Global Campus
The WMO Global Campus E-Library
The WMO Global Campus initiative is proud to offer this WMOLearn Library of resources. This library provides a searchable collection of educational resources, including WMO publications and education and training materials from various contributing organisations and individuals. Search by WMO competency framework, Main Topics, Region and Country, and/or Nature of Information to find materials useful for training or self-directed learning.
Please note that resources contributed by Members will reside on other websites and may allow limited access or require login. For copyright information, see the WMO Global Campus Copyright Practice Standards and the contributor’s website. Quality standards are described in the Recommended Quality Guidelines for Global Campus E-Library Submissions.
WMO Global Campus resources provided on this Site are provided “as is”, without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose and non-infringement. The WMO specifically does not make any warranties or representations as to the accuracy or completeness of any such resources.
WMO Global Campus resources provided on this Site are provided “as is”, without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose and non-infringement. The WMO specifically does not make any warranties or representations as to the accuracy or completeness of any such resources.
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Fire Model Matrix
The Fire Model Matrix is an on-line resource that presents four fire community models in a matrix that facilitates the exploration of the characteristics of each model. As part of the Advanced Fire Weather Forecasters Course, this matrix is meant to sensitize forecasters to the use of weather data in these fire models to forecast potential fire activity.
ASMET 7: Forecasting Fog for Aviation: Kenya Case Study
This lesson aims to improve aviation forecasts of fog in the African airspace by teaching forecasters to make more accurate forecasts using satellite imagery, numerical weather prediction, and other available data. A process for diagnosing and forecasting fog is presented and applied to a case over the Nairobi, Kenya region. Learners assume the role of aviation forecaster, analysing various products to determine whether the current Terminal Aerodrome Forecast (TAF) is valid or needs to be amended. The lesson is intended for aviation forecasters, general weather forecasters interested in aviati ...
Vorticity Maxima and Comma Patterns
Vorticity maxima signatures are very common and indicate areas of ascending circulation and atmospheric forcing. The correct placement of vorticity maxima is vital to the placement of related dynamic features such as the axis of maximum winds and deformation zones. This module is part of the series “Dynamic Feature Identification: The Satellite Palette”.
Quasi Geostrophic Vorticity Equation
This learning object/widget is designed for upper-level undergraduates or forecaster interns who want to apply their knowledge of the Quasi-geostrophic Vorticity Equation to forecast situations. The interactivity helps users see how each variable interacts within the equation and shows data for different phase shifts of 500hPa and 1000hPa heights. Instructors can use this learning object with their own question sets as well to build more understanding and application into their dynamics/synoptic courses.
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 ...
Introduction to Ocean Tides
Ocean tides profoundly impact coastal maritime operations. This module provides an introduction to the origin, characteristics, and prediction of tides. After introducing common terminology, the module examines the mechanisms that cause and modify tides, including both astronomical and meteorological effects. A discussion of tide prediction techniques and products concludes the module. This module includes rich graphics, audio narration, embedded interactions, and a companion print version.
Introduction to VIIRS Imaging and Applications
This lesson introduces the VIIRS imager that operates on the current U.S. Suomi NPP satellite and is planned for future JPSS environmental satellites. VIIRS has many advanced features that improve both spectral and spatial resolution and enable the delivery of consistent, high quality, and high resolution data to users worldwide. The lesson covers the enhanced capabilities of VIIRS and highlights some of its applications. These include single channel and multispectral products used to monitor dust, volcanic ash, convection, fog and low clouds, sea surface temperature, tropical cyclones, contra ...
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.
Analyzing Ocean Swell
This module describes the main elements to consider when analyzing wave model and buoy data. The module focuses on data products available from NOAA including spectral plots, maps, and text bulletins. East and West Coast wave-masking exercises conclude the module. The content in this module is an excerpt from the previously published COMET module Rip Currents: Forecasting.
SatFC-G: Near-IR Bands
This lesson introduces you to three of the four near-infrared imager bands (at 1.37, 1.6, and 2.2 micrometers) on the GOES R-U ABI (Advanced Baseline Imager), focusing on their spectral characteristics and how they affect what each band observes. For information on the 0.86 micrometer near-IR "veggie" band which is not included here, refer to the Visible and Near-IR Bands lesson. This lesson is a part of the NWS Satellite Foundation GOES-R Course.
Satellite Meteorology: Introduction to Using the GOES Sounder
This module, adapted for the Web from the CD-ROM released in 1998, reviews GOES sounder characteristics, data products, and applications concurrent with the GOES I(8)-P satellites. Topics covered include the electromagnetic spectrum and sounder channel selection, weighting functions for temperature and moisture determination, and assessment of GOES sounder products. Sample imagery and products are provided along with several short case examples that demonstrate how these products are beneficial to meteorological analysis and forecasting applications.
Australian Severe Thunderstorm Case Studies
In this southern hemisphere-focused module, the student can work through a major Australian severe thunderstorm event in detail and examine aspects of two other severe thunderstorm events. Follow a forecast time-line to assess data and make decisions from the pre-storm phase through the warning phase. This module was developed for and the copyrights are owned by the Bureau of Meteorology Australia.
Introduction to Electromagnetic and Electro-Optic Propagation
This lesson describes the properties of electromagnetic and electro-optical radiation and how their propagation is affected by the atmosphere and weather. Atmospheric variables that affect EM propagation include temperature, moisture, pressure, and composition. These variables control processes including refraction, absorption, and scattering.
Basics of Visible and Infrared Remote Sensing
This lesson presents the scientific and technical basis for using visible and infrared satellite imagery so forecasters can make optimal use of it for observing and forecasting the behaviour of the atmosphere. The concepts and capabilities presented are common to most international geostationary (GEO) and low-Earth orbiting (LEO) meteorological satellites since their inception, and continue to apply to both current and newer satellite constellations. The lesson reviews remote sensing and radiative transfer theory through a series of conceptual models. Discussions contain explanations of the di ...
S-290 Unit 10: Fuel Moisture
S-290 Unit 10: Fuel Moisture provides information about live and dead fuel moisture contents and their relation to fire behavior. Influences on fuel moisture and methods for estimating dead fuel and live fuel moisture in the field are summarized, and guidance is offered for assessing the potential fire danger based on fuel moisture and other fireline information. The module is part of the Intermediate Wildland Fire Behavior Course.
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