Validation of 12.5 km Resolution Coastal Winds. Barry Vanhoff, COAS/OSU Funding by NASA/NOAA

Similar documents
Validation of 12.5 km and Super-High Resolution (2-5 km)

Reprocessed QuikSCAT (V04) Wind Vectors with Ku-2011 Geophysical Model Function

A. Bentamy 1, S. A. Grodsky2, D.C. Fillon1, J.F. Piollé1 (1) Laboratoire d Océanographie Spatiale / IFREMER (2) Univ. Of Maryland

Development of SAR-Derived Ocean Surface Winds at NOAA/NESDIS

High resolution wind retrieval for SeaWinds

Cross-Calibrating OSCAT Land Sigma-0 to Extend the QuikSCAT Land Sigma-0 Climate Record

SENSOR SYNERGY OF ACTIVE AND PASSIVE MICROWAVE INSTRUMENTS FOR OBSERVATIONS OF MARINE SURFACE WINDS

The Ice Contamination Ratio Method: Accurately Retrieving Ocean Winds Closer to the Sea Ice Edge While Eliminating Ice Winds

WaMoS II Wave Monitoring System

Jackie May* Mark Bourassa. * Current affilitation: QinetiQ-NA

PRELIMINARY STUDY ON DEVELOPING AN L-BAND WIND RETRIEVAL MODEL FUNCTION USING ALOS/PALSAR

SAR images and Polar Lows

Sentinel-1A Ocean Level-2 Products Validation Strategy

HIGH RESOLUTION WIND RETRIEVAL FOR SEAWINDS ON QUIKSCAT. Jeremy B. Luke. A thesis submitted to the faculty of. Brigham Young University

On the Quality of HY-2A Scatterometer Winds

SIMON YUEH, WENQING TANG, ALEXANDER FORE, AND JULIAN CHAUBELL JPL-CALTECH, PASADENA, CA, USA GARY LAGERLOEF EARTH AND SPACE RESEARCH, SEATTLE, WA, US

HIGH RESOLUTION WIND AND WAVE MEASUREMENTS FROM TerraSAR-X IN COMPARISON TO MARINE FORECAST

Characterization of ASCAT measurements based on buoy and QuikSCAT wind vector observations

JET PROPULSION LABORATORY INTEROFFICE MEMORANDUM

The RSS WindSat Version 7 All-Weather Wind Vector Product

EVALUATION OF ENVISAT ASAR WAVE MODE RETRIEVAL ALGORITHMS FOR SEA-STATE FORECASTING AND WAVE CLIMATE ASSESSMENT

Advancements in scatterometer wind processing

Evaluation of the HY-2A Scatterometer wind quality

Satellite information on ocean vector wind from Scatterometer data. Giovanna De Chiara

THE QUALITY OF THE ASCAT 12.5 KM WIND PRODUCT

Coastal Scatterometer Winds Working Group

Dynamic validation of Globwave SAR wave spectra data using an observation-based swell model. R. Husson and F. Collard

TRMM TMI and AMSR-E Microwave SSTs

CHANGE OF THE BRIGHTNESS TEMPERATURE IN THE MICROWAVE REGION DUE TO THE RELATIVE WIND DIRECTION

OAFlux: global, 0.25, daily

Dynamics and variability of surface wind speed and divergence over mid-latitude ocean fronts

OCEAN vector winds from the SeaWinds instrument have

Aquarius Wind Speed Retrievals and Implica6ons for SMAP Ocean Vector Winds

An algorithm for Sea Surface Wind Speed from MWR

Using several data sources for offshore wind resource assessment

Geophysical Model Functions for the Retrieval of Ocean Surface Winds

Scatterometer-Based Assessment of 10-m Wind Analyses from the Operational ECMWF and NCEP Numerical Weather Prediction Models

Swell (wind) fields obtained from Satellite Observation CLS Christian Ortega - Mission blue Journées Annuelles des Hydrocarbures 2013

On the assimilation of SAR wave spectra of S-1A in the wave model MFWAM

Accuracy of 10 m winds from satellites and NWP products near land-sea boundaries

Combining wind and rain in spaceborne scatterometer observations: modeling the splash effects in the sea surface backscattering coefficient

Intraseasonal Variability in Sea Level Height in the Bay of Bengal: Remote vs. local wind forcing & Comparison with the NE Pacific Warm Pool

Review of Equivalent Neutral Winds and Stress

THE SEAWINDS scatterometer was flown twice, once on

Monitoring Conditions Offshore with Satellites

Singularity analysis: A poweful technique for scatterometer wind data processing

High Resolution Sea Surface Roughness and Wind Speed with Space Lidar (CALIPSO)

Offshore wind resource mapping in Europe from satellites

Study of an Objective Performance Measure for Spaceborne Wind Sensors

THE EFFECT OF RAIN ON ASCAT OBSERVATIONS OF THE SEA SURFACE RADAR CROSS SECTION USING SIMULTANEOUS 3-D NEXRAD RAIN MEASUREMENTS

Deborah K. Smith, Frank J. Wentz, and Carl A. Mears Remote Sensing Systems

Statistics of wind and wind power over the Mediterranean Sea

Assessing the Accuracy of High Spatial Resolution Effort Data

ERS-1/2 Scatterometer new products: mission reprocessing and data quality improvement

Assessment and Analysis of QuikSCAT Vector Wind Products for the Gulf of Mexico: A Long-Term and Hurricane Analysis

Energy Output. Outline. Characterizing Wind Variability. Characterizing Wind Variability 3/7/2015. for Wind Power Management

Assimilation of Scatterometer Winds at Météo-France

The Cross-Calibrated Multi-Platform (CCMP) Ocean Vector Wind Analysis (V2.0)

Climate-Quality Intercalibration of Scatterometer Missions

ON THE USE OF DOPPLER SHIFT FOR SAR WIND RETRIEVAL

Wind Stress Working Group 2015 IOVWST Meeting Portland, OR

Wind Direction Analysis over the Ocean using SAR Imagery

FULL-WAVEFORM INVERSION

Determination of Nearshore Wave Conditions and Bathymetry from X-Band Radar Systems

SeaWinds Validation with Research Vessels

Fuga. - Validating a wake model for offshore wind farms. Søren Ott, Morten Nielsen & Kurt Shaldemose Hansen

Evaluation of Marine Surface Winds Observed by SeaWinds and AMSR on ADEOS-II

A GENERALIZED WAVE-RAY APPROACH FOR PROPAGATION ON A SPHERE AND ITS APPLICATION TO SWELL PREDICTION

JPEG-Compatibility Steganalysis Using Block-Histogram of Recompression Artifacts

IMPROVED OIL SLICK IDENTIFICATION USING CMOD5 MODEL FOR WIND SPEED EVALUATION ON SAR IMAGES

ERS WAVE MISSION REPROCESSING- QC SUPPORT ENVISAT MISSION EXTENSION SUPPORT

Archimer

RapidScat wind validation report

Aquarius Sca+erometer Calibra3on

Institut Français pour la Recherche et l Exploitation de la MER

Impact of the tides, wind and shelf circulation on the Gironde river plume dynamics

TRIAXYS Acoustic Doppler Current Profiler Comparison Study

COMPARISON OF DEEP-WATER ADCP AND NDBC BUOY MEASUREMENTS TO HINDCAST PARAMETERS. William R. Dally and Daniel A. Osiecki

First studies with the high-resolution coupled wave current model CWAM and other aspects of the project Sea State Monitor

PROPAGATION OF LONG-PERIOD WAVES INTO AN ESTUARY THROUGH A NARROW INLET

Assessing the quality of Synthetic Aperture Radar (SAR) wind retrieval in coastal zones using multiple Lidars

ERGS are large expanses of sand in the desert. Aeolian

IMPROVED BAYESIAN WIND VECTOR RETRIEVAL SCHEME USING ENVISAT ASAR DATA: PRINCIPLES AND VALIDATION RESULTS

IMPROVEMENTS IN THE USE OF SCATTEROMETER WINDS IN THE OPERATIONAL NWP SYSTEM AT METEO-FRANCE

DEVELOPMENT AND VALIDATION OF A SAR WIND EMULATOR

The Effects of Gap Wind Induced Vorticity, the ITCZ, and Monsoon Trough on Tropical Cyclogenesis

SPATIAL AND TEMPORAL VARIATIONS OF INTERNAL WAVES IN THE NORTHERN SOUTH CHINA SEA

Currents measurements in the coast of Montevideo, Uruguay

Analyses of Scatterometer and SAR Data at the University of Hamburg

Quantifying variance due to temporal and spatial difference between ship and satellite winds

SEA SURFACE TEMPERATURE RETRIEVAL USING TRMM MICROWAVE IMAGER SATELLITE DATA IN THE SOUTH CHINA SEA

The relevance of ocean surface current in the ECMWF analysis and forecast system. Hans Hersbach Jean-Raymond Bidlot

Comparison of data and model predictions of current, wave and radar cross-section modulation by seabed sand waves

Vika Grigorieva and Sergey Gulev. Sea Atmosphere Interaction And Climate Laboratory P. P. Shirshov Institute of Oceanology, Russia

GLOBAL VALIDATION AND ASSIMILATION OF ENVISAT ASAR WAVE MODE SPECTRA

The Use of ILI In Dent Assessments

ENVISAT WIND AND WAVE PRODUCTS: MONITORING, VALIDATION AND ASSIMILATION

Imprints of Coastal Mountains on Ocean Circulation and Variability

Wave Prediction in the Santa Barbara Channel

On the quality of high resolution scatterometer winds

Transcription:

Validation of 12.5 km Resolution Coastal Winds Barry Vanhoff, COAS/OSU Funding by NASA/NOAA

Outline Part 1: Determining empirical land mask Characterizing σ 0 near coast Part 2: Wind retrieval using new mask Methodology Comparisons with NDBC buoy winds Future work

Overview of Land Masks Current QuikSCAT land mask is fixed 35km for 25km resolution wind vectors 20km for 12.5km resolution wind vectors Use backscatter measurements (σ 0 ) to 0 determine empirical land mask Key Assumption: At a fixed viewing geometry and location, σ 0 will have a larger variability over ocean than over land Long QSCAT mission provides accurate statistics

Characterizing σ 0 Near Coast Calculations of temporal mean and variability (sdev) of σ 0 slices in region within 50km of coast Function of: Measurement location Latitude and longitude of σ 0 center Viewing geometry antenna azimuth angle, χ incidence angle, θ ascending/descending Use 8 years of QuikSCAT σ 0 data, 2000-2007 mean(lat,lon; θ,χ) and sdev(lat,lon; θ,χ); Gridded on a 1/120 th degree grid Each calculation includes all σ 0 within 3km of grid point ~200-400 σ 0 slice values in each calculation Examples of slices at different azimuth angles.

Mean of Coastalσ o - Topography is from GTOPO30 database

Variability of Coastalσ o - Topography is from GTOPO30 database

Construction of Land Mask Your eye can see contamination (aided by choice of color palette) Apply median filter to de-speckle images Robust calculation Use a spatial extent of ~5km If too small, resulting mask will be noisy If too large, details will be lost Determine criteria for good vs. contaminated σ 0

Variability of Coastalσ o (raw) (median filtered)

Variability of Coastalσ o (raw) (median filtered)

Construction of Land Mask Your eye can see contamination (aided by choice of color palette) Apply median filter to de-speckle images Robust calculation Use a spatial extent of ~5km If too small, resulting mask will be noisy If too large, details will be lost Determine criteria for good vs. contaminated σ 0

Sdev vs. meanσ o -All grid points within 50km of land -Both H-pol and V-pol -All azimuth angles - One size fits all? 50 km > D > 20 km D < 20 km 99.98% 46% 0.02% 54%

Sdev vs. meanσ o -All grid points within 50km of land -Both H-pol and V-pol -All azimuth angles - One size fits all? 50 km > D > 20 km D < 20 km 98% 46% 2% 54%

Variability of Coastalσ o Red line: New empirical land mask

Variability of Coastalσ o Red line: New empirical land mask

Conclusions: Part 1 Current 20 km land mask is about right for global solution at all azimuth angles Characterizing σ 0 near coast Variability is smaller near land (Mean is larger in regions near land) Depends upon slice orientation Validates initial assumption Determine empirical land mask Used conservative slice through 2-dimensional sdev vs. mean space to remove contamination

Wind Retrieval Details Convert land mask into table Do coastal wind retrievals Only do retrievals within 50 km of coast (<<CPU time) Flag σ 0 slices for contamination prior to compositing 0 Can use either MGDR-NRT or science code for retrievals Merge coastal retrievals with science Apply ambiguity removal Treat new coastal winds (d<20 km) similar to rain to avoid propagation of possible spurious coastal wind vectors to open ocean

Validation Status Comparisons with NDBC buoys Collocate with QuikSCAT: Within 30 minutes d<12.5 km from buoys Use selected ambiguity Use buoys ~20 km from land Coastal retrievals do not fall within collocation radius (d<12.5 km) if buoy is too far from land

NDBC Buoy Locations Selected buoys -Four open ocean buoy -Six coastal buoys Collocations with these six coastal buoys include winds that are <20 km from land.

NDBC Buoy Info Open Ocean buoys Buoy lon lat npts dist VC CC1 CC2 srms drms ======================================================================== 46002 229.74 42.53 8215 >99 1.69 0.93 0.76 0.9 23.8 46005 229.00 46.08 8081 >99 1.73 0.93 0.81 1.0 22.4 46006 222.51 40.84 5272 >99 1.76 0.92 0.84 1.1 22.2 46059 230.00 37.98 9650 >99 1.66 0.94 0.73 0.9 24.3 Coastal buoys Buoy lon lat npts dist VC CC1 CC2 srms drms ======================================================================== 46011 239.13 34.88 4604 21 1.20 0.88 0.32 1.3 29.4 46013 236.70 38.23 6671 23 1.23 0.91 0.32 1.5 28.7 46014 236.03 39.22 4042 20 1.14 0.91 0.23 2.1 30.7 46022 235.49 40.74 4421 22 1.21 0.90 0.30 1.8 35.6 46027 235.62 41.85 2635 17 1.20 0.88 0.32 2.6 35.6 46054 239.55 34.27 4871 17 1.04 0.88 0.16 1.7 29.0

25 km NDBC 46013

RMS Directional Difference Open ocean Distance from land (km)

RMS Speed Difference vs. distance Open ocean Distance from land (km)

QuikSCAT Speed Histograms vs. dist RMS Speed Difference Open ocean Distance from land (km)

Conclusions: Part 2 Processing Simple code adaptations allow for use of new land mask Merging with science winds allows for rapid retrieval times Validation Validation Low vector correlations result from little signal in offshore direction Along-coast correlations are high, ~0.9 Dir diff RMS is slightly larger than open-ocean (~30 deg vs. ~24 deg) Spd diff RMS increases as QuikSCAT wind vectors get closer to land; SCAT speed histograms are narrower

Future Work Expand analysis to other regions Validate using SAR Use open ocean QuikSCAT/SAR comparison as benchmark; Use results from open-ocean comparison to validate coastal QuikSCAT wind vectors

END

Science Retrievals

Merged Retrievals

Coastal Retrievals

Canonical Correlations vs. VC

NDBC Buoys

NDBC Buoys