AHW Ensemble Data Assimilation and Forecasting System

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AHW Ensemble Data Assimilation and Forecasting
System

• Ryan D. Torn, Univ. Albany, SUNY
• Chris Davis, Wei Wang, Steven Cavallo, Chris
  Snyder, James Done, NCAR/MMM

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Overview

• Since participation in HFIP HRH test, we have
  been using cycling EnKF approach to create
  initial conditions for AHW model
• Wanted initial conditions that
• Have a good estimate of environment
• Have a decent estimate of TC structure
• Does not lead to significant initialization
  problem
• Since then, we have upgraded the system based on
  observed flaws in both model and initial
  conditions

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Assimilation System

• WRF ARW (v3.3), 36 km horizontal resolution over
  basin, 96 ensemble members, DART assimilation
  system.
• Observations assimilated each six hours from
  surface and marine stations (Psfc), rawinsondes,
  dropsondes gt 100 km from TC, ACARS, sat. winds,
  TC position, MSLP, GPS RO

• Initialized system this year on 29 July,
  continuous cycling using GFS LBC
• No vortex bogusing or repositioning, all updates
  to TC due to observations

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AHW Model Setup

• WSM6 Microphysics (includes graupel)
• Tiedtke cumulus parameterization (includes
  shallow convection)
• YSU PBL, NOAH land surface model
• Updated Ck/Cd formulation in Davis et al. 2010
• Pollard 1D Column ocean model
• SSTs from NCEP 1/12 degree analysis
• HYCOM Mixed-layer depths

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Data Assimilation Nesting Strategy

• Each time NHC declares an INVEST area, generate a
  12 km resolution two-way interactive nest that
  moves with the system until NHC stops tracking it
  (1600 km x 1600 km nest)
• Observations are assimilated on the nested domain
  each 6 h
• Nest movement determined by extrapolating NHC
  positions over the previous 6 h
• Works better than vortex-following nests, which
  have largest covariances associated with
  differences in land position

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Nest Example
Earl
Fiona
INVEST
Gaston
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Cycling Nest Experiments

• No Nest (HRH test setup)
• Fixed 12 km two-way nest (1000 km x 1000 km)
  generated for each TC in domain at each analysis
  time. Discarded at end of model advance (2009
  real-time setup)
• Moving 12 km two-way nest (1000 km x 1000 km)
  generated when TD is declared. Nest is cycled
  along with the coarse domain. Motion based on
  NHC advisory position over previous 6 hr (2010
  real-time setup)

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TC Vitals Error
RMS Error
Bias
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Deterministic Forecast

• For each TC, choose one analysis ensemble member
  whose TC properties are closest to ensemble mean
  (see below)
• Remove other 12 km nests, add additional 4 km
  nest to 12 km for that storm (800 km on a side),
  runs without cumulus parameterization.

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2011 Retrospective Forecasts
Track
Maximum Wind Speed
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Ensemble Forecasts

• Currently running 15 member ensemble for NHC
  highest priority TC
• Take first 15 members of the analysis ensemble
  since all are equally likely
• All members use same lower BC, lateral BC, and
  model physics (will be relaxed in the future)

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0000 UTC 2 Aug. Ensemble
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Lessons to Date

• Ensemble can produce fairly large variance in
  intensity without significant variance in
  large-scale environment parameters
• Biases due to deficiencies in model physics (in
  particular aerosol and ozone treatment) lead to
  many situations where truth is outside ensemble