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Basic Satellite and NWP Integration
NWP is one of the most important forecasting tools in our toolbox. Yet identifying when/where it isn’t capturing reality is difficult. In the short-term forecasting range, it is important as a forecaster to identify when/where NWP output isn’t matching reality. Then you can make appropriate changes to the forecast output. To find those mismatches anywhere in the world, one of the best tools is satellite imagery. In this lesson, we will focus on a few cases using satellite imagery to help identify mismatched features/processes between the satellite imagery and the NWP. Anyone trying to add valu ...
Available online: https://www.meted.ucar.edu/training_module.php?id=1408
Published by: The University Corporation for Atmospheric Research ; 2019
NWP is one of the most important forecasting tools in our toolbox. Yet identifying when/where it isn’t capturing reality is difficult. In the short-term forecasting range, it is important as a forecaster to identify when/where NWP output isn’t matching reality. Then you can make appropriate changes to the forecast output. To find those mismatches anywhere in the world, one of the best tools is satellite imagery. In this lesson, we will focus on a few cases using satellite imagery to help identify mismatched features/processes between the satellite imagery and the NWP. Anyone trying to add value to short-term NWP forecasts could benefit from taking this lesson to learn a process for assessing NWP output compared to observations. This lesson focuses on fog and convection in Africa, however this lesson can apply to many other cases, and is generalized enough to help forecasters from anywhere in the world.
Disclaimer regarding 3rd party resources: WMO endeavours to ensure, but cannot and does not guarantee the accuracy, accessibility, integrity and timeliness of the information available on its website. WMO may make changes to the content of this website at any time without notice.
The responsibility for opinions expressed in articles, publications, studies and other contributions rests solely with their authors, and their posting on this website does not constitute an endorsement by WMO of the opinion expressed therein.
WMO shall not be liable for any damages incurred as a result of the use of its website. Please do not misuse our website.Language(s): English
Format: Digital (Standard Copyright)Tags: Weather forecasting ; Numerical weather prediction ; Fog ; Convection ; Lesson/ Tutorial ; NWP Skills and Knowledge for Operational Meteorologists ; Satellite Skills and Knowledge for Operational Meteorologists
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GOES-R Geostationary Lightning Mapper (GLM) North America Examples
The Geostationary Lightning Mapper (GLM) aboard the GOES-R series satellites provides continuous lightning detection from space, giving forecasters a unique tool to monitor developing thunderstorms. This 45 minute lesson introduces learners to the benefits of using GLM gridded products, primarily Flash Extent Density (FED). Learners will explore several North American convective events and use Flash Extent Density, in combination with other satellite and radar data, to diagnose convective initiation, storm intensification, and areal extent of lightning activity. Helpful hints to keep in mind w ...
Available online: https://www.meted.ucar.edu/training_module.php?id=1601
Published by: The University Corporation for Atmospheric Research ; 2019
The Geostationary Lightning Mapper (GLM) aboard the GOES-R series satellites provides continuous lightning detection from space, giving forecasters a unique tool to monitor developing thunderstorms. This 45 minute lesson introduces learners to the benefits of using GLM gridded products, primarily Flash Extent Density (FED). Learners will explore several North American convective events and use Flash Extent Density, in combination with other satellite and radar data, to diagnose convective initiation, storm intensification, and areal extent of lightning activity. Helpful hints to keep in mind while using GLM gridded products will be discussed. Finally, learners will get a look into future GLM gridded products and their advantages.
Disclaimer regarding 3rd party resources: WMO endeavours to ensure, but cannot and does not guarantee the accuracy, accessibility, integrity and timeliness of the information available on its website. WMO may make changes to the content of this website at any time without notice.
The responsibility for opinions expressed in articles, publications, studies and other contributions rests solely with their authors, and their posting on this website does not constitute an endorsement by WMO of the opinion expressed therein.
WMO shall not be liable for any damages incurred as a result of the use of its website. Please do not misuse our website.Language(s): English
Format: Digital (Standard Copyright)Tags: Weather forecasting ; Convection ; Lesson/ Tutorial ; Aeronautical Meteorological Forecaster ; Aeronautical Meteorological Observer ; Satellite Skills and Knowledge for Operational Meteorologists
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GOES-R Series Multilingual Training Resources
This listing of multilingual training materials for the GOES-R series includes both foundational lessons and quick guides developed by various partners at the request of the U.S. National Weather Service and NESDIS. The selections included here represent materials translated to Spanish and Portuguese. Training contributors include COMET, RAMMB/CIRA, CIMSS, and SPoRT. Translation contributors/reviewers include the Servicio Meteorológico Nacional (SMN) in Argentina and the University of São Paulo in Brazil.
Available online: https://www.meted.ucar.edu/training_module.php?id=1405
Published by: The University Corporation for Atmospheric Research ; 2018
This listing of multilingual training materials for the GOES-R series includes both foundational lessons and quick guides developed by various partners at the request of the U.S. National Weather Service and NESDIS. The selections included here represent materials translated to Spanish and Portuguese. Training contributors include COMET, RAMMB/CIRA, CIMSS, and SPoRT. Translation contributors/reviewers include the Servicio Meteorológico Nacional (SMN) in Argentina and the University of São Paulo in Brazil.
Disclaimer regarding 3rd party resources: WMO endeavours to ensure, but cannot and does not guarantee the accuracy, accessibility, integrity and timeliness of the information available on its website. WMO may make changes to the content of this website at any time without notice.
The responsibility for opinions expressed in articles, publications, studies and other contributions rests solely with their authors, and their posting on this website does not constitute an endorsement by WMO of the opinion expressed therein.
WMO shall not be liable for any damages incurred as a result of the use of its website. Please do not misuse our website.Language(s): English
Format: Digital (Standard Copyright)Tags: Satellite ; Weather forecasting ; Mesoscale ; Data assimilation ; Remote sensing ; Convection ; Lesson/ Tutorial ; Satellite Skills and Knowledge for Operational Meteorologists
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GOES-16 GLM Case Exercise: Buenos Aires Tornado and Hail Event
The Geostationary Lightning Mapper (GLM) flies aboard the GOES-R series satellites and provides lightning detection data at a quality and resolution not previously available from space. The GLM's continuous lightning monitoring capability is a valuable asset to detecting and monitoring developing thunderstorms 24 hours a day. This 30 minute lesson introduces learners to the benefits of using Geostationary Lightning Mapper (GLM) observations in assessing convection. Learners will explore a severe weather event near Buenos Aires, Argentina, and practice using GLM observations to determine initia ...
Available online: https://www.meted.ucar.edu/training_module.php?id=1427
Published by: The University Corporation for Atmospheric Research ; 2018
The Geostationary Lightning Mapper (GLM) flies aboard the GOES-R series satellites and provides lightning detection data at a quality and resolution not previously available from space. The GLM's continuous lightning monitoring capability is a valuable asset to detecting and monitoring developing thunderstorms 24 hours a day. This 30 minute lesson introduces learners to the benefits of using Geostationary Lightning Mapper (GLM) observations in assessing convection. Learners will explore a severe weather event near Buenos Aires, Argentina, and practice using GLM observations to determine initial convection, supplement other data tools in estimating tendencies in storm strength, and evaluate the potential for severe weather.
Disclaimer regarding 3rd party resources: WMO endeavours to ensure, but cannot and does not guarantee the accuracy, accessibility, integrity and timeliness of the information available on its website. WMO may make changes to the content of this website at any time without notice.
The responsibility for opinions expressed in articles, publications, studies and other contributions rests solely with their authors, and their posting on this website does not constitute an endorsement by WMO of the opinion expressed therein.
WMO shall not be liable for any damages incurred as a result of the use of its website. Please do not misuse our website.Language(s): English
Format: Digital (Standard Copyright)Tags: Weather forecasting ; Lesson/ Tutorial ; Tornado ; Hail ; Remote sensing ; Convection ; Satellite Skills and Knowledge for Operational Meteorologists
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GOES-R Series Faculty Virtual Course: Geostationary Lightning Mapper
In this webinar recording Scott Rudlosky and Geoffrey Stano discuss and demonstrate the capabilities of the GOES-R/16 Geostationary Lightning Mapper (GLM) in both operational and research applications. You will learn how the GLM, the first lightning mapper in geostationary orbit, differs from land-based lightning detection. The presenters summarize important processes known as lightning events, group, flashes, and lightning jumps and show products that illustrate the location and areal extent of lightning, and its evolution in cloud systems. With this information you should be able to integrat ...
Available online: https://www.meted.ucar.edu/training_module.php?id=1381
Published by: The University Corporation for Atmospheric Research ; 2017
In this webinar recording Scott Rudlosky and Geoffrey Stano discuss and demonstrate the capabilities of the GOES-R/16 Geostationary Lightning Mapper (GLM) in both operational and research applications. You will learn how the GLM, the first lightning mapper in geostationary orbit, differs from land-based lightning detection. The presenters summarize important processes known as lightning events, group, flashes, and lightning jumps and show products that illustrate the location and areal extent of lightning, and its evolution in cloud systems. With this information you should be able to integrate lightning data into studies about storm type and evolution, lightning safety, lightning climatology, multi-sensor products, wildfire initiation, and more. This is a recorded webinar presented by instructors at their home institutions. Audio variations may exist.
Disclaimer regarding 3rd party resources: WMO endeavours to ensure, but cannot and does not guarantee the accuracy, accessibility, integrity and timeliness of the information available on its website. WMO may make changes to the content of this website at any time without notice.
The responsibility for opinions expressed in articles, publications, studies and other contributions rests solely with their authors, and their posting on this website does not constitute an endorsement by WMO of the opinion expressed therein.
WMO shall not be liable for any damages incurred as a result of the use of its website. Please do not misuse our website.Language(s): English
Format: Digital (Standard Copyright)Tags: Weather forecasting ; Convection ; Lesson/ Tutorial ; Satellite Skills and Knowledge for Operational Meteorologists
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Using Climatology in Forecasting Convection in West and Central Africa
This case-study lesson provides an opportunity to apply the information in the ASMET lesson “Satellite-Derived Climatology Products for Monitoring Convection Over West and Central Africa” to a case that occurred over West and Central Africa in June 2014. It demonstrates how to integrate climatology information with satellite, global instability indices (GII), and NWP data when convection is forecast to occur.Permalink![]()
Forecasting Aviation Convective Impacts with INSITE
The National Weather Service (NWS) has developed the INSITE tool (INtegrated Support for Impacted air-Traffic Environments) to improve NWS convective impact forecasts by providing functionality that enables forecasters to include more precise impact areas in aviation convective weather forecast products. The tool lets forecasters identify potential constraints to the National Airspace System by combining forecast weather and air-traffic data. Improved convective weather forecast products can reduce delays in air-traffic and increase efficiency in the National Airspace System (NAS). In this 45- ...Permalink![]()
GOES-R Series Faculty Virtual Course: RapidScan Imaging
In this webinar recording, Dr. Dan Lindsey presents GOES-16/GOES-R 30-second and 1-minute rapid scan imagery to demonstrate unprecedented views of convection, wildfire, storm intensification, and other quickly-evolving features. GOES-16 rapid scan also enables cloud and feature tracking in and around tropical cyclones. The webinar includes examples of how rapid scan sectors may be prioritized and selected by the National Weather Service. Instructions about how to obtain and use archived data are also provided. This is a recorded webinar presented by an instructor at his home institution. Audio ...Permalink![]()
GOES-16 Case Exercise: 8 May 2017 Colorado Hail Event
GOES-16, the first satellite in the GOES-R series, launched in November 2016 and now provides 16 multispectral bands of satellite data, including CONUS scans every five minutes, with 0.5 kilometer visible imagery resolution and 2.0 km longwave infrared resolution. This lesson harnesses GOES-16’s increased temporal and spatial resolutions to identify convective development and intensity signatures on traditional longwave IR and visible band imagery, and compares the experience to using legacy GOES products. The lesson is geared toward early-career forecasters, those forecasters wanting more exp ...Permalink![]()
Met 101: Introduction to the Atmosphere
This lesson provides an overview of Earth’s atmosphere, its vertical structure, the fundamental forces acting on air, and how the atmosphere's composition affects the colors we see in the sky. The lesson also includes information about how Earth receives energy from the Sun as solar and infrared radiation, and the mechanisms for transferring heat around the globe. Learners will be introduced to the components of Earth’s water cycle, and also briefly explore the main types of systems used to observe the atmosphere.Permalink![]()
Limitations of High-Resolution NWP Models
This scenario-based lesson examines how the limitations of high-resolution NWP forecasts affect their analyses and forecasts of winter and severe weather, and how best to use the output in light of the limitations. The lesson is structured around a case that occurred in Texas in December 2015 when winter weather and severe weather hit Amarillo and Dallas-Ft. Worth, respectively. As users go through the case, they learn how spin-up time, errors in initial conditions, and deficiencies in the modeling of mesoscale phenomena can impact high-resolution forecasts in the NAM nest and HRRR models.Permalink![]()
Satellite Foundational Course for GOES-R: SatFC-G (SHyMet Full Course Access)
The Satellite Foundational Course for GOES-R (SatFC-G) is a series of nearly 40 lessons designed specifically for National Weather Service (NWS) forecasters and decision makers to prepare for the U.S.’ next-generation geostationary environmental satellites. The course is intended to help learners develop or improve their understanding of the capabilities, value, and anticipated benefits from the GOES-R suite of instruments. These instruments and imagery offer improved monitoring of meteorological, environmental, climatological, and space weather phenomena and related hazards. The course will a ...Permalink![]()
Predicting Convective Cessation for Aviation Forecasters
This module introduces aviation forecasters to a conceptual framework for analyzing, diagnosing and predicting convective cessation and resulting conditions near airports. Users will first learn about five main environments with respect to convection, and three patterns in which these environments are commonly arranged. Next, users are immersed into an adjustable-time case simulator to practice applying the convective environment frameworks to their forecast process, while periodically amending TAFs and responding to warning, storm report and caller interruptions. Finally, a case summary ties ...Permalink![]()
Satellite-Derived Climatology Products for Monitoring Convection Over West and Central Africa
A weather forecaster’s knowledge of climatology is important to the success of a forecast, especially where convection is involved. That’s particularly true over Central and West Africa where convection has a strong diurnal cycle and usually develops over particular geographic regions and during specific time intervals. The lesson describes satellite-derived cloud climatology products and several global instability indices, all of which can be integrated with other products to forecast convection. Although the lesson uses examples of climatology products from specific months, it makes the full ...Permalink![]()
Forecasting Heavy Rains and Landslides in Eastern Africa
Good rainfall draws many people to settle across the eastern Africa highlands for farming and other businesses. However, factors such as steep terrain, logging, livestock grazing, agriculture, and construction, have increased erosion and contributed to less stable slopes. These factors can lead to devastating landslides and mudslides, especially during episodes of very heavy rain. Forecasting and monitoring heavy rainfall is challenging, especially in mountainous regions that have few surface observations. This make satellite data critical for meteorologists and hydrologists forecasting for th ...Permalink![]()
ASMET 7: Convective Weather and Aviation in West and Central Africa
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 conve ...Permalink![]()
Multispectral Satellite Applications: RGB Products Explained
This lesson provides an overview of meteorological and environmental RGB products, namely, how they are constructed and how to use them. The first half provides background information on the RGB development process and the rapid evolution of RGB products as newer geostationary and polar-orbiting satellite imagers incorporate additional spectral channels. The second half of the lesson, the Applications section, focuses on the formulation and uses of RGB products; providing examples, interpretation exercises, satellite specific information, and other background information for many of the common ...Permalink![]()
Weather Decision Support for the National Airspace System
This three-hour lesson describes the impacts of weather on aviation operations and highlights the role of the National Weather Service (NWS) in supporting the Federal Aviation Administration's air traffic management organization. The lesson contains an Introduction (40 min), several cases (10-20 min each) focused on various weather phenomena, and a detailed case (35 min) allowing forecasters to follow the planning for and evolution of an event. The content emphasizes best practices for aviation forecasters, including identifying and communicating the threat, understanding partners' needs, and ...Permalink![]()
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 ...Permalink![]()
Skywarn Spotter Convective Basics
The "SKYWARN® Spotter Convective Basics" module will guide users to a basic understanding of convective storms. Through three different scenarios, you will cover reporting and proper communication of local storm reports to the National Weather Service (NWS), personal safety during these events, and field identification of convective storm hazards. After completing the scenarios, you will be given the opportunity to practice identifying storm features from a spectrum of photos.Permalink![]()
Development of a Nonhydrostatic Version of the Mesoscale-Convection-Resolving Model and its Application to the Eyewall and Spiral Rainbands of Tropical Cyclones
Journal of the Meteorological Society of Japan, Vol. 88. No 4. Yamasaki Masanori - Meteorological Society of Japan, 2010A numerical model in which the effects of cumulus convection are incorporated as the subgrid-scale and mesoscale organized convection is resolved by the grid (mesoscale-convection-resolving model, MCRM) was developed in the 1980s with an intention of improving the parameterization schemes for moist convection, which had been used since the 1960s. As in many numerical models with parameterization in the 1980s, hydrostatic equilibrium was assumed. The present paper describes a nonhydrostatic version of the MCRM, with some modifications of the subgrid-scale effect formulation used in the hydrosta ...Permalink![]()
Forecast Study of the Cold December of 2005 in Japan: Role of Rossby Waves and Tropical Convection
Journal of the Meteorological Society of Japan, Vol. 88. No 4. Inaba Morio; Kodera Kunihiko - Meteorological Society of Japan, 2010Japan experienced unusually heavy snowfall and low temperatures in December 2005 owing to the cold air advected from Siberia. As a result of this strong and sustained cold surge, record-breaking snowfalls occurred repeatedly along the coast of the Sea of Japan. To determine the cause and to examine the accuracy of numerical forecasts of such unusual weather as well as to investigate the impact of initial and boundary conditions on the forecasts, we conducted one-month ensemble forecasts for December 2005 by changing lower boundary conditions, such as sea-surface temperature (SST) and sea-ice c ...Permalink![]()
How Models Produce Precipitation and Clouds - version 2
This module, part of the "NWP Training Series: Effective Use of NWP in the Forecast Process", explores how NWP models handle both grid-scale microphysical (precipitation) and convective processes through parameterizations and/or explicit methods, with an emphasis on how model treatment (and errors in the triggering) of these processes affects forecast depiction of precipitation and related forecast variables. Back in 2000, the subject matter expert for this module was Dr. Ralph Petersen of the National Centers for Environmental Prediction, Environmental Modeling Center (NCEP/EMC). Revisions to ...Permalink![]()
Satellite Feature Identification: Ring of Fire
Satellite Feature Identification: Ring of Fire introduces forecasters to the potentially damaging convection that can develop in conjunction with blocking high pressure centers and examines how to identify it from a water vapor imagery perspective. This module is part of the series "Dynamic Feature Identification: The Satellite Palette".PermalinkPermalink![]()
Severe Convection: Mesoscale Convective Systems
Mesoscale convective systems occur worldwide and year-round and are accompanied by the potential for severe weather and flooding. This lesson describes typical system evolution by examining squall line, bow echo, and MCC characteristics throughout their life cycles. This lesson has less emphasis on the physical processes controlling MCS structure and evolution than our previously released Mesoscale Convective Systems: Squall Lines and Bow Echoes lesson. Instead, this newly updated lesson includes more material on tropical squall lines, MCC's, and on NWP’s ability to predict convective systems. ...Permalink![]()
Synoptic Weather Considerations: Forecasting Fog and Low Stratus
In order to assess whether a fog or stratus event is possible, you must evaluate the synoptic-scale influences that will drive the local conditions. In this module, we examine several common synoptic situations to understand the processes involved in fog or low stratus development. Most of these are forced primarily by advective or dynamic processes (although radiation does play a role). A more detailed discussion of radiation processes is contained in the Radiation Fog module. This module is part of the Distance Learning Course 1: Forecasting Fog and Low Stratus.Permalink![]()
Principles of Convection II: Using Hodographs
This lesson provides a basic understanding of how to plot and interpret hodographs, with application to convective environments. Most of the material previously appeared in the CD lesson, Anticipating Convective Storm Structure and Evolution, developed with Dr. Morris Weisman. Principles of Convection II: Using Hodographs includes a concise summary for quick reference and a final exam to test your knowledge. The lesson comes with audio narration, rich graphics, and a companion print version.Permalink![]()
A Convective Storm Matrix: Buoyancy/Shear Dependencies
In order to help forecasters build a strategy for anticipating convective storm structures, their evolution, and the potential for severe weather, A Convective Storm Matrix provides learners the opportunity for extensive exploration of the relationship between a storm's environment and its structure. The matrix is composed of 54 four-dimensional numerical simulations based on the interactions of 16 different hodographs and 4 thermodynamic profiles. By comparing animated displays of these simulations, learners are able to discern the influences of varying buoyancy and vertical wind shear profil ...Permalink![]()
Principles of Convection III: Shear and Convective Storms
This module discusses the role of wind shear in the structure and evolution of convective storms. Using the concept of horizontal vorticity, the module demonstrates how shear enhances uplift, leading to longer-lived supercell and multicell storms. The module also explores the role of shear in the development of mesoscale convective systems, including bow echoes and squall lines. Most of the material in this module previously appeared in the COMET modules developed with Dr. Morris Weisman. This version includes a concise summary for quick reference and a final exam to test your knowledge. The m ...Permalink![]()
Thermally-forced Circulation I: Sea Breezes
This module describes the phenomena of the sea breeze. It examines factors that lead to the formation of a sea breeze, modifying effects on sea breeze development, how mesoscale NWP models handle sea breezes, and sea breeze forecast parameters. The module places instruction in the context of a sea breeze case from Florida and compares surface and satellite observations to a model simulation using the AFWA MM5. Like other modules in the Mesoscale Meteorology Primer, this module comes with audio narration, rich graphics, and a companion print version.Permalink![]()
Principles of Convection I: Buoyancy and CAPE
This module provides a brief overview of Buoyancy and CAPE. Topics covered include the origin of atmospheric buoyancy, estimating buoyancy using the CAPE and Lifted Index, factors that affect buoyancy including entrainment of mid-level air, water loading, convective inhibition, and the origin of convective downdrafts. This module delivers instruction with audio narration, rich graphics, and a companion print version.Permalink![]()
Thermally-forced Circulation II: Mountain/Valley Breezes
This is a foundation module in the Mesoscale Meteorology Primer series. Topics covered include up- and downslope breezes, up- and down-valley winds, associated hazards, and forecasting techniques. Like other modules in the Mesoscale Meteorology Primer, this module comes with audio narration, rich graphics, and a companion print version.Permalink