lidar meeting 2007 snowmass

23
R. A. Brown 2007 Snowmass Lidar

Upload: noam

Post on 07-Jan-2016

39 views

Category:

Documents


2 download

DESCRIPTION

Lidar Meeting 2007 Snowmass. The Scatterometer Past, Present and Future?. R. A. Brown 2007 Snowmass Lidar. Past. R. A. Brown 2003 U. Concepci Ó n. ASCAT on MetOp 2007 - 2019. Present. Surface Pressures from Space. Present. R. A. Brown 2007. Present. Dashed: ECMWF. - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: Lidar Meeting 2007 Snowmass

R. A. Brown 2007 Snowmass Lidar

Page 2: Lidar Meeting 2007 Snowmass

R. A. Brown 2003 U. ConcepciÓn

Page 3: Lidar Meeting 2007 Snowmass

ASCAT on MetOp 2007 - 2019

Page 4: Lidar Meeting 2007 Snowmass

R. A. Brown 2007

Page 5: Lidar Meeting 2007 Snowmass

Dashed:ECMWF J. Patoux & R. A. Brown

Page 6: Lidar Meeting 2007 Snowmass

Raw scatterometer windsUWPressure field smoothed

JPL Project Local GCM nudge smoothed = Dirth (with ECMWF fields)

(JPL)

R. A. Brown 2007

Page 7: Lidar Meeting 2007 Snowmass

NCEP real time forecasts use PBL model

Even the best NCEP analysis, used as the first guess in the real time forecasts, is improved with the QuikScat surface pressure analyses. (Yes, this includes hurricanes.)

R. A. Brown 2007 Snowmass Lidar

Page 8: Lidar Meeting 2007 Snowmass

OPC Sfc Analysis and IR Satellite Image 10 Jan 2005 0600 UTC UWPBL 10 Jan 2005 0600 UTC

a b

c d

QuikSCAT 10 Jan 2005 0709 UTC

991

982

996

996

999

984

This example is from 10 January 2005 0600UTC. Numerical guidance from the 0600UTC GFS model run (a) indicated a 999 hPa low at 43N, 162E. QuikScat winds (b) suggested strong lows --- OPC analysis uses 996. UW-PBL analysis indicates 982.

GFS Sfc Analysis 10 Jan 2005 0600 UTC

Page 9: Lidar Meeting 2007 Snowmass

Observations from Senate hearings, 7-11-07

* NPOESS was/is a mess. Senators’ comments: “A hydra headed monster” “Can’t decide anything” “Is the administration serious about getting this information?”

• A senator or congressman can speak more freely than a government scientist

• A Univ. Professor can speak more freely….• A parrot can……• Bill Porenza was right! (Q.E.D. above.)• Mike Freilich now wears a NASA hat• The ‘Follow-on’ awaits new money + 5-years. (+ A new

administration.)• Thus Quikscat must last until 2013, the earliest date for a

NASA follow-on

R. A. Brown 2007 Snowmass Lidar

Page 10: Lidar Meeting 2007 Snowmass

R. A. Brown 2007

RIP (USA)

Page 11: Lidar Meeting 2007 Snowmass

SeaSat 1978 ERS -1 1991-95

ERS-2 1995-2001 NSCAT 1996-97

QuickScat 1999 -

SeaWinds1 1998-1998

SeaWinds2 2002 - 2002 ASCAT 2007-

R. A. Brown 2003 U. ConcepciÓn

ERS-2 1995-2001; 2003 -

Page 12: Lidar Meeting 2007 Snowmass

Someone who makes money off Oil?

• I first suggested this conspiracy as fiction in a novel, then as a 'far-out' idea to the working groups. Since then so many things have fit, and so much positive feedback has arisen, supporting a conspiracy campaign that I'm beginning to believe it is true.

• One of the most believable aspects involves the hypothesized decision by the energy moguls in 1978 to fight global warming science and all alternate energy solutions. They were immediately successful in 1980 when Reagan removed the solar panels on the white house installed by Carter and subsequently eliminated all subsidies to alternate energies.

• This alone set the US back 20-years.Two more decades of control and trillions of dollars more to the conspirators.

• With the advent of the current president, and the right-wing conservative majorities in the house, senate, executive and judicial branches, the conspirators clearly accomplished their goal.

• See: PBL.atmos.washington.edu; new papers

R. A. Brown 2007 Snowmass Lidar

Page 13: Lidar Meeting 2007 Snowmass

Definition of Follow-on: It happens at some unspecified time after the original dies

R. A. Brown 2007 Snowmass Lidar

Page 14: Lidar Meeting 2007 Snowmass

A rotating, multi-freequency, SAR-scatterometer-radiometer plus lidar

Page 15: Lidar Meeting 2007 Snowmass

Or

Page 16: Lidar Meeting 2007 Snowmass

On the Positive side

• Big plans: a dual frequency scatterometer, high resolution, high and low winds, rotating coverage; possibly integrated SAR

• Support from a new administration in 2008 (Hence Freilich’s 2013)

• Don Quixote believes a lidar is coming.• I’m retiring (to 1%, for lidar).• You are still members of the dominant

species on this hunk of dirt! (Panzaic Plea)

R. A. Brown 2007 Snowmass Lidar

Page 17: Lidar Meeting 2007 Snowmass

Station B

2 - 5 km

Taking measurements in the Rolls

with Tower, Sondes & Lidar from space

Station A

1-km

RABrown 9/2001

Lidar

Page 18: Lidar Meeting 2007 Snowmass

Programs and Fields available onhttp://pbl.atmos.washington.edu

Questions to rabrown, Ralph or jerome @atmos.washington.edu

• Direct PBL model: PBL_LIB. (’75 -’05) 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 - 2005)

• 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) (2005)

• Surface stress fields from PBL_LIB corrected for stratification effects along all swaths (2006)

R. A. Brown 2007

Page 19: Lidar Meeting 2007 Snowmass

U

V

OLE

Hodographfrom center zone

Station B

Z/

Lateral Motion of OLE

1-2 m/s near neutral

0 convective

R.A. Brown 2000

Page 20: Lidar Meeting 2007 Snowmass

U

V

Hodograph

from convergent zone

Station A

1 km

OLE

1- 3 km

Counter-rotating

Helical Roll

Vortices

R.A. Brown 2000

Page 21: Lidar Meeting 2007 Snowmass

ECMWF analysis

QuikScat analysis

Surface Pressures

J. Patoux & R. A. Brown

Page 22: Lidar Meeting 2007 Snowmass

R. A. Brown 2007 Snowmass Lidar

They like to study global warming, strong hurricanes, tornados, new events

Page 23: Lidar Meeting 2007 Snowmass

SLP from Surface Winds

• UW PBL similarity model joins two layers:

• Use “inverse” PBL model to estimate from satellite . Get non-divergent field UG

N.• Use Least-Square optimization to find best fit

SLP to swaths• There is extensive verification from ERS-1/2,

NSCAT, QuikSCAT

10 10( , , , , , )G

f P T SST q CSu∗

= ∇ K

( )10

10logN

o

uU

k z u∗

=

10NU

P∇ (UGN )

UG

R. A. Brown 2006 AMS