# Presentation: 047254

## 
Science and Technology Infusion Plan
for
Severe Weather

**Science and Technology Infusion Plan**
**for**
**Severe Weather**

*Daniel Meléndez*

- NWS S&T Committee
- September 17, 2002

## Outline

**Team Composition**
**Vision / Benefits**
**Goals / Targets**
**Key Information Gaps **
**Key Solutions**
**Outstanding R & D Needs**
**Summary**

## Severe WeatherTeam Composition

**Daniel Meléndez (NWS/OST)**
**Richard Okulski (NWS/OS)**
**John Weaver (NESDIS)**
**Don Burgess (OAR/NSSL)**
**Robert Saffle (OST)**
**Steve Weiss (SPC)**
**Ron Przybylinski (WFO/STL)**

**Dan Smith (SRH)**
**Liz Quoetone (WDTB)**
**John Ferree (WDTB)**
**David Sharp (WFO/MLB)**
**Terry Schuur (OAR/NSSL)**
**Brian Motta (NWS/OCWWS)**
**Bard Zajac (U. No. Co.)**

## Severe WeatherVision / Benefits

_**2025 Vision**_
***Tornado Warning Lead Times Beyond Tornadic Lifetimes (************ 30 min) at 1-km resolution***

**Save Lives**
**Increased Lead Times Enables Necessary Actions to Minimize Impact of Severe Local Storms**
**Millions in Savings to Transportation & Similar Industries**

## Severe WeatherGoals/Targets to FY 12

| Existing GPRA Performance Measure | FY01 Skill | FY07 Goal | FY12 Target  |
| --- | --- | --- | --- |
| Tornado Warning Lead Time (min) | 10  | 14 | 18  |
| Tornado Warning POD | 68% | 74% | 78% |
| Tornado Warning FAR | 72% | 68% | 64% |

| Other Performance Measure | FY01 Skill | FY07 Target | FY12 Target |
| --- | --- | --- | --- |
| Severe Thunderstorm Warning Lead Time (min) | 16 | 18 | 22  |
| Severe Thunderstorm Warning POD | 80% | 83% | 88% |
| Severe Thunderstorm Warning FAR | 44% | 40% | 35% |

## Severe Weather Goals/Targets to FY 12

| Existing GPRA (G) or Strategic Plan (S) Performance Measure | Current Skill | FY07            Goal     Target |  | FY12 Target  |
| --- | --- | --- | --- | --- |
| Tornado Warning Lead Time (min)  (G) | 10  | 14 | 16 | 18  |
| Tornado Warning POD (G) | 68% | 74% | 76% | 78% |
| Tornado Warning FAR (G) | 72% | 68% | 68% | 64% |
| Severe Thunderstorm Warning Lead Time (min) (S) | 16 | 18 | 19 | 22  |
| Severe Thunderstorm Warning POD (S) | 80% | 83% | 85% | 88% |
| Severe Thunderstorm Warning FAR (S) | 44% | 40% | 38% | 35% |

## Severe WeatherKey Information Gaps

**Higher Resolution and Density** **Storm-Scale Data****	**
**Improved Specification and Forecasting of Pre-Storm Environment**
**Improved Specification and Forecasting of Boundaries**
**Improved Understanding and Specification of Severe Weather Signatures**
**Improved Verification **

## Severe Weather Key S&T Solutions

| Gap | Solution | Impact |
| --- | --- | --- |
| Higher Resolution and Density Storm-Scale Data
 | Finer/Faster Volume Coverage Patterns (ORPG)
Angular resolution (0.5o radials, ORDA)
1/4km Reflectivity (ORDA)
WSR-88D + TDWR Data Integration
Local-Scale Model (3km WRF)
MDCRS Data Assimilation
Rapid Algorithm Update (ORPG) | Up to 40% Improvement in Detection
Several Minutes Improvement in Lead time |
| Improved Specification and Forecasting of Pre-Storm Environment
 | WSR-88D + TDWR Data Integration
Finer/Faster Volume Coverage Patterns 
Range/Velocity Dealising (ORDA)
More and Improved Data Assimilation (e.g., MDCRS, 88D Radial Speeds...)
Modeling (GFS, Hi-Resolution WRF)
Training
Satellite Remote Sensing | Improved Forecast of Long-lived Severe Weather Systems
Improved POD
 |

**Severe Weather**** ***Key S&T Solutions*

## Severe Weather Key S&T Solutions

| Gap | Solution | Impact |
| --- | --- | --- |
| Improved Understanding and Specification of Severe Weather Signatures
 | Dual Polarization
Enhanced SCAN (WDSS)
Total Lightning Data
Improved Verification
Continued R&D
Local-Scale Modeling
“Climatology” of Storms
Training | Improved FAR
Improved POD
Improved Lead Time
Improved Adaptive Observational Strategies |
| Improved Specification and Forecasting of Boundaries | WSR-88D + TDWR Data Integration 
Finer/Faster Volume Coverage Patterns 
Higher Resolution Satellite Remote Sensing | Better Sampling of Boundaries Improves POD
Storm Initiation |
| Improved Verification  | More and Better Trained Spotters
Enhanced WFO Effort
Improved Spotter-WFO Comm
Polygon Verification  | More Accurate Performance Data
Improved FAR |

**Severe Weather**** ***Key S&T Solutions*

## Severe Weather Key S&T SolutionsCurrent Programmatic Phase

** *****Dual Pol**

**WRF**

** ****Ensembles**

- Deployment

- OTE

- DTE

- R&D

**Observations**

**DA/Models**

**Satellite Remote Sensing**

** ****SCAN+**

***ORPG/Finer and FasterVCPs/ORDA/TDWR+**

**Enabling Process**

***Training PDT**

**Training**

**WES**

***Severe Weather R&D**

**MDCRS Water Vapor/EDR**

## Severe WeatherOutstanding R&D Needs

**Improved Understanding of Tornado Formation**
**Improved Understanding of Severe Weather Meteorology**
**Objective Verification**
**Improved Cloud-Scale Models**
**Improved Situational Awareness Tools and Training**
**Improved Understanding of Total Lightning Data in Severe Weather Forecasting**
**Improved Understanding of Radar Polarimetry in Severe Weather Forecasting**
**Improved Understanding of Predictability Limits**
**Improved Understanding of Socioeconomic Impact**

## Severe Weather Summary

**Severe Weather**** ***Summary*

_**R&D Needs**_
**Tornadogenesis**
**R&D on severe weather**
** ****Objective verification**
**Cloud-scale models**
**Situational awareness tools and training**
**R&D on total lightning data and radar polarimetry data **
**Predictability Limits**
**Improved Understanding on Socioeconomic Impact**

- WSR88D Radar Upgrades
- TDWR integration
- WES/Training
- MDCRS

- Implement WRF
- Deploy Advanced Ensemble Techniques
- Dual Polarization
- New Satellite Remote Sensing
- Enhanced Training

_**Vision**_

**Increasing Performance**

- R&D

**2007**

**2012**

**2020**

**2002**

***Tornado Warning Lead Times Beyond Tornadic Lifetimes ***
***(************ 30 min) at 1-km resolution***

## Severe WeatherSummary

**Severe weather warning and detection FY07 improvements will be driven by observational (radar) increases in resolution and coverage**
**Need continued training and severe weather research as part of threshold progress**
**Improved verification is critical to overall progress**
**FAR is a consequence of verification accuracy so emphasis should be on detection**
**Synoptic forecasting models on track**

## BACKGROUND SLIDES

**Severe Weather**

## Slide 15

## WSR-88D Lesson: New technologies temporarily raise POD at the expense of FAR 
Long-term FAR reduction trails POD increase

**Long-term FAR reduction trails POD increase**

**Severe Weather***Why FAR May Be at High Risk?*

## Slide 17

## Descriptive Statistics:

- Constant = -131.1915
- Coefficient = 0.0708
- Rsqr = 0.053

***U95***

***Trend***

***Actual***

***L95***

- T-value for slope = 0.53
- 2-tailed t-test 95% CI w/ 5 degrees of freedom = 2.57

## Descriptive Statistics:

- Constant = 10.0956
- Coefficient = -0.0047
- Rsqr = 0.127

- T-value for slope = -0.85
- 2-tailed t-test 95% CI w/ 5 degrees of freedom = 2.57

***U95***

***Trend***

***Actual***

***L95***

## Descriptive Statistics:

- Constant = -31.8362
- Coefficient = .0163
- Rsqr = 0.623

- T-value for slope = 2.87
- 2-tailed t-test 95% CI w/ 5 degrees of freedom = 2.57

***U95***

***Trend***

***Actual***

***L95***

## Slide 21

## Vision 2025 – Storm Scale Modeling

**Severe Weather***Primary Customers/Partners*

## Severe WeatherKey Products/Services

## Severe WeatherS & T  Roadmap

**(Insert Spreadsheet)**