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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.
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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- ...
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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 ...
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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 ...
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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.
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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.
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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 ...
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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 ...
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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 ...
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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 ...
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