UW-CIMSS MURI Management & Progress Report Wayne Feltz (Program Manager)
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Transcript of UW-CIMSS MURI Management & Progress Report Wayne Feltz (Program Manager)
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
UW-CIMSS MURI ManagementUW-CIMSS MURI Management & Progress Report
Wayne Feltz(Program Manager)
• MURI Research Update
• UW & UH Co-Investigator Interactions• Research Timeline for UW–MURI• Overall Status• Progress Reports: The UW & other Co-Is
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
Hyperspectral WBS & Personnel AllocationHyperspectral WBS & Personnel Allocation
MURI
Clouds & Cloud Modeling
RetrievalAlgorithms
Ocean Emiss.Modeling
ForwardModeling
PBL Winds
NumericalModeling
Land SurfaceModeling
Stability &Turbulence
SurfaceCharacterization
Dust &Visibility
Allen Huang (PI)Wayne F. Feltz (PM)
Jun LiWang Xuanji
Dave TobinLeslie Moy, Jim Davies
Steve AckermanR. Dengel, D. Stettner
Chris Velden, B. HuangWayne FeltzKris Bedka
Paul van Delst Jason Otkin
Ping Yang(UT A&M)
G. Jedlovec(UAH)
Paul Lucey(UH-HIGH)
Robert KnutesonSuzanne SeemanEva Borbas
UW-CIMSS Support Staff: Hal Woolf, Elizabeth Weise, Erik Olson, Dave Santek, Kevin Baggett, Tom Rink, Tom Whittaker
Students: Ryan Aschbrenner Benjamin Johnson seeking others
1st Order
2nd Order
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
MURI HighlightsMURI Highlights
• 1st Phase (Years 1-3) Reviewed and Optional 2nd Phase (Year 4-5) granted funding
• Basic research will be honed for hyperspectral meteorological applications during Years 4-5
• Leveraging with other hyperspectral funding (GOES-R Risk Reduction) to support general Navy, NOAA, and NASA hyperspectral science
• More than 20 conference papers and 6 journal papers published with MURI related efforts
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
Tasks for UW-MURITasks for UW-MURI
1 Mathematical Quantification of Useful Hyperspectral
Information 2 Radiative Transfer Modeling
• Clear and Cloudy Sky Emission/Absorption• Atmospheric Particulate Emission/Absorption• Surface Emission/Absorption• Adjoint & Linear Tangent
3 Mathematical Retrieval Algorithm Development• Atmospheric Parameters• Suspended Particulate Detection and Quantification• Sea Surface Temperature• Surface Material Identification
4 Product Research• Ocean and Land Surface Characterization• Lower Tropospheric Temperature, Moisture and Winds• Surface Material Products• Aerosols• Derived (Second Order) Products• Visibility
New Additions (in Red)
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
Progress Reports: The UW & UH Co-IsProgress Reports: The UW & UH Co-Is
• NWP in support of Simulating Hyperspectral data• Information Content• “Clear Sky” RTE Development• Hyperspectral Clear/Cloudy Retrievals
• Simulated• Measurements
• Derived Winds & Atmospheric Parameters; SST
UW–CIMSS:
UH–HIGP:• AHI field experiments & hyperspectral modeling• Surface Emissivity
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
New ScienceApplications
Science Use of GIFTS Data:Science Use of GIFTS Data:Where do we stand today?Where do we stand today?
SimulatingGIFTS data
Fast Modeldevelopment
InformationContent
First Retrievals(T, q, wind)
Convection &Stability
DataAssimilation
Studies
EstimatingVisibility
CloudProperties
Dust & AerosolRetrievals
0 50 95
6.26.4
EstimatingTurbulence
UW-MURI
Y0 Y1 Y2 Y3-Y5Y3-Y5 Y4-Y5
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
Forward Modeling WorkForward Modeling Work“ LBLRTM based PLOD fast model”
LBLRTM runs:• HITRAN ‘96 + JPL extended
spectral line parameters
• CKD v2.4 H2O continuum
Spectral Characteristics:• ~586-2347 cm-1• ~0.8724 cm MOPD• Kaisser Bessel #6 apodization
Fast Model:• 32 profiles from
NOAA database• 6 view angles• AIRS 100 layers
• Fixed, H2O, and O3
• AIRS PLOD predictors
Run time:• ~0.8 Sec on a 1 GHz CPU
Temp. OzoneSurface
Type
Water Vapor
Dust/Aerosol Temp.CO
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
Cloudmicrophysics
(water sphere /Ice crystal habit,
ref. ind., size dist.)
Atmosphericprofiles for training
(P,T,H2O,O3)
Surfaceparameters
(emissivity: UW-CIMSS,UH-HIGP, UCSB)
Aerosol parametersfor important species *
(Ref. ind., size dist.:I. Sokolik -> ω0, : g Mie)
Solar spectrum at GIFTS
*instrument bands
( )Irradiance
Single scattering parameter computation
( : water sphereMie, < 100 ice μ : m T- ,matrix > 100 ice μ : /m GOMMie)
Single scatteringparameters
(Qe, Qa, )g
& LBLRTM correlatedk-distribution
computation for GIFTS bands
Coefficients for computing TOA to layer
clear sky optical depths
( , , 2 , 3)as FN of P T H O O
DISORT radiative transfer for cloud
particles only
Cloud layer opticalproperties
(albedo, )transmittance
Clear sky optical depthparameter
computation
Pressure layer ( )optical depth PLOD
( TOA to layer clear )sky optical depths
Cloud layer albedoandtransmittance
parameterization
Coefficients for computing cloudalbedo
and transmittance
( ,as FN of ODeff. ,size zenithθ)
Case to simulate
Atmospheric profile( , , 2 , 3)P T H O O
Cloud configuration( , ,Z OD eff. , / )size ice liquid
Aerosol configuration( , , ) *Z AOD species
GIFTS fast RT model
: Clear sky: 6 / (Speed s full spectrum cf 4 )m with LBLRTM
: 0.1 Accuracy approx K cf LBLRTM
:Cloudy sky: 7 / (Speed s full spectrumcf 7 )m with LBLDIS
: 0.5 Accuracy approx K cf LBLDIS
Radiance spectrum
Tangent linear
Adjoint operator
Gas component optical depth
* Not implemented &In collaboration with Texas A M . In collaboration with ISokolik In collaboration with U Hawaii
MURI Hyperspectral Cloud/Aerosol/Haze Radiative Transfer Modeling
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
Completed a high-resolution MM5 simulation of an intense upper-tropospheric jet streak that occurred over the north-central Pacific during the 2003 THORPEX field study. This simulated atmosphere was passed through the GIFTS forward model to obtain top of atmosphere radiances.
GIFTS Spectrum: Clear Sky
Installed and successfully performed several multiple-processor Weather Research and Forecasting (WRF) simulations. Ongoing work involves comparing WRF and MM5 model output to determine the ability of the WRF model to simulate the fine-scale water structure during a convective initiation event.
MURI Hyperspectral Modeling Activities
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
• Clear sounding retrieval –Regression and–Regularization (physical retrieval)
• Cloudy Sounding retrieval–Hole hunting for single FOV–Cloud clearing using imager/sounder (ABI/HES, MODIS/AIRS are be used for testing the algorithm)–Cloudy regression
Hyperspectral Clear/Cloudy Sounding Retrieval
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
1. Cube study
2. MODIS/AIRS demonstration(IHOP, June 12, 2002)
AIRS Single FOV RTV vs. ECMWF Analysis : TPW 09-02-2003, granule 192, daytime
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
Simulated GIFTS winds (left) versus GOES current oper winds (right)
GIFTS - IHOP simulation 1830z 12 June 02 GOES-8 winds 1655z 12 June 02
Hyperspectral Winds Retrieval
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
Hyperspectral NAST-I/S-HIS RetrievalsPTOST and ATOST Campaigns
Scanning HIS Relative Humidity and Cloud Phase Lidar cloud boundaries
MODIS Airborne Simulator
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
UW-CIMSS Satellite Convective Storm UW-CIMSS Satellite Convective Storm NowcastingNowcasting
GOES-12 1 km Visible and 4 km Imager: 4 May 2003
Convective Cloud Mask
Nowcast Time
Multi-spectral Techniques
Cloud-top Cooling Estimates Using Satellite-Derived
Winds Identify pre-CI signatures in GOES Visible and IR data using: 1) convective cloud masking
2) multi-spectral band differencing techniques 3) cloud-top temperature trend assessments
Develop CI nowcasts (0-1 hour) by accumulating pre-CI satellite indicators attributed to the first occurrence of a ≥ 30 dBZ radar echo
Incorporate Satellite-Based Convective Cloud Analyses for Nowcasting Convective
Initiation (CI)
CI Nowcast Algorithm
Red: CI Nowcasts Grey: Cirrus Anvil
Doppler Radar for Validation
1 Hour Later
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
Land Surface Temperature from AIRSLand Surface Temperature from AIRS
DOE Southern Great Plains ARM site temperature contrast.
B.T. (K)
UWOnline/OfflineTs (K)
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
UW-Navy Hardware Investments*
UW HSSP Parallel Computing System
Objective: In support of a government/industry Broad Scope of
Hyperspectral Activities
SystemGeneral
Specification $
Computing Cluster
72 AMD Opteron CPU (64 bits)
16 SGI Itanium CPU (64 bits)
$360K
Server & Storage
48 Terabytes $100K
Grand Total$460K
*ONR DURIP Award
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
STATUSSTATUS
• The UW & UH MURI is a healthy research collaboration which includes two other external investigators
• We are through our proposed Year 3 and have been granted funding for two optional years of MURI work.
• We are progressing on many fronts, from RTE and toward atmospheric/surface applications development
• We are using the simulated GIFTS and operational AIRS/NAST-I/S-HIS data and and our rapidly implementing the new knowledge gained through this grant towards future hyperspectral applications
• More investigator details to follow
4th Annual Workshop on Hyperspectal Meteorological Science of UW MURI, GIFTS,and GOES-R27-28 April 2004, Madison, Wisconsin
Today1:452:05 pm Clear Forward Models & linear operators L. Moy2:052:25 pm Cloudy Fast Forward Model J. Davies2:252:45 pm Simulated Profiles Retrievals: Clear & Cloudy J. Li4:505:30 pm IMAPP AIRS Sounding Demonstration Baggett/Weisz
Tomorrow8:30-8:50 am Multiple Spectral and Hyperspectral Wind Demonstration Velden/Huang8:50-9:10 am Demonstration of 3D Water Vapor Tracked Winds B. Huang9:10-9:30 am Training database for Hyperspectral …Applications S. Seemann9:30-9:50 am Hyperspectral cloud boundary retrieval R. Holz
10:10-10:30 am Hyperspectral Land Surface Modeling & Retrieval R. Knuteson10:30-10:50 am Infrared Sea Surface Emissivity (IRSSE) Model P. Van Delst10:50-11:10 am Hyperspectral Applications for Aviation W. Feltz11:10-11:30 am Automatic GOES Nowcasting of Convective Initiation K. Bedka11:30-12:00 pm Hyperspectral Signature Survey: Fire Plumes, .. Clouds D. Tobin1:00-1:45 pm UW Hyperspectral Sounder Simulator & Processor A. Huang2:30-3:20 pm Hyperspectral Visualization Demonstration Rink/Tobin
SSEC MURI PresentationsSSEC MURI Presentations