DRAFT

Integrated Sensor Training (IST) PDS Outline

11-12 August 1998

GOAL: Integrated Sensor Training provides training and education to support the integration of all sensor data (remote and in-situ) into operational weather forecasting

Executive Producer: Anthony Mostek NWS/Office of Meteorology

UNIT 1: Profiler

Producer – Sam Beckman NWS/Training Center

(Draft 12 Aug 1998 prepared by Sam Beckman, Gary Hufford, and Tom Schlatter)

Goal

Evaluate profiler observations and integrate them with other meteorological information.

Description of Job Competency to be Achieved

Exploit fully profiler observations in the daily forecast routine.

Description of Need

Forecasters need to understand the capabilities and limitation of three closely related component systems referred to as "profiler":

wind profiling radar

Radio Acoustic Sounding System (RASS)

Integrated Precipitable Water (IPW) from GPS signal analysis

Forecasters need to learn the applications of profiler data to nowcasting and very short-term prediction.

Specific Job Task Skills and Knowledge

A. For each profiler component system (provide forecasters with some proficiency on):

1) principles of operation

2) conditions of valid measurement

3) quality control procedures

4) system status

5) methods of display

6) interpretation

B. Application to specific forecast problems

1) low-level jet

2) characterizing shear environment for thunderstorms

3) application to mountain wave activity

4) diagnosing turbulence

5) timing arrival of upper air features

6) inversion depth

C. Data integration: How do profilers supplement or complement other observing systems?

Profilers versus: raobs

ACARS

WSR-88D

GOES

POES

Instructional Components

4 manuals / 4 videotapes - FSL

NWSTC note guide

(These two sources address wind profiling radar almost exclusively; they need updating)

Need new material on RASS and GPS/IPW

Use of Web sites for training (modify existing sites?)

Use of 6-min moment data - teletraining

Returned power (zeroth moment)

Radial velocity (first moment)

Spectrum width (second moment)

Make 6-min data available on AWIPS.

Inferring vertical moisture gradient from 0th, 1st, and 2nd moment data

Web site for watching local changes in IPW

Proposed Evaluation

Application oriented evaluation

2. UNIT 2: Lightning -

Proposed Producers: NWS/SR/Scientific Services Division (Dan Smith and Ken Waters)

Proposed SME: Dick Orville (with DFW Office)

(prepared by Don Burgess, Dick Livingston, and Fred Mosher)

Description of Job Duty Competency to be Achieved

Develop an understanding of the causes of lightning and relate that understanding to the internal conditions of thunderstorm development and decay for various meteorological conditions.

Description of Need

As part of the NWS Warnings and QPF decision making processes, forecasters should know how to relate remotely sensed lightning to conceptual models of thunderstorm structures and processes. Forecasters need to understand the strengths and limitations of this new data set.

Specific Job Task Skills and Knowledge

1. Knowledge

Evaluate the strengths and limitations of the lightning data to augment radar and satellite date as related to thunderstorm evolution.

2. Task Skill

Determine the magnitude and extent of (thunderstorm – lightning) hazards to the public, aviation and fire weather.

Instructional Components

1. Storm Electrification Processes (Only basic level information as required by forecasters)

This component will focus on what causes charge separation within thunderstorms that lead to lightning. Topics will include charge separation mechanisms, temperature/ liquid water/ ice relationships to charge separation; discharge processes; positive vs negative flash polarity; strokes vs flashes; current; cloud-to-ground vs intracloud.

2. Lightning Detection Systems

This component will focus on the lightning detection systems. Topics will include theory of operation, direction finding technology, time of arrival technology, Lightning Mapper system; ASOS and other single site sensors, the current National Lightning Detection Network (NLDN; proprietary) and the NLDN detection efficiency, location accuracy, and uniformity of coverage; system status and plans(?).

3. Lightning Climatology

This component will focus on the historic distribution of thunderstorms. Topics will cover thunderstorm day climatologies, the 10 year NLDN climatology, regional climatologies, local climatologies (develop), and studies of lightning deaths and injuries; lightning safety rules.

4. Lightning Applications to Weather Phenomena

This component will relate lightning to specific weather phenomena. Topics will include heavy rain, severe thunderstorms (tornado, hail, microbursts, and MCS), hurricane and tropical storms, winter events, and convective hazards to aircraft.

5. Examples

This component will provide interactive examples for various meteorological situations on how to incorporate into NWS products and services. Case studies would include a severe storm case, a hail case, a heavy rain case, a heavy snow case, and other case studies of interest.

6. References/ Glossary

This component will provide an on line list of references and related reading material. A glossary of terms used should also be provided.

7. Proposed evaluation

Application oriented evaluation

3. PCU 3: ASOS

(Proposed producer - Sam Beckman NWS/TC)

PCU material will be converted from residence course to WEB-based training

4. PCU 4: RAOB and others under NAOS program

(Proposed producer – Greg Mandt NWS/OM)

PCU material will come from NAOS studies

5. PCU 5: Radar - Done

Producer - D. Burgess NWS/OSO/OTB

Organize existing materials from OTB radar course, workshops and CDs.

6. PCU 6: Satellite – GOES Done; POES underway

Producer - T. Mostek NWS/OM

Organize existing materials from COMET satmet course, webpages, and CD modules, and CIRA tutorials.

7. UNIT 7: AWIPS Multi-Source Data Displays

Producer - Brian Motta - Cooperative Institute for Research in the Atmosphere (CIRA)

(prepared by Don Hillger, Kevin Schrab, Brian Motta, and Laurie Hermes)

Description of Job Duty Competency to be Achieved

Access, evaluate, and integrate information from various data sources used in NWS products and services.

Description of Need

As part of the integrated data analysis and forecasting process, forecasters should know how to properly integrate and display in-situ, remote sensing, map, and model data. Forecasters need to understand the strengths and limitations of the various data sets, displays, and procedures necessary to expeditiously and accurately determine the most relevant depictions from all available data.

Specific Job Task Skills and Knowledge

1) Develop a basic proficiency with the AWIPS user interface for each data source.

a) animation

b) image display

c) overlay

d) map databases

2) Create AWIPS procedures (macros) for various data displays

3) Display point/grid data with an image background

4) Know the necessary steps for image combinations necessary to perform multi-data-source analysis

a) image combination tool

b) product maker *

c) volume browser

5) Incorporate image combinations with other data sources.

6) Knowledge of all AWIPS data intervals and spatial resolutions available for all domains (scales). (not covered elsewhere)

7) Knowledge of appropriate color tables for particular data sets.

a) discrete versus continuous data

8) Skill in creating and comparing vertical profiles (RAOB, model, RADAR, profiler)

9) Knowledge of appropriate use of "hot cursor" functionality in analysis of data sets.

10) Skill in using merged data sets with the fade tool.

11) Skill in using the feature tracking tool to compare with various image data sources and algorithm outputs.

12) Skill in using cross-sections from various data sources.

13) Understand the limitations of image combinations (geolocation)

14) Knowledge and skill in interpreting mosaic-ed imagery.

15) Knowledge and skill in understanding the display consequences of AWIPS remapping

Instructional Components

1) Display products

a) AWIPS User's Guide

b) additional considerations (we provide)

2) AWIPS procedure creation

a) AWIPS User's Guide

b) additional considerations of procedure creation (we provide)

3) (web page) Maximizing image combinations and modifying color tables in order to best produce the merged product.

4) (web page) Module will explain the AWIPS versions of the data sets' intervals, spatial resolutions, and domains.

5) (teletraining/www) Learn about the way color tables are used to display data

6) Learn the differences in measurement techniques and which measurements should be compared.

7) Develop cross-sectional analysis skills using appropriate AWIPS data sets.

8) Examine sensor and observation geolocations on scales from greater than synoptic to less than WFO (ie. county scale) for warning/analysis and forecast applications.

9) Understand the time-matching and data compositing processes for observational data sets (ie. satellite, radar, etc.)

Proposed Evaluation

Proficiency Checklist

8. PCU 8: Model Data Assessment -

Producer - LeRoy Spayd

(prepared by Ken Waters, LeRoy Spayd, and Tony Mostek)

Description of Job Competency

Assess the mesoscale and synoptic scale numerical model analysis using integrated datasets to determine timing and accuracy of key features.

Description of Need

As part of the model data assessment, forecasters should know how to evaluate the accuracy of the current model analysis/initialization based on the integrated datasets. To improve the selection of the appropriate model guidance and to adjust this guidance for analysis errors, known biases and systematic errors.

Job Task Skills and Knowledge

1. Use available integrated datasets and products to identify key synoptic and sub-synoptic scale features.

2. Use model overlay display capability to verify previous model forecast and new model analysis using model and integrated datasets.

3. Use available integrated datasets and products to identify key mesoscale features to analyze problem of the day.

4. Use mesoscale model and continuous data assimilation cycles to obtain understanding of the current state of the models with respect to the key mesoscale features and problem of the day.

Instructional Components

These will be developed in conjunction with the NWP PDS.

9. PCU 9: Phenomena-Based Case Studies Demonstrating Forecast Process

Producer: Scott Bachmeier – Cooperative Institute for Meteorological Satellite Studies (CIMSS)

(prepared by Scott Bachmeier, Mike Eilts, Mike Massig, and Karen Winston)

Purpose

Demonstrate the effective use of AWIPS in solving a variety of forecast problems; build a library of short case studies (similar to the CIRA Satellite Interpretation Discussion and the CIMSS GOES Gallery); solicit input from WFO's for case study candidates or topics

Instructional Components

Case studies should be short and concise (2-3 Web pages), phenomenon-based, follow the forecast process and contain the following points:

1. Statement of the Forecast Problem

2. Conceptual models which are applicable

3. Case-specific details

- Explain the Forecast Process

- Discuss the various sensor and algorithm strengths/weaknesses

- Outline specific AWIPS procedures, with links to more detailed instructions if needed

- Show why the integrated approach is helpful

4. Allow the ability to pose questions to Subject Matter Experts (SME's) via threaded discussion groups