In August 2008, the "Mountain Weather Workshop: Bridging the Gap Between Research and Forecasting" was held in Whistler, BC, Canada. It was sponsored by the American Meteorological Society, UCAR/COMET, and the Meteorological Service of Canada. The workshop brought together researchers, faculty, students, and operational forecasters. Its primary goals were to help provide a better understanding of the state of the science of mountain meteorology from both a research and an operational perspective, and to discuss ways of improving interaction between the research and forecasting communities. The workshop consisted of lectures by distinguished speakers covering numerous topics related to weather in complex terrain. This webcast collection contains recordings of the presentations from the workshop.
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The module examines the 2009 drought in the Greater Horn of Africa (GHA), focusing on conditions in Kenya. The module begins by reviewing drought conditions in the years leading up to 2009. From there, it examines the seasonal climate forecast for the beginning of 2009 and see what it portends. Satellite products are used to study rainfall performance throughout the year and its impact on the drought situation. Finally, the module describes the climate oscillations that can impact drought in the GHA and identifies patterns that were present in 2009 and contributed to its severity. By the end of the module, weather forecasters and students should have a better understanding of drought and the tools available for its early detection and monitoring.
The hazards associated with convective systems present some of the most dangerous conditions encountered by aircraft and pose many challenges to aviation operations. When convection is forecast to develop, aviation forecasters are required to issue a series of warning messages and other meteorological aeronautical products to various members of the aviation community. This lesson teaches these forecasters how to produce the products, doing so in the context of a case study in which learners assume the role of aeronautical forecaster on duty at the airport in Niamey, Niger on a night when convection develops. The lesson is one of three aviation weather case studies developed by the ASMET team to improve aviation forecasting in Africa.
Turbulence is a major concern for the aviation industry. It often goes undetected in cloud-free areas, catching pilots off guard when they fly into it. Turbulence can injure passengers and crew, and cause structural damage to aircraft. This makes it critical for aviation weather forecasters to closely monitor the atmosphere for signs of turbulence and issue special warnings when it is likely to be present. This lesson helps prepare forecasters for these tasks by providing general information about turbulence and showing them how to detect it using satellite imagery, tephigrams, and NWP products. The latter is presented in the form of a case study in which learners assume the role of aviation forecaster at Cape Town International Airport (South Africa), and need to determine if turbulence is likely to be present along a particular flight path. The lesson is intended for aviation weather forecasters, general weather forecasters interested in aviation meteorology, and meteorological instructors and students. Note that the lesson is one of three aviation weather case studies developed by the ASMET team to improve aviation forecasting in Africa.
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 aviation meteorology, and meteorological forecasting instructors and students. This lesson is one of three aviation weather case studies developed by the ASMET project to improve aviation forecasting in Africa. They also support COMET's Review of Aeronautical Meteorology – Africa online learning curriculum, which provides training that supports the WMO/ICAO competencies for Aeronautical Meteorological Forecasters.
The rainy season in Sahelian West Africa extends from June to September and is tied to the position of the intertropical front. During this period, mesoscale convective systems (MCSs) often produce significant rainfall that can lead to flooding. This module examines an extreme flooding event that occurred in Ouagadougou, Burkina Faso from 31 August to 1 September 2009. Learners assume the role of forecaster, assessing meteorological conditions to see if an MCS will develop that can lead to heavy rain and flooding. They follow a forecast process that emphasizes the use of satellite data, standard surface and upper-air charts, and model output. The forecast process is tied to a conceptual model of the key features that drive convective activities in West Africa.
This module introduces a variety of meteorological and hydrological products that can improve the quality of heavy rainfall forecasts and assist with hydrological management during extensive precipitation events in Southern Africa. Among the products are the satellite-based ASCAT, SMOS, and ASAR GM soil moisture products and the hydro-estimator. The products are presented within the context of a case, the flooding of South Africa's Vaal Dam region in 2009/2010.
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.
The “Advanced Fire Weather Forecasters Course Orientation” module introduces the organization of the course, the topics presented, and the intended audience, as well as the motivation for converting this course to online training. This web module is part of the Advanced Fire Weather Forecasters Course..
This brief lesson provides an overview of the AHI on Himawari and highlights its differences from the GOES-R Advanced Baseline Imager (ABI). It discusses AHI’s improved capabilities in spectral coverage, spatial resolution, and imaging interval over the MTSAT-2 imager; the differences in spectral coverage and scan strategy between AHI and ABI and the impact on products; and how AHI data and products benefit forecasters in Alaska, Pacific Region, and CONUS. Note that the lesson complements COMET’s GOES-R ABI lesson, which should be taken before going through this lesson.
This lesson is an update to the 2008 expert lecture on hyperspectral observations presented by Dr. Mitch Goldberg, Program Scientist for NOAA's Joint Polar Satellite System (JPSS) Program. The lesson discusses what hyperspectral observations are, how they are made, some current products, their contributions to improved monitoring of the atmosphere, oceans, and land surfaces, as well as their impact on numerical weather prediction. The lesson begins by discussing the importance of satellite observing systems. From there, it reviews the principles of remote sensing that are needed for deriving products from hyperspectral infrared observations. The third and largest section of the lesson examines results from and operational applications of the AIRS, IASI, and CrIS hyperspectral sounders. The final section discusses the importance of hyperspectral soundings from geostationary satellites. The lesson has been updated from the original presentation to include information about NASA and NOAA's new polar orbiting programs and CrIS, the Cross-track Infrared Sounder on the Suomi NPP polar orbiter.
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.
This module describes characteristics of African easterly waves including horizontal and vertical structure, evolution, speed, frequency, methods of tracking, and their downstream transformation over the Atlantic, Caribbean, and East Pacific. Mechanisms for wave formation are presented. Also explored are differences between waves that develop into tropical cyclones and those that do not. The final sections focus on extratropical interactions and variability of easterly waves.
This case study focuses on a snow and blowing snow event in the Canadian prairies and US northern high plains on 11-13 November 2003. The key aim of this module is to step through the forecast process during an Alberta Clipper event from the perspective of a forecaster with the Meteorological Service of Canada. This involves consideration of various observations and model guidance, identification of potential areas of snowfall and blowing snow, nowcasting snowfall development and termination, and considering and providing nowcast updates throughout.
This module discusses global climate change that is occurring largely because of greenhouse gases emitted by human activities, and in particular the impact that tropical deforestation plays in the climate system. It also covers signs of climate change, the current thinking on future changes, and international agreements that are attempting to minimize the effects of climate change. The United Nations Collaborative Programme on Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (UN-REDD Programme) is also discussed.
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.
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.
Antarctica: Challenging Forecasts for a Challenging Environment features two educational pieces. The first is the overview giving the general audience a broad look at Antarctica including some history, interesting facts, real-life experiences, climate, and the challenges inherent to this frozen continent. The second is the main presentation where experts in Antarctic research and forecasting, share their knowledge of the continent. They discuss forecasting challenges as well as present and future research topics while providing elaborations on the uniqueness in Antarctica’s location, topography, and forecasting techniques as compared to other parts of the globe.
Anticipating Hazardous Weather and Community Risk, 2nd Edition provides emergency managers and other decision makers with background information about weather, natural hazards, and preparedness. Additional topics include risk communication, human behavior, and effective warning partnerships, as well as a desktop exercise allowing the learner to practice the types of decisions required as hazardous situations unfold. This module offers web-based content designed to address topics covered in the multi-day Hazardous Weather and Flood Preparedness course offered by the Federal Emergency Management Agency (FEMA) and the National Weather Service (NWS). The module also complements other onsite courses by those agencies and provides useful information for evaluating and preparing for threats from a range of weather and natural hazards.
This is a planned series of short case studies demonstrating critical thinking in the use of NWP products based on an understanding of the characteristics and limitations of NWP models and the NWP forecast process. We welcome any comments you may have regarding the case content, its discussion, or the instructional use and benefits of this material. In particular, we are interested in any additions or modifications to this type of case discussion that would make it more relevant and useful for the training of your forecasters.
This module discusses how to apply various observational data and remote sensing tools such as satellite, METARS, soundings, profilers, radar, and model analyses to diagnose the potential for fog and/or low stratus. Various forecast tools (such as model forecast fields, forecast soundings, and BUFKIT) used to assess fog and/or low stratus potential onset, intensity, and duration are also examined. This module is part of the Distance Learning Course 1: Forecasting Fog and Low Stratus.
Diminishing sea ice has opened the Arctic to navigation and operations like never before. Forecasters are increasingly predicting weather in support of those operations. This module is intended to provide forecasters with a brief introduction to the Arctic, including its geography, climatology, and the forecast problems they are likely to encounter. The module follows a U.S. Coast Guard Cutter on a voyage from Dutch Harbor, in the Aleutian Islands, to Barrow, on the north coast of Alaska. Various topics are addressed along the way in a series of short, stand-alone lessons.
The “Assessing Fire Danger” distance learning module explores techniques for recognizing weather and fuel conditions contributing to fire danger. The module includes a matrix of data sources offering useful weather, fuels, and other information related to fire ignition, spread, and intensity. An overview of situational awareness practices provides information relevant to forecasters in the office or field. This module is part of the Advanced Fire Weather Forecasters Course.
You've seen it happen repeatedly. Forecasters have a tough forecast ahead of them. But how are they supposed to know which model data will be the best one to help them come to a conclusion about the situation? In situations like this, the first step should always be to assess the model data against a set of current observations that should show a 1-to-1 relationship with the model output. Which variable should be plotted? On which surface? Which current observations will make the most sense to assess against? If you know the answers to some, but not all of these questions, find these answers and more by going through this lesson.
Atmospheric dust storms are common in many of the world's semi-arid and arid regions and can impact local, regional, and even global weather, agriculture, public health, transportation, industry, and ocean health. This module takes a multifaceted approach to studying atmospheric dust storms. The first chapter examines the impacts of dust storms, the physical processes involved in their life cycle, their source regions, and their climatology. The second chapter explores satellite products (notably dust RGBs) and dust models used for dust detection and monitoring, and presents a process for forecasting dust storms. The third and final chapter of the module examines the major types of dust storms: those that are synoptically forced, such as pre- and post-frontal dust storms and those induced by large-scale trade winds; and those caused by mesoscale systems such as downslope winds, gap flow, convection, and inversion downburst storms.
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.
Avalanches form through the interaction of snowpack, terrain, and weather, the latter being the focus of this module. The module begins with basic information about avalanches, highlighting weather's role in their development. The rest of the module teaches weather forecasters how to make an avalanche weather forecast, that is, one in which key weather parameters are evaluated for their impact on avalanche potential. The forecasts are used primarily by avalanche forecasters, who integrate them with other information to determine when to issue avalanche hazard warnings. The module contains five cases that let users apply the avalanche weather forecast process to different combinations of snowpack, terrain, and weather conditions. It is a companion to the COMET module "Snowpack and Its Assessment," which describes snowpack development and various assessment techniques.
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.
This case exercise looks at a barrier jet event over central and eastern Colorado that took on historic significance in terms of snow amounts and variability in snow distribution. The module emphasizes the mechanisms for producing both very large accumulations and extreme small-scale variability. These mechanisms involved both dynamic and thermodynamic processes in this storm. Model and observed analyses and forecasts are considered in detail as the storm unfolds.
This brief presentation provides an overview of the COMET Basic Hydrologic Sciences course including: goal and target audiences, structure of the course and adapting it to your needs, and a brief description of course components.
"Basic Terminal Forecast Strategies" is the first component of the Distance Learning Course 2, Producing Customer-Focused TAFs. Basic Terminal Forecast Strategies is comprised of two lessons that provide 1) an introduction to understanding aviation customers and their needs and 2) a technique to meet those needs by producing clear, concise, and consistent terminal aerodrome forecasts (TAFs).
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 different Meteosat First Generation imager channels and the phenomena that they can monitor individually and in combination. This lesson is an online version of the first ASMET (African Satellite Meteorology Education and Training) lesson published on CD-ROM in 1997. Conversion to HTML is courtesy of EUMETSAT. While the images have not been updated, the concepts are fundamental and remain relevant today. Most of the images are from Meteosat and depict weather conditions over Africa, although some GOES imagery is included as well.
Aimed at surveyors and GIS professionals who use geodetic-quality GNSS equipment to determine positions for land planning, coastal monitoring and other purposes, this video covers best practices for reducing errors in the areas of: 1. location and environment, 2. equipment setup and 3. observation times and accuracy checks. This resource is hosted on COMET's YouTube Channel.
Crafting clear, concise and effective messages focused on customer needs is a crucial skill in every decision-support situation. Tropical cyclones that threaten a coastline have the potential to inflict devastating damage to communities and communicating relevant weather information will assist decision-makers in their plans and preparation work. This lesson examines how to effectively prepare for the hurricane season and then focuses on how best to support NWS partners through meteorological briefings during tropical cyclone events. Basic familiarity with probabilistic forecast guidance is required. It is strongly recommended that users review the "Determining the Onset and Risk of Tropical Cyclone Winds," "Forecasting Tropical Cyclone Storm Surge" and "Use of Probabilistic Surge Guidance in Local Storm Surge Forecasting" lessons on MetEd before viewing this lesson.
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 remember are presented. Optional materials on downloading bias correction data files from NCEP and on the model climate used to calculate anomalies for the North American Ensemble Prediction System are also available.
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.
This case exercise focuses on a potential fog event in Melbourne, Australia, on 6-7 April 2008. The key aim of this module is to step through the forecast process during a potential fog event from the perspective of an aviation forecaster with the Australian Bureau of Meteorology. This involves consideration of model guidance and observations, identification of potential areas of fog, forecasting and nowcasting fog formation and clearance, and considering and providing TAF updates throughout.
The goal of the EPV chart is to aid operational forecasters in predicting CSI and slantwise convection. The description includes links to the online chart, which is updated twice daily by the CMC, as well as a list of synoptic considerations that will support your use of the EPV chart in identifying regions favorable for CSI and slantwise convection.
This module presents radar case studies taken from events in the Caribbean that highlight radar signatures of severe weather. These cases include examples of deep convection, squall lines, bow echoes, tornadoes, and heavy rain resulting in flooding. Each case study includes a discussion of the conceptual models of each type of event as a review before showing the radar signatures and allowing the learner to analyze each one.
This module provides examples of radar imagery from various locations in the Caribbean to demonstrate the different types of images available. Also, examples of different meteorological and non meteorological features are presented to show features seen in island locations.