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 winds o 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 Scatterometers ERS (ESA); Quikscat (USA) ( ); 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  U 10 (u*) land 8  U 10 (u*) ocean 5  PBL U(z) (similarity) 7  Scatterometer Model Function u* (  o ) 4 U 10 (  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 (”) , 5/00, 7/01 RAB Practical Aspects of Wind Measurements (Surface ‘Truth’ Limits)

Height meters The Surface Layer = the log layer = the law of the wall V U 10 /V G  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 U 10 Surface Layer Ekman Layer with OLE Thermal Wind Nonlinear OLE Advection,centrifugal terms Non steady-state U 10 (u*) effects Stratification Variable Surface Roughness V G (u*) effects R.A. Brown PORSEC 2000 Gradient Wind 1-3 km 0 – 100 m

 The surface layer relation, hence U 10 {u*(  o ) }works well 0 < z < 100 meters There is almost no surface truth --- buoy or GCM surface winds with U 10 > 25 m/s The U 10 model function can be extrapolated to about 35 m/s There are indications that  o responds to the sea state for U 10 >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 U 10. Requires Stratification Information CONCLUSIONS RABrown, ’99; ‘01

Dark Ages 11 in USA I Star Wars 11 A Brief History of Scatterometers SeaSat Built --- with Scat, SAR, SMMR, Alt SeaSat Launch --- Lasts 99 days NSCAT conceived and built Dark Ages: launch $ to gulf & carribean wars, refurbish battleships, 200 ship fleet, Star Wars ERS-1 Launch (turned off) NSCAT launched on ADEOS mos. ERS-2 Launch Quikscat Launch R. A. Brown 1/2001 SeaWinds on ADEOS - II ESA A-SCAT

Programs and Fields available on Questions to rabrown, neal or Direct PBL model: PBL_LIB. (’75 -’01) An analytic solution for the PBL flow with rolls, U(z) = f(  P,  T o,  T a, ) The Inverse PBL model: Takes U 10 field and calculates surface pressure field (V G )  P (U 10,  T o,  T a, ) ( ) 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