Dual-Polarized Backscatter Features of Surface Currents in the Open Ocean During Typhoon Lan (2017)

remote sensing

Letter Dual-Polarized Backscatter Features of Surface Currents in the Open Ocean during Typhoon Lan (2017)

Guosheng Zhang 1,2,* ID and William Perrie 2 1 Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China 2 Fisheries and Oceans Canada, Bedford Institute of Oceanography, Dartmouth, NS B2Y 4A2, Canada; [email protected] * Correspondence: [email protected]; Tel.: +1-902-426-7797

Received: 26 April 2018; Accepted: 31 May 2018; Published: 5 June 2018

Abstract: Ocean surface current measurements from satellites have historically been limited. We propose a new approach to detect ocean surface currents as observed by dual-polarized (VV and VH) spaceborne synthetic aperture radar (SAR). This approach is based on the assumptions that the VH-polarized SAR signal is only generated by the effects of ocean winds creating surface waves, whereas the VV-polarization data are due to the effects of both ocean winds and surface currents. Therefore, the surface currents features may be extracted after retrieving the ocean winds from VH-polarized backscatter and inputting signal due to the wind to the VV-polarized backscatter data. To investigate the performance of this approach under extreme wind conditions, we consider a scene of C-band RADARSAT-2 dual-polarized ScanSAR images over Typhoon Lan (2017) in the open ocean, and we verify our results with current estimates from altimeter data. The ocean current features extracted from the backscatter data that were collected from the SAR images are shown to correspond to an area of strong currents and an oceanic front observed by altimeters. We suggest that the proposed method has the potential capacity to provide information about ocean surface currents from high-resolution dual-polarized ScanSAR images.

Keywords: ocean surface currents; typhoon impacts on the ocean; synthetic aperture radar (SAR)

1. Introduction Observations of surface currents in the open ocean have historically been limited; high-frequency (HF) radar has been used for a limited range in coastal areas and ADCP (acoustic Doppler current profiler) and buoy deployments have provided data at specific point locations [1]. Compared to the passive remote sensing instruments that operate from satellites in the visible and infrared bands, the microwave data such as Special Sensor Microwave Imager (SSM/I), Tropical Rainfall Measuring Mission (TRMM) imagery, Quick Scatterometer (QuikSCAT), and Advanced Scatterometer (ASCAT) have the advantage of essentially being able to work in all-weather conditions, day or night, penetrating fog and cloud [2]. These instruments are sensitive to sea surface waves generated by the wind. However, it is difficult for them to detect ocean current features. For the ocean currents, spaceborne altimeters onboard satellites such as TOPEX/POSEIDON, Jason-1, Jason-2, and ERS1-2 are widely used to detect large-scale oceanic Rossby waves [3] and mesoscale eddies [4]. Until the SWOT (Surface Water and Ocean Topography) satellite is launched in 2021 (https://swot.jpl.nasa.gov), only measurements of sea surface height along points of the narrow altimeter tracks are available. Recently, spaceborne active microwave synthetic aperture radars (SARs) have been reported as a potential tool for the detection of sea surface currents [5]. SAR techniques can be grouped into two

Remote Sens. 2018, 10, 875; doi:10.3390/rs10060875 www.mdpi.com/journal/remotesensing Remote Sens. 2018, 10, 875 2 of 11 methodologies: (1) Doppler velocity detection, which is caused by the motions of the SAR sensor relative to the ocean surface, and (2) the SAR backscatter signal which is based on the surface wave modulations by the ocean surface currents on the Bragg resonance scales [6]. However, a stationary location (i.e., land or island) is needed for the calibration of the current measurements using Doppler velocity methods, because the motions of the sea surface on the scale of meters per second are negligible compared to the movement of the satellite SAR sensor (e.g., about 7500 m/s for RADARSAT-2). Previous studies have used modulations by ocean currents in spaceborne SAR images to analyze the processes of ocean dynamics, i.e., the detection of oceanic fronts [7] and studies of nonlinear Ekman divergence [8]. Thus, a transfer mechanism was proposed for the modulations by ocean currents [6]. In a recent study [9], we inferred that the resonance process between ocean surface waves and the radar microwave signal mostly occurs for the backscatter signal in the VV-polarization channel, but is negligible in the VH-polarization channel. Therefore, theoretically, two-dimensional ocean surface current features and ocean winds can be extracted together from two channels (VV and VH), which are acquired simultaneously by RADARSAT-2. Moreover, the VH-polarized SAR image in RADARSAT-2 dual-polarized (VV and VH) ScanSAR mode appears not to saturate in high wind speeds under tropical cyclone (TC) conditions, and also appears to be linearly related to the ocean wind [10,11]. Because the sea surface Bragg waves on the scale of the radar microwave may interact with the surface currents [7], the radar signal of VV-polarization may be modulated by the surface currents through the Bragg resonance process. Therefore, the C-band VH-polarized radar signal is dominated by ocean wind, whereas the VV-polarized signal includes both effects of ocean winds and surface currents. For simplicity, we assume that the VH-polarized radar signal is only induced by wind, especially under the extreme TC conditions. The main goal for our study is to extract two-dimensional current features from the dual-polarized (VV and VH) SAR images at high spatial resolution. In future studies, it may be possible to combine these ‘current features’ with Doppler-shift information from the SAR raw data to extract the actual current speeds. This study is also motivated by the urgent need for veriﬁcation observations for ocean models, especially for high spatial resolution [12]. In this study, we report a new approach for the decomposition of RADARSAT-2 dual-polarized (VV and VH) ScanSAR images over Typhoon Lan (2017) and we verify the extracted currents features with altimeter data. There are three steps for the decomposition approach: (1) retrieve wind vectors from the VH-polarized SAR image, (2) simulate the theoretical VV-polarized SAR image, and (3) extract the ocean surface current features by comparing the simulated and observed VV-polarized SAR images. Data sets of dual-polarized RADARSAT-2 ScanSAR images of Typhoon Lan (2017) and the composite ﬁve-day ocean currents from satellite altimeters are described in Section2. The methodology we propose for the extraction of ocean surface currents from dual-polarized ScanSAR images is given in Section3. The ocean surface currents features derived from the SAR images and the comparisons to altimeter currents are presented in Section4. Finally, discussions and conclusions are given in Section5.

2. Materials and Methods

2.1. Data Sets Typhoon Lan was the third-most intense tropical cyclone worldwide in 2017. A scene of C-band dual-polarized (VV and VH) RADARSAT-2 ScanSAR images was acquired at 09:20 UTC on 21 October, 2017 over Typhoon Lan. The location of the SAR frame is shown in Figure1. The ocean current speeds from the Ocean Surface Current Analysis (OSCAR) of 22 October, 2017 are also shown in Figure1, which are supplied by the Physical Oceanography Distributed Active Archive Center (PO.DAAC) [13]. The OSCAR currents are estimated by using sea surface height from the satellite altimeters: TOPEX/ POSEIDON, Jason-1, Jason-2, ERS1-2, GFO, and ENVISAT, as well as other measurements. The spatial grid is 1/3◦ × 1/3◦ with a 5-day resolution. The currents in Figure1 on October 22 are the composite data acquired for a period extending over ﬁve days. The Best Track of Typhoon Lan (2017) in Figure1 Remote Sens. 2018, 10, x FOR PEER REVIEW 3 of 11 other measurements. The spatial grid is 1/3° × 1/3° with a 5-day resolution. The currents in Figure 1 on October 22 are the composite data acquired for a period extending over five days. The Best Track of Typhoon Lan (2017) in Figure 1 is provided by the Japan Meteorological Agency (http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/Besttracks/). The dual-polarized (VH and VV) RADARSAT-2 ScanSAR wide imaging mode provides large

Remoteswaths, Sens. high2018 , 10resolution,, 875 all-weather, and day-and-night surveillance, which is suitable for3 ofthe 11 accurate analysis of the ocean surface conditions under tropical cyclones (TCs). The swath width is 450 km and the pixel spacing is 50 m. The noise floor for the dual-polarization ScanSAR wide-swath isdata provided is about by − the29 dB, Japan with Meteorological a radiometric Agency error that (http://www.jma.go.jp/jma/jma-eng/jma-center/ is less than 1 dB [14]. The ocean backscatter is rsmc-hp-pub-eg/Besttracks/described by the normalized ).radar cross section (NRCS).

FigureFigure 1.1. The dual-polarized SAR (synthetic aperture radar)radar) image position and the best tracktrack forfor TyphoonTyphoon LanLan (2017).(2017). TheThe backgroundbackground displaysdisplays thethe OSCAROSCAR currentcurrent speeds.speeds.

Our theory model for the backscatter from ocean winds and currents is based on Bragg The dual-polarized (VH and VV) RADARSAT-2 ScanSAR wide imaging mode provides large resonance between the sea surface waves and the radar microwaves. The sea surface waves that are swaths, high resolution, all-weather, and day-and-night surveillance, which is suitable for the accurate induced by wind are simulated by a model for the wave spectrum. Because the wave spectrum is a analysis of the ocean surface conditions under tropical cyclones (TCs). The swath width is 450 km and statistical concept, large samples need to be acquired to provide a stable relationship between the pixel spacing is 50 m. The noise ﬂoor for the dual-polarization ScanSAR wide-swath data is about winds and sea surface waves. Thus, a particular spatial scale of the ocean surface is needed to −29 dB, with a radiometric error that is less than 1 dB [14]. The ocean backscatter is described by the include a sufficient amount of waves. For example, under constant, stable winds, ocean surface normalized radar cross section (NRCS). waves with various length scales will be generated, and various radar backscatters will be imaged Our theory model for the backscatter from ocean winds and currents is based on Bragg resonance by the SAR. There are no stable relationships between the wind and a single individual sea surface between the sea surface waves and the radar microwaves. The sea surface waves that are induced wave. We can only get a stable relationship between the wind and a spectrum of sea surface waves by wind are simulated by a model for the wave spectrum. Because the wave spectrum is a statistical with various spatial scales generated by constant, stable wind conditions. Therefore, we calibrated concept, large samples need to be acquired to provide a stable relationship between winds and sea the SAR image and then averaged the spatial resolution to 5 km using the boxcar averaging method surface waves. Thus, a particular spatial scale of the ocean surface is needed to include a sufﬁcient (as shown in Figure 2). Moreover, with averaging, the SAR speckle noise is almost removed. The amount of waves. For example, under constant, stable winds, ocean surface waves with various length latitude and longitude information is also acquired with the calibration process using the transfer scales will be generated, and various radar backscatters will be imaged by the SAR. There are no function provided by the Canadian Space Agency (CSA, Saint-Hubert, QC, Canada). stable relationships between the wind and a single individual sea surface wave. We can only get a stable relationship between the wind and a spectrum of sea surface waves with various spatial scales generated by constant, stable wind conditions. Therefore, we calibrated the SAR image and then averaged the spatial resolution to 5 km using the boxcar averaging method (as shown in Figure2). Moreover, with averaging, the SAR speckle noise is almost removed. The latitude and longitude information is also acquired with the calibration process using the transfer function provided by the Canadian Space Agency (CSA, Saint-Hubert, QC, Canada).

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FigureFigure 2.2. Dual-polarized RADARSAT-2 ScanSARScanSAR images over Typhoon LanLan (09:20(09:20 UTC,UTC, 2121 OctoberOctober 2017):2017): ( a) VV-polarizationVV-polarization andand ((bb)) VH-polarization.VH-polarization. RADARSAT-2 RADARSAT-2 Data andand ProductsProducts MacDonald,MacDonald, Dettwiler,Dettwiler, andand AssociatesAssociates Ltd.Ltd. (Toronto,(Toronto,ON, ON,Canada), Canada),All AllRights RightsReserved. Reserved.

ToTo furtherfurther demonstratedemonstrate that that the the current current modulations modulations are are different different in in the the different different polarizations polarizations of VVof VV and and VH, VH, we employwe employ additional additional dual-polarized dual-polarized (VH and(VH VV) and RADARSAT-2VV) RADARSAT-2 ScanSAR ScanSAR images images of the Bayof the of FundyBay of (Figure Fundy3 ).(Figure Because 3). of Because the very highof the tidal very range high in tidal the Bay range of Fundy, in the the Bay currents of Fundy, are very the strongcurrents [15 are]. It very is obvious strong that[15]. the It is current obvious signatures that the current are much signatures clearer in are the much VV-pol clearer image in (Figure the VV-pol3a,c) thanimage in (Figure the VH-pol 3a,c) imagethan in (Figure the VH-pol3b,d). image (Figure 3b,d).

FigureFigure 3. 3. Dual-polarizedDual-polarized RADARSAT-2 RADARSAT-2 ScanSAR ScanSAR images images in the in Bay the of Bay Fundy of Fundy(22:20 UTC, (22:20 14 UTC,May 142017): May (a 2017) VV-polarization,): (a) VV-polarization, (b) VH-polarization, (b) VH-polarization, (c) VV-polarized (c) VV-polarized sub-scene sub-scene of the white of the box, white and box, (d) andVH-polarized(d) VH-polarized sub-scenesub-scene of the white of the box. white RADARS box.AT-2 RADARSAT-2 Data and Products Data and MacDonald, Products MacDonald, Dettwiler, Dettwiler,and Associates and Associates Ltd., All Rights Ltd., AllReserved. Rights Reserved.

2.2.2.2. Surface Currents DetectionDetection ApproachApproach AsAs shownshown inin ourour previousprevious study [[9],9], the Bragg resonanceresonance plays a main role inin thethe VV-polarized NRCS,NRCS, butbut is is negligible negligible for thefor VH-polarizationthe VH-polarization NRCS. NRCS. Moreover, Moreover, the non-Bragg the non-Bragg scattering dominatesscattering dominates the VH-polarized NRCS, but is negligible for the VV-polarized NRCS. Because the sea surface Bragg waves on the scale of the microwave radar may interact with the surface currents, the

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radar signal due to Bragg resonance may therefore be modulated by the surface currents. Moreover, the strong currents in the Bay of Fundy are obviously captured by VV-polarization backscatter, but there are almost no features in the VH-polarized backscatter. A summary is presented in Table 1 for the roles of the above two main backscatter mechanisms with respect to the two different polarizations. We propose an approach to detect surface current features from dual-polarized (VV and VH) SAR images based on assumptions that: (1) the VH-polarized NRCS is only induced by ocean wind; and (2) that the VV-polarized NRCS includes information related to both ocean winds and surface currents. Therefore, the approach is as follows: (1) retrieve wind vectors from the VH-polarized

RemoteSAR image; Sens. 2018 (2), 10 ,simulate 875 the VV-polarized NRCS induced by wind by using the Bragg resonance5 of 11 mechanism (Equations (2) and (3)) and the non-Bragg scattering mechanism (Equation (4)); and (3) extract the ocean surface current features by removing the non-Bragg scattering contributions from thethe VH-polarizedVV-polarized NRCS,SAR image but isand negligible by comparing for the the VV-polarized results to the NRCS. simulated Because Bragg the searesonance surface NRCS. Bragg wavesThe approach on the scale is displayed of the microwave in the flow radar chart may in Figure interact 4. with the surface currents, the radar signal due to Bragg resonance may therefore be modulated by the surface currents. Moreover, the strong currents in the BayTable of Fundy 1. The areroles obviously of the two captured mechanisms by with VV-polarization respect to the backscatter,two polarizations but there(VV & areVH). almost no features in the VH-polarized backscatter. A summary is presented in Table1 for the roles of the above Mechanisms VV-Pol VH-pol two main backscatter mechanisms with respect to the two different polarizations. Bragg Resonance Main Negligible Table 1. The roles of(Current the two mechanismsmodulation) with respect to the two polarizations (VV & VH). Non-Bragg Negligible Main Mechanisms(few current effects) VV-Pol VH-pol Bragg Resonance Main Negligible After removing the(Current non-Bragg modulation) scatter from the SAR VV-polarized NRCSs, we can estimate the surface currents by comparingNon-Bragg the resultant NRCSs to the NRCSs resulting from the two-scale Negligible Main Bragg resonance. The flowchart(few current in effects)Figure 4 displays our approach including: (1) retrieval of wind fields from the VH-polarized images (Figure 2b), (2) simulation of two-scale Bragg resonance NRCSs, (3) extraction of the non-Bragg scattering, and (4) detection of ocean surface currents from We propose an approach to detect surface current features from dual-polarized (VV and VH) VV-polarized NRCS data (Figure 2a). The backscatter features (Tcurrent) of ocean currents are: SAR images based on assumptions that: (1) the VH-polarized NRCS is only induced by ocean wind; − and (2) that the VV-polarized NRCS includes information related to both ocean winds and surface = −1 (1) currents. Therefore, the approach is as follows: (1) retrieve_ wind vectors from the VH-polarized

SARwhere image; (2)is the simulate VV-polarized the VV-polarized NRCS, as NRCS imaged induced by SAR by wind (Figure by using2a), the_ Bragg is the resonance NRCS mechanismsimulated by (Equations two-scale (2)Bragg and scattering (3)) and the (Equations non-Bragg (2) scattering and (3)) by mechanism inputting (Equationthe wind vectors (4)); and that (3) extractare retrieved the ocean from surface the VH-polarized current features NRCS, by removing and the is non-Bragg the Non-Bragg scattering scattering contributions (Equation from (4)), the VV-polarizedwhich is independent SAR image of polarizations. and by comparing the results to the simulated Bragg resonance NRCS. The approach is displayed in the ﬂow chart in Figure4.

Observations: Models: Outputs:

VH-NRCS C-3PO & SHEW Wind field

Bragg & Non-Bragg NRCS features VV-NRCS Wind induced modulated by VV-NRCS Currents

Figure 4. Flow chart for wind ﬁeld retrieval and the backscatter features of surface currents. Figure 4. Flow chart for wind field retrieval and the backscatter features of surface currents.

After removing the non-Bragg scatter from the SAR VV-polarized NRCSs, we can estimate the To calculate the Bragg scattering, we retrieve the wind speeds from the VH-polarized SAR surface currents by comparing the resultant NRCSs to the NRCSs resulting from the two-scale Bragg image (Figure 2b) using the C-3PO (C-band Cross-polarization Coupled-Parameters Ocean) model resonance. The ﬂowchart in Figure4 displays our approach including: (1) retrieval of wind ﬁelds from [9], and we simulate the wind directions using the SHEW (Symmetric Hurricane Estimates for the VH-polarized images (Figure2b), (2) simulation of two-scale Bragg resonance NRCSs, (3) extraction of the non-Bragg scattering, and (4) detection of ocean surface currents from VV-polarized NRCS data (Figure2a). The backscatter features ( Tcurrent) of ocean currents are:

σ0VV − σ0nb Tcurrent = − 1 (1) σoVV_CB where σ0VV is the VV-polarized NRCS, as imaged by SAR (Figure2a), σoVV_CB is the NRCS simulated by two-scale Bragg scattering (Equations (2) and (3)) by inputting the wind vectors that are retrieved from the VH-polarized NRCS, and σ0nb is the Non-Bragg scattering (Equation (4)), which is independent of polarizations. Remote Sens. 2018, 10, 875 6 of 11

To calculate the Bragg scattering, we retrieve the wind speeds from the VH-polarized SAR image Remote Sens. 2018, 10, x FOR PEER REVIEW 6 of 11 (Figure2b) using the C-3PO (C-band Cross-polarization Coupled-Parameters Ocean) model [ 9], and we Wind)simulate model the [10] wind which directions is based using on thethe SHEWtyphoon (Symmetric structure. Hurricane The wind Estimates vectors and for retrieved Wind) model wind [10 ] speedswhich from is based the VH-polarized on the typhoon SAR structure. image are The shown wind in vectors Figure and 5a, retrieved as well as wind the speedsreconstructed from the hurricaneVH-polarized core structure SAR image in Figure are shown 5b. in Figure5a, as well as the reconstructed hurricane core structure in Figure5b.

FigureFigure 5. 5.WindWind vectors vectors from from a VH-polarized a VH-polarized SAR SAR image image showing: showing: (a) (Winda) Wind speeds speeds in incolor color as as retrievedretrieved by by the the C-3POC-3PO (C-band(C-band Cross-polarization Cross-polarization Coupled-Parameters Coupled-Parameters Ocean) Ocean) model, model, and directions and directionsas estimated as estimated by the SHEW by (Symmetricthe SHEW Hurricane(Symmetric Estimates Hurricane for Wind)Estimates model; for ( bWind)) Reconstructed model; ( windb) Reconstructedspeeds by the wind SHEW speeds model. by the SHEW model.

2.2.1.2.2.1. Bragg Bragg Resonance Resonance Model Model OnOn the the real real ocean ocean surface, surface, the the Bragg Bragg short short waves waves run run along along the the longer longer surface surface waves waves which which changechange the the local local incidence incidence angles angles and and the the local local polarization polarization relationship. relationship. Accounting Accounting for for all allof ofthe the possiblepossible surface surface tilting tilting by by using using a aprobability probability density density function function (PDF) for thethe oceanocean surfacesurface slopes, slopes, we wefound found that that the the two-scale two-scale Bragg Bragg scattering scattering of of the the sea sea surface surface [16 [16]] is: is: ∞ ∞ +∞ +∞ Z Z _ =tan tan tan , tan (2) σ0VV_CB(θ) = d(tan ϕ) d(tan δ)σ0VV (θi)p(tan ϕ, tan δ) (2) −∞ −∞ where tan , tan is the PDF of sea surface slopes which is described by a Gram-Charlier where p(tan ϕ, tan δ) is the PDF of sea surface slopes which is described by a Gram-Charlier distribution [17] in this study, and is the backscattering cross section of a slightly rough patchdistribution for VV polariza [17] intion this as study, given and by: σ0VV (θi) is the backscattering cross section of a slightly rough patch for VV polarization as given by: cos sin = 16 cos + , (3) 2 2 2 αcos δ sin δ ( ) = 4 4 ( ) + ( ) σ0VV θi 16πk cos θi gvv θi ghh θi W KBx , KBy (3) αi αi where , is the wave spectrum induced by wind which may be modulated by the surface currents, gpq are the Bragg scattering geometric coefficients for different polarizations [18], where W KBx , KBy is the wave spectrum induced by wind which may be modulated by the surface is the local incidence angle, =sin, =sin+, = cos+, and φ and δ are the g anglescurrents, of thepq tiltingare the surface Bragg scatteringin the radar geometric incidence coefﬁcients plane forand different is perpendicular polarizations to the [18 ],plane,θi is the local incidence angle, αi = sin θi, α = sin(θ + ϕ), γ = cos(θ + ϕ), and ϕ and δ are the angles of the respectively. The two wavenumber components of the Bragg resonance waves are =2 and tilting surface in the radar incidence plane and is perpendicular to the plane, respectively. The two =2sin. Here, the wind-wave spectrum follows that of Kudryavtsev et al. [19], which was wavenumber components of the Bragg resonance waves are K = 2kα and K = 2kγ sin δ. Here, the adapted to calculate the wave spectrum in Equation (3) with theBx input of vectorBy winds. Details of wind-wave spectrum follows that of Kudryavtsev et al. [19], which was adapted to calculate the wave the parameters are given by [9] and [16]. With the retrieved wind vectors (Figure 5a) and model spectrum in Equation (3) with the input of vector winds. Details of the parameters are given by [9] described in Equations (2) and (3), the VV-polarized NRCSs of the two-scale Bragg scattering signal and [16]. With the retrieved wind vectors (Figure5a) and model described in Equations (2) and (3), the are simulated, as shown in Figure 6a. VV-polarized NRCSs of the two-scale Bragg scattering signal are simulated, as shown in Figure6a.

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Figure 6. (a) Simulated VV-polarized NRCSNRCS byby thethe two-scaletwo-scale BraggBragg model.model. (b) Simulated Non-Bragg scattering NRCS.

2.2.2. Non-Bragg Ratio To describedescribe thethe non-Braggnon-Bragg scatteringscattering mechanism,mechanism, a phenomenologicalphenomenological model was originally proposed byby Phillips Phillips [20 [20].]. Thereafter, Thereafter, Kudryavtsev Kudryavtse et al.v [et19 ]al. reviewed [19] reviewed and simpliﬁed and simplified this non-Bragg this modelnon-Bragg by using model experimental by using experimental results of Ericson results etof al. Er [icson21] and et al. a conceptual [21] and a approachconceptual of approach Wetzel [22 of]. BasedWetzel on [22]. a high-quality Based on a database high-quality of ﬁve database RADARSAT-2 of five dual-polarizedRADARSAT-2 (VVdual-polarized & VH) ScanSAR (VV images& VH) collocatedScanSAR images with aircraft collocated observations with aircraft obtained observations within aobtained time window within ofa time±30 min,window we proposedof ±30 min, a non-Braggwe proposed ratio a non-Bragg [23]. Moreover, ratio [23]. the Non-Bragg Moreover, scatteringthe Non-Bragg is simulated scattering here is by:simulated here by:

= Br ∙ (4) σ0nb = 1+·σ0VH (4) 1 + Br where is VH-polarized NRCS imaged by SAR (Figure 2b), and Br is the non-Bragg ratio with a where σ is VH-polarized NRCS imaged by SAR (Figure2b), and B is the non-Bragg ratio with a constant0 VHvalue of 7.3. We note that the VV-polarized NRCS duer to non-Bragg scattering is constant value of 7.3. We note that the VV-polarized NRCS due to non-Bragg scattering is calculated calculated using Equation (4) by also imputing the VH-polarized SAR image (). The reason for using Equation (4) by also imputing the VH-polarized SAR image (σ0VH). The reason for this is that this is that the non-Bragg scattering () is suggested to be independent of polarizations [9,19]. the non-Bragg scattering (σ ) is suggested to be independent of polarizations [9,19]. This implies that This implies that the non-Bragg0nb scattering has the same values for VV or VH polarizations. the non-Bragg scattering has the same values for VV or VH polarizations. Therefore, the VV-polarized Therefore, the VV-polarized (or VH-polarized) NRCSs values of the non-Bragg scattering () are (or VH-polarized) NRCSs values of the non-Bragg scattering (σ ) are shown in Figure6b. shown in Figure 6b. 0nb 3. Results 3. Results The surface currents’ backscatter features that were detected from the dual-polarized SAR images The surface currents’ backscatter features that were detected from the dual-polarized SAR at 09:20 UTC on 21 October are shown in Figure7. The isoclines are from OSCAR ﬁve-day composite images at 09:20 UTC on 21 October are shown in Figure 7. The isoclines are from OSCAR five-day currents for 22 October. The OSCAR zonal and meridional currents, as well as the wind vectors from composite currents for 22 October. The OSCAR zonal and meridional currents, as well as the wind VH-polarization data are shown in Figure8. The strongest OSCAR currents are in area A, which vectors from VH-polarization data are shown in Figure 8. The strongest OSCAR currents are in area exceed 0.3 m/s. The surface current features that were extracted from the dual-polarized SAR images A, which exceed 0.3 m/s. The surface current features that were extracted from the dual-polarized appear to agree with the strong currents in area-A. We also checked the OSCAR currents for October SAR images appear to agree with the strong currents in area-A. We also checked the OSCAR 17 and 27, where the strong currents continued to exist near area A. Figure8 shows that the strongest currents for October 17 and 27, where the strong currents continued to exist near area A. Figure 8 currents are westward whereas the wind is towards the southeast. Thus, the currents tend to encounter shows that the strongest currents are westward whereas the wind is towards the southeast. Thus, the the wind-waves and enhance the ocean surface roughness. Therefore, the SAR images reveal these currents tend to encounter the wind-waves and enhance the ocean surface roughness. Therefore, the strong current features. SAR images reveal these strong current features. In Figure 7, the isoclines that are indicated by the red dashed line-B are similar to those of the red dashed line-C, whereas the backscatter features from SAR images near the two lines are totally different. These differences are due to the ocean current front along line-B where the meridional currents move in different directions, as shown in Figure 8b. Although the absolute values of the OSCAR currents around the two lines are similar, the directional distributions are different.

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Figure 7. Ocean currents’ manifestations (colors) from dual-polarized ScanSAR images. The isoclines are the OSCAR currents.

Thus, through these comparisons, we suggest that the backscatter features of the ocean currents extracted by our proposed approach correspond to the observed strong currents (>0.3 m/s) and the ocean front, even under TC conditions. Because it is difficult to distinguish the upper limits on the values in Figure 7 that were induced by strong currents and the ocean front, we therefore cannot apply this method to directly retrieve the ocean currents. However, this approach has the potential to provide validations of oceanic processes as simulated by numerical models, which is very important for the ocean studies [12], especially for high spatial resolutions. Moreover, as noted, OSCAR currents are 5-day composites, whereas SAR provides instantaneous snapshots with the typical revisit times being in the range of a few days. Thus, the high values for the current features aroundFigureFigure the 7.7.typhoon Ocean currents’ eyes are manifestationsmanifestations not found (colors)(colors)in OSCA fromfromR currents, dual-polarizeddual-polarized which ScanSARScanSAR may be images.images. induced TheThe isoclinesisoclinesby the high windsareare near thethe OSCARtheOSCAR typhoon currents.currents. eyewall.

Thus, through these comparisons, we suggest that the backscatter features of the ocean currents extracted by our proposed approach correspond to the observed strong currents (>0.3 m/s) and the ocean front, even under TC conditions. Because it is difficult to distinguish the upper limits on the values in Figure 7 that were induced by strong currents and the ocean front, we therefore cannot apply this method to directly retrieve the ocean currents. However, this approach has the potential to provide validations of oceanic processes as simulated by numerical models, which is very important for the ocean studies [12], especially for high spatial resolutions. Moreover, as noted, OSCAR currents are 5-day composites, whereas SAR provides instantaneous snapshots with the typical revisit times being in the range of a few days. Thus, the high values for the current features around the typhoon eyes are not found in OSCAR currents, which may be induced by the high winds near the typhoon eyewall. Figure 8.8. DecompositionsDecompositions of of OSCAR OSCAR currents currents in( ain)zonal (a) zonal direction direction (positive (positive is eastward is eastward and negative and negativeis westward); is westward); and (b) meridional and (b) directionmeridional (positive direction is northward (positive andis northward negative is southward).and negative The is windsouthward). vectors The (black) wind as vectors shown in(black) Figure as5 shown. in Figure 5.

4. DiscussionIn Figure 7, the isoclines that are indicated by the red dashed line-B are similar to those of the red dashedThe approach line-C, whereasproposed the in backscatterthis study is features based on: from (1) SAR our imagesrecent study near the investigating two lines are different totally mechanismsdifferent. These of the differences dual-polarized are due ScanSAR to the ocean observations current front under along TC line-Bconditions where and the (2) meridional different observedcurrents movefeatures in differentcorresponding directions, to the as tidal shown current in Figures in the8 b.Bay Although of Fundy the for absolutethe different values polarized of the channelsOSCAR currents (Figure around3). Although the two the lines results are similar, agree the well directional with the distributions 5-day composite are different. currents from OSCARThus, retrieved through from these altimeters, comparisons, there we is suggest still furt thather the study backscatter that is featuresneeded ofin theorder ocean to currentsretrieve extracted by our proposed approach correspond to the observed strong currents (>0.3 m/s) and the ocean front, even under TC conditions. Because it is difﬁcult to distinguish the upper limits on the Figure 8. Decompositions of OSCAR currents in (a) zonal direction (positive is eastward and values in Figure7 that were induced by strong currents and the ocean front, we therefore cannot apply negative is westward); and (b) meridional direction (positive is northward and negative is this method to directly retrieve the ocean currents. However, this approach has the potential to provide southward). The wind vectors (black) as shown in Figure 5. validations of oceanic processes as simulated by numerical models, which is very important for the ocean4. Discussion studies [12], especially for high spatial resolutions. Moreover, as noted, OSCAR currents are 5-day composites, whereas SAR provides instantaneous snapshots with the typical revisit times being in theThe range approach of a few proposed days. Thus, in thethis highstudy values is based for theon: current (1) our features recent study around investigating the typhoon different eyes are notmechanisms found in OSCARof the dual-polarized currents, which ScanSAR may be induced observations by the under high winds TC conditions near the typhoon and (2) eyewall. different observed features corresponding to the tidal currents in the Bay of Fundy for the different polarized channels (Figure 3). Although the results agree well with the 5-day composite currents from OSCAR retrieved from altimeters, there is still further study that is needed in order to retrieve

Remote Sens. 2018, 10, 875 9 of 11

4. Discussion The approach proposed in this study is based on: (1) our recent study investigating different mechanisms of the dual-polarized ScanSAR observations under TC conditions and (2) different observed features corresponding to the tidal currents in the Bay of Fundy for the different polarized channels (Figure3). Although the results agree well with the 5-day composite currents from OSCAR retrieved from altimeters, there is still further study that is needed in order to retrieve precise estimates for surface currents from SAR images, especially under hurricane conditions. However, this approach provides insight into the SAR image through the strong wind signature that is generated by TC conditions, and also provides a methodology to extract surface current features by removing the strong wind signature. Because of the strong characteristics that are related to extreme winds in TC conditions, the surface current features from the original VV-polarized SAR image (Figure2a) are not as obvious as the low wind conditions in Figure3a,c. However, when we remove the signal that is related to the winds from the VV-polarized SAR image, the extracted current features appear to agree with the 5-day composite OSCAR currents (Figure7). The dominant current features (area A in Figure7) represent the current modulations on the sea surface roughness generated by the wind, which demonstrates that the sea surface roughness can still be enhanced under extreme wind conditions. Regarding the oceanic feature around line-B, previous studies have suggested that it is a front under low or moderate winds [7,24]. Kudryavtsev et al. [5] indicated that the ocean surface current signatures are mostly dominated by non-Bragg backscatter through the analysis of the VV and HH polarizations from quad-polarized RADARSAT-2 SAR images. However, in this study, we remove the non-Bragg backscatter before extracting the current features. Our results are partly veriﬁed by the composite OSCAR currents and by our analysis, and the differences are due to spatial resolutions. The spatial resolution used here is about 5 km, compared to about 5 m in the azimuth direction for their studies. Finally, heavy precipitation is always associated with typhoons and can attenuate the radar signal [23]. However, the surface current features around area A and line-B in Figure7 are evident, which implies that these features are not due to rain, or that the rain rates around area A and line-B are not sufﬁciently high enough to obscure the modulations due to the currents in the C-band RADARSAT-2 dual-polarized (VV and VH) ScanSAR images.

5. Conclusions To extract the current backscatter features imaged by SAR under extreme wind conditions, we propose an approach for C-band RADARSAT-2 dual-polarized (VV and VH) ScanSAR images. This approach is based on the fact that ocean winds and surface currents are both imaged by two channels at the same time (VV and VH). Because of the different roles of the two main backscatter mechanisms for the two different channels, we assume that the sea surface waves on the scales of the radar microwaves are modulated by the surface currents, and that these are only imaged by VV-polarization backscatter, and not by VH-polarization data. Thus, the process is simpliﬁed, and we retrieve the wind from VH-polarization backscatter and then extract the current features from the VV-polarization backscatter. Therefore, the dual-polarized ScanSAR mode makes it possible to detect the ocean surface features in the backscatter signal. Comparisons to the OSCAR currents from satellite altimeters suggest that the surface current features derived from SAR agree well with OSCAR currents under Typhoon Lan (2017) with extreme winds in regard to: (1) strong currents opposing the wind directions and (2) ocean fronts with opposing meridional directions. We also note that although this approach extracts possible current features under extreme winds in Typhoon Lan (2017), it is still a simpliﬁed process that is based on the assumed approximation that the currents have no effect on the VH-polarized SAR image. With more observations and the development of backscattering theories, the relationship between the VH-polarized SAR image and ocean currents can be developed. However, the basic idea of this study remains meaningful that the two variabilities (winds and currents) can be detected using two different channel observations Remote Sens. 2018, 10, 875 10 of 11 simultaneously. The C-band Sentinel-1 SAR also has the dual-polarization (VV and VH) mode [25]. So, the approach or basic idea proposed here should possibly be applied to Sentinel-1 for ocean current feature detections.

Author Contributions: G.Z. was responsible for designing this study, processing datasets, building the model, and writing-Original Draft Preparation; W.P. was responsible for the supervision, writing-review, and editing. Funding: This research was funded by an Open Fund of the Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University (Grant No. KLGIS2017A06), in part by the Canadian Space Agency SWOT and Office of Energy Research and Development (OERD) Programs, and in part by the National Natural Science Youth Foundation of China under Grant 41706193. Acknowledgments: The authors thank the Canadian Space Agency for providing RADARSAT-2 data, PO.DAAC for supplying OSCAR currents (http://dx.doi.org/10.5067/OSCAR-03D01), and Japan Meteorological Agency best track data (http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/Besttracks/). Conflicts of Interest: The authors declare no conflict of interest.

Appendix A The abbreviations used in this study are as following:

ADCP acoustic Doppler current proﬁler C-3PO C-band Cross-polarization Coupled-Parameters Ocean CSA Canadian Space Agency HF radar High-frequency radar NRCS Normalized Radar Cross Section OSCAR Ocean Surface Current Analysis PDF probability density function PO.DAAC Physical Oceanography Distributed Active Archive Center SAR Synthetic Aperture Radar ScanSAR Synthetic Aperture Radar in Scan mode SHEW Symmetric Hurricane Estimates for Wind TC Tropical Cyclones UTC Coordinated Universal Time VH Transmits on Vertical (V) polarization but receives on Horizontal (H) polarization VV Transmits on Vertical (V) polarization receives on Vertical (V) polarization

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