Lesson 1:
Introduction to the Top-Down Methodology
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Description |
The lesson, narrated by Randy Graham (SLC), provides an overview of the top-down methodology in forecasting precipitation type. This method helps forecasters intelligently assess observed and model sounding data in determining p-type because there are higher resolution model data to analyze and implicit microphysical concepts to consider on all levels in the atmosphere. The methodology addressed in this lesson considers operational issues such as assessing the potential for heterogeneous nucleation, impacts of warm layers, near surface (wet-bulb) effects, seeder-feeder mechanism, and precipitation intensity. |
Estimated Lesson Completion Time |
45 min. |
Module Type |
Articulate Presenter Module
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| Resources |
Exercises |
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Review Sheets & Hand Outs |
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Lesson Links |
NOAA employees should access this module via the NWS Learning Center as they will need to complete the exam and survey in the LMS to receive credit for completion. All others wishing to take this lesson should use the follow link(s):
IC 6.1: Introduction to the Top-Down Methodology
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Lesson 2:
Strengths and Weaknesses of Precipitation Type Algorithms
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Description |
This lesson, developed by Randy Graham (SLC) and Mike Evans (BGM), describes the top 4 precipitation type algorithms used in the field: Baldwin, Ramer (Part 1); Bourgouin Method and Partial Thickness (Part 2). The lesson describes the strengths and weaknesses of each algorithm. From this lesson, forecasters will be able to assess the validity of algorithm output in various forecast situations. |
Estimated Lesson Completion Time |
60 min. |
Module Type |
Articulate Presenter Modules
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| Resources |
Exercises |
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Review Sheets & Hand Outs |
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Lesson Links |
NOAA employees should access this module via the NWS Learning Center as they will need to complete the exam and survey in the LMS to receive credit for completion. All others wishing to take this lesson should use the follow link(s):
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Lesson 3:
Using Ensembles in Winter Weather Forecasting
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Description |
This lesson, developed by Richard Grumm (CTP), describes why forecasters should use ensemble forecast information in the outlook, watch, and warning phases of winter storms. The lesson illustrates conceptually and via case studies how to recognize uncertainty/high probability outcomes in EPS data. A section has been added in 2008 to discuss the state of current ensemble systems. |
Estimated Lesson Completion Time |
30 min. |
Module Type |
Articulate Presenter Module
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| Resources |
Exercises |
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Review Sheets & Hand Outs |
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Lesson Links |
NOAA employees should access this module via the NWS Learning Center as they will need to complete the exam and survey in the LMS to receive credit for completion. All others wishing to take this lesson should use the follow link(s):
IC 6.3: Using Ensembles in Winter Weather Forecasting
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Lesson 4:
The Ingredients-Based method for forecasting heavy precipitation
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Description |
This lesson, narrated by Ken Harding (ABR), describes the main components in the ingredients method for forecasting heavy precipitation. It also shows the student how to display the various ingredients and how you can combine the ingredients to produce a conceptual model for heavy precipitation. |
Estimated Lesson Completion Time |
15 min. |
Module Type |
Articulate Presenter Module
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| Resources |
Exercises |
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Review Sheets & Hand Outs |
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Lesson Links |
NOAA employees should access this module via the NWS Learning Center as they will need to complete the exam and survey in the LMS to receive credit for completion. All others wishing to take this lesson should use the follow link(s):
IC 6.4: The Ingredients-Based Method for Forecasting Heavy Precipitation
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Lesson 5:
Snowfall Forecasting
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Description |
This lesson, narrated by Dan Cobb (GRR) and Dan Petersen (HPC), describes how to diagnose and convert quantitative precipitation forecasts to actual snowfall amounts. Part 1 covers snow ratio basics, snow ratio climatologies, and reviews snow microphysics. Part 2 discusses snow production, including the role of vertical motion in producing snow crystals of different densities, how to modify snowfall accumulation rates based on sub-cloud and surface conditions, and how to convert NWP forecasts of equivalent liquid precipitation to snowfall. Additionally, the authors present two diagnostic tools for assessing snow ratio and snowfall. |
Estimated Lesson Completion Time |
50 min. |
Module Type |
Articulate Presenter Module
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| Resources |
Exercises |
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Review Sheets & Hand Outs |
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Lesson Links |
NOAA employees should access this module via the NWS Learning Center as they will need to complete the exam and survey in the LMS to receive credit for completion. All others wishing to take this lesson should use the follow link(s):
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