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Numerical Prediction of Inland Tropical Cyclone (TC) Impacts Gary Lackmann North Carolina State University With Briana Gordon and Brian Etherton. RAH Barrett Smith. Thank You, NWS! - For providing excellent research topics and ideas - For organizing meeting, being here & participating

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Presentation Transcript
slide1

Numerical Prediction of Inland

Tropical Cyclone (TC) Impacts

Gary Lackmann

North Carolina State University

With Briana Gordon and Brian Etherton

RAH Barrett Smith

slide2

Thank You, NWS!

- For providing excellent research topics and ideas

- For organizing meeting, being here & participating

- For helping realize the benefit of applied research

- For past and future collaborations

slide3

Outline

Part I: TC Initialization (Briana Gordon, yesterday)

Part II: Research Opportunity (the problem)

Part III: Collaboration

hanna 2008
Hanna (2008)

NWS RAH

HPChttp://www.hpc.ncep.noaa.gov/tropical/rain/tcrainfall.html

Acknowledgement to RAH (Barrett Smith, Jonathan Blaes), HPC (David Roth), OU NMQ

Q2RAD http://nmq.ou.edu/

hanna 2008 radar summary
Hanna (2008) Radar summary

Barrett Smith, RAH

hanna 20081
Hanna (2008)

Rain ahead of Hanna: Evaporational cooling, boundary forms

Weak cold-air damming develops, enhanced thermal gradient

Boundary hypothesized to aid isentropic ascent

hanna 2008 example
Hanna (2008) Example

Inland wind prediction – also related to boundary?

Strong surface winds east of boundary (unstable), weaker winds to west (heavier precipitation there)

Verifying severe weather reports and wind analyses based on spotter reports and other available data: Boundary location not coincidental

synoptic preconditioning
Synoptic Preconditioning

- Outer circulation gives rise to boundaries, “preconditioning”

- Interactions with boundaries, synoptic flow: PREs

- Impact timing for approaching TC related to size of storm

Srock and Bosart (2009)

slide9

Objective:

  • Improve numerical prediction of inland TC impacts, including QPF and winds
  • Potential Benefits:
  • - Credible TC wind & precipitation prediction (incl. ensemble)
  • - Resolution of outer-core hazards (e.g., spiral bands)
  • - Improved prediction of TC-synoptic interactions (e.g, boundaries, PREs)
  • - Dynamical model output useful in connection with wind project
slide10

Obstacle:

  • Operational TC initial conditions very poor
    • - Esp. w/ strong TC at initial time, close to landfall
  • Compromises direct dynamical prediction
  • May compromise prediction of secondary features
    • - Synoptic interactions (e.g., PREs)
    • - CAD and thermal boundary formation
  • Useful ensemble prediction precluded
recent example initialization of earl
Recent Example: Initialization of Earl
  • Operational GFS, NAM, RUC:
    • - Strong storm at initial time: model too weak (inner core)
    • - Poor/no representation of spiral bands, outer wind field
    • - Not just a resolution issue

EARL: TPC Best Track: 948 mb

NAM, 9/3/00Z: 990 mb

GFS, 9/3/00Z: 982 mb

slide12

Hurricane Earl (September 2010)

15-20 kt

40+ kt

NAM 33-h forecast valid 09Z 3rd (212)

slide13

Prerequisite to credible dynamical prediction of inland TC impacts:

Improved TC initialization (both inner- and outer-core features)

slide14

Part II: Research Opportunity

Towards improved numerical prediction of inland TC impacts

hur nc wrf at renci for tc prediction
HUR-NC: WRF at RENCI for TC Prediction

RENCI computing resources allow high-resolution TC simulations (explicit convection)

27-km outer domain, 9-, 3-km mobile inner grids

Utilize large computational domain, moving nest vortex-tracking feature of WRF-ARW model

Spin up at high resolution offshore, strength, structure closer to observations at landfall

hur nc wrf at renci for tc prediction1
HUR-NC: WRF at RENCI for TC Prediction

“Out-of-box” configuration: Promising (3 years)

Differences relative to NAM and GFS?

Moving-nest tracks TC (3 km): Explict convection

Ocean Mixed Layer: Accounts for wake cooling

Effective “dynamical downscaling”

Main limitation: Initial conditions, esp. with strong storm at initial time (use 0.5° GFS)

wrf ocean mixed layer model oml
WRF Ocean Mixed Layer Model (OML)

Ocean Mixed Layer: simple parameterization

Only mixing, no upwelling

No ocean currents

Initial SST field from GFS

Specify thermocline depth (m)

Specify temperature lapse rate (deg/m)

slide18

Ike: 72-hour Forecast SST (°C)

No OML

OML, 25 m mixed layer

OML, 50 m mixed layer

OML, 75 m mixed layer

slide19

HUR-NC Examples: Earl, initialized 00 UTC 2 September 2010

Domain 1 composite reflectivity (27-km)

slide20

HUR-NC Examples: Earl, initialized 00 UTC 2 September 2010

Domains 1, 2, 3 reflectivity (27/9/3) with D1 SLP

slide21

NCSU-RENCI HUR-NC 33-h Forecast, initialized 00 UTC 2 Sep, Valid 09Z Friday 3 Sep: 3-km domain

Best Track: 955 mb

slide22

NAM (212 grid – 40 km)

HURNC 3-km

> 70kt

33-h wind speed fcsts valid 09Z 3 Sept

hur nc initial conditions
HUR-NC Initial Conditions
  • - Weak initial TC: Acceptable; Strong initial TC: Problematic
  • - For strong initial TC, several options for improvement:
    • - GFDL bogus vortex? Doesn’t help much in test cases
    • - Ensemble Kalman Filter? Computational expense…
      • Ryan Torn (U Albany) generates EnKF ICs, available
    • - HRRR 3-km diabatic initialization? Will try, offshore??
    • - Perform our own vortex cycling or DA at high resolution?
  • BUT FIRST… the “science questions”
science questions initial conditions
Science Questions: Initial Conditions

- What features must be captured in IC for “good forecasts”?

- At what scale must DA be run to capture these features?

- What data are needed to capture these features?

Hypotheses:

- Inland impacts strongly sensitive to initial circulation size

- Inclusion of outer-core features required for prediction of synoptic/mesoscale preconditioning

science questions inland impacts
Science Questions: Inland Impacts
  • Mechanisms of formation for boundaries?
    • - Evaporational cooling, solar sheltering critical
    • - Terrain, cold-air damming?
    • - Role of TC, synoptic features in establishing boundary?
  • Predictability of boundary formation?
    • - Difficult NWP representation of diabatic, cloud-radiation
    • - Representation of PBL, moist processes in NWP?
  • Even with correct boundary: QPF, wind forecasts?
    • - Importance of boundary to total precipitation?
    • - Strength of influence on stability, surface winds?
research plan year 1
Research Plan: Year 1
  • Utilize HUR-NC for retrospective cases (testbed)
  • Evaluate HUR-NC forecasts from different ICs:
    • Re-run challenging events
    • Examine sensitivity to size, outer-core features in ICs
    • Diagnosis of synoptic preconditioning with landfalling TC
  • Identify optimal strategy for TC ICs
research plan year 2
Research Plan: Year 2
  • Identify critical IC features and processes for credible TC and inland impact predictions
  • Address predictability issues for inland boundary formation
  • Work with inland wind team, link dynamical with statistical models & observations
research plan year 3
Research Plan: Year 3

When available, implement improved ICs in ensemble, HUR-NC (Deliverable)

Make ICs available for local modeling (Deliverable)

Retrospective & real-time runs, evaluate forecasts with various ICs to measure impact (Deliverable)

Work with NWS to identify ways to utilize NWP output in forecast process

collaboration
Collaboration

How can the research plan be improved to optimize results, collaborative benefit?

What aspects of project would be most useful to the NWS, and in what form?

How often should research updates be shared?

What training materials, if any, would be helpful?

collaborative opportunities
Collaborative Opportunities
  • What cases should we use in testing?
  • What kinds of dynamical NWP output most valuable?
    • - parameters? - resolution?
    • - lead time? - tools for NWP manipulation?
    • - training materials? - high-resolution example cases?
  • If specialized TC ICs were available, would they be useful in local modeling efforts?
  • Help us learn about current forecast processes, how high-resolution NWP might fit in?
  • How can HMT-SE be leveraged in this effort?
    • - Perhaps high-resolution EnKF analysis?
acknowledgements
Acknowledgements

Jonathan Blaes for doing a fantastic job coordinating meeting, CSTAR input, etc. and RAH (Darin Figurskey) for hosting

NOAA CSTAR program, Sam Contorno, and USWRP, HMT-SE for support (Tim Schneider, Marty Ralph)

Regional CSTAR NWS offices (RAH, GSP, ILM, MHX, CAE, CHS, FFC, RNK, LWX, AKQ)

National Center Partners: Dave Novak (SPC), Mike Brennan (TPC), Steve Weiss (SPC)

NWS Eastern Region Headquarters – Jeff Waldstreicher

Barrett Smith (NWSFO RAH) for Hanna materials

NWSFO RAH Case Summary Archive: http://www4.ncsu.edu/~nwsfo/storage/cases/20080906/