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Science and Technology Infusion Plan for Tropical Cyclones. 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. Tropical Cyclones Team Composition.

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Presentation Transcript
slide1
Science and Technology Infusion Plan

for

Tropical Cyclones

Daniel Meléndez

NWS S&T Committee

September 17, 2002

outline
Outline
  • Team Composition
  • Vision / Benefits
  • Goals / Targets
  • Key Information Gaps
  • Key Solutions
  • Outstanding R & D Needs
  • Summary
tropical cyclones team composition
Tropical CyclonesTeam Composition
  • Daniel Meléndez (NWS/OST)
  • Scott Kiser (NWS/OS)
  • Richard Knabb (TPC)
  • Miles Lawrence (TPC)
  • Xiaofan Li (NESDIS)
  • Frank Marks (OAR/HRD)
  • Morris Bender (GFDL)
  • Scott Braun (NASA/GFDL)
  • Gregg Engel (JTWC)
  • Naomi Surgi (NCEP/EMC)
  • Robert Tuleya (NCEP)
  • Frank Wells (WFO/Guam)
  • Hugh Willoughby (OAR/HRD)
tropical cyclones vision benefits
Tropical CyclonesVision / Benefits
  • 2025 Vision
  • 48-hr Track Forecast Error of 85 nm
  • 48-hr Intensity Forecast Error 12 kt
  • Save Lives / Enhanced Public Safety
  • Improved Response Capability of Emergency Managers
  • Mitigate Property Loss
  • Economic Impact Increasingly Complex (coastal development….)
tropical cyclones key information gaps not ranked
Tropical CyclonesKey Information Gaps (not ranked)
  • Improved Forecasting of Rapidly Changing Storms
  • More Accurate Cyclone Track and Intensity Forecast
  • Understanding of Model Guidance Uncertainty
  • More Precise Position of Circulation Center
  • Higher Resolution Storm Wind Data
tropical cyclones key s t solutions current programmatic phase

10

02

05

06

07

08

04

09

11

12

03

Tropical Cyclones Key S&T SolutionsCurrent Programmatic Phase

Targeted Obs*

*Aircraft Upgrades (SFMR, GPS dropsondes…)

Observations

Adaptive Obs

*Airborne Upgrade Radar Wind DA

Deployment

*Advanced DA of Satellite Data

OTE

*Oceanic DA

DA/Models

HWRF 7km

*Hurricane WRF

DTE

Core Init

*GFS Ensembles

R&D

*Advanced Data Assimilation Techniques

*JHT Tech Transfer

Enabling Process

tropical cyclones outstanding r d needs
Tropical CyclonesOutstanding R&D Needs
  • Rapid Intensity Changing Storms
  • Shear Effects on Track and Intensity
  • Statistical “Guidance-on-Guidance” on Model Output
  • Improved Data Assimilation
  • Improved Model Physics (microphysics, air-sea fluxes…)
  • Model Physics Sensitivities
  • Ensemble Techniques
  • Adaptive Observations/Targeting
  • Predictability Limits
tropical cyclones summary
Tropical CyclonesSummary
  • Vision
  • 48-hr Track Forecast Error of 85 nm
  • 48-hr Intensity Forecast Error 12 kt
  • R&D Needs
  • Rapid Intensity Changing Storms
  • Shear Effects on Track & Intensity
  • Statistical “Guidance-on-Guidance
  • Improved Data Assimilation
  • Improved Model Physics
  • Model Physics Sensitivities
  • Ensemble Techniques
  • Adaptive Observations
  • Predictability Limits
  • Implement Hurricane WRF
  • Data Assimilation
  • Deploy Advanced Ensemble Techniques
  • Expand Adaptive Strategies
  • New Satellite Remote Sensing

Increasing Performance

  • Aircraft Instrumentation Upgrades
  • Expand Targeted Observations

Joint Hurricane Testbed

2002

2007

2012

2020

tropical cyclones summary1
Tropical CyclonesSummary
  • Improved track and intensity performances depend mostly on advances in numerical prediction/data assimilation
  • Intensity error performance is virtually “flat” – awaits significantly improved storm core specification and numerical forecasting R & D
tropical cyclones
Tropical Cyclones

BACKGROUND SLIDES

tropical cyclones primary customers partners
Tropical CyclonesPrimary Customers/Partners
  • Public
  • Media
  • Federal, State, Local Government
  • DOD
  • 53 WRS
  • State EMA’s
  • WMO RA-IV
  • Mariners
  • Private Sector
tropical cyclones s t roadmap
Tropical CyclonesS & T Roadmap
  • (Insert Spreadsheet)
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