MetEd: Meteorology Education and Training. Operated by the COMET Program

Description:
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.

Objectives:
State some key meteorological applications for ocean surface winds

• Describe the benefits of using microwave remote sensing to observe ocean winds
• Describe the differences between active and passive microwave remote sensing
• Describe in general terms, the emission, transmission, and scattering of microwave energy within the Earth-atmosphere system
• State the key assumptions for derivation of wind speed and direction from passive observation of microwave radiation
• Describe the limitations of passive microwave remote sensing and impacts on deriving wind speed and direction (this applies to both product limits and accuracy)
• Use cloud liquid water imagery to help assess the validity of the wind speed and direction vector

Estimated time to complete: 45 min

Includes audio: yes

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
 * Plug-in information

Last published on: 2005-11-28

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Description:
A course outline is available online at http://www.comet.ucar.edu/class/POES_2001/outline.htm.

Estimated time to complete: 75 min

Includes audio: yes

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
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Last published on: 2002-07-09

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Description:
This Webcast provides an overview of the EUMETSAT Polar System (EPS), Europe's first dedicated operational polar-orbiting weather satellite program. EPS contributes to the Initial Joint Polar System (IJPS) under a cooperation agreement between EUMETSAT and NOAA to provide and improve operational meteorological and environmental forecasting and global climate monitoring services worldwide. The highly innovative features implemented with EPS include high-level sounding performance and enhanced data streams that further improve the capabilities of advanced NWP systems. The Webcast takes one hour to complete.

Objectives:
After completing this Webcast, learners will be able to:

* Identify the three major disciplines to which EPS contributes.
* Describe the role of EPS within the Global Operational Satellite Observation System (GOSOS) and the Initial Joint Polar-Orbiting Operational Satellite System (IJPS).
* Describe the main differences between polar and geostationary satellites.
* Describe the EPS programme elements and how they contribute to the flow of data products.
* Identify the instruments on the Metop satellite and their primary applications.
* Describe the capabilities and anticipated benefits of the IASI hyperspectral sounder.
* Describe the main services provided by EPS.

Estimated time to complete: 1 h

Includes audio: yes

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
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Last published on: 2006-09-22

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Description:
This case exercise takes an in-depth look at a blowing snow event in the northern mainland of Canada. The case addresses specific low-level wind and snow conditions. Model data, satellite imagery, and observations are provided for assessing the potential for blowing snow and blizzard conditions as the event unfolds.

Objectives:
1. Review the winter climatology of this central Canadian region.
2. Recognize the specific low-level wind and snow conditions conducive to blowing snow/blizzard conditions.
3. Recognize the common synoptic patterns associated with a blowing snow event.
4. Consider the wind speed and direction forecasts for this event.
5. Examine the cessation of blowing snow conditions, from a forecasting standpoint.

Estimated time to complete: 60 min

Includes audio: yes

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
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Last published on: 2004-11-08

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Description:
The quick analysis of deformation zones provides an overview of system-relative atmospheric circulations. Since deformation is a primary factor in frontogenesis and frontolysis, understanding of these system-relative circulations is crucial to the diagnosis of atmospheric processes and weather prediction. This module is part of the series: "Dynamic Feature Identification: The Satellite Palette".

Objectives:
* Analyze the air masses and circulations
* Analyze the related paired and companion vorticity centers
* Analyze the related axis of maximum wind and wind maxima
* Analyze the location, orientation and shape of the deformation zone

Estimated time to complete: 75-90 min

Includes audio: no

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
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Last published on: 2007-03-22

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Description:
Following an analysis of the main features of a deformation zone, the diagnosis of temporal and spatial changes in these features can be used to deduce underlying meteorological processes and their progression. In turn, this knowledge can then be used in the forecast process to adjust the forecast accordingly. This module takes 35-45 minutes to complete. It is part of the series: "Dynamic Feature Identification: The Satellite Palette".

Objectives:
* Diagnose the relative intensities of each vorticity center associated with a deformation zone
* Predict the evolution of each associated vorticity center
* Predict the evolution of the deformation zone's location, orientation and shape
* Based on the predicted evolution of a deformation zone, identify areas of frontolysis and frontogenesis and trends in the weather

Estimated time to complete: 35-45 min

Includes audio: no

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
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Last published on: 2007-11-05

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Description:
The distribution of vorticity centres along an axis of maximum winds follows a fairly predictable pattern based on the characteristics of the flow. By diagnosing these characteristics, the meteorologist is able to quickly deduce the location and relative intensities of the associated vorticity centres as well as the relative sizes of the associated circulations. This information is summarized within the shape and orientation of the associated deformation zones. The deformation zones in turn reveal important details regarding feature motion and thermal advection and thus their diagnosis should be a critical part of the forecast process. This module takes 30-40 minutes to complete. It is part of the series: "Dynamic Feature Identification: The Satellite Palette".

Objectives:
* Compare the different characteristics of various flow patterns
* Locate the position and predict the relative intensities of vorticity centres along a flow
* Predict the position of the associated deformation zones based on the location and intensities of the vorticity centres

Estimated time to complete: 30-40 min

Includes audio: yes

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
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Last published on: 2008-03-21

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Description:
This 10-minute Webcast was developed from a presentation at the Naval Research Laboratory in April 2003 by LTJG Matt Henigin. LTJG Henigin reviews techniques for making visibility forecasts by combining surface observations with remote sensing data to estimate visibility in areas where no surface observations are available. Examples in the Webcast are drawn from southwest Asia.

Objectives:
• Describe the process for extrapolating visibility conditions in areas with no in-situ observations
• State the advantages of enhancing imagery for visibility forecasting
• State the reason for looping data for feature identification

Estimated time to complete: 10 min

Includes audio: yes

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
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Last published on: 2003-07-23

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Description:
The Dust Enhancement Techniques Using MODIS and SeaWiFS Webcast features Dr. Steven Miller of the Naval Research Laboratory (NRL) in Monterey, California and takes about one hour to complete. Dr. Miller explains two techniques for detecting blowing dust using multispectral satellite imagery from the MODIS and SeaWiFS instruments. He also provides guidelines for the best uses of these techniques. The Webcast includes several recent operational examples from southwest Asia. This presentation was originally given at a workshop hosted by NRL in April, 2003.

Objectives:
After completing the module the user will be able to:

• Describe the process for creating RGB or “true-color” enhancements
• State the limitations of the RGB enhancement for detecting dust
• Describe the process for creating “false-color” dust specific enhancements
• Identify dust plumes using the dust enhancement
• Identify surface features that mimic dust signatures using the dust enhancement
• Identify source regions for dust using dust enhancement imagery
• Distinguish smoke and clouds from dust using the dust enhancement
• State the limitations of the false-color dust enhancement

Estimated time to complete: 45 min

Includes audio: yes

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
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Last published on: 2003-07-16

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Description:
This series addresses the use of satellite imagery and focuses attention on the identification of dynamic features using high-resolution satellite imagery with NWP verification. The series will eventually include more than 20 feature presentations on topics such as comma clouds, jet streaks, deformation zones, surface features, convection, and blocking.

Each feature presentation includes interactive identification exercises, analysis and diagnosis, conceptual models, and forecast implications.

Objectives:
• Analyze and diagnose dynamic features in satellite imagery
• Identify discrepancies between numerical model forecasts and atmospheric features
• Apply conceptual models to an atmospheric feature and correct for discrepancies between observed and numerical model analysis

Estimated time to complete: 20-90 min

Includes audio: no

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
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Last published on: 2006-01-10

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Description:
This module consists of four exercises where users identify surface features, distinguish clouds from snow on the ground, and determine cloud phase using multispectral analysis. The module also includes an overview of multispectral techniques available on many operational and research polar-orbiting satellites. A page with links to real-time polar-orbiting data and information is also included.

Objectives:
• State the properties of the 1.6 micrometer channel used in feature identification
• State the properties channels in the 3.5 to 4 micrometer region in feature identification
• List the advantages and limitations of the 1.6 micrometer channel in cloud identification
• List the advantages and limitations of the 1.6 micrometer channel in identifying snow on the ground
• List the advantages and limitations of channels in the 3.5 to 4 micrometer region for cloud identification
• List the advantages and limitations of channels in the 3.5 to 4 micrometer region in identifying snow on the ground
• Apply the properties of the visible, IR Window, 1.6 micrometer, and 3.7 micrometer channels to:
o Distinguish clouds from snow on the ground
o Determine the phase (ice or water) of clouds
o Detect the presence of fog
o Distinguish open water from ice-covered areas of lakes and rivers

Estimated time to complete: 1-2 h

Includes audio: yes

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
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Last published on: 2002-07-03

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Description:
This Webcast, presented by Tom Lee of the Naval Research Laboratory, focuses on feature identification using a combination of high-resolution multispectral polar and geostationary satellite imagery products.

The Webcast is made up of five short sections focus on a set of particularly challenging feature identification problems including: clouds over snow; contrails/thin cirrus; fires, hot spots, and smoke; blowing dust; snow, icebergs, and pack ice. Examples are included from Asia, Europe, and North America. A table summarizes suggested detection strategies for each phenomena type, based on available polar and geostationary capabilities and whether the event occurs during daytime or nighttime.

Objectives:
Using multispectral imagery identify the following features:
• Contrails/thin cirrus
• Fires, smoke, and hot spots,
• Blowing dust
• Snow, icebergs, and pack ice

Use multispectral imagery to:
• Distinguish clouds from show on the ground
• Distinguish smoke from clouds
• Distinguish blowing dust from clouds

Estimated time to complete: 1 h

Includes audio: yes

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
 * Plug-in information

Last published on: 2002-10-24

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Description:
Forecasting Dust Storms is the latest module in the Mesoscale Meteorology Primer. The module starts by discussing the conditions required for a dust storm, including an appropriate source of dust, sufficient wind and turbulence, and an unstable atmosphere. The module then explores the fate of dust in the atmosphere including dispersion, advection, and settling. The concluding section on forecasting examines a case in the Middle East and demonstrates the use of a mesoscale NWP model, as well as next-generation dust forecasting models.

Objectives:
After completing this module, the learner should be able to do the following things:

With regard to dust storm characteristics:

• Describe how visibility varies near severe dust storms
• Recall the average height of dust storms
With regard to sources of dust:
• Describe the soil types in appropriate source regions for dust storms
• Recall that blowing dust usually does not occur for at least 24 hours after a rainfall
• Identify potential source regions with satellite imagery

With regard to atmospheric conditions required for dust storms:

• Recall the threshold wind speed for lifting fine dust particles.
• Describe the atmospheric conditions that promote lofting of dust in terms of stability and turbulence
• List the 3 ways that turbulence typically arises in the atmosphere
• Describe the effect of nightfall on dust storms

With regard to the dissipation and dispersion of dust storms:

• Describe the atmospheric factors that influence the dispersion of dust
• Describe the effect of precipitation on suspended dust and why this occurs
• Recall how quickly dust settles once winds die down

With regard to the climatology of dust storms:

• List the most common synoptic patterns for raising dust in the Middle East
• Define Shamal
• List at least 3 mesoscale weather phenomena that result in dust storms
• Describe how haboobs and dust devils originate
• Describe how winter dust storms differ from summer dust storms

With regard to the satellite detection of blowing dust:

• Describe how dust appears on IR images, during both day and night and over both land and water
• Describe how dust appears on visible images, during both day and night and over both land and water
• Describe the advantages of imagery from polar orbiting and geostationary satellites
• With regard to forecasting dust storms:
• List the tools available for observing dust storms.
• Describe how mesoscale NWP models can help with a dust storm prediciton
• List the dust storm forecasting models and describe their respective advantages

Estimated time to complete: 2 h

Includes audio: yes

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
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Last published on: 2003-10-23

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Description:
The FORMOSAT-3 (Taiwan's Formosa Satellite Mission #3)/COSMIC (Constellation Observing System for Meteorology, Ionosphere & Climate) mission involves deployment of six satellites. Using the radio occultation technique, these satellites will interact with GPS satellites and Earth systems to gather data on our planet’s atmosphere. This mission not only has great value for weather, climate, and space weather research and forecasting, but also geodesy, gravity research, and other applications. Assimilation schemes are being developed to effectively integrate the data into existing operational weather forecasting models.

Objectives:
After completing the module the learner will be able to:

1) Describe the history of radio occultation.
2) State the principle of radio occultation and why it is so effective for Earth.
3) Describe the inversion of radio occultation data and the information derived.
4) State how radio occultation data has been validated with other data sources.
5) Describe the advantage of the open-loop versus phased-locked-loop tracking method.
6) State how radio occultation aids in the measurement of the planetary boundary layer.
7) List significant satellite missions and explain their contributions to radio occultation.
8) Describe the main features of the FORMOSAT-3/COSMIC mission.
9) List the payloads of FORMOSAT-3/COSMIC mission and describe what each does.
10) Explain how radio occultation will help monitoring and forecasting of weather.
11) Explain how radio occultation will help monitoring and forecasting of climate.
12) Explain how radio occultation will help monitoring and forecasting of space weather.
13) Describe the responsibilities of the CDAAC in the processing and flow of data.
14) Explain how and where to get archived or real-time radio occultation data.

Estimated time to complete: 75 min

Includes audio: yes

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
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Last published on: 2006-07-07

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Description:
This module introduces the NPOESS VIIRS imager that will fly on the NPOESS Preparatory Project and the NPOESS satellites. The VIIRS imager has many advanced features that will improve both spectral and temporal resolution. Ninety-five percent of VIIRS data will be available within 28 minutes of overpass time, providing consistent, high-quality, high-resolution data to users. This module covers the improvements to VIIRS by examining the systems that contributed to its development. Special attention is paid to the Day/Night Visible channel as VIIRS will be the first civilian satellite to image atmospheric and terrestrial features with and without moonlight.

Objectives:
• Name the important heritage instruments that led to the development of NPOESS
• State the advantages of multispectral imagery in fire and hot spot detection/interpretation
• Use true color imagery to identify surface, atmospheric, and ocean
surface features and characteristics
• Discriminate between nadir and edge of scan passes from AVHRR
• Describe the difference between fine and smooth OLS data
• State the advantages of the nighttime visible channel on OLS
• State features that can be seen during no-moon, half-moon, and full-moon illuminations
• Identify features in no-moon, half-moon, and full-moon illuminations

Estimated time to complete: 45 min

Includes audio: yes

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
 * Plug-in information

Last published on: 2004-10-25

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Description:
Chapter 3: Tropical Remote Sensing Applications, is the first published chapter of the online textbook, "Introduction to Tropical Meteorology." It covers remote sensing—the primary method of observing weather and climate across the global tropics. Learners will become familiar with the scientific basis and applications of radar and satellite remote sensing from examples in which clouds and precipitation are observed by measuring microwave signals using ground-based radar, spaceborne radar, and satellite radiometers. Wind estimation, dust and volcanic ash tracking, vertical sounding techniques, and remote measurement of sea-surface, soil and land surface properties are also covered. The online textbook has many special features, including individual chapter review questions and quiz, topic focus sections, direct access to operational forecasting topics, box sections that elaborate on theoretical concepts, links to resources for further study, critical thinking questions interspersed throughout the text, icons that identify resource links and critical thinking exercises, and science biographies.

Objectives:
At the end of this chapter, users should understand and be able to describe:

* Why remote sensing is important in the tropics
* Several tropical applications of ground-based radars
* The advantages and limitations of airborne and spaceborne radar
* Several tropical meteorology applications of satellite radar and microwave remote sensing
* The benefits and weaknesses of satellite estimates of water vapor content
* How GPS satellite signals are used to derive temperature and humidity profiles and how this benefits tropical meteorology
* The benefits and weaknesses of satellite precipitation estimates
* How lightning is detected by satellite
* The benefits and weaknesses of satellite wind estimation
* Why microwave sensors are useful for identifying surface moisture
* How vegetation and other land use/land cover changes are monitored by satellite
* How meteorologically important features, such as cloud properties, are monitored with satellite imagery
* How satellites are used for air quality assessment, such as dispersion of volcanic ash, chemical pollutants, dust, and smoke

Estimated time to complete: 100-110 mins

Includes audio: no

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
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Last published on: 2007-08-31

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Description:
This module provides background information on microwave remote sensing with polar-orbiting satellites. It reviews coverage, orbits, and data latency issues of current operational and selected research satellites and notes improvements expected in the NPP and NPOESS era. The module contrasts active vs. passive remote sensing, discusses advantages and limitations of different microwave instrument scanning strategies, and addresses viewing geometry with implications for spatial resolution and swath coverage. Finally, it offers a review of the microwave spectrum and special characteristics of microwave energy important for understanding microwave imagery and derived products. This module takes about 1 hour to complete.

Objectives:
* Describe the orbits and coverage of current polar-orbiting environmental satellites.
* Describe improvements in data latency with the implementation of pipeline processing and the NPOESS SafetyNet© ground system.
* State the differences between active and passive microwave remote sensing.
* Describe crosstrack, conical, and fan beam scanning strategies, the advantages and limitations of each, and their impacts on viewing geometry and spatial resolution.
* Describe the difference between window regions and absorption regions of the electromagnetic spectrum.
* State the relationship between observed microwave energy, sensor field-of-view, and spatial resolution.
* Describe the basic principle of polarization, how it can affect emitted microwave radiation, and its importance for characterizing surface features and atmospheric constituents.
* Describe why water surfaces generally appear relatively cold and land surfaces appear relatively warm in the microwave.
* Describe how passive microwave observations can be used to infer ocean surface wind speed and direction.
* Describe the relationship between dielectric effect, scattering, and emissivity and its importance for microwave remote sensing.
* Name some of the remote sensing applications that rely on the dielectric effect on observed microwave radiation.

Estimated time to complete: 1 h

Includes audio: yes

Required plug-ins:   Flash RealPlayer Java Adobe® Reader®
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Last published on: 2007-04-20

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Description:
This module provides an introduction to polar-orbiting-satellite-based microwave remote sensing products that depict moisture and precipitation in the atmosphere. The module begins with definitions and descriptions of total precipitable water and cloud liquid water products, contrasting each with more familiar infrared water vapor and window channel products. This is followed by an overview of microwave precipitation e