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GCRF African SWIFT
GCRF African-SWIFT is a programme of research and capability building, led by the National Centre for Atmospheric Science (NCAS), and funded by UK Research and Innovation Global Challenges Research Fund. The project aims to deliver a step change in African weather forecasting capability from hourly to seasonal timescales, and build research capability to continue forecasting improvements in Africa for the foreseeable future.
The GCRF African-SWIFT team works with forecast users across sectors from aviation to agriculture, energy, water and emergency response to understand how to ...
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Available online: https://africanswift.org/resources/
Published by: University of Leeds ; 2019
GCRF African-SWIFT is a programme of research and capability building, led by the National Centre for Atmospheric Science (NCAS), and funded by UK Research and Innovation Global Challenges Research Fund. The project aims to deliver a step change in African weather forecasting capability from hourly to seasonal timescales, and build research capability to continue forecasting improvements in Africa for the foreseeable future.
The GCRF African-SWIFT team works with forecast users across sectors from aviation to agriculture, energy, water and emergency response to understand how to tailor the provision and delivery of weather forecasts and to ensure improved response to high-impact events (e.g. onset of rains, heat-waves, dry spells, strong winds); rapid emergency response to extreme events, such as urban flooding and prolonged droughts; and increased resilience, through integration of weather prediction into strategies for response to climate change.Notes: Primary Author: GCRF African SWIFT
Publisher: University of LeedsDisclaimer 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 (Free) (Variable)Tags: Weather forecasting ; Numerical weather prediction ; Climate services ; Text/ Reading ; Competencies for Provision of Climate Services ; NWP Skills and Knowledge for Operational Meteorologists ; PWS - Personnel Engaged in Operational Forecasting ; PWS - Weather Broadcasters and Communicators ; Satellite Skills and Knowledge for Operational Meteorologists ; PWS - Competency Requirements for Persons Engaged in the Development and Delivery of Products and Services to Meet User Requirements ; Basic Instructional Package for Meteorologists
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GCOS, 229. Plan for improving observations around Lake Victoria that support numerical weather predictions, climate services and adaptation
World Meteorological Organization (WMO) ; United Nations Educational, Scientific and Cultural Organization (UNESCO); Intergovernmental Oceanographic Commission (IOC); et al. - WMO, 2019
Plan for improving observations around Lake Victoria that support numerical weather predictions, climate services and adaptation
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World Meteorological Organization (WMO) ; United Nations Educational, Scientific and Cultural Organization ; Intergovernmental Oceanographic Commission ; United Nations Environment Programme ; International Council for Science
Published by: WMO ; 2019Collection(s) and Series: GCOS- No. 229
Language(s): English
Format: Digital (Free)Tags: Global Climate Observing System (GCOS) ; Numerical weather prediction ; Climate services ; Adaptation
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The Forecast Process: Using the Forecast Funnel
This lesson was developed by meteorologist, Dr. Mick Pope, with sponsorship from the Australian Bureau of Meteorology (BoM). The lesson is a somewhat broad-brush review of the overall forecast process, but with specific application of the forecast funnel approach as used by Australia's Bureau of Meteorology (BoM). The forecast process components include decision support and communication, use of numerical weather prediction, and applying the forecast funnel approach. The forecast funnel is described in detail, along with the forecaster time pyramid, and it is applied using a BoM forecast polic ...
Available online: https://www.meted.ucar.edu/training_module.php?id=10004
Published by: The University Corporation for Atmospheric Research ; 2019
This lesson was developed by meteorologist, Dr. Mick Pope, with sponsorship from the Australian Bureau of Meteorology (BoM). The lesson is a somewhat broad-brush review of the overall forecast process, but with specific application of the forecast funnel approach as used by Australia's Bureau of Meteorology (BoM). The forecast process components include decision support and communication, use of numerical weather prediction, and applying the forecast funnel approach. The forecast funnel is described in detail, along with the forecaster time pyramid, and it is applied using a BoM forecast policy example.
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 ; North Atlantic Oscillation (NAO) ; Jet stream ; Rossby Waves ; Outgoing longwave radiation (OLR) ; Lesson/ Tutorial ; NWP Skills and Knowledge for Operational Meteorologists
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CESM Distance Learning Course
The Community Earth System Model (CESM) is a fully-coupled, community, global climate model that provides state-of-the-art computer simulations of the Earth's past, present, and future climate states. The CESM Distance Learning Course is based on the CESM Tutorial held annually at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado. This course consists of 12 lectures and 4 practical sessions on simulating the climate system and practical sessions on running Community Earth System Model (CESM), modifying components, and analyzing data. The course is targeted at the graduat ...
Available online: https://www.meted.ucar.edu/training_module.php?id=1363
Published by: The University Corporation for Atmospheric Research ; 2019
The Community Earth System Model (CESM) is a fully-coupled, community, global climate model that provides state-of-the-art computer simulations of the Earth's past, present, and future climate states. The CESM Distance Learning Course is based on the CESM Tutorial held annually at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado. This course consists of 12 lectures and 4 practical sessions on simulating the climate system and practical sessions on running Community Earth System Model (CESM), modifying components, and analyzing data. The course is targeted at the graduate student level.
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: Hydrology ; Weather forecasting ; Numerical weather prediction ; Sea ice ; Atmospheric chemistry ; Atmospheric physics ; Climate services ; Lesson/ Tutorial ; Competencies for Provision of Climate Services ; NWP Skills and Knowledge for Operational Meteorologists
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Convection-allowing Models (CAMs): Winter Applications
In this lesson, forecasters will practice using guidance from different convection-allowing models (CAMs) over the short term. As they review and analyze the model guidance they will encounter some of the advantages and limitations of using CAMs for winter weather.
Available online: https://www.meted.ucar.edu/training_module.php?id=1459
Published by: The University Corporation for Atmospheric Research ; 2019
In this lesson, forecasters will practice using guidance from different convection-allowing models (CAMs) over the short term. As they review and analyze the model guidance they will encounter some of the advantages and limitations of using CAMs for winter 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 ; Numerical weather prediction ; Lesson/ Tutorial ; NWP Skills and Knowledge for Operational Meteorologists
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Introducing the FORMOSAT-7/COSMIC-2 Satellite System - Next Generation Observations for Weather and Climate
The latest-generation Constellation Observing System for Meteorology, Ionosphere, and Climate (FORMOSAT-7/COSMIC-2) provides high-resolution observations of Earth's atmosphere, including the ionosphere. In this video, scientists and mission planners introduce the instrumentation used and describe the collaborations that made the COSMIC-2 mission possible. These experts describe how COSMIC uses a technique called radio occultation—making use of existing navigation satellite signals passing through the atmosphere to provide detailed measurements of temperature, pressure, and water vapor. They ex ...
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What's New in NBM v3.2
The U.S. National Weather Service (NWS) National Blend of Models (NBM) is scheduled to be upgraded to version 3.2 in November 2019. It includes the first probabilistic blended guidance for temperature, precipitation, snow, and ice. There are more blended forecast products for aviation, marine, water resources, fire weather, winter weather, and tropical weather. Version 3.2 uses more model components to improve guidance, and introduces a new Guam domain. For a transcript, see What’s New in NBM v3.2. (https://www.meted.ucar.edu/nwp/blend_v32_video/NBM_v32_script.pdf)
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Satellite Signals from Space: Smart Science for Understanding Weather and Climate
Want to know about COSMIC, and how satellite signals can provide information about Earth's atmosphere? This video provides anyone interested in the topic with a brief overview of the Constellation Observing System for Meteorology, Ionosphere, and Climate, called COSMIC. Targeted to students and teachers in Grades 5-9 but accessible to anyone, the video introduces the latest COSMIC mission (COSMIC-2), which uses satellites orbiting near Earth to measure how the atmosphere affects signals from global positioning system (GPS) satellites high above the surface. This technique is called radio occul ...
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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 ...
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NWP Comparisons: Total-column Variables
Another way to try to find mismatches between observed weather and NWP output is by using total-column variables. There are a few of them to choose from, and they make for a relatively simple comparison method for finding correctable mismatches. In this lesson, we'll address appropriate methods for making these comparisons and build to a point where we will focus on bigger picture atmospheric processes. This is the second in a series of video lessons that introduces three different methods for modifying NWP output to add human value to forecasts.
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PV Modification
You know what PV is, yet aren't quite sure how to modify it to make a better forecast. In this short lesson, we will discuss how to modify the PV surface to match water vapour imagery and how those adjustments affect the surface sensible weather. This is the fifth in a series of video lessons that introduces three different methods for modifying NWP output to add human value to forecasts. Pre-requisite Knowledge: Satellite Water Vapour Interpretation -- Short Course
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Interpreting and Communicating EPS Guidance: Germany Winter Event
This 45-minute lesson briefly introduces learners to the benefits of using probabilistic forecast information to assess weather and communicate forecast uncertainties. Learners will explore a winter weather event in Germany and practice synthesizing deterministic and probabilistic forecast guidance to better understand forecast uncertainties based on lead-time. Also, learners will decide how to best communicate the potential weather threats and impacts to local end users. The lesson is another component of the Forecast Uncertainty: EPS Products, Interpretation, and Communication distance learn ...
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Introduction to Modifying NWP Output
Surface observations are usually the first place we go when trying to find mismatches between observed weather and NWP output. We'll talk in this lesson about appropriate methods for making those comparisons and build to a point where we will focus on bigger picture atmospheric processes. This is the first in a series of video lessons that introduces three different methods for modifying NWP output to add human value to forecasts.
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Adjusting NWP: Direct Comparison
If there were a way to make direct comparisons between satellite imagery and NWP output, that would appear to be the best possible way to find mismatches between the observed weather and NWP output. In this lesson, we'll address possible methods for making direct comparisons, starting with pseudo or synthetic satellite imagery and building to a point where we focus on a relatively unused NWP output. This is the third in a series of video lessons that introduces three different methods for modifying NWP output to add human value to forecasts. Pre-requisite Knowledge: Satellite Water Vapour Inte ...
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Interpreting and Communicating EPS Guidance: Iberian Heat Wave
This 45-minute lesson briefly introduces learners to the benefits of using probabilistic forecast information to assess the weather and communicate forecast uncertainties. Learners will explore a heat wave event in Spain and practice interpreting EPS forecast products effectively to determine various forecast parameters based on lead-time. Also, learners will decide how to best communicate the potential weather threats and impacts information to local end users.
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