Some Background
• I’m in the wind business ---– My thesis dealt with the mathematical
solution for PBL winds
– I’ve written two texts on flow equations; in the PBL and entire atmosphere.
– At one time I was PI or co-PI on 5 EOS grants: LAWS, Seawinds, SSMI (Wetnet) and 2 interdisciplinaries
– We have programs to use winds in weather & climate analyses
– I want winds from ANY source
Winds are not --- have never been --- on
NASA/s menu. Why?• I surveyed EOS investigators:
“It is assumed that the winds will be provided by GCMs”
• Scatterometer data showed this is not true:– Missing storms, details
– PBL Winds unphysical, often too low
• Mainly a resolution problem, but also because GCMs cannot handle Turbulence in many cases (PBL, Conv. Towers, tropopause, jets….) or sub-grid organized flow (OLE).
Better GCM Progs
Better Storms Definition
Higher Winds (heat fluxes)
Little Science things like: Proof of ubiquity of Rolls (OLE)
Applications
RABrown 2001
Better Climate Models
A Winds Motivation• High Marine Surface Winds
do not appear in: – Buoy data– Climate records– General Circulation Models– Satellite sensor algorithms
• High Marine Surface Winds do appear in:– Ocean Meteorology Ship reports– Dedicated Airplane PBL Flights– A PBL model that includes OLE
• Higher winds imply higher heat fluxes in climatology; revised ocean mixed layer models.
R.A. Brown, 1997, 2000; ‘01
There exists an opportunity for satellite data
• Measurements from sondes, ships & buoys incur large errors due to turbulence & OLE• There are few measurements of winds in the PBL in situ• There are no satellite determined winds IN the PBL
o The fluxes (air-surface) require boundary layer windso Climate Analyses have been made on extremely poor climatology data
R. A. Brown 1/2001
Sources of Surface Wind Fields for Climate Studies
• From Surface Measurements– Ships & Buoys– Radiosondes
• From Models– GCM (with K-theory PBLs)– UW Similarity Model (with OLE)
R.A. Brown, 1997, 2001
Satellite Wind Sensors
•ScatterometersERS (ESA); Quikscat (USA) (2001 - );SeaWinds on Adeos (USA,Japan) (2002); AScat (ESA) (2004)
•SARs ERS (ESA); Radarsat (Canada);
Envisat (ESA)**********
• Passive Radiometers Windsat (USA) (2002)
•Lidars ESA (2008)
Scatterometer wind fields here
Pressure field
SAR Wind field
A conversation in 1977: Businger to Brown: “You’re a fluiddynamacist, we’d like the solution to the relation between the surface wind and the wave generation”
Brown to Businger: “OK”
(I know it’s impossible, but it’s a living)
Bottom line: (20 years later) There is no proven theory for wind generation of waves. However, in the best tradition of Atmospheric Science --- there is a curve fit
Epilogue: Satellite Data Prove PBL Winds Theory
Appraisal of Basics: Theory for
Scatterometer, SAR, radiometer
Data: cm-scale, average density of capillaries and short gravity waves in a footprint. 50km 25km 7km 100m (SAR)
Theory: State: 1-10, poor to excellent
Wind generation of water waves 1 % energy into short/long waves 2 Wave-wave interaction 3 Surface layer wind 8 PBL wind (without OLE) 4
(with OLE) 8
R.A. Brown 2001
Appraisal of Basics:
Microwave Data from Scatterometry, SAR, Radiometers
Data: cm-scale, average density of capillaries and short gravity waves in a footprint. 50km 25km 7km 100m (SAR)And surface ‘truth’ wind.
Parameterizations State: 1-10, poor to excellent
U10 (u*) land 8 U10 (u*) ocean 5 PBL U(z) (similarity) 7
Scatterometer Model Function
u* (o) 4 U10 (o) 8 P (o) 7
R.A. Brown 2001
Ship winds: Sparse and inaccurate (except Met. Ships).Buoy winds: Sparse; a point. Tilt; variable height - miss high winds and low wind directions.GCM winds: Bad physics in PBL Models; Too low high winds, too high low winds. Resolution coarse (getting better).Satellite winds: Lack good calibration data. Resolution (”).
11-99, 5/00, 7/01 RAB
Practical Aspects of Wind Measurements (Surface ‘Truth’ Limits)
Height meters
200
100
The Surface Layer = the log layer
= the law of the wall
V
U10/VG
0.7
Practical Aspects of a Geostrophic Wind Model
Function (Pressures)Surface ‘Truth’ Limits
• Radiosondes (winds) Sparse; NG in PBL
• Buoy and ship pressures: Accurate in low and high wind regimes; sparse• GCM (winds & pressures): Poor winds. Good pressure verification, compatible
11-99, 7/01 RAB
Surface Stress, u*
Ocean surface
Geostrophic
Flow
U10Surface Layer
Ekman Layer with OLE
Thermal Wind
Nonlinear OLE
Advection,centrifugal termsNon steady-state
U10(u*) effects
Stratification
Variable Surface Roughness
VG(u*) effects
R.A. Brown PORSEC 2000
Gradient Wind
1-3 km
0 – 100 m
The surface layer relation, hence U10 {u*(o ) }works well 0 < z < 100 meters
• There is almost no surface truth --- buoy or GCM surface winds with U10 > 25 m/s
• The U10 model function can be extrapolated to about 35 m/s
• There are indications that o responds to the sea state for U10>40 m/s. (H-pol > 60 m/s?)
• There is a Model function yielding winds possibly to 60 m/s (2000)
The PBL model yields U(z), 0 < Z < 1 km (gradient)
• Requires U10.
• Requires Stratification Information
CONCLUSIONS
RABrown, ’99; ‘01
Dark Ages 11 in USAI Star Wars 11
A Brief History of Scatterometers1970
1980
1990
2000
2010
SeaSat Built --- with Scat, SAR, SMMR, AltSeaSat Launch --- Lasts 99 days
NSCAT conceived and built
Dark Ages: launch $ to gulf & carribean wars, refurbish battleships, 200 ship fleet, Star WarsERS-1 Launch (turned off)
NSCAT launched on ADEOS --- 9 mos.ERS-2 LaunchQuikscat Launch
R. A. Brown 1/2001
SeaWinds on ADEOS - II
ESA A-SCAT
Programs and Fields available onhttp://pbl.atmos.washington.edu
Questions to rabrown, neal or [email protected]
• Direct PBL model: PBL_LIB. (’75 -’01) 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 (VG) P (U10 , To , Ta , ) (1986 - 2001)
• Pressure fields directly from the PMF: P (o) along all swaths (exclude 0 - 5° lat) (2001; in progress)
• Surface stress fields from PBL_LIB corrected for stratification effects along all swaths (2001; in progress) R.A. Brown 2000, ‘01