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Science and Technology Infusion Plan

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Terry Schuur (OAR/NSSL) Brian Motta (NWS/OCWWS) Bard Zajac (U. No. Co.) 4. Severe Weather ... Increased Lead Times Enables Necessary Actions to Minimize Impact ... – PowerPoint PPT presentation

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Title: Science and Technology Infusion Plan


1
  • Science and Technology Infusion Plan
  • for
  • Severe Weather

Daniel Meléndez
NWS ST Committee September 17, 2002
2
Outline
  • Team Composition
  • Vision / Benefits
  • Goals / Targets
  • Key Information Gaps
  • Key Solutions
  • Outstanding R D Needs
  • Summary

3
Severe WeatherTeam 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.)

4
Severe WeatherVision / 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

5
Severe WeatherGoals/Targets to FY 12
6
Severe Weather Goals/Targets to FY 12
7
Severe WeatherKey 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

8
Severe Weather Key ST Solutions
9
Severe Weather Key ST Solutions
10
Severe Weather Key ST SolutionsCurrent
Programmatic Phase
MDCRS Water Vapor/EDR
SCAN
Dual Pol
ORPG/Finer and FasterVCPs/ORDA/TDWR
Deployment
Observations
OTE
Satellite Remote Sensing
WRF
Ensembles
DTE
DA/Models
RD
Enabling Process
Severe Weather RD
Training PDT
WES
Training
11
Severe WeatherOutstanding RD 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

12
Severe Weather Summary
Vision
  • Tornado Warning Lead Times Beyond Tornadic
    Lifetimes
  • (? 30 min) at 1-km resolution
  • RD Needs
  • Tornadogenesis
  • RD on severe weather
  • Objective verification
  • Cloud-scale models
  • Situational awareness tools and training
  • RD on total lightning data and radar polarimetry
    data
  • Predictability Limits
  • Improved Understanding on Socioeconomic Impact
  • Implement WRF
  • Deploy Advanced Ensemble Techniques
  • Dual Polarization
  • New Satellite Remote Sensing
  • Enhanced Training

Increasing Performance
  • WSR88D Radar Upgrades
  • TDWR integration
  • WES/Training
  • MDCRS

RD
2007
2012
2002
2020
13
Severe WeatherSummary
  • 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

14
Severe Weather
  • BACKGROUND SLIDES

15
(No Transcript)
16
Severe WeatherWhy FAR May Be at High Risk?
  • WSR-88D Lesson New technologies temporarily
    raise POD at the expense of FAR
  • Long-term FAR reduction trails POD increase

17
(No Transcript)
18
U95
Trend
Actual
L95
Descriptive Statistics Constant
-131.1915 Coefficient 0.0708 Rsqr 0.053
T-value for slope 0.53 2-tailed t-test 95 CI
w/ 5 degrees of freedom 2.57
19
U95
Trend
Actual
L95
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
20
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
21
(No Transcript)
22
Vision 2025 Storm Scale Modeling
23
Severe WeatherPrimary Customers/Partners
24
Severe WeatherKey Products/Services
25
Severe WeatherS T Roadmap
  • (Insert Spreadsheet)
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