R. A. Brown 2007 Snowmass Lidar. R. A. Brown 2003 U. Concepci Ó n.

Slides:



Advertisements
Similar presentations
SNPP VIIRS green vegetation fraction products and application in numerical weather prediction Zhangyan Jiang 1,2, Weizhong Zheng 3,4, Junchang Ju 1,2,
Advertisements

RADCOR for US Sondes Dr. Bradley Ballish NCEP/NCO/PMB 10 March 2011.
R. A. Brown 2003 U. ConcepciÓn. UW; Patoux, ‘03 R. A. Brown 2003 U. Concepci Ó n.
Ocean-atmosphere Coupling over Midlatitude Ocean Fronts 1. Difference between Wind & Stress 2. Signature above Boundary Layer W. Timothy Liu, Xiaosu Xie,
An Investigation of Cool Season Extratropical Cyclone Forecast Errors Within Operational Models Brian A. Colle 1 and Michael Charles 1,2 1 School of Marine.
Using Scatterometers and Radiometers to Estimate Ocean Wind Speeds and Latent Heat Flux Presented by: Brad Matichak April 30, 2008 Based on an article.
CONVECTION IN TROPICAL CYCLONES John Molinari and David Vollaro University at Albany, SUNY Northeast Tropical Conference Rensselaerville, NY June 2009.
R. A. Brown 2005 AGU. The Satellite + PBL Model calculation of surface pressure The microwave scatterometers, radiometers, SARs and altimeters have now.
The Satellite – PBL Model Connection The microwave scatterometers, radiometers, SARs and altimeters have now provided nearly three decades of inferred.
Using Short Range Ensemble Model Data in National Fire Weather Outlooks Sarah J. Taylor David Bright, Greg Carbin, Phillip Bothwell NWS/Storm Prediction.
Some Preliminary Modeling Results on the Upper-Level Outflow of Hurricane Sandy (2012) JungHoon Shin and Da-Lin Zhang Department of Atmospheric & Oceanic.
The Impact of GPS Radio Occultation Data on the Analysis and Prediction of Tropical Cyclones Bill Kuo UCAR.
The Scatterometer is no longer a competitor for lidar winds R. A. Brown 2007 Lidar Miami.
1 Supercell Thunderstorms Adapted from Materials by Dr. Frank Gallagher III and Dr. Kelvin Droegemeier School of Meteorology University of Oklahoma Part.
Things to look for on the weather maps Visible and IR satellite images (& radar too): Look at cloud movements and locations - do they correlate with what.
G O D D A R D S P A C E F L I G H T C E N T E R Status of the HIWRAP and URAD Conical Scan Radars for Wind Measurements Gerald Heymsfield NASA/Goddard.
ATS/ESS 452: Synoptic Meteorology Friday 09 Jan 2014 Finish Overview Presentation Current Weather Discussion Begin Review Material.
AMSR3/DFS Joint Research and Operational Users Working Group Meeting Tokyo, Japan - 20 April 2009 Requirements for Mid and High Latitude Applications Joe.
Also known as CMIS R. A. Brown 2005 LIDAR Sedona.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Climatology of Hurricane.
Mike Freilich, Seawinds project scientist, was heard to say at my retirement party: Bob keeps us abreast of PBL applications, and what the ‘real’ PBL.
How Small-Scale Turbulence Sets the Amplitude and Structure of Tropical Cyclones Kerry Emanuel PAOC.
Applications of Satellite Derived
Downscaling tropical cyclones from global re-analysis and scenarios: Statistics of multi-decadal variability of TC activity in E Asia Hans von Storch,
Sources of Surface Wind Fields for Climate Studies From Surface Measurements –Ships –Buoys From Models –GCM (with K-theory PBLs) –UW Similarity Model.
R. A. Brown 2003 U. Concepci Ó n Nov 9 ‘96 18Z Gulf of Alaska rab.
Scatterometers at KNMI; Towards Increased Resolution Hans Bonekamp Marcos Portabella Isabel.
1 Results from Winter Storm Reconnaissance Program 2008 Yucheng SongIMSG/EMC/NCEP Zoltan TothEMC/NCEP/NWS Sharan MajumdarUniv. of Miami Mark ShirleyNCO/NCEP/NWS.
1 Results from Winter Storm Reconnaissance Program 2007 Yucheng SongIMSG/EMC/NCEP Zoltan TothEMC/NCEP/NWS Sharan MajumdarUniv. of Miami Mark ShirleyNCO/NCEP/NWS.
R. A. Brown 2003 U. Concepci Ó n. High Winds Study - Motivation UW PBL Model says U 10 > 35 m/s Composite Storms show high winds Buoy limits:
Advanced interpretation and verification of very high resolution models National Meteorological Administration Rodica Dumitrache, Aurelia LUPASCU,
The Advection of Mesoscale Atmospheric Vortices over Reykjavík Hálfdán Ágústsson 123 and Haraldur Ólafsson 234 (1) Institute for Meteorological Research,
The Operational Impact of QuikSCAT Winds at the NOAA Ocean Prediction Center Joe Sienkiewicz – NOAA Ocean Prediction Center Joan Von Ahn – STG/NESDIS ORA.
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.
1. Analysis and Reanalysis Products Adrian M Tompkins, ICTP picture from Nasa.
Some Definitions Turbulence: –Usually includes the terms “random” and “unpredictable” Becomes: –Turns in to; produces as a result Chaos –Usually includes.
LWG, Destin (Fl) 27/1/2009 Observation representativeness error ECMWF model spectra Application to ADM sampling mode and Joint-OSSE.
IOVWST Meeting May 2011 Maryland Calibration and Validation of Multi-Satellite scatterometer winds Topics  Estimation of homogeneous long time.
R. A. Brown 2005 Miami Active Radars. From Neil Tyson’s address/campaign On the Future of NASA Univ. Wash. Jan 20, 2005 “LEO (low earth orbits) are old.
Ocean Vector Wind Workshops and the Role of Cal/Val in Preparing for Future Satellite Wind Sensors Dudley Chelton Cooperative Institute for Oceanographic.
1 An Overview of Recent Actions/Events to Assure a Continued OSVW Capability.
Satellites Storm “Since the early 1960s, virtually all areas of the atmospheric sciences have been revolutionized by the development and application of.
A Subtropical Cyclonic Gyre of Midlatitude Origin John Molinari and David Vollaro.
A Revolution in Earth Science? “It is time for a change”; “restore science to its rightful place” Obama. Global Warming is coming; be it a natural cycle.
9 Feb 2005, Miami 1 An Introduction to SeaWinds Near-Real Time Data Ross Hoffman Mark Leidner Atmospheric and Environmental Research, Inc. Lexington, MA.
Probabilistic Forecasts Based on “Reforecasts” Tom Hamill and Jeff Whitaker and
Satellite Derived Ocean Surface Vector Winds Joe Sienkiewicz, NOAA/NWS Ocean Prediction Center Zorana Jelenak, UCAR/NOAA NESDIS.
NOAA, version 1.0, 7 June 2016 Coordination Group for Meteorological Satellites - CGMS El Nino Rapid Response Presented to CGMS-44, Working Group 2, agenda.
NOAA use of Scatterometry Products Presented to CGMS-43 Working Group 2 session, agenda item 10 Author: Paul Chang.
Advection of lee-side shed vortices over Reykjavík
1. Analysis and Reanalysis Products
Numerical Weather Forecast Model (governing equations)
Satellite Data for CLIMODE
Retrieving Extreme wind speeds using C-band instruments
Meteorological charts
Hurricane Vortex X L Converging Spin up Diverging Spin down Ekman
Boundary Layer Equations
Inspiration for REMOTE SENSING satellites
Jackie May* Mark Bourassa * Current affilitation: QinetiQ-NA
Shuyi S. Chen, Ben Barr, Milan Curcic and Brandon Kerns
Update on the Northwest Regional Modeling System 2017
Cliff Mass University of Washington
Wanda Reeves Department of Marine Environmental Systems
The Wind Hodograph METR 4433: Mesoscale Meteorology Spring 2013 Semester Adapted from Materials by Drs. Kelvin Droegemeier, Frank Gallagher III and Ming.
ESTEC Contract N° 4000/10/NL/AF
OC Remote Sensing of the Atmosphere and Ocean - Summer 2001
14th Cyclone Workshop Brian Ancell The University of Washington
Nowcast guidance of afternoon convection initiation for Taiwan
Shuyi S. Chen1 Wei Zhao1, Ralph Foster2, W. Timothy Liu3
Serendipity the faculty or phenomenon of finding valuable or agreeable things not sought for R. A. Brown 2006.
Presentation transcript:

R. A. Brown 2007 Snowmass Lidar

R. A. Brown 2003 U. Concepci Ó n

ASCAT on MetOp

R. A. Brown 2007

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

Raw scatterometer winds UW Pressure field smoothed JPL Project Local GCM nudge smoothed = Dirth (with ECMWF fields) (JPL) R. A. Brown 2007

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

OPC Sfc Analysis and IR Satellite Image 10 Jan UTCUWPBL 10 Jan UTC ab cd QuikSCAT 10 Jan UTC This example is from 10 January UTC. 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 UTC

Observations from Senate hearings, * 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

R. A. Brown 2007 RIP (USA)

SeaSat 1978 ERS ERS NSCAT QuickScat SeaWinds SeaWinds ASCAT R. A. Brown 2003 U. Concepci Ó n ERS ;

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

Definition of Follow-on: It happens at some unspecified time after the original dies R. A. Brown 2007 Snowmass Lidar

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

Or

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

Station B km Taking measurements in the Rolls with Tower, Sondes & Lidar from space Station A 1-km RABrown 9/2001 Lidar

Programs and Fields available on Questions to rabrown, Ralph or Direct PBL model: PBL_LIB. (’75 -’05) 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  P (U 10,  T o,  T a, ) ( ) 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

U V OLE    Hodograph from center zone Station B Z/  Lateral Motion of OLE 1-2 m/s near neutral 0 convective R.A. Brown 2000

U V    Hodograph from convergent zone Station A 1 km OLE 1- 3 km Counter-rotating Helical Roll Vortices R.A. Brown 2000

ECMWF analysis QuikScat analysis Surface Pressures J. Patoux & R. A. Brown

R. A. Brown 2007 Snowmass Lidar They like to study global warming, strong hurricanes, tornados, new events

SLP from Surface Winds UW PBL similarity model joins two layers: Use “inverse” PBL model to estimate from satellite. Get non-divergent field U G N. Use Least-Square optimization to find best fit SLP to swaths There is extensive verification from ERS-1/2, NSCAT, QuikSCAT (U G N ) UGUG R. A. Brown 2006 AMS