Banks kind.
COMET has developed a lot of new training modules specifically on the use and understanding of models. Some of the stuff is a little advanced, but if you actually want to do more with model output that say "Here is what the NAM says" then you need this info.
http://www.meted.ucar.edu/topics_nwp.php
I'd suggest you start from the bottom and work up...
24 November 2009
Understanding Assimilation Systems: How Models Create Their Initial Conditions - version 2
Understanding Assimilation Systems: How Models Create Their Initial Conditions, is part of the NWP Distance Learning Course: "Effective Use of NWP in the Forecast Process." This module explains the data assimilation process, including the role of the model itself as well as the observations. It provides learners an appreciation for how models use data as a function of model resolution and data type, how data influence the analysis, the limitations of data assimilation systems, the importance of initial conditions on the quality of NWP guidance, as well as the challenges of assessing the quality of NWP guidance based on the initial conditions. The differences between 3d-var with isotropic background covariances, anisotropic background covariances, 4d-var, and ensemble Kalman filter are conceptually illustrated.
return to top^
<hr noshade="noshade" size="1"> 24 November 2009
Impact of Model Structure and Dynamics - version 2
Impact of Model Structure & Dynamics, part of the NWP Distance Learning Course: "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.
return to top^
<hr noshade="noshade" size="1"> 17 November 2009
Influence of Model Physics on NWP Forecasts - version 2
This module, part of the NWP Distance Learning Course: "Effective Use of NWP in the Forecast Process", describes model parameterizations of surface, PBL, and free atmospheric processes, such as surface snow processes, soil thermal and moisture processes, surface vegetation effects such as evapotranspiration, radiative processes involving clouds and trace gases, and turbulent processes in the PBL and free atmosphere. It specifically addresses how models treat these processes, how such processes can potentially interact with each other, and how they can influence forecasts of sensible weather elements.
return to top^
<hr noshade="noshade" size="1"> 10 November 2009
How Models Produce Precipitation and Clouds - version 2
This module, part of the NWP Distance Learning Course: "Effective Use of NWP in the Forecast Process", explores how NWP models handle both grid-scale microphysical (precipitation) and convective processes through parameterizations and/or explicit methods, with an emphasis on how model treatment (and errors in the triggering) of these processes affects forecast depiction of precipitation and related forecast variables.
The subject matter expert for this module is Dr. Ralph Petersen of the National Centers for Environmental Prediction, Environmental Modeling Center (NCEP/EMC).
<hr noshade="noshade" size="1"> 10 November 2009
Intelligent Use of Model-Derived Products - version 2
This module, part of the NWP Distance Learning Course: "Effective Use of NWP in the Forecast Process", discusses three aspects of forecast guidance developed from raw NWP model data:
1. Post-processing
2. Statistical guidance
3. Model assessment tools
Post-processing methods, including a new section of downscaling of coarser resolution data, bias correction, and post-processing of ensemble forecast system data, are introduced. Interpolation of raw model data to produce the data seen by operational meteorologists is also described.
Next, we present information on statistical guidance methods and techniques, including perfect-prog and Model Output Statistics (MOS). Strengths and limitations of each technique are described.
Finally, we present model assessment tools for verification of NWP model data. The effects of aggregating the data over space and time are discussed, including
1. Point verification versus area verification
2. Short-term versus long-term verification
3. The effect of analysis methods on verification scores
4. Statistics used in verification
and more.
<hr noshade="noshade" size="1"> 05 November 2009
Model Fundamentals - version 2
Model Fundamentals, part of the Numerical Weather Prediction Professional Development Series and the NWP Distance Learning Course, describes the components of an NWP model and how they fit into the forecast development process. It also explores why parameterization of many physical processes is necessary in NWP models.
The module covers background concepts and terminology necessary for learning from the other modules in this series on NWP.
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.
COMET has developed a lot of new training modules specifically on the use and understanding of models. Some of the stuff is a little advanced, but if you actually want to do more with model output that say "Here is what the NAM says" then you need this info.
http://www.meted.ucar.edu/topics_nwp.php
I'd suggest you start from the bottom and work up...
24 November 2009
Understanding Assimilation Systems: How Models Create Their Initial Conditions - version 2
Understanding Assimilation Systems: How Models Create Their Initial Conditions, is part of the NWP Distance Learning Course: "Effective Use of NWP in the Forecast Process." This module explains the data assimilation process, including the role of the model itself as well as the observations. It provides learners an appreciation for how models use data as a function of model resolution and data type, how data influence the analysis, the limitations of data assimilation systems, the importance of initial conditions on the quality of NWP guidance, as well as the challenges of assessing the quality of NWP guidance based on the initial conditions. The differences between 3d-var with isotropic background covariances, anisotropic background covariances, 4d-var, and ensemble Kalman filter are conceptually illustrated.
return to top^
<hr noshade="noshade" size="1"> 24 November 2009
Impact of Model Structure and Dynamics - version 2
Impact of Model Structure & Dynamics, part of the NWP Distance Learning Course: "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.
return to top^
<hr noshade="noshade" size="1"> 17 November 2009
Influence of Model Physics on NWP Forecasts - version 2
This module, part of the NWP Distance Learning Course: "Effective Use of NWP in the Forecast Process", describes model parameterizations of surface, PBL, and free atmospheric processes, such as surface snow processes, soil thermal and moisture processes, surface vegetation effects such as evapotranspiration, radiative processes involving clouds and trace gases, and turbulent processes in the PBL and free atmosphere. It specifically addresses how models treat these processes, how such processes can potentially interact with each other, and how they can influence forecasts of sensible weather elements.
return to top^
<hr noshade="noshade" size="1"> 10 November 2009
How Models Produce Precipitation and Clouds - version 2
This module, part of the NWP Distance Learning Course: "Effective Use of NWP in the Forecast Process", explores how NWP models handle both grid-scale microphysical (precipitation) and convective processes through parameterizations and/or explicit methods, with an emphasis on how model treatment (and errors in the triggering) of these processes affects forecast depiction of precipitation and related forecast variables.
The subject matter expert for this module is Dr. Ralph Petersen of the National Centers for Environmental Prediction, Environmental Modeling Center (NCEP/EMC).
<hr noshade="noshade" size="1"> 10 November 2009
Intelligent Use of Model-Derived Products - version 2
This module, part of the NWP Distance Learning Course: "Effective Use of NWP in the Forecast Process", discusses three aspects of forecast guidance developed from raw NWP model data:
1. Post-processing
2. Statistical guidance
3. Model assessment tools
Post-processing methods, including a new section of downscaling of coarser resolution data, bias correction, and post-processing of ensemble forecast system data, are introduced. Interpolation of raw model data to produce the data seen by operational meteorologists is also described.
Next, we present information on statistical guidance methods and techniques, including perfect-prog and Model Output Statistics (MOS). Strengths and limitations of each technique are described.
Finally, we present model assessment tools for verification of NWP model data. The effects of aggregating the data over space and time are discussed, including
1. Point verification versus area verification
2. Short-term versus long-term verification
3. The effect of analysis methods on verification scores
4. Statistics used in verification
and more.
<hr noshade="noshade" size="1"> 05 November 2009
Model Fundamentals - version 2
Model Fundamentals, part of the Numerical Weather Prediction Professional Development Series and the NWP Distance Learning Course, describes the components of an NWP model and how they fit into the forecast development process. It also explores why parameterization of many physical processes is necessary in NWP models.
The module covers background concepts and terminology necessary for learning from the other modules in this series on NWP.
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.
