|
National Weather Service |
Apply an understanding of the general methodology of numerical weather prediction to develop realistic expectations for guidance produced by operational models.
Different applications of the basic processes that occur in numerical models lead to distinctly different guidance in both analyses and predictions. This PCU explains how numerical models are developed and helps forecasters interpret model guidance with an understanding of model constraints and features.
1. Assess the validity of available NWP guidance based on an assessment of an individual model's ability to resolve the weather features of concern
2. Determine the impact of common sources of model error on NWP model guidance
3. Determine how the parameterization of physical, atmospheric processes impacts NWP model guidance
Instructional Component 1.1: Model Fundamentals: Briefly describes the components of an NWP model and how they fit into the forecast development process and why parameterization of many physical processes is necessary in NWP models.
Instructional Component 1.2: Impact of Model Structure and Dynamics: Provides operationally-significant background information about model type, horizontal resolution, vertical coordinate systems, vertical resolution, and domain and boundary conditions. Discusses how each can affect a model's ability to depict and forecast meteorological features.
Instructional Component 1.3: How Models Produce Precipitation and Clouds: Provides operationally significant background information about precipitation and cloud parameterization schemes and convective parameterization schemes. Discusses how these parameterizations can affect a model's ability to depict and forecast precipitation.
Instructional Component 1.4: Influence of Model Physics on NWP Forecasts: Describes model parameterizations of sub-surface, boundary layer, and free atmospheric processes, such as surface snow processes, soil model characteristics, vegetation, evapotranspiration, PBL processes and parameterizations, and trace gases, and their impact on the radiative transfer process. Specifically addresses how models treat these physical processes and how they can influence forecasts of sensible weather elements.
Instructional Component 1.5: Intelligent Use of Model-Derived Products: Many NWP output products must undergo internal processing in order to be readily displayed and used. This module examines how such products are developed, their strengths and weaknesses, and their application in the forecast process. The module focuses on three primary groups of model-derived products: post-processed products, statistical guidance products, and model assessment tools.
Instructional Component 1.6: Understanding Data Assimilation: Describes the data assimilation systems used in NWP models. Discusses the processes and components of NWP models involved in data gathering and quality control. Discusses how data assimilation ultimately influences model analyses and forecasts.
Instructional Component 1.7: The Balancing Act of Geostrophic Adjustment: provides a primer on geostrophic adjustment concepts, then discusses their application for understanding and forecasting real weather features, interpreting model forecasts, and recognizing the type and duration of impact that observations exert on the model forecast.
Evaluation 1.1: Web-based pre- and post-tests will be provided for each instructional component (not currently available). The pre-tests will allow the forecaster to assess his or her current knowledge of the topic in order to identify sections in need of completion. Post-tests will assess the forecaster's level of mastery of the material presented in the instructional component. Results of each post-test will be sent electronically to the appropriate training officer.
Return to Numerical Weather Prediction PDS page