Yeartoyear variations of shortscale wintertime waveluence in NH polar regions have been discussed by

1
Year-to-year variations of short-scale wintertime
waveluence in NH polar regions have been
discussed by Siskind et al. (GRL-2007)
2
NOGAPS
3
2005-2006 Zonal mean GW-drag in NOGAPS-best
simulations
4
75-80 N GEOS5 and Multi-Instrument Satellite
Limb Viewing T-Observations (TIMED/SABER
Aura/HIRDLS-MLS)
2006-SSW
2005-RW
5
Examples of the broad wave-spectra identification
with S-Transform
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Spectra of HIRDLS (2007-2005, 70o-80oN, Jan
20-31) and GEOS5 Temperature -data performed by
S-transform
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Simulations of GW-rms in T-fields between 70-80 N
with ensemble of waves launched between 8-16 km
(right) with GEOS-5 Jan 2005 and 2006 background
atmosphere (left). Jan 2006 HIRDLS short-wave
T-rms (bottom plot).
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GWP and Data Assimilation (DA) similarities and
differences

• Both procedures gt to shift model simulations
  towards reliable observations to produce
  well-established climate signatures.
• Both overall modify momentum and heat
  tendencies. GWP makes it directly at every model
  grid and time step, while DA modifies variables
  incrementally.
• Both procedures establish non-local response of
  models to local adjustment of tendencies through
  the mass-wind balances.
• Stochastic GW-rms of wind and T can in principle
  represent uncertainties of forecast (error
  covariance in DA).

• Current GWP are formulated in vertical column
  physics framework, while DA employs horizontal
  correlations to spread analysis increments.
• GWPs are mainly solicited in the adjustment of
  momentum sources, while operational DA systems
  provide mainly the wind adjustment through
  calculated temperature analysis increments
• Foundation of DA is error metrics of data and
  forecast uncertainties Current GWPs are
  relatively deterministic although uncertainties
  of GW sources are large and waves are stochastic.
  in nature.

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On DA language, Generalized Inverse related to
effects of GWs and possible cost functions
10
NOGAPS sensitivity studies suggest GW control
mechanisms during SW events to reproduce high
elevation of the stratopause
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Jan WACCM (Base GWPD) simulations and HRDI/UARS
UKMO (93 94) wind data
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Possible inversion (balanced bias propagator)
schemes for ZMF with global Temperature-data

• Scheme 1 /extratropical balance, HSEq-scheme /
  Temperature OmF gt geopotential increment,
  restoring dU-increment and dAx-guess
  /parameterization dependent/. Spectral iterative
  solutions of zonal mean vorticity-divergence
  equations with updated GW momentum deposition
  without explicit vertical layer coupling.
• Scheme 2 /HSEq XiEq-scheme/ adds vertical layer
  coupling through explicit adjustment of
  meridional streamfunction (Xi) and
  time-dependent U-T iterations with inluence of
  meridional advection terms (layer coupling gt
  elliptical equation for Xi, iterations gt time
  integrations of U and T equations with observed
  composition).

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U-balances in WACCM simulations (Base GWPD)
/fV Ax, leading MLT terms are forced/
SF5
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WACCM twins HSEq, HSEqXIEq wind inversions
through mass-wind balances
Setup 2 WACCM runs
Results Compare 1 3 colums
Sensitivity V-bar to momentum forcing terms
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Temperature structures produced by GEOS5 and by
simple KF mapping with HIRDLS T data (2006-01-20,
top and 20006-01-27, bottom, at Z40km, 20 km)
GEOS5
KF-HIRDLS
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2005 (strong vortex) and 2006 (major warming)
HIRDLS short-scale T-oscillations in polar NH
latitudes /70N-80N, Jan/
2005
2006