The Satellite

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Surface Pressures from Space
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The Satellite PBL Model calculation of surface
pressure

• The microwave scatterometers, radiometers, SARs
  and altimeters have now provided nearly three
  decades of inferred surface winds over the
  oceans. These can all be converted to excellent
  surface pressure fields.

• Often these products are revolutionary,
  changing the way we view the world.

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1980 2005 Using surface roughness as a lower
boundary condition on the PBL, considerable
information about the atmosphere and the PBL has
been inferred.

• The symbiotic relation between surface
  backscatter data and the PBL model has been
  beneficial to both.
• The PBL model has established superior surface
  truth winds and pressures for the satellite
  model functions.
• Satellite data have shown that the nonlinear PBL
  solution with OLE is observed most of the time.

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The PBL Model (surface winds to pressures
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State of The analytic solution for a PBL
fV K Uzz - pz /? 0 fU - K Vzz pz
/ ? 0 The solution, U (f, K,?p ) was found by
Ekman in 1904.
Unfortunately, this was almost never observed.
fV K Uzz - pz/? 0 fU - K
Vzz pz/? A(v2w2) Solution, U (f, K,?p )
found in 1970. OLE are part of solution for 80
of observed conditions (near-neutral to
convective).
Unfortunately, this scale was difficult to
observe.
The complete nonlinear solution for OLE exists,
including 8th order instability solution,
variable roughness, stratification and
baroclinicity, 1996. Being integrated into MM5,
NCEP (2005)
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Hazards of taking measurements in the Rolls

Hodograph from center zone
Hodograph from convergent zone
1-km
The OLE winds
Station A
3
2 - 5 km
U
2
The Mean Wind
Z/?
1
Station B
V
Mean Flow Hodograph
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• The dynamics of the typical PBL revealed in
  remote sensing data indicate that K-theory in the
  PBL models is physically incorrect. This will
  mean revision of all GCM PBL models as resolution
  increases.
• Brown, R.A., 2001 On Satellite
  Scatterometer Model functions, J. Geophys. Res.,
  Atmospheres, 105, n23, 29,195-29,205 Patoux,
  J. and R.A. Brown, 2001 Spectral Analysis of
  QuikSCAT Surface Winds and Two-Dimensional
  Turbulence, J. Geophys. Res., 106, D20,
  23,995-24,005 Patoux, J. and R.A. Brown,
  2002 A Gradient Wind Correction for Surface
  Pressure Fields Retrieved from Scatterometer
  Winds, Jn. Applied Meteor., Vol. 41, No. 2, pp
  133-143 R.A. Brown P. Mourad, 1990 A
  Model for K-Theory in a Multi-Scale Large Eddy
  Environment, AMS Preprint of Symposium on
  Turbulence and Diffusion, Riso, Denmark. On the
  Use of Exchange Coefficients and Organized Large
  Scale Eddies in Modeling Turbulent Flows. Bound.
  Layer Meteor., 20, 111-116, 1981.

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SLP from Surface Winds

• UW PBL similarity model
• joins two layers
• The nonlinear Ekman
• solution

U10
to the log layer solution.
Use inverse PBL model to estimate
from satellite . Use vector math to get
non-divergent field UGN. Use Least-Square
optimization to find best fit SLP to swaths
G
(UG) ?P(U10)
There is extensive verification from ERS-1/2,
NSCAT, QuikSCAT
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The solution for the PBL boundary layer (Brown,
1974, Brown and Liu, 1982), may be written U/VG
ei ? - e ze-iz ieizsin ? U2
where VG is the geostrophic wind vector, the
angle between U10 and VG is ?u, ?HT, (Ta
Ts,)PBL and the effect of the organized large
eddies (OLE) in the PBL is represented by
U2(u, Ta Ts, ?HT)
This may be written
U/VG ??(u), U2(u), u, zo(u), VT(?HT),
?(Ta Ts), ? Or U/VG ?u, VT(?HT), ?(Ta
Ts), ?, k, a ? u, ?HT, Ta Ts,
for ? 0.15, k 0.4 and a 1
In particular,
VG ? (u,?HT, Ta Ts) ? ?n(?P, ?, f) Hence ?P
?n u(k, a, ?), ?HT, Ta Ts, ?, f ? fn(?o)
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The nonlinear solution applied to satellite
surface winds yields accurate surface pressure
fields. These data show
The agreement between satellite and ECMWF
pressure fields indicate that both the
Scatterometer winds and the nonlinear PBL model
(VG/U10) are accurate within ? 2 m/s.
A 3-month, zonally averaged offset angle
ltVG, U10gt of 19 suggests that the mean marine
PBL state is near neutral (the angle predicted by
the nonlinear PBL model).
Swath deviation angle observations can be used
to infer thermal wind and stratification.
Higher winds are obtained from pressure
gradients and used as surface truth (rather than
from GCM or buoy winds).
VG (pressure gradients) rather than U10 could
be used to initialize GCMs
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• The nonlinear PBL solution applied to satellite
  surface winds provides sufficient accuracy to
  determine surface pressure fields from satellite
  data alone.
• Patoux, J. and R.A. Brown, 2002 A Scheme
  for Improving Scatterometer Surface Wind Fields,
  J. Geophys. Res., 106, No. 20, pg 23,985-23,994

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Dashed ECMWF
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Surface Pressures
QuikScat analysis
ECMWF analysis
J. Patoux R. A. Brown
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a
b
QuikSCAT 10 Jan 2005 0709 UTC
OPC Sfc Analysis and IR Satellite Image 10 Jan
2005 0600 UTC
c
d
UWPBL 10 Jan 2005 0600 UTC
GFS Sfc Analysis 10 Jan 2005 0600 UTC
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GFS 08 Jul 2005
OPC 08 Jul 2005
1003
996
996
b
a
UWPBL 08 Jul 2005
QuikSCAT 08 Jul 2005
1001
992
c
d
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To get smooth synoptic wind fields from a
scatterometer
(JPL)
Raw scatterometer winds
UW Pressure field smoothed
JPL Project Local GCM nudge smoothed Dirth
(with ECMWF fields)
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• We can uniquely offer a continuous record of
  QuikScat-derived surface pressure fields These
  pressure fields extend through the Tropics - a
  region that is poorly characterized by numerical
  weather forecast models - and contain fine
  details that are absent from numerical model
  analyses
• Patoux, J., R.C. Foster and R.A. Brown,
  2003 Global Pressures from Scatterometer
  Winds, Jn. Applied Meteor. 42, 813-826

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• Surface pressures as surface truth yield high
  wind predictions. This suggests that the global
  climatology surface wind record is too low by 10
  20.
• Brown, R.A., Lixin Zeng, 2001 Comparison
  of Planetary Boundary Layer Model Winds with
  Dropwindsonde Observations in Tropical Cyclones,
  J. Applied Meteor., 40, 10, 1718-1723 Foster
  Brown, 1994, On Large-scale PBL Modelling
  Surface Wind and Latent Heat Flux Comparisons,
  The Global Atmos.-Ocean System, 2, 199-219.

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• There is evidence from these data that the
  secondary flow characteristics of the nonlinear
  PBL solution (Rolls or Coherent Structures) are
  present more often than not over the worlds
  oceans. This contributes to basic understanding
  of PBL modelling and air-sea fluxes.
• Brown, R.A., 2002 Scaling Effects in Remote
  Sensing Applications and the Case of Organized
  Large Eddies, Canadian Jn. Remote Sensing, 28,
  340-345 Levy G., 2001, Boundary Layer Roll
  Statistics from SAR. Geophysical Research
  Letters. 28(10),1993-1995.

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Programs and Fields available onhttp//pbl.atmos.
washington.edu Questions to rabrown, neal
or jerome_at_atmos.washington.edu

• Direct PBL model PBL_LIB. (75 -00) An
  analytic solution for the PBL flow with rolls,
  U(z) f( ?P, ?To , ?Ta , ?)
• The Inverse PBL model Takes U10 field and
  calculates surface pressure field ?P (U10
  , ?To , ?Ta , ?) (1986 - 2000)
• Pressure fields directly from the PMF ?P (?o)
  along all swaths (exclude 0 - ? 5 lat.?) (2001)
  (dropped in favor of I-PBL)
• Global swath pressure fields for QuikScat swaths
  (with global I-PBL model) (2004)
• Surface stress fields from PBL_LIB corrected for
  stratification effects along all swaths (2005)

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Marine Weather from Satellites and PBL models

• Surface Winds Pressure Fields from Space
• The ability to extract surface pressure maps from
  satellite scatterometer data has been described
  in a series of papers since the 80s. The
  technique has been recently improved for the
  purpose of providing near real-time surface
  pressures for NCEP forecasters. The fields have
  proved more valuable to the forecasters than the
  raw QuikScat winds while providing more detail in
  the pressure fields than ever before.

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Status of organized large eddies (OLE)
verification

• Airplane campaigns in cold air outbreaks (1976
  - ).
• Ground based Lidar detects OLE (1996 -) Lidar
  from Aircraft PBL flights (1999 -).
• Satellite derived surface pressures (1997) using
  nonlinear PBL model are accurate.
• Satellite SAR data of ocean surface shows
  evidence of ubiquitous OLE (1978 1986 1997-).

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• Surface Pressure fields
• The basic PBL model uses the geostrophic wind
  (aka pressure gradient) as a boundary condition
  to calculate the wind profile and surface stress.
  It was evident that the same conceptual model
  could use surface stress as input and calculate
  the UG or SP. Gad Levy took this task for his
  thesis work (1981) and the result was the
  "Inverse Model" which was used to calculate
  surface pressure fields from satellite data (plus
  a surface pressure magnitude) (Ocean Surface
  Pressure Fields from Satellite Sensed Winds,
  (R.A. Brown and G. Levy), Mon. Wea. Rev., 114, pp
  2197-2206, 1986). This has proven to be an
  extremely valuable contribution of scatterometer
  data and has been revised and perfected by Lixin
  Zeng and Jerome Patoux (Estimating Central
  Pressures of Oceanic Mid-latitude Cyclones, (R.A.
  Brown and Lixin Zeng) J. Applied Meteor., 33, 9,
  1088-1095, 1994 A Scheme for Improving
  Scatterometer Surface Wind Fields, J. Geophys.
  Res., Patoux, J. and R.A. Brown, 106, No. 20, pg
  23,985-23,994, 2002 Global Surface Pressures
  from Satellite Scatterometers, Patoux and Brown,
  in press, Jn. Applied Meteor. )
• The Surface Pressure (SP) fields were used to
  correct the MF for high winds by assuming that
  the pressure measurements on the buoys were still
  OK in high winds and using SP plus the PBL model
  to calculate U10. They were routinely 10 higher
  than the GCM products. Since the inverse pressure
  fields agreed well with GCM values (in the
  Northern Hemisphere where there were sufficient
  surface measurements for the GCM), I proposed
  that the scatterometer could be viewed as a
  pressure measurement instrument, and we developed
  a MF that successfully related SP directly to the
  scatterometer backscatter measurement.
• On the other hand, the remote sensing data has
  given proof that the nonlinear equilibrium PBL
  solution is the correct one. The first
  verification came when Mike Freilich ran a UG
  field simultaneous with the U10 MF
  parameterization analysis. He noted that they
  were both good robust model functions and that
  the UG was turned 19 deg from U10 direction. The
  model predicts a turning of 18 deg at neutral
  stratification. The data suggests that the model
  is correct in the mean, and that the average
  oceanic PBL is nearly neutrally stratified.
• However, the most convincing satellite data for
  rolls comes from the synthetic aperture Radar
  (SAR) data. These show that a wind MF applied to
  backscatter data on 100-m resolution reveal long
  (100s-km) lines of higher roughness/winds,
  roughly parallel to the wind and separated by the
  usual roll wavelength of 1-3-km. We obtained a
  NASA grant to analyze the statistics of these
  observations and Levy found roll signatures over
  50 of the time in the North Pacific. Since I
  expected the downdraft regions to be sufficient
  to see only occasionally, the large frequency of
  observations indicates that the rolls are almost
  always there.

R. A. Brown 2005 EGU