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SatFC-G: Near-IR Bands
This lesson introduces you to three of the four near-infrared imager bands (at 1.37, 1.6, and 2.2 micrometers) on the GOES R-U ABI (Advanced Baseline Imager), focusing on their spectral characteristics and how they affect what each band observes. For information on the 0.86 micrometer near-IR "veggie" band which is not included here, refer to the Visible and Near-IR Bands lesson. This lesson is a part of the NWS Satellite Foundation GOES-R Course.
Available online: https://www.meted.ucar.edu/training_module.php?id=1268
Published by: The University Corporation for Atmospheric Research ; 2016
This lesson introduces you to three of the four near-infrared imager bands (at 1.37, 1.6, and 2.2 micrometers) on the GOES R-U ABI (Advanced Baseline Imager), focusing on their spectral characteristics and how they affect what each band observes. For information on the 0.86 micrometer near-IR "veggie" band which is not included here, refer to the Visible and Near-IR Bands lesson. This lesson is a part of the NWS Satellite Foundation GOES-R Course.
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.
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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: Aerosols ; Weather forecasting ; Ice cloud ; Water cloud ; Lesson/ Tutorial ; Satellite Skills and Knowledge for Operational Meteorologists
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Weather Forecast Uncertainty Information for Everyday Users - Presentation at 2015 Workshop on Communicating Uncertainty to Users of Weather Forecasts
Although previous research suggests that we are not very good at reasoning with uncertainty, the research described in this talk is far more encouraging. Unlike earlier work that compares peoples' decisions to a rational standard, these experiments compared decisions made by people with uncertainty information to decisions made by people without uncertainty information. The results suggest that including specific numeric uncertainty estimates in weather forecasts leads to better decisions. This talk was part of Meteorological Service of Canada's 2015 Workshop on Communicating Uncertainty to Us ...Weather Forecast Uncertainty Information for Everyday Users - Presentation at 2015 Workshop on Communicating Uncertainty to Users of Weather Forecasts
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Available online: https://www.meted.ucar.edu/training_module.php?id=1250
Published by: The University Corporation for Atmospheric Research ; 2016
Although previous research suggests that we are not very good at reasoning with uncertainty, the research described in this talk is far more encouraging. Unlike earlier work that compares peoples' decisions to a rational standard, these experiments compared decisions made by people with uncertainty information to decisions made by people without uncertainty information. The results suggest that including specific numeric uncertainty estimates in weather forecasts leads to better decisions. This talk was part of Meteorological Service of Canada's 2015 Workshop on Communicating Uncertainty to Users of Weather Forecasts precursor to the 49th CMOS Congress & 13th AMS Conference on Polar Meteorology and Oceanography. This resource is made available courtesy of Dr. Susan Joslyn, Environment Canada, CMOS and The Eumetcal Project, and is not produced, owned or hosted by UCAR/COMET.
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 ; Simulation ; NWP Skills and Knowledge for Operational Meteorologists
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Short-Range Ensemble Forecast Upgrade
The Short-Range Ensemble Forecast (SREF) system underwent a major upgrade in Fall 2015. The intended result of the upgrade was to improve the SREF ensemble spread and probabilistic skill, and to reduce a cool, wet bias in surface and near-surface temperatures and moisture. This 20-minute lesson addresses the changes to improve the SREF, including the increase in ensemble size, the increase in initial condition and model physics diversity, and drier land surface parameters to lessen the cool, wet bias. Each is introduced by comparing the old and new SREF forecasts for a potential winter storm f ...
Available online: https://www.meted.ucar.edu/training_module.php?id=1214
Published by: The University Corporation for Atmospheric Research ; 2016
The Short-Range Ensemble Forecast (SREF) system underwent a major upgrade in Fall 2015. The intended result of the upgrade was to improve the SREF ensemble spread and probabilistic skill, and to reduce a cool, wet bias in surface and near-surface temperatures and moisture. This 20-minute lesson addresses the changes to improve the SREF, including the increase in ensemble size, the increase in initial condition and model physics diversity, and drier land surface parameters to lessen the cool, wet bias. Each is introduced by comparing the old and new SREF forecasts for a potential winter storm from December 2014. The results from the case study and long-term seasonal results are used to show the extent to which changes to the SREF succeeded in improving its forecasts.
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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SatFC-G: GOES-R Impacts on Satellite Data Assimilation
This five minute lesson presents a brief overview of how GOES-R observations are expected to support and potentially enhance NWP for various analysis and forecast applications. This lesson is a part of the NWS Satellite Foundation GOES-R Course.
Available online: https://www.meted.ucar.edu/training_module.php?id=1259
Published by: The University Corporation for Atmospheric Research ; 2016
This five minute lesson presents a brief overview of how GOES-R observations are expected to support and potentially enhance NWP for various analysis and forecast applications. This lesson is a part of the NWS Satellite Foundation GOES-R Course.
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 ; Data assimilation ; Lesson/ Tutorial ; NWP Skills and Knowledge for Operational Meteorologists ; Satellite Skills and Knowledge for Operational Meteorologists
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JPSS River Ice and Flood Products
This lesson introduces hydrologists, meteorologists, and the education community to two new JPSS (Joint Polar Satellite System) satellite capabilities for monitoring river ice and flooding. It begins by describing the need for information on river ice and flooding, the capabilities of the Suomi NPP and future JPSS VIIRS imagers to provide products for monitoring river conditions, and the new river ice and flood products. This is followed by several cases, notably the May 2013 Galena, AK flood event, that demonstrate the use and value of the products in monitoring river ice and related flooding ...
Available online: https://www.meted.ucar.edu/training_module.php?id=1178
Published by: The University Corporation for Atmospheric Research ; 2016
This lesson introduces hydrologists, meteorologists, and the education community to two new JPSS (Joint Polar Satellite System) satellite capabilities for monitoring river ice and flooding. It begins by describing the need for information on river ice and flooding, the capabilities of the Suomi NPP and future JPSS VIIRS imagers to provide products for monitoring river conditions, and the new river ice and flood products. This is followed by several cases, notably the May 2013 Galena, AK flood event, that demonstrate the use and value of the products in monitoring river ice and related flooding. The cases also show additional applications in flooding and ice cover scenarios that are not related to ice jam events. Finally, they highlight the products’ role in supplementing other types of observations commonly relied on for monitoring river conditions.
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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Forecasting Sensible Weather from Water Vapour Imagery
Forecaster nowcasting at the synoptic scale is rapidly being replaced by the numerical weather prediction models. However, there are plenty of opportunities for you as a forecaster to improve on those forecasts with simple comparisons of water vapour hand analyses and surface hand analyses. The goal of this lesson is to improve your skills in water vapour and surface analyses to evaluate the three-dimensionality of the atmosphere and thus forecast the sensible weather better. This is the capstone for the entire Satellite Interpretation distance learning course.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![]()
SatFC-G: Tropical to Extratropical Transition
This lesson uses water vapor satellite imagery from Himawari-8 to describe the typical extratropical transition of a tropical cyclone. The Himawari-8 imager previews comparable capabilities coming online with the GOES-R ABI imager. The lesson also provides a brief overview of subtropical cyclones and their transition to tropical cyclones. This lesson is a part of the NWS Satellite Foundation GOES-R Course.Permalink![]()
SatFC-G: Impact of Satellite Observations on NWP
This lesson covers how satellite data inform numerical weather prediction models. From a basic overview of how satellite data is assimilated to how a new instrument's data might get into a model. This lesson is a part of the NWS Satellite Foundation GOES-R Course. More in-depth discussions and a quiz on the impacts of satellite observations on NWP can be found in the COMET lesson, How Satellite Observations Impact NWP.Permalink![]()
HiresW HREF Upgrade
This 20-minute lesson presents upgraded versions of the two NWP models used as High Resolution Window (HiresW), the Weather Research and Forecasting-Advanced Research WRF (WRF-ARW) and the Non-Hydrostatic Multiscale Model on the B-grid (NMMB). Domains include the CONtinental US (CONUS), Alaska, Hawaii, Guam, and Puerto Rico. The CONUS runs of the NMMB and WRF-ARW became part of a new High Resolution Ensemble Forecast (HREF) system in 2015, the first of its kind produced at the National Centers for Environmental Prediction. To familiarize the operational forecaster with the HREF, products from ...Permalink![]()
SatFC-G: Introduction to the GLM
This lesson describes the need for real-time lightning information and the capabilities of the Geostationary Lightning Mapper (GLM), which will fly on the next-generation GOES-R satellites as the first operational lightning detector in geostationary orbit. This lesson is a part of the NWS Satellite Foundation GOES-R Course. More in-depth discussions and a quiz on the lightning flash cycle and lightning applications can be found in the COMET lesson, GOES-R GLM: Introduction to the Geostationary Lightning Mapper.Permalink![]()
Verification Methods in the NWS National Blend of Global Models
This lesson introduces learners to the methods used in verifying the various weather element forecasts included in Version 1.0 of the U.S. National Weather Service (NWS) National Blend of global Models (NBM). This Level 2 lesson is intended for forecasters and users of NWS forecast products; some prior knowledge of numerical weather prediction and statistics is useful. Learners will be introduced to the analysis of record used to verify the NBM. Learners will also explore single event, grid-to-observation, and grid-to-grid verification methods, as well as how to interpret the results using the ...Permalink![]()
Statistical Methods in the NWS National Blend of Global Models
This lesson introduces users to the statistics used in generating the various weather element forecasts included in Version 1.0 of the U.S. National Weather Service (NWS) National Blend of global Models (NBM). This Level 3 lesson is intended for forecasters and users of NWS forecast products; some prior knowledge of numerical weather prediction and statistics is useful. Learners will be introduced to the analysis of record used to calibrate the NBM’s bias and error estimates. Learners will also explore the downscaling, bias correction, and weighting procedures applied to the model products, an ...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![]()
SatFC-G: IR Bands, Excluding Water Vapor
This lesson introduces seven of the ten infrared imager bands on the GOES R-U ABI (Advanced Baseline Imager). It examines the spectral characteristics of each band to facilitate a better understanding of band selection and what each band observes, and to shed light on some of the many potential applications. This lesson is a part of the NWS Satellite Foundation GOES-R Course.Permalink![]()
The Science of Radio Occultation and the COSMIC Mission
The lesson provides an overview of radio occultation and its contributions to our understanding of Earth's atmosphere as demonstrated by the COSMIC mission launched in 2006. The lesson is divided into three chapters: Chapter 1 describes the science of radio occultation and how atmospheric profiles are obtained. Chapter 2 focuses on the benefits of radio occultation and COSMIC observations for numerous applications related to meteorology, climate, and space weather. Chapter 3 describes the COSMIC-2/FORMOSAT-7 mission and its expected improvements to further inform meteorology, climate, and iono ...Permalink![]()
Communicating Forecast Uncertainty
This scenario-based lesson introduces the topic of communicating forecast uncertainty to decision-makers, such as emergency managers, related industry professionals, the public, and other end-users. In a case that spans the lesson, learners begin by developing a forecast discussion using deterministic data, refine it with probabilistic ensemble data, and evaluate how well it conveys uncertainty information. Then they assume several end-user roles, assessing how well the forecast discussion addresses their needs. From there, important research findings on communicating uncertainty are discussed ...Permalink![]()
SatFC-G: Visible and Near-IR Bands
This lesson introduces you to the two visible and one of the near-infrared imager bands on the GOES R-U ABI (Advanced Baseline Imager), focusing on their spectral characteristics and how they affect what each band observes. Also included is a brief discussion of the customization of visible enhancements as an important consideration for improving the depiction of various features of interest. This lesson is a part of the NWS Satellite Foundation GOES-R Course.Permalink![]()
Fog Forecasting for Heathrow, Northolt and Kenley Aerodromes Using Model Output Statistics
Fog though a rare event has adverse economic implications to both the airline and aviation service providers if it’s occurrence, duration and dissipation periods are not properly predicted. This work assesses the accuracy and skill in forecasting fog events and suggesting possible adjustments to improve forecast accuracy and skill. The forecast used in this study are produced by MeteoGroup using Model Output Statistics (MOS). Forecasts for Heathrow, Northolt and Kenley are considered for analysis. These forecasts are used by British Airports Authority (BAA) in planning airport operations. The ...Permalink![]()
Study on the Dynamical and Thermodynamical Process Intensifying the Squall Lines over Guinea
This research investigates the dynamical and thermodynamical process of mesoscale convective system that intensifies squall lines wind speed propagation. The generation of African Easterly Waves (AEWs) and its lifecycle. The characteristics of squall lines (SLs) over West Africa (WA) which occurred In Guinea for two cases periods June 01-02 and June 13-14, 2015. In all six (6) AEWs have been tracked using reanalysis data from European Centre for Medium-Range Weather Forecasts (ECMWF). European Meteorological Satellite images (EUMETSAT) and Earth Networks WeatherBug StreamerRT were also used to ...Permalink![]()
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GAW Report, 226. Coupled Chemistry-Meteorology/ Climate Modelling (CCMM): status and relevance for numerical weather prediction, atmospheric pollution and climate research
Online coupled meteorology atmospheric chemistry models have undergone a rapid evolution in recent years. Although mainly developed by the air quality modelling community, these models are also of interest for numerical weather prediction and climate modelling as they can consider not only the effects of meteorology on air quality, but also the potentially important effects of atmospheric composition on weather. This report provides the main conclusions from the Symposium on “Coupled Chemistry-Meteorology/Climate Modelling: Status and Relevance for Numerical Weather Prediction, Air Quality and ...Permalink![]()
Vol. 66 No. 3 - July 2015 - Special issue on forecast verification
is an issue of MAUSAM. Government of India, 2015Permalink![]()
The Future of the Weather Enterprise
At a time when the impacts of weather and climate are still growing dramatically, it is important to look for strategies to strengthen the science and technology that have resulted in substantial improvements in the skill of weather predictions and services over the past four decades. It was not that long ago – when many baby-boomers were just entering the workforce – that accurate, reliable forecasts did not extend beyond 24 hours. Today, high-quality 5 to 7 day forecasts are the norm. This improvement has resulted in lives being saved and avoidable damage and economic impacts being averted. ...Permalink![]()
The Weather: What’s the Outlook?
New sources of atmospheric observations, faster supercomputers and advances in science together revolutionized weather forecasting in the latter part of the 20th century. On the global scale, we can today predict up to five days ahead as accurately as we could do for three days 20 years ago. This means society has much more advance warning of weather hazards than before, permitting people to prepare and, thereby, limit the loss of lives and property. Expectations are high for even greater advances in the years to come.Permalink![]()
Interview: Qing-Cun Zeng
Qing-Cun Zeng, a famous academic meteorologist, is a pioneer of numerical weather prediction, dynamic climate prediction and remote sensing theory for meteorological satellites. His semi-implicit (1961) and quadratic (1981) schemes as well as his inversion variation method (1974) are still widely applied to theoretical and practical studies in meteorology and geophysical fluid dynamics. Through his active involvement in the study of global climate and environmental change, he has contributed to advancements in the study of meteorological hazards and related disaster risk reduction. He has rece ...Permalink