Topics
Sorted by (Issue date descending, Date of update descending, Date of creation descending, Number of collection descending) Add the result to your favourites Refine your search
Introduction to Aircraft Meteorological Data Relay (AMDAR)
Introduction to Aircraft Meteorological Data Relay (AMDAR) provides national meteorological services worldwide, airlines, and aviation organizations with information about the World Meteorological Organization (WMO) aircraft-based observing system. The audience includes meteorological service managers and providers, observational development groups, the aviation industry, and others interested in benefiting from an aircraft-based observing system in their region. The content includes interviews with several experts to provide examples of AMDAR use for both meteorological and aviation applicati ...
How Satellite Observations Impact NWP
Satellite observations have a huge impact on numerical weather prediction (NWP) model analyses and forecasts, with sounding data from polar orbiting and GPS-radio occultation satellites reducing model forecast error by almost half. All of this despite the fact that NWP models only assimilate 5% of all satellite observations! This lesson discusses the use of satellite observations in NWP and how model limitations prevent more of the data from being assimilated. The lesson begins by briefly describing the history of satellite observations in NWP and their impact on NWP model forecast skill. The ...
Introduction to Ensembles: Forecasting Hurricane Sandy
This module provides an introduction to ensemble forecast systems with an operational case study of Hurricane Sandy. The module concentrates on models from NCEP and FNMOC available to forecasters in the U.S. Navy, including NAEFS (North American Ensemble Forecast System), and NUOPC (National Unified Operational Prediction Capability). Probabilistic forecasts of winds and waves developed from these ensemble forecast systems are applied to a ship transit and coastal resource protection. Lessons integrated in the case study provide information on ensemble statistics, products, bias correction and ...
WRF-EMS Aviation Products
This lesson illustrates how numerical guidance from the Weather Research and Forecasting Model - Environmental Modeling System (WRF-EMS) can be added to surface observations, satellite graphics, and conceptual models of important aviation phenomena, to produce TAFs. Specifically, the lesson describes how visibility, cloud ceilings, and the flight categories variables provide values for aviation forecasts in Africa.
Gridded Forecast Verification and Bias Correction
To become a better forecaster, it is not enough to simply know that a forecast did not verify. One must determine what happened and identify methods for improvement through forecast verification. The forecast verification process helps answer questions like: Is there a particular method that has been more effective in the past in similar circumstances? Is there guidance that is more accurate? Are there persistent biases in our forecasts? Do our forecasts perform better in certain regimes than others? In the era of gridded forecasts, grid-based verification provides more information about the s ...
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 ...
Add tag 
