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Unified Terrain in the National Blend of Models
This lesson discusses errors associated with the use of inconsistent terrain in the analyses in the Real-Time and the Un-Restricted Mesoscale Analyses (RTMA and URMA, respectively), and in downscaling numerical weather prediction model data to the resolution of the U.S. National Weather Service National Blend of Models (NBM). The sources of these inconsistencies are examined, and the errors that result are discussed. A solution is to use a unified, consistent terrain in the analyses and the NBM. This solution is only partial however, as resolution of small, meteorologically significant feature ...
Available online: https://www.meted.ucar.edu/training_module.php?id=1376
Published by: The University Corporation for Atmospheric Research ; 2018
This lesson discusses errors associated with the use of inconsistent terrain in the analyses in the Real-Time and the Un-Restricted Mesoscale Analyses (RTMA and URMA, respectively), and in downscaling numerical weather prediction model data to the resolution of the U.S. National Weather Service National Blend of Models (NBM). The sources of these inconsistencies are examined, and the errors that result are discussed. A solution is to use a unified, consistent terrain in the analyses and the NBM. This solution is only partial however, as resolution of small, meteorologically significant features is still somewhat limited. Poorly resolved physical features will still result in analysis and forecast error in some circumstances.
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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GOES-16 and S-NPP/JPSS Case Exercise: Hurricane Harvey Surface Flooding
Satellite data are important tools for analyses and short-term forecasts of surface floodwater. This lesson will highlight the August 2017 flooding associated with Hurricane Harvey in southeastern Texas, one of the most costly weather disasters in U.S. history. Through the use of interactive exercises the learner will become familiar with use and interpretation of satellite imagery in regions with surface flooding. The lesson will use data from both the S-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) and the GOES-16 Advanced Baseline Imager (ABI). The satellite-derived flood map and th ...
Available online: https://www.meted.ucar.edu/training_module.php?id=1397
Published by: The University Corporation for Atmospheric Research ; 2018
Satellite data are important tools for analyses and short-term forecasts of surface floodwater. This lesson will highlight the August 2017 flooding associated with Hurricane Harvey in southeastern Texas, one of the most costly weather disasters in U.S. history. Through the use of interactive exercises the learner will become familiar with use and interpretation of satellite imagery in regions with surface flooding. The lesson will use data from both the S-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) and the GOES-16 Advanced Baseline Imager (ABI). The satellite-derived flood map and the data that go into the flood map will both be highlighted in the lesson. Examples of floodplain inundation, interbasin transfer, and water pooling in reservoirs will be shown along with issues related to spatial and temporal resolution.
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 ; Satellite Skills and Knowledge for Operational Meteorologists
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National Water Model, Part 1: Science and Products
This lesson provides an introduction to the benefits, important input (forcing data), and key products of the National Water Model. Both official and evolving products are presented. The lesson uses the flooding associated with Hurricane Harvey in August 2017 to demonstrate key products.
Available online: https://www.meted.ucar.edu/training_module.php?id=1296
Published by: The University Corporation for Atmospheric Research ; 2018
This lesson provides an introduction to the benefits, important input (forcing data), and key products of the National Water Model. Both official and evolving products are presented. The lesson uses the flooding associated with Hurricane Harvey in August 2017 to demonstrate key products.
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: Drought ; Flood ; Weather forecasting ; Numerical weather prediction ; Water cycle ; Flash flood ; Runoff ; Stream discharge ; Soil moisture ; Lesson/ Tutorial ; NWP Skills and Knowledge for Operational Meteorologists
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SatFC-J: The AMSR2 Microwave Imager
This short lesson describes the Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the next-generation polar-orbiting satellite platforms. AMSR2’s primary mission is to improve scientists’ understanding of climate by providing estimates of precipitation, water vapor, cloud water, wind velocity, sea surface temperature, sea ice concentration, snow depth, and soil moisture. AMSR2 also advances weather forecasting through real-time imagery, value-added products, and input to numerical weather prediction. This lesson is part of the Satellite Foundational Course for JPSS (SatFC-J).
Available online: https://www.meted.ucar.edu/training_module.php?id=1303
Published by: The University Corporation for Atmospheric Research ; 2018
This short lesson describes the Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the next-generation polar-orbiting satellite platforms. AMSR2’s primary mission is to improve scientists’ understanding of climate by providing estimates of precipitation, water vapor, cloud water, wind velocity, sea surface temperature, sea ice concentration, snow depth, and soil moisture. AMSR2 also advances weather forecasting through real-time imagery, value-added products, and input to numerical weather prediction. This lesson is part of the Satellite Foundational Course for JPSS (SatFC-J).
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: Climate ; Weather forecasting ; Sea ice ; Lesson/ Tutorial ; Satellite Skills and Knowledge for Operational Meteorologists
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SatFC-J: The VIIRS Imager
This lesson introduces the VIIRS imager on board the Suomi NPP and JPSS satellites. The lesson briefly describes the capabilities, improvements, and benefits that VIIRS brings to operational meteorology. Numerous images are shown that demonstrate a variety of applications available in the AWIPS weather display system. This lesson is part of the Satellite Foundational Course for JPSS (SatFC-J).
Available online: https://www.meted.ucar.edu/training_module.php?id=1309
Published by: The University Corporation for Atmospheric Research ; 2018
This lesson introduces the VIIRS imager on board the Suomi NPP and JPSS satellites. The lesson briefly describes the capabilities, improvements, and benefits that VIIRS brings to operational meteorology. Numerous images are shown that demonstrate a variety of applications available in the AWIPS weather display system. This lesson is part of the Satellite Foundational Course for JPSS (SatFC-J).
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 ; Satellite Skills and Knowledge for Operational Meteorologists
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SatFC-J: Orbits and Data Availability
This lesson presents a brief overview of NOAA's operational low Earth orbiting satellites, focusing on how their orbits define observational coverage and how ground receiving capabilities impact data latency from the observation time to product availability. This lesson is part of the Satellite Foundational Course for JPSS (SatFC-J).Permalink![]()
Rapid Scan Applications and Benefits
This lesson introduces the capabilities and benefits of rapid scan imaging from geostationary meteorological satellites with a special focus on the current Meteosat Second Generation satellites. The lesson begins with an overview of current rapid scan imaging strategies and the products made from those observations. It then addresses nowcasting applications that benefit from these products with a focus on convection and its evolution. Other application areas that benefit from rapid scan observation are mentioned including the monitoring of fog and low stratus, wildfires, tropical cyclones, and ...Permalink![]()
Interpreting and Communicating EPS Guidance: British Columbia Winter Storm
This 45-minute lesson provides an opportunity to use ensemble prediction system products to evaluate uncertainty in the forecast and then communicate that information effectively to a public audience. The lesson places learners in the role of a Meteorological Service of Canada forecaster who must assess forecast uncertainty and then issue early warning notifications to decision-makers regarding the winter storm. In a subsequent work shift during the event, the learner must effectively deliver forecast information via social media and respond to questions from the general public. The lesson is ...Permalink![]()
Operational Environmental Monitoring Applications using the Community Satellite Processing Package (CSPP)
This resource demonstrates the variety of satellite imagery and products accessible through the Community Satellite Processing Package (CSPP). Two videos, the first focused on imagery applications and the second on microwave applications, provide an overview of the types of weather and environmental information available through CSPP. Using CSPP, forecasters and others needing timely access to data can download and display imagery and products from Joint Polar Satellite System (JPSS) instruments. The resource provides some background information for obtaining and using the CSPP software, which ...Permalink![]()
SatFC-J: The VIIRS Day/Night Band
This lesson introduces the innovative Day/Night Band (DNB). Producing both daytime and nighttime visible images, the unique aspect of the DNB is its nocturnal low-light imaging capability. It views reflected moonlight from clouds and Earth's surface, surface light emissions from various natural sources (such as fires) and anthropogenic sources (such as city lights and gas flares), and even from certain atmospheric light emissions such as the aurora, airglow, and lightning flashes. The lesson describes the capabilities and benefits of the DNB, in particular using the Near-Constant Contrast (NCC ...Permalink![]()
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 ...Permalink![]()
Гидродинамический прогноза погоды на территории Гвинеи
Agriculture is the largest employer in the world and is probably the most dependent on the climate of all human activities. In recent years there have been events that have put in evidence the vulnerability of global food security to major meteorological phenomena, both in global agricultural markets and the world economy. The food price crisis and the subsequent economic crisis reduced the purchasing power of large segments of the population in many developing countries, which seriously reduced their access to food and thus undermined their food security. During the years 2009 and 2010 in Ven ...Permalink![]()
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Guidance on Verification of Operational Seasonal Climate Forecasts
The purpose of this publication is to describe and recommend procedures for the verification of operational probabilistic seasonal forecasts, including those from the Regional Climate Outlook Forums (RCOFs), National Meteorological and Hydrological Services and other forecasting centres. The recommendations are meant to complement the WMO Commission for Basic Systems Standardized Verification System for Long-range Forecasts (SVSLRF). SVSLRF defines standards for verifying model outputs from Global Producing Centres (GPCs), and so includes procedures for measuring the quality of ensemble predic ...Permalink![]()
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ETR, 22. Seasonal Climate Forecast - COURSE PACKAGE T.O.P. : Theory and Operational Principles, Project Report
This is the report on the project to create the Seasonal Climate Forecast - Course Package T.O.P. The goal of this online course package is to allow the transfer of seasonal climate forecast knowledge to improve and increase the operational capabilities of the targeted users. The package provides both a theoretical and a practical set of knowledge on seasonal forecast and predictability models, climate and data analysis, forecast verification, and specific application of seasonal forecast for agriculture and water management.Permalink![]()
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SP, 12. Guidelines on Satellite Skills and Knowledge for Operational Meteorologists
This document describes the underpinning skills that support the WMO competencies that relate to the use of satellite data by operational meteorologists.Permalink