Phase Resolved X-Band Wave Inversions in Multi-modal Seas

Slides:



Advertisements
Similar presentations
Tracking an Atlantic Wave Storm with Jason-2 Altimeter Sérgio Muacho - IPMA.
Advertisements

7. Radar Meteorology References Battan (1973) Atlas (1989)
Lecture 12 Content LIDAR 4/15/2017 GEM 3366.
Active Remote Sensing Systems March 2, 2005 Radar Nomenclature Radar Logic Synthetic Aperture Radar Radar Relief Displacement Return Exams Next Class:
Lynn K. Shay 1, J. Martinez-Pedraja 1, M. Powell 2, B. Haus 1, and J. Brewster 1 1 Division of Meteorology and Physical Oceanography, RSMAS 2 Hurricane.
Radar Remote Sensing RADAR => RA dio D etection A nd R anging.
Remote sensing in meteorology
Sonar Chapter 9. History Sound Navigation And Ranging (SONAR) developed during WW II –Sound pulses emitted reflected off metal objects with characteristic.
Oil Spill Detection and Tracking Technologies Aircraft and Autonomous Aircraft Detection Methods HF Radar Tracking Methods Autonomous Surface Vessel Tracking.
Model Simulation Studies of Hurricane Isabel in Chesapeake Bay Jian Shen Virginia Institute of Marine Sciences College of William and Mary.
Active Remote Sensing Systems March 2, 2005
Proposed Capabilities ASIS – Pulse-Coherent Sonars (RaDyO/SO GasEx) – Bubble-Size Distribution (Duck) Ship-Based – WaMoS II (SO GasEx) – Scanning LIDAR.
Where does background noise in the ocean come from? ORE 654 Guest Lecture Fred Duennebier October 21, 2011.
Ship-Based Observations of Ocean Waves Using Multiple X-Band Radars Christa McKelvey, Shanka Wijesundara, Andrew O’Brien, Graeme Smith, Joel T. Johnson,
ElectroScience Lab IGARSS 2011 Vancouver Jul 26th, 2011 Chun-Sik Chae and Joel T. Johnson ElectroScience Laboratory Department of Electrical and Computer.
ATMS 373C.C. Hennon, UNC Asheville Observing the Tropics.
Chapter 7 Light.
GUIDELINES FOR (SHIP BORNE) AUTO-MONITORING OF COASTAL AND OCEAN COLOR. Wernand, M.R., Royal Netherlands Institute for Sea Research (Royal NIOZ), PO Box.
WMO/ITU Seminar Use of Radio Spectrum for Meteorology Earth Exploration-Satellite Service (EESS)- Active Spaceborne Remote Sensing and Operations Bryan.
Quantitative Estimates of Biomass and Forest Structure in Coastal Temperate Rainforests Derived from Multi-return Airborne Lidar Marc G. Kramer 1 and Michael.
A Simple Model for Marine Radar Images of the Ocean Surface David R. Lyzenga David T. Walker SRI International, Inc. Ann Arbor, MI SOMaR-3 Workshop July.
Surface Current Mapping with High Frequency RADAR.
GISMO Simulation Study Objective Key instrument and geometry parameters Surface and base DEMs Ice mass reflection and refraction modeling Algorithms used.
L. K. Shay 1, J. Martinez-Pedraja 1, B. K. Haus 1, Brad Parks 1, Peter Vertes 1, Lew Gramer 2, and J. Brewster 1 1 Division of Meteorology and Physical.
Application of a Portable Doppler Wind Lidar for Wildfire Plume Measurements Allison Charland and Craig Clements Department of Meteorology and Climate.
SWOT Near Nadir Ka-band SAR Interferometry: SWOT Airborne Experiment Xiaoqing Wu, JPL, California Institute of Technology, USA Scott Hensley, JPL, California.
Introduction Acknowledgements Funding for the CSU-MAPS is provided through a joint NSF-MRI R 2 grant (AGS# , ) awarded to San Francisco and.
SCCOOS Web Site Training Surface Currents and Wave Conditions.
DATA QUALITY CONTROL Julie Thomas Coastal Data Information Program (CDIP) Scripps Institution of Oceanography CI Design Workshop October 2007 La.
Wind Profile Measurements with VisibleWind: Further Developments Tom Wilkerson, Alan Marchant, Bill Bradford, Tom Apedaile, Cordell Wright & Eve Day Space.
Synthetic Aperture Radar Specular or Bragg Scatter? OC3522Summer 2001 OC Remote Sensing of the Atmosphere and Ocean - Summer 2001.
Ship-Based Measurements of Cloud Microphysics and PBL Properties in Precipitating Trade Cumuli During RICO Institutions: University of Miami; University.
How well can we model air pollution meteorology in the Houston area? Wayne Angevine CIRES / NOAA ESRL Mark Zagar Met. Office of Slovenia Jerome Brioude,
Application of Radial and Elliptical Surface Current Measurements to Better Resolve Coastal Features  Robert K. Forney, Hugh Roarty, Scott Glenn 
NATO UNCLASSIFIED Tuesday, 18 October 2014 Access to Amphibious Watch and Forecast Report FIRST PAGE.
Airborne Studies of Atmospheric Dynamics
Airborne Measurement of Horizontal Wind and Moisture Transport Using Co-deployed Doppler and DIAL lidars Mike Hardesty, Alan Brewer, Brandi McCarty, Christoph.
REAL-TIME ESTIMATION OF OCEAN WAVE FIELDS FROM MARINE RADAR DATA David R. Lyzenga, Okey G. Nwogu, and Robert F. Beck University of Michigan, Ann Arbor,
Higher Physics – Unit Waves. a a λ λ crest trough Wave Theory All waves transmit energy. The energy of a wave depends on its amplitude. a = amplitude.
Ship-Image map derived from a Terra MODIS image from October 20, 2003 (01:35 UT acquisition time), showing the course of the ARISE cruise (red line) between.
Azimuthal Variation of Hurricane Waves (1) Problem: How do ocean waves in the vicinity of a hurricane vary in height, wavelength, propagation direction.
Extrapolated fresh water and extrapolated 32.5 PSU T are shown in red and blue (extrapolation done using all available instruments for period) Green and.
Observations to Operations: Why validation is important? Julie Thomas Scripps Institution of Oceanography Hydrographic Review Panel Los Angeles, CA April.
Estimation of wave spectra with SWIM on CFOSAT – illustration on a real case C. Tison (1), C. Manent (2), T. Amiot (1), V. Enjolras (3), D. Hauser (2),
LIGHT. LIGHT HAS WAVE PROPERTIES. THE TYPE OF LIGHT IS CHARACTERIZED BY WAVELENGTH – THE DISTANCE FROM ONE PEAK TO THE NEXT. LIGHT ALSO HAS PARTICLE PROPERTIES.
Challenges in PBL and Innovative Sensing Techniques Walter Bach Army Research Office
ISTP 2003 September15-19, Airborne Measurement of Horizontal Wind and Moisture Transport Using Co-deployed Doppler and DIAL lidars Mike Hardesty,
Active Remote Sensing for Elevation Mapping
UNIT 2 – MODULE 7: Microwave & LIDAR Sensing. MICROWAVES & RADIO WAVES In this section, it is important to understand that radio waves and microwaves.
SCM x330 Ocean Discovery through Technology Area F GE.
Detection of Wind Speed and Sea Ice Motion in the Marginal Ice Zone from RADARSAT-2 Images Alexander S. Komarov 1, Vladimir Zabeline 2, and David G. Barber.
1 Experimental Study of the Microwave Radar Doppler Spectrum Backscattered from the Sea Surface at Small Incidence Angles Titchenko Yu. A., Karaev V. Yu.,
Integrating LiDAR Intensity and Elevation Data for Terrain Characterization in a Forested Area Cheng Wang and Nancy F. Glenn IEEE GEOSCIENCE AND REMOTE.
(2) Norut, Tromsø, Norway Improved measurement of sea surface velocity from synthetic aperture radar Morten Wergeland Hansen.
Specialised in FMCW radar level, tide and wave monitoring
Question 1 – 5 marks Law of Reflection:
Institutions: University of Miami; University of Colorado; NOAA ETL
COASTAL DATA INFORMATION PROGRAM present
The Langmuir Cell Dri dataset Taken March/April 2017
Class 12 Assessment of Classification Accuracy
Reflection in Plane Mirrors
Cross-Polarized SAR: A New Potential Technique for Hurricanes
Ocean Winds.
OPERATIONAL OCEANOGRAPHY
Natalie Laudier Operational Oceanography 13Feb2009
Michael E Wall, James B Clarage, George N Phillips  Structure 
Unit 2 Particles and Waves Interference
Remote sensing in meteorology
V. Corcione, G. Grieco, M. Portabella, F. Nunziata, M. Migliaccio
Presentation transcript:

Phase Resolved X-Band Wave Inversions in Multi-modal Seas SOMaR-3 July 14-17, 2015 Eric Terrill, Tony de Paolo, Tom Cook, Sean Celona, Heidi Batchelor Scripps Institution of Oceanography – UCSD La Jolla, CA

Environment and Ship Motion Forecasting (ESMF) September 9-17, 2013 R/V Melville track shown to the right SIO assets: Rutter/WAMOS II X-Band System 5-point bow laser array Miniature wave buoys (GPS) Datawell 0.7m Waveriders Airborne scanning LIDAR (MASS)

Environment and Ship Motion Forecasting (ESMF) September 14, 2013 Location: south of Santa Rosa Island Winds: early 12 m/s wind spike from the WNW, then light and variable, then a sharp increase to 14 m/s WNW Waves: bi-modal, decreasing 13 seconds 270 degrees, rising south swell 18-20 seconds degrees, combined significant wave from 2 to 2.5 meters

Wind 11.6 m/s from 292 degrees LIDAR flight path is going upwind X-Band processing box is also oriented upwind

LIDAR data on top, shows wind waves and south swell X-Band wave inversion does not show the south swell since it is imaging along the crests, rather than imaging perpendicular to the crests 2-D correlation R = 0.60

The lack of low frequency (south swell) components is evident in the wave number spectra derived from the LIDAR (black) and X-Band (red).

Same day, a little later X-Band processing box placed downwind, but more oriented into the south swell

Results are better, X-Band inversion is picking up the south swell to a greater extent Correlation R = 0.66 Still room for improvment

Wavenumber spectrum compares better, but X-Band still doesn’t pick up enough south swell energy.

SoCal 2013 November 8-22, 2013 Fixed location near San Clemente Island R/V Melville R/P FLIP SIO assets: Rutter/WAMOS II X-Band Systems Miniature wave buoys (GPS) Moored Datawell 0.9m Waverider Airborne scanning LIDAR (MASS) ADCPs And many more instruments unrelated to this presentation…….

November 14, 2013 1600UTC Bi-modal seas, SW swell, NW wind waves, overall Hs=1.18m R/V Melville radar scan, LIDAR flight path, and wave inversion processing area shown

R/V Melville LIDAR X-Band comparison R=0.78 X-Band does a better job of detecting both wave systems due to position of processing area

Inversion still does not get all of the low frequency south swell energy

R/P FLIP Range resolution = 3m

R = 0.75

Case study of R/P FLIP X-Band wave inversions - November 14, 2013 1700UTC Multi-modal seas present an interesting challenge in recreating sea surface elevation maps from X-Band backscatter Wave inversion accuracy has a large dependence on look angle, or where the processing area lies LIDAR comparisons from over 65 aircraft flights can be as high as R=0.85, or can be very uncorrelated Other factors in success include Wind speed Significant wave height (Hs) LIDAR data is higher resolution and contains much higher wavenumber content X-Band wave inversion is band limited due to lack of SNR at very low, and very high wavenumbers We will attempt to analyze wave inversion quality over multiple processing areas at different azimuths

Processing areas are all 256x256 pixels at angles of: 180 210 240 270 300 325 Wave inversions and 2-D directional spectra are computed in each processing area

Processing Area at 180 degrees azimuth

Processing Area at 210 degrees azimuth

Processing Area at 240 degrees azimuth

Processing Area at 270 degrees azimuth

Processing Area at 300 degrees azimuth

Processing Area at 325 degrees azimuth

Analysis of 2-D Wavenumber Spectrum 6 sectors, 30 degrees wide Compute relative, normalized, power in each sector, using each X-Band processing area/azimuth angle

Normalized power by look angle X-axis is processing box angle Y-axis is normalized power in each of the following sectors 165-195 (dark blue) 195-225 (green) 225-255 (red) 255-285 (black) 285-315 (cyan) 315-345 (yellow)

Preliminary conclusions There are three wave modes sensed South swell from 210 Southwest swell from 255 Wind waves from 295 Some of the processing areas/angles see all three modes, the best being 180 degrees As we look more and more into the wind, the swells tend to diminish, one-by-one In this case, the best look angle to sense all modes is into the south swell

Ongoing and Future Work Continue working on our huge database of X-band radar images HiRes 2010 New River Inlet 2012 (my talk Thursday) Mouth of the Columbia River 2013 (my talk Thursday) ESMF 2013 SoCal 2013 Western Scotland/North Atlantic 2014 Potential collaboration with interested parties in the areas of Waves Currents Bathymetry Kelvin Hughes SharpEye Coherent Radar now on site at SIO!