Atelier Moment Cinetique Paris 26 Novembre 2012 Les Vents de Surface Diffusiométriques ERS-1 ERS-2 ADEOS-1 QuikSCAT ADEOS-2 MetopA OSCAT2 HY-2A MetopB CFOSAT HY-2B Meteor-M3

Atelier Moment Cinetique Paris 26 Novembre 2012 Les Vents de Surface Diffusiométriques Bentamy, A., D. Croize-Fillon, and C. Perigaud, 2008: Characterization of ASCAT measurements based on buoy and QuikSCAT wind vector observations, Ocean Sci., 4, 265–274. Bentamy, A.; D. Croize-Fillon, P. Queffeulou; C. Liu, H. Roquet, 2009: Evaluation of high-resolution surface wind products at global and regional scales. Journal of Operational Oceanography, vol. 2, 15-27(13). Bentamy, A., S. A. Grodsky, J. A. Carton, D. Croizé-Fillon, and B. Chapron, 2012: Matching ASCAT and QuikSCAT Winds, J. Geoph. Res., doi: /2011JC Grodsky S. A., V. N. Kudryavtsev, A. Bentamy, J. A. Carton, and B. Chapron, 2012: Does direct impact of SST on short wind waves matter for scatterometry?, Geophys. Res. Letters, doi: /2012GL052091

Atelier Moment Cinetique Paris 26 Novembre 2012  The main scatterometer measurements are the backscatter coefficients calculated as a ratio between the emitted power P e and the received one P r : : the wavelength, G the antenna gain, A the radar footprint, R the distance between the sensor and the reached target.  Scatterometers are active microwave sensors: they send out a signal and measure how much of that signal returns after interacting with the target. Microwaves are Bragg scattered by short water waves; the fraction of energy returned to the satellite (backscatter) is a function of wind speed and wind direction. Scatterometer measurement

Scatterometer Calibration  Retrieving Surface Winds from Backscatter Coefficient Measurements is not Trivial Atelier Moment Cinetique Paris 26 Novembre 2012  Calibration Procedure: Determination of Geophysical Model Function (GMF):  ° = f(U, , , P,fc, ….)

PORSEC 2012 Kochi Tutorial GMF : Scatterometer Geophysical Relationships Buoy Wind Speed Range 8m/s

PORSEC 2012 Kochi Tutorial GMF : Scatterometer Geophysical Relationships Buoy Wind Speed Range 3m/s

PORSEC 2012 Kochi Tutorial GMF : Scatterometer Geophysical Relationships Buoy Wind Speed Range 12m/s

Atelier Moment Cinetique Paris 26 Novembre 2012 ASCAT / QuikSCAT ( Bentamy et al, 2011 )  Study Period: April 2007 – November 2009  Focus : November 2008 – November 2009 ASCAT Data Source: OSI SAF / KNMI Products: L1b & L2b 25 & L2b 12.5 GMF : CMOD5 and CMOD5n Wind retrieval: Selected solution Data selection:  All WVC  Wind Speed : 0 – 50m/s  Wind direction : 0° – 360°  Quality flags QuikSCAT / QuikSCAT V3 Data Source: PODAAC / JPL Products: L1b & L2b 25 / L2b 12.5 GMF : QSCAT-1/F13 / QuikSCAT (Ku2011)‏ Wind retrieval: Selected solution Data selection:  All WVC  Wind Speed : 0 – 50m/s  Wind direction : 0° – 360°  Quality flags / New Rain flags

Atelier Moment Cinetique Paris 26 Novembre 2012 Local Assessment for ASCAT/QSCAT Collocated Data  Comparisons with NDBC buoy hourly measurements

Atelier Moment Cinetique Paris 26 Novembre 2012 Global Comparisons  Bias (top), STD (middle), and Correlation (bottom) of collocated QuikScat and ASCAT winds.

Analysis of ASCAT and QSCAT Differences Atelier Moment Cinetique Paris 26 Novembre 2012  Wind speed difference. QuikSCAT rain flag and MRP<0.05 are applied  Spatial distribution of the time mean  Wind speed difference after applying the correction function  Histogram of wind speed difference before (gray bar) and after (empty bar) applying of dW

Mean Difference of Wind Speeds: QSCAT / ASCAT / ECMWF / ERA Interim Atelier Moment Cinetique Paris 26 Novembre 2012 QSCAT ASCAT ECMWFERAI

Mean Difference of Wind Components : QSCAT / ASCAT / ECMWF Atelier Moment Cinetique Paris 26 Novembre 2012 | QSCAT | - | ASCAT | | QSCAT | - | ECMWF | | ASCAT | - | ECMWF | ZonalMeridional

Mean Difference of Wind Components: QSCAT / ASCAT / ERA Interim Atelier Moment Cinetique Paris 26 Novembre 2012 |QSCAT| - | ASCAT | | QSCAT | - | ERAI | | ASCAT | - | ERAI | ZonalMeridional

Zonal Means of Wind Components Within 3 degree of 140°W Atelier Moment Cinetique Paris 26 Novembre 2012

16 High Wind Field Spatial and Temporal Resolution QuikSCAT SSMI AMSR-E TMI Jason METOP Objectives  Estimation of high spatial and temporal resolution of surface wind fields (wind vector and wind stress) using ECMWF Numerical Weather analysis outputs with high remotely sensed surface parameters. 6-hourly, 0.25° x 0.25°  Set-up and carry-out a demonstration experiment, to produce in near real-time merged wind fields : 6-hourly, 0.25° x 0.25°  Assess the quality of derived blended wind fields at near shore and offshore areas. E.U. MyOcean-1/2 Projects Operational ECMWF Analysis Atelier Moment Cinetique Paris 26 Novembre 2012

17 Objective Method  Objective Method : External Drift  Wind Observations (U) are from NRT Scatterometer and SSM/I External Data (S) are from ECMWF analysis.  Assumption : E(U(X,t)) = a + b*S(X,t)  The space and time correlation is parameterized by Atelier Moment Cinetique Paris 26 Novembre 2012

AMS Conference August 2007 Portland 18 Blended Surface Wind Fields  Method : Objective OI (Bentamy et al, 2007; 2009) Results : 6-hourly global wind vector 0.25°×0.25° May 4 th h:00 May 4 th h:00 Atelier Moment Cinetique Paris 26 Novembre 2012

Evaluation Versus QuikSCAT (off-line) Wind Observations January 2005 ( Bentamy et al, 2009 ) QuikSCAT – Blended BiasRms QuikSCAT – ECMWF BiasRms W U V