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Introduction to Climate Models
This module explains how climate models work. Because the modeling of both weather and climate share many similarities, the content throughout this module draws frequent comparisons and highlights the differences. We explain not only how, but why climate models differ from weather models. To do so, we explore the difference between weather and climate, then show how models are built to simulate climate and generate the statistics that describe it. We conclude with a discussion of models are tuned and tested. Understanding how climate responds to changes in atmospheric composition and other fac ...
Optimizing the Use of Model Data Products
Each model forecast tells a story about the weather events to unfold. As a forecaster, you employ diagnostics to understand and interpret that story, in order to modify it, blend it with other stories, and generate your own forecast. This lesson will help you sift through the abundance of model data so you can understand and interpret the model’s story. Other lessons cover evaluating the model’s story against observations and against your conceptual models of the evolving situation, blending the stories, and adjusting the forecast to add value over an objective forecast. The diagnostic approac ...
Preparing to Evaluate NWP Models
This lesson prepares the forecaster to evaluate NWP analyses and forecasts using physically based conceptual models of the atmosphere, and the "Vertical Phenomenon Analysis Funnel". This funnel divides the atmosphere into three sections: lower stratosphere and tropopause, mid-to-upper troposphere, and lower troposphere. We discuss tools to use and atmospheric features to assess for each section of the atmosphere, using interactive case examples, and summarize the methodology with a comprehensive example. Finally, we compare model capabilities and the time and space scales of assessment tools u ...
Adding Value to NWP Guidance
The purpose of this module is to train operational meteorologists at NWS WFOs and elsewhere how to maximize opportunities to add value to NWP forecasts. The training includes use of the methods and tools from earlier modules in Course 2 of Effective Use of NWP in the Forecast Process. Included in the module are two case examples for the short- and medium-range. Additionally, a WES "caselet" is available from the NWS Warning Decision Training Branch that further illustrates how to add value to NWP guidance.
Determining Plausible Forecast Outcomes
The content of this lesson will assist the forecaster with the third step of the forecast process, namely, determining plausible forecast outcomes forward in time. The lesson will highlight the role of probabilistic forecast tools to assess the degree of uncertainty in a forecast, as well as suggest an approach for evaluating past and present model performance.
How NWP Fits into the Forecast Process
This introductory module presents the basis for the other modules in the new NWP Series: Effective Use of NWP in the Forecast Process. We present the four steps in the forecast process, as determined by best practices in U.S. National Weather Service (NWS) Weather Forecast Offices (WFOs). Then we show the module topics and summarize how to navigate through the course.
Analysis, Diagnosis, and Short-Range Forecast Tools
This lesson is divided into three sections. The first section discusses the importance of analysis and diagnosis in evaluating NWP in the forecast process. In section two, we discuss a methodology for dealing with discrepancies between both the official forecast and NWP compared to analysis and diagnosis. The third section shows a representative example of the methodology.
Bias Correction of NWP Model Data
The lesson "Bias Correction of NWP Model Data" first describes what affects bias in NWP models: regime continuity, timing of features that affect sensible weather, and existence (or not) of those features in the models. After discussing examples of each of these, three bias correction methods are presented: Model Output Statistics (MOS), decaying average, and a SmartInit tool developed at the Boise ID WFO called BOIVerify. Situations where each perform well and each perform poorly are discussed. Finally, after a comprehensive review question and feedback, a summary and series of points to reme ...
Downscaling of NWP Data
Forecasters utilize downscaled NWP products when producing forecasts of predictable features, such as terrain-related and coastal features, at finer resolution than provided by most NWP models directly. This lesson is designed to help the forecaster determine which downscaled products are most appropriate for a given forecast situation and the types of further corrections the forecaster will have to create. This module engages the learner through interactive case examples illustrating and comparing the major capabilities and limitations of some commonly-used downscaled products for 2-m tempera ...
Forecasting Dust Storms - Version 2
Forecasting Dust Storms Version 2 provides background and operational information about dust storms. The first part of the module describes dust source regions, the life cycle of a dust storm, and the major types of dust storms, particularly those found in the Middle East. The second part presents a process for forecasting dust storms and applies it to a case in the Middle East. Although the process refers to U.S. Department of Defense models and tools, it can easily be adapted to other forecast requirements and data sources. Note that this module is an updated version of the original one publ ...
Introduction to Tropical Meteorology, 2nd Edition, Chapter 9: Observations, Analysis, and Prediction
The chapter describes the challenges of tropical weather forecasting. We examine types of observations and weather analysis techniques used by tropical forecasters. Those analysis tools are applied to examples of tropical synoptic weather systems as well as mesoscale analysis and nowcasting. The last three sections focus on numerical weather prediction (NWP) including: the fundamentals, data assimilation, comparisons of statistical and dynamical models, ensemble techniques, cumulus convection in NWP, tropical cyclone prediction, and methods of forecast verification and validation. We have spec ...
Understanding the Role of Deterministic versus Probabilistic NWP Information
Understanding the Role of Deterministic versus Probabilistic NWP Information is part of the "NWP Training Series: Effective Use of NWP in the Forecast Process." This lesson first covers deterministic (single) NWP model forecasts and explains advantages and limitations through a case example. Then it discusses overcoming the limitations in deterministic forecasts through the use of ensemble forecast systems, and the use of deterministic and probabilistic forecasts together, through case examples.
Effective Use of High-Resolution Models
High-resolution models have transitioned from research into forecast operations, helping forecasters utilize additional mesoscale information after accounting for the inherent unpredictability of many small-scale phenomena. This module covers the major capabilities and limitations of models run without a convective parameterization using grid spacings of around 4 km or less. Model forecast interpretation issues are discussed, including introducing convective mode diagnostics such as updraft helicity and interpreting the forecast as an event prediction rather than as a precise point forecast. M ...
Introduction to the North American Ensemble Forecast System (NAEFS)
This webcast introduces the forecaster to the new multiple-forecast-center North American Ensemble Forecast System (NAEFS). Beginning with a brief review of the theory behind ensemble prediction, this presentation then introduces the elements of the NAEFS. These include the U.S. National Centers for Environmental Prediction’s Global Ensemble Forecast System (GEFS) and the Canadian Meteorological Center’s Ensemble Forecast System (CEFS). A description of each separate ensemble system is followed by a discussion of how the NAEFS improves the ensemble forecast over either the GEFS or CEFS alone. ...
How Models Produce Precipitation and Clouds - version 2
This module, part of the "NWP Training Series: 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. 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 ...
Model Fundamentals - version 2
Model Fundamentals, part of the Numerical Weather Prediction Professional Development Series and the "NWP Training Series: Effective Use of NWP in the Forecast Process", 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 Environmen ...
Intelligent Use of Model-Derived Products - version 2
This module, part of the "NWP Training Series: Effective Use of NWP in the Forecast Process", discusses three aspects of forecast guidance developed from raw NWP model data: Post-processing Statistical guidance 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, incl ...
Influence of Model Physics on NWP Forecasts - version 2
This module, part of the "NWP Training Series: 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. B ...
Impact of Model Structure and Dynamics - version 2
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 ...
Effective Use of NWP in the Forecast Process: Introduction
This lesson, part of the "NWP Training Series: Effective Use of NWP in the Forecast Process", introduces the student to the full series. Motivation for the series is presented by Mr. LeRoy Spayd, Chief of the National Weather Service Training Division; this includes a demonstration of the value added by human forecasters to NWP forecasts through recent precipitation verification. Contributors to the series are acknowledged as well. Then Dr. Bill Bua, a member of the NWP Training Team, expands on points raised by Mr. Spayd by posing and answering a question on the role of NWP in the forecast pr ...
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 Training Series: 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 ...
Operational Use of Wave Watch III
In this webcast, Dr. Hendrik Tolman (NOAA Marine Analysis Branch) discusses the operational use of NOAA WAVEWATCH III. The NOAA WAVEWATCH III is a forecast system that predicts wind-generated ocean waves. Dr. Tolman discusses what WAVEWATCH III can and cannot predict along with the model physics, numerics, and forecast products. Numerous examples illustrate the practical effects of several recent model improvements including high-resolution hurricane winds, surf zone physics, wave partitioning, and use of a multi-grid mosaic. The webcast concludes with a discussion of future improvements plann ...
Wave Ensembles in the Marine Forecast Process
The NCEP Marine Modeling and Analysis Branch (MMAB) Ensemble Global Ocean Wave Forecast System (EGOWaFS) provides five-day forecasts of global winds, wind wave and swell conditions in probabilistic terms. This product became available early in 2007 both through an NCEP non-operational web page and, for raw data, through FTP for use by marine forecasters at NWS WFOs and other locations. The data from the EGOWaFS can be used in a number of ways, including:* As input to probabilistic marine forecasts for wind waves and swell* As input to a local wave ensemble, such as Simulated Waves Nearshore (S ...
Real-Time Mesoscale Analysis (RTMA): What is the NCEP RTMA and how can it be used?
The NCEP Real-Time Mesoscale Analysis (RTMA), provides current conditions in digital form on the NWS National Digital Forecast Database (NDFD) 5-km grid. This product was upgraded in early July 2007 to the point where its use by forecast offices is now encouraged for situational awareness, creating short-term forecast grids, and evaluating recent forecast grids and forecast bias. Unique to the RTMA is an uncertainty or error estimate for some of its analysis parameters. These uncertainty estimates perhaps could be used to determine when a forecast is “good enough”. This Webcast discusses why t ...
Using the WRF Mesoscale Model
This module provides insights on how to best use WRF mesoscale model guidance in the forecast process. Using two cases in southwest Asia where AFWA WRF is currently in use, it examines improvements offered by the WRF for forecasting fronts, topographic impacts, precipitation type, and hazards to aviation. The module also discusses some mesoscale model limitations, and offers strategies for transitioning between using mesoscale and global NWP guidance for medium-range forecasts, even when the models differ significantly.
Advances in Microwave Remote Sensing: Ocean Wind Speed and Direction
This Webcast covers the ocean surface wind retrieval process, the basics of microwave polarization as it relates to wind retrievals, and several operational examples. Information on the development of microwave sensors used to retrieve ocean surface wind speed and the ocean surface wind vector (speed and direction) is also included.
Introduction to Ensemble Prediction
This webcast is a shorter companion to the Ensemble Prediction Explained module, focusing more directly on immediate operational needs. Introductory content includes the role of ensemble forecasts, presentation of basic ensemble forecasting terms, and discussion of how ensemble prediction systems (EPSs) are created. The largest section is focused on common ensemble forecast products, including how they differ from traditional NWP products, how we interpret ensemble forecast products, the advantages and limitations of each product, how EPS products are verified, and how to use ensemble products ...
Ensemble Forecasting Explained
This module, the latest in our series on Numerical Weather Prediction, covers the theory and use of ensemble prediction systems (EPSs). The module will help forecasters develop an understanding of the basis for EPSs, the skills to interpret ensemble products, and strategies for their use in the forecast process. It contains six sections: an Introduction that briefly presents background theory; Generation, which describes how ensemble systems are constructed; Statistical Concepts, which provides a brief refresher on knowledge required for ensemble product interpretation; Summarizing Data, which ...
The Balancing Act of Geostrophic Adjustment
This 7-page module provides a primer on geostrophic adjustment concepts. It 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. The module also includes an interactive Exercises section.
Ten Common NWP Misconceptions
This lesson introduces forecasters to ten of the most commonly encountered or significant misconceptions about NWP models. This list of ten misconceptions includes issues surrounding data assimilation, model resolution, physical parameterizations, and post-processing of model forecast output.
Freezing and Melting, Precipitation Type, and Numerical Weather Prediction
This Webcast is based on a COMET classroom presentation by Dr. Gary Lackmann at the 2nd MSC Winter Weather Course held in Boulder, Colorado on 22 February 2002. Dr. Lackmann reviews the basic thermodynamics of freezing and melting and how operational models represent these processes. He also touches upon the biases that occur in the models by looking at examples of melting snow aloft, melting snow at the surface, freezing aloft (ice pellets), and freezing rain. Dr. Lackmann is a faculty member in the Department of Marine, Earth, and Atmospheric Sciences at North Carolina State University.
How Mesoscale Models Work
The goal of this training module is to help you increase your understanding of how mesoscale models work. Such understanding, in turn, can help you more efficiently and accurately evaluate model-generated forecast products.
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