The MetEd website, COMET’s signature offering, is a free collection of hundreds of training resources intended for the geoscience community. We deliver over 240,000 hours of online education each year in disciplines such as aviation weather, climate, convective weather, emergency management, hydrology, numerical modeling, satellite meteorology and winter weather, among many others.
A variety of MetEd lessons are translated in multiple languages. COMET partners with many international stakeholders and is sponsored by global agencies such as, National Oceanic and Atmospheric Administration (NOAA), European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), Meteorological Service of Canada (MSC), National Science Foundation (NSF), World Meteorological Organization (WMO) and many more.
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Latest MetEd Publications
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Satellite Applications for Winter Weather: Mesoscale Banded Snowfall
New-generation GOES-R and JPSS satellite products offer improved capabilities for detecting and monitoring some of the more subtle elements of winter weather events, including mesoscale banded snowfall. In this lesson learners will investigate an April 2020 banded snowfall event that occurred over the Great Plains of the United States. Throughout the lesson, learners will use several satellite tools in tandem with model forecasts and observations including radar, sounding and surface data. As learners analyze the data they will be asked to determine how particular satellite products can aid in different aspects of the forecast process, from situational awareness and precursor ingredient assessment, to monitoring the initiation and evolution of the snowband. This lesson is intended for forecasters familiar with the dynamics of winter storms and experienced in using a broad suite of observational tools and model outputs.
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Satellite-NWP Integration: Weather System Analysis Challenge
This 15-minute lesson uses GOES-R RGB composites and single channel imagery in combination with numerical weather prediction (NWP) model output for analysis of synoptic scale weather systems. In this lesson, the learner is challenged to use the Air Mass RGB and potential vorticity fields to locate weather systems not easily identified using water vapor imagery alone. The learner will experience the benefits of using animated satellite products and through comparing single channel imagery to RGB imagery be able to make more informed forecasting decisions. This lesson addresses the following primary performance components from the WMO Competency Framework Satellite Skills: 3.2 Identify synoptic-scale systems 7.2 Identify and assess various weather features by integrating satellite and NWP products 7.4 Use NWP information to enhance the understanding of the features shown in the satellite images
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How to Interpret the Hydrologic Ensemble Forecast Service (HEFS) Short-Term Guidance
The Hydrologic Ensemble Forecast Service (HEFS) is an ensemble river level (or river flow) forecasting service provided by the National Weather Service (NWS). This training comprises three videos that explain what the HEFS is and how to interpret the HEFS Short-Term Probabilistic Guidance. The first of these videos introduces the purpose and benefits of the HEFS for river level forecasting, and provides a high-level explanation of each of its components. The second video explains how 10-day probabilistic guidance is produced from the HEFS ensemble river level forecast. The third video provides examples of how to communicate this probabilistic guidance in river flood briefings.
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Meteorological Analysis and Forecast Tools for Aviation
This lesson provides learners with the opportunity to familiarize themselves with several essential analysis and forecast tools required to perform effectively in their aviation weather roles. This lesson is meant to provide both foundational knowledge about a select list of analysis and forecast tools as well as information about how they can best be used within the aviation space. Topics covered in the lesson include Corridor Integrated Weather System (CIWS) and Consolidated Storm Prediction for Aviation (CoSPA), various aviation-specific NWP model outputs, and several Aviation Weather Center tools including Current Icing Product/Forecast Icing Product (CIP/FIP), Traffic Flow Management Convective Forecast, and Gate Forecasts.
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What is the Hydrologic Ensemble Forecast Service (HEFS)?
The Hydrologic Ensemble Forecast Service (HEFS) is an ensemble streamflow forecasting service provided by the National Weather Service (NWS). This training comprises three videos that explain what the HEFS is and how it works. The first of these videos introduces the purpose and benefits of the HEFS for river level forecasting, and provides a high-level explanation of each of its components. The second and third videos describe, in more detail, the scientific process used by two major components of the HEFS: the Meteorological Ensemble Forecast Processor (MEFP), and the Ensemble Post Processor (EnsPost).
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Communicating Probabilistic Forecasts
The ability to effectively communicate probabilistic information is an important and growing aspect that the National Weather Service is developing in the workforce. This lesson lets learners practice communicating probabilistic information to the public and decision makers. Learners are given information for four different locations and weather events and then create an Area Forecast Discussion and a social media post.
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Communicating Threats and Impacts During Tsunami Events
This lesson highlights products from the National Tsunami Warning Center and Pacific Tsunami Warning Center that provide useful information to forecasters during tsunami events. In this lesson, the learner takes on the role of a weather service coastal forecaster attending the community phone lines after a M9.0 earthquake occurs offshore the Alaska Peninsula. As a forecaster, the learner interprets the NTWC and PTWC products to practice conveying potential threats and impacts to various decision-makers in Alaska, Hawaii, and along the U.S. West Coast. The lesson demonstrates best practices for communicating tsunami threat information to stakeholders and illustrates how information from the warning centers is refined or updated as the event evolves.
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Communicating Subseasonal to Seasonal Impacts: Drought
Practice decision support related to drought impacts through two scenarios where you are asked to prepare talking points for briefings with stakeholders. These scenarios feature example locations where drought is having a significant impact on communities: water resource managers in the drought-stricken Southwestern United States and an agricultural community in North Dakota grappling with evolving drought conditions. You will tailor your messages to be clear, proactive, authoritative, accurate, audience-focused, representative, and organized. You will gain experience in using NOAA drought monitoring products, tools, and outlooks in the context of providing decision support.
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Communicating Subseasonal to Seasonal Impacts: Climate Change
As heat, wildfires, and other events affect communities, forecasters and others in the weather sector are increasingly called upon to answer questions about climate change. This lesson provides learners with three different scenarios to practice interpreting climate products and communicating information to stakeholders in public health, wildland management, and municipal planning.Weather and climate are closely related and it is important for meteorologists to be able to talk about climate scale impacts. As a weather professional, you may be your stakeholders' best source for climate information. Being able to correctly discuss extremes, sub-seasonal and seasonal outlooks, and climate projections will help you provide the most useful decision support information to your stakeholders as they prepare for climate variations and impacts in their daily responsibilities and longer-term planning.
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Working with Water Level Data: QA/QC
Having accurate water level data ensures that the resulting data products, such as tidal datums, are also accurate. Poor data quality can affect the derived water level products and impact applications such as marsh restoration or coastal engineering. In this lesson, we examine the origins of bad data, how to recognize bad data, how to discriminate between bad data and anomalous, but very real data, and when and how to remediate bad data. This lesson is intended for those interested in examining water level data that has been collected and saved, as opposed to real-time data. Saved data is useful for applications like the determination of tidal datums and inundation analysis.