Characterization of Ocean Wind Vector Retrievals Using ERS-2 Scatterometer High-Resolution Long-term Dataset and Buoy Measurements Supervisor: Prof. Frank S. Marzano Candidate: Federica Polverari 1205617 Assistant Supervisors: Eng. Raffaele Crapolicchio Dr. Marco Talone Master’s Degree in Electronic Engineering curriculum in Complex Systems and Remote-Sensing for the Environment Image of ESA

Outline The ERS-2 Scatterometer Data Data Selection Methodology L1 Validation L2 Validation Main Results L1 L2 Conclusions

ERS-2 Scatterometer The European Remote-sensing Satellite (ERS)-2 was involved in Earth Observation activities and it was launched in 1995 as follow-on of the ERS-1 mission ERS-2 embarks an Active Microwaves Instrument (AMI) in which it is incorporated a radar instrument called Scatterometer working at 5.3 GHz The scatterometer is designed to measure the Normalized Radar Cross Section (NRCS) of the sea surface Image from ESA Website Image from Stoffelen, 2008 The NRCS is obtained by the scattering mechanism (Bragg Scattering) of wind-generated capillary waves which are in equilibrium with the near-surface wind over the ocean R: distance target-radar Wr: received power Wt :transmitted power F: scatterometer foootprint Lampda: radar wavelenght D: Directivity gain Thanks to the Geophysical Model Function and Inversion Algorithms, from NRCS measurements it is possible to estimate the WIND SPEED and WIND DIRECTION at 10 m above the mean sea level

Image from PIRATA Website Data The European Remote sensing Satellite (ERS)-2 Wind Speed (WS) and Direction (WD) This database covers the period during 1997-2003 The products available for the users are the Advanced Scatterometer Processing System (ASPS ) Level 2.0 products The investigation has been carried out using the High Resolution (25 km) products The In-Situ Wind Speed and Direction provided by the Prediction and Research Moored Array in the Atlantic (PIRATA) Site Date first deployed 0 0 Feb 1998 0 10W Sept 1997 2N 10W Nov 1999 2S 10W 5S 10W Jan 1999 6S 10W Mar 2000 10S 10W 0 23W  Dec 2001 0 35W Jan 1998 15N 38W 12N 38W Feb 1999 8N 38W 4N 38W Image from PIRATA Website

Data Selection One buoy measurement several satellite measurements The spatial and temporal collocation is the way to find satellite and buoy data pairs which can be compared. Spatial Collocation: Nodes whose distance from a buoy position is less than 1 degree (~100km) are selected Temporal Collocation: From the spatial collecated data, nodes whose time difference from buoy acquisition time is less than 10 min are selected One buoy measurement several satellite measurements

Data Selection One buoy measurement several satellite measurements Repetition of buoy WS and WD for each scatterometer measurement Average of scatterometer WS and WD Weighted average on square distance

Methodology – L1 σ° σ°* A0, A1, A2 A0*, A1*, A2* remotely sensed Validation at Level1: comparison between predicted and estimated coefficients of the C-band Geophisical Model Function (GMF) for equivalent neutral wind CMOD5.N remotely sensed in situ WS,WD Repetition WS*,WD* CMOD5.N σ° σ°* Fitting Fitting A0, A1, A2 A0*, A1*, A2*

Mean Difference between predicted and estimated A0 Main Results – L1 4 m/s (blue), 8 m/s (red),12 m/s (black) The estimated (dots) and predicted (full line) A0 exhibit a similar behaviour for each beam Mean Difference between predicted and estimated A0 WS 3m/s 8m/s 12 m/s Fore -1.4215 0.6216 1.4104 Mid -2.7363 0.2212 1.1618 Aft -1.8671 0.5547 1.9064

Mean Difference between predicted and estimated Main Results – L1 Mean Difference between predicted and estimated A1 WS 3m/s 8m/s 12 m/s Fore -0.0332 -0.1002 1.4522 Mid -0.0023 0.0060 0.0647 Aft -0.0647 0.0295 -0.4953

Mean Difference between predicted and estimated Main Results – L1 Mean Difference between predicted and estimated A2 WS 3m/s 8m/s 12 m/s Fore 0.0179 0.0026 0.2658 Mid 0.1983 0.3526 1.7009 Aft 0.1036 0.1315 1.1892

Main Results-L1:Fore Beam Additional analysis: Spatial collocation 50 km Benefit: reduction of the Representativity Error Number of samples is strongly reduced 821021 188670 Threshold: 80 measurements Spatial collocation: 100 km Spatial collocation: 50 km

Main Results-L1:Mid Beam Spatial collocation: 100 km Spatial collocation: 50 km

Main Results-L1: Aft Beam Spatial collocation: 100 km Spatial collocation: 50 km

Methodology – L2 Comparison and statistical analysis between buoys and scatterometer in term of wind speed and wind direction The case of buoy 10S 10W (out of 13): with the greatest number of matches In order to have collocated measurements couples, we have considered the following criteria : Mean of satellite WS and WD related to each bouy measurements Weighted average on square distance

Wind Speed Misfit (considering the mean) Main Results – L2 Comparison and statistical analysis between buoys and scatterometer in term of wind speed and wind direction The case of buoy 10S 10W (out of 13): with the greatest number of matches Wind Speed Misfit (considering the mean) Normalized Histogram σ = 1.5

Main Results – L2 Seasonal Trend of Wind Speed 0.2058 0.2133 1.3150 STATISTICS OF WS MISFIT Mean Misfit (m/s) Mean Misfit (weighted average) (m/s) Misfit Std (weighted average) 0.2058 0.2133 1.3150 1.3600 Seasonal Trend of Wind Direction STATISTICS OF WD MISFIT Mean Misfit (deg) Mean Misfit (weighted average) (deg) Misfit Std (weighted average) 3.6564 3.1420 19.1301 20.3608

Main Results-L2 Wind Speed Misfit indeces: 0 - 0.2 m/s 0.2 - 0.5 m/s Combining the collocated measurements from all the available buoys Wind Speed Misfit indeces: 0 - 0.2 m/s 0.2 - 0.5 m/s 0.5 - 1 m/s > 1m/s Wind Direction Misfit indeces: 0° - 3° 3° - 10° 10° - 30° > 30°

Main Results-L2 To characterize the three wind speed ranges: Combining the collocated measurements from all the available buoys To characterize the three wind speed ranges: Buoys and ERS-2 wind speed difference against buoy wind speed WS < 4 m/s: negative differences thus the satellite tends to overestimate the lower wind. WS > 9 m/s: positive differences thus the satellite tends to underestimate higher wind 4 m/s < WS < 9 m/s greatest concentration of measurements whose differences are around 0 m/s

Main Results-L2 Characterization of the misfit in term of buoy wind speed Characterization of the misfit in term of ERS-2 wind speed Buoy Wind Speed Range (m/s) Number of data Mean Difference (m/s) Standard Deviation 0 - 2 134 -2.4231 1.7028 2 - 4 428 -1.1425 1.6602 4 - 6 973 -0.2073 1.5019 6 - 8 1778 0.3142 1.3062 8 - 10 1269 0.7557 1.2543 10 - 18 242 1.5226 1.8969

Conclusions From the validation at Level 1 From this first analysis of the ERS-2 and PIRATA buoys datasets during the period between 1997-2003, with the chosen criteria we can conclude that: From the validation at Level 1 The validity of the ERS-2 GMF has been checked: the buoy wind measurements are able to retrieve the characteristics of ERS-2 backscatter coefficient measurements with main discrepancies for higher winds; Not significant changes can be observed with the reduction of the spatial collocation. From the validation at Level 2 The ERS-2 measurements are consistent with the buoys wind measurements : the Wind Speed difference is less than 1 m/s on average; the Wind Direction difference is less than 30 degree on average; ERS-2 overestimates lower winds and underestimates higher winds. Reference: A., Bentamy, D. Croize-Fillon, C., Perigaud, “Characterization of ASCAT measurements based on buoy and QuikSCAT wind vector observations”, Ocean Sci., 4, 265-274, 2008.

Thank you for your attention! Acknoledgements Thanks to: Prof. Frank S. Marzano Raffaele Crapolicchio Marco Talone All colleagues of Serco SpA Thank you for your attention!

Focusing On CMOD5.N: similar to a second order Fourier expression, the power 1.6 was included because it avoids the need of higher harmonics. 2) Neutral Wind: is the wind at 10-metre heigh for given surface stress that would be observed if there was neutral atmospheric stratification [Geernaert and Katsaros 1986].

Statistics for each buoy Main Results – L2 Statistics for each buoy Buoy Site WS Mean Misfit (m/s) WD Mean Misfit (Deg) WS Misfit Std WD Misfit Std 0 0 0.3267 -28.0087 1.6617 195.2192 0N 10W 0.2618 17.7188 1.4139 105.2327 0N 23W 0.2896 3.3124 1.7453 69.2682 0N 35W 0.1407 -2.8660 1.6601 52.3953 2N 10W 0.1279 -58.9163 1.5944 135.1405 2S 10W 0.2580 13.8862 1.3981 93.5314 4N 38W 0.0337 -5.3355 1.8407 78.9810 5S 10W 0.1442 20.0663 1.1880 51.1689 6S 10W 0.2851 3.7537 1.4149 32.1188 8N 38W 0.0725 -10.4287 1.8389 86.5640 12N 38W 0.1166 -4.8897 1.6466 57.0439 ON AVERAGE 0.1870 -4.7007 1.5821 86.9694