C-band Geophysical Model Function Research Articles

Verification of C-Band Geophysical Model Function for Wind Speed Retrieval in the Open Ocean and Inland Water Conditions

Verification of the C-band geophysical model functions (GMF) for the open ocean and the Gorky reservoir was carried out using Sentinel-1 IW-mode Synthetic aperture radar (SAR) images. CMOD5.N, CMOD7, GMF for the Caspian Sea, and CSARMOD2 were considered. The motivation for this study is concerned with the clarification of applying C-band GMFs for SAR images including for the conditions of inland water bodies, as well as with the study of the influence of various wind speed direction sources on the results of wind speed magnitude retrieval for ocean conditions. Comparison of wind speed from the CMOD5.N algorithm using wind direction data from NOAA NDBC oceanographic buoys together with the data provided by NCEP reanalysis data showed that regardless of the geographic location, the result does not depend significantly on the choice of the wind direction source. Novel results of CMOD5.N, CMOD7, GMF for the Caspian Sea, and CSARMOD2 applications to the conditions of the Gorky reservoir are presented. The comparison of these results with the meteorological station measurements showed the best agreement for CMOD5.N. The preliminary results on the construction of new C-band GMF adjusted to the Gorky Reservoir have shown statistical parameters better than for Caspian Sea GMF and CSARMOD2.

Uncertainty Analysis in SAR Sea Surface Wind Speed Retrieval through C-Band Geophysical Model Functions Inversion

The purpose of the study is to assess the suitability of synthetic aperture radar (SAR) data to provide sea surface wind (SSW) fields along with a spatial distribution of both SSW speed and direction uncertainty. A simple methodology based on geophysical model function (GMF) inversion to obtain a spatial distribution of both SSW speed and its uncertainty is proposed. Exploiting a dataset of Sentinel-1 images, a sensitivity analysis of the SSW speed uncertainty is carried out on both the uncertainties and the mean values of SAR normalised radar cross section (NRCS), incidence angle and SSW direction, at different spatial scales. The results show that SSW speed uncertainty significantly increases with wind vector cell (WVC) dimension. Moreover, the dominant contribution to the SSW speed uncertainty due to both NRCS and SSW direction uncertainty must always be taken into account. A better precision and accuracy in the estimation of SSW speed and its uncertainty is evidenced by C-band model 7 (CMOD7) GMF rather than the C-band model 5.N (CMOD5.N). To evaluate the results of SSW retrievals, wind data from the European Centre for Medium-Range Weather Forecasts (ECMWF) model are also exploited for comparisons. Findings indicate a high correlation between the uncertainty from SAR estimations and that from the comparison of SAR vs. ECMWF.

Comparison of the application of co- and cross-polarized sentinel-1 synthetic aperture radar data to tropical cyclone evaluation

ABSTRACT Spaceborne synthetic aperture radar (SAR) is considered one of the most powerful sensors for tropical cyclone assessment. In this study, 14 tropical cyclone (TC) events captured by the Sentinel-1A/B satellite are collected to compare the similarities, differences and quantitative relationships between co- and cross-polarization SAR applications for tropical cyclone evaluation. This study uses multiple co-polarized C-band geophysical model functions (GMFs) and cross-polarized ocean backscatter models, including a C-band Cross-Polarized Ocean Backscatter (C-2PO) model and a C-band Cross-Polarization Coupled-Parameters Ocean (C-3PO) model to estimate the sea surface tropical cyclone wind field. The results reveal that the structure values of the wind circle radius by co-polarization SAR wind inversion are similar to those of cross-polarization. The combination of the two polarization modes can get a more accurate estimation on tropical cyclone rating of the intensity level and hazard of the potential tropical cyclone damages. In addition, a corresponding formula with a correlation coefficient of 0.677 between co- and cross-polarization at 10-km resolution is obtained.

On the Nonlinear Mapping of an Ocean Wave Spectrum into a New Polarimetric SAR Image Spectrum

AbstractA new nonlinear transformation relation is derived to describe the mapping of a two-dimensional ocean wave spectrum into a new polarimetric synthetic aperture radar (SAR) image spectrum. It is a further expansion and improvement of Hasselmann’s work. First, the nonlinear mapping relation proposed is derived on the basis of a new polarimetric SAR image instead of the conventional single-polarization SAR image. Second, the nonlinear mapping relation no longer includes the complex hydrodynamic modulation transfer function (MTF). Third, the traditional tilt MTF, which is not accurate enough for the retrieval of sea wave spectrum, is replaced by an empirical tilt MTF derived on the basis of the C-band geophysical model function [i.e., C-band synthetic aperture radar (CSAR) normalized radar cross section (NRCS) model]. A sea wave spectrum retrieval algorithm is then proposed that is based on the new nonlinear mapping and the empirical tilt MTF. The retrieved spectra from C-band polarizedRADARSAT-2SAR images are compared with the results obtained by the ECMWF Ocean Wave Model (ECWAM) and buoy measurements.

A C-Band Geophysical Model Function for Determining Coastal Wind Speed Using Synthetic Aperture Radar

A new geophysical model function (GMF), called C_SARMOD2, has been developed to relate high-resolution C-band normalized radar cross section (NRCS), acquired in VV polarization over the ocean, to the 10-m height wind speed. A total of 3078 RADARSAT-2 and Sentinel-1A VV-polarized synthetic aperture radar (SAR) images, acquired under different wind speed conditions, were collocated with in situ buoy measurements. The paired dataset was used to derive transfer functions and coefficients of C_SARMOD2, and then to validate the wind speed retrievals. The comparison between SAR-retrieved wind speeds and buoy measurements show almost no bias and a root mean square error of 1.84 m/s. Two representative quad- and dual-polarization SAR images, acquired from coastal regions, are used as case studies to examine C_SARMOD2 performances. The case study and statistical validation results suggest that the proposed C_SARMOD2 has the potential to measure coastal wind speeds at subkilometer resolutions. Although derived from low resolution NRCS measurements, this study also confirms the great robustness of CMOD5.N and recent CMOD7 when applied to SAR data. In addition, it shows that with the new generation of SAR satellite-borne sensors, it is no longer mandatory to rely on scatterometers in order to build a GMF, which will be used for SAR applications. Such an approach is particularly important in view of the upcoming RADARSAT Constellation Mission with new polarization configurations. Moreover, it also opens new perspectives on the derivation of GMFs in HH-polarization. However, these results also suggest that for coastal areas, the increase of the resolution to define the GMF is less important than adding other geophysical parameters to improve wind retrieval performance. This advocates for the necessity of revisiting the methodologies for ocean surface wind speed measurements in coastal areas.

Spatial Scale Effect on Wind Speed Retrieval Accuracy Using Sentinel-1 Copolarization SAR

High-spatial-resolution wind fields derived from synthetic aperture radar (SAR) instruments are crucial to a wide range of applications. However, the spatial scale effect on wind speed retrieval accuracy has seldom been reported. For the purpose of understanding this issue, this letter makes a quality assessment of wind speed retrieval accuracy based on four commonly used C-band geophysical model functions (CMOD4, CMOD-IFR2, CMOD5, and CMOD5.N) at spatial resolutions ranging from 50 m to 50 km using Sentinel-1 interferometric wide (IW) swath mode images. Our results show that the CMOD5 function is the most effective among these functions, owing to a low root-mean-square error (RMSE) of 1.17 m/s and a bias of −0.28 m/s for wind speed retrieval at a spatial resolution of 500 m. It is further observed that the variance of wind speeds retrieved from copolarized SAR images decreases exponentially with the decrease of spatial resolutions. For Sentinel-1 IW mode images, the variance of wind speeds retrieved with CMOD5 decreases rapidly from 50 to 500 m, with a drop in RMSE of 40%, and thereafter levels off. Thus, a spatial resolution of 500 m, with the CMOD5 function, is recommended optimal in this letter, for wind speed retrieval using Sentinnel-1 IW mode data.

A Preliminary Analysis of Wind Retrieval, Based on GF-3 Wave Mode Data.

This paper presents an analysis of measurements of the normalized radar cross-(NRCS) in Wave Mode for Chinese C-band Gaofen-3(GF-3) synthetic aperture radar (SAR). Based on 2779 images from GF-3 quad-polarization SAR in Wave Mode and collocated wind vectors from ERA-Interim, this experiment verifies the feasibility of using ocean surface wind fields and VV-polarized NRCS to perform normalized calibration. The method uses well-validated empirical C-band geophysical model function (CMOD4) to estimate the calibration constant for each beam. In addition, the relationship between cross-pol NRCS and wind vectors is discussed. The cross-pol NRCS increases linearly with wind speed and it is obviously modulated by the wind direction when the wind speed is greater than 8 m/s. Furthermore, the properties of the polarization ratio, denoted PR, are also investigated. The PR is dependent on incidence angle and azimuth angle. Two empirical models of the PR are fitted, one as a function of incidence angle only, the other with additional dependence on azimuth angle. Assessments show that the retrieved from new PR models as well as is in good agreement with extracted from SAR images directly.

Meteo-Marine Parameters from Sentinel-1 SAR Imagery: Towards Near Real-Time Services for the Baltic Sea

A method for estimating meteo-marine parameters from satellite Synthetic Aperture Radar (SAR) data, intended for near-real-time (NRT) service over the Baltic Sea, is presented and validated. Total significant wave height data are retrieved with an empirical function CWAVE_S1-IW, which combines spectral analysis of Sentinel-1A/B Interferometric Wide swath (IW) subscenes with wind data derived with common C-Band Geophysical Model Functions (GMFs). In total, 15 Sentinel-1A/B scenes (116 acquisitions) over the Baltic Sea were processed for comparison with off-shore sea state measurements (52 collocations) and coastal wind measurements (357 colocations). Sentinel-1 wave height was spatially compared with WAM wave model results (Copernicus Marine Environment Monitoring Service (CMEMS). The comparison of SAR-derived wave heights shows good agreement with measured wave heights correlation r of 0.88 and with WAM model (r = 0.85). The wind speed estimated from SAR images yields good agreement with in situ data (r = 0.91). The study demonstrates that the wave retrievals from Sentinel-1 IW data provide valuable information for operational and statistical monitoring of wave conditions in the Baltic Sea. The data is valuable for model validation and interpretation in regions where, and during periods when, in situ measurements are missing. The Sentinel-1 A/B wave retrievals provide more detailed information about spatial variability of the wave field in the coastal zone compared to in situ measurements, altimetry wave products and model forecast. Thus, SAR data enables estimation of storm locations and areal coverage. Methods shown in the study are implemented in NRT service in German Aerospace Center’s (DLR) ground station Neustrelitz.

Development and validation of an ocean wave retrieval algorithm for VV-polarization Sentinel-1 SAR data

The purpose is to study the accuracy of ocean wave parameters retrieved from C-band VV-polarization Sentinel-1 Synthetic Aperture Radar (SAR) images, including both significant wave height (SWH) and mean wave period (MWP), which are both calculated from a SAR-derived wave spectrum. The wind direction from in situ buoys is used and then the wind speed is retrieved by using a new C-band geophysical model function (GMF) model, denoted as C-SARMOD. Continuously, an algorithm parameterized first-guess spectra method (PFSM) is employed to retrieve the SWH and the MWP by using the SAR-derived wind speed. Forty–five VV-polarization Sentinel-1 SAR images are collected, which cover the in situ buoys around US coastal waters. A total of 52 subscenes are selected from those images. The retrieval results are compared with the measurements from in situ buoys. The comparison performs good for a wind retrieval, showing a 1.6 m/s standard deviation (STD) of the wind speed, while a 0.54 m STD of the SWH and a 2.14 s STD of the MWP are exhibited with an acceptable error. Additional 50 images taken in China’s seas were also implemented by using the algorithm PFSM, showing a 0.67 m STD of the SWH and a 2.21 s STD of the MWP compared with European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis grids wave data. The results indicate that the algorithm PFSM works for the wave retrieval from VV-polarization Sentinel-1 SAR image through SAR-derived wind speed by using the new GMF C-SARMOD.

Ocean Wind Study Using Simulated RCM Compact-Polarimetry SAR

. The incidence angle, wind speed, and wind direction dependence of compact polarimetry (CP) synthetic aperture radar (SAR) parameters are presented for open water. Selected CP parameters are related to C-band geophysical model function (CMOD) output. Wind speeds range between 0 and 24 m/s, and incidence angles range between 18 and 50°. SAR data are coincident with meteorological buoy data. CP parameters are simulated from polarimetric RADARSAT-2 data and emulate data available on the pending RADARSAT Constellation Mission (RCM). Analysis is performed for 20 CP parameters, based on RADARSAT-2 images. Five linear-polarization SAR parameters are included for comparison. Results show robust relationships for CP parameters related to CMOD. For CP parameters unrelated to CMOD, results provide first-, second-, or third-order linear regression models, as functions of incidence angle, wind speed, wind direction, or combinations thereof. These models provide a set of values for comparison with sea ice or other features on, or adjacent to, open water. The results of this study are of value to the Canadian Ice Service of the Meteorological Service of Canada, as well as other government of Canada departments, for implementing CP SAR data in their operational workflows once RCM is launched.Résumé. La dépendance à l’angle d’incidence, à la vitesse et à la direction du vent des paramètres mesurés en polarimétrie compacte (CP) est présentée pour l’eau libre. Les paramètres de CP sélectionnés sont liés aux sorties de la fonction du modèle géophysique en bande C (CMOD). Les vitesses du vent varient entre 0 et 24 m/s, et les angles d’incidence varient entre 18 et 50 degrés. Les données SAR coïncident avec les données des bouées météorologiques. Les paramètres en CP sont simulés à partir des données polarimétriques de RADARSAT-2, et ils simulent les données qui seront disponibles à partir de la mission de la Constellation RADARSAT prévue (MCR). L’analyse est effectuée pour 20 paramètres en CP, sur la base des images RADARSAT-2. Cinq paramètres SAR en polarisation linéaire sont inclus pour comparaison. Les résultats montrent des relations robustes pour les paramètres en CP liés à CMOD. Pour les paramètres en CP non liés à la CMOD, les résultats fournissent des modèles de régression linéaire de première, deuxième ou troisième ordre, en fonction de l’angle d’incidence, de la vitesse et de la direction du vent, ou des combinaisons de ceux-ci. Ces modèles fournissent un ensemble de valeurs de comparaison avec la glace de mer; ou d’autres éléments sur, ou à proximité de, l’eau libre. Les résultats de cette étude seront importants pour le Service canadien des glaces du Service météorologique du Canada, ainsi que pour d’autres ministères du gouvernement du Canada, pour mettre en œuvre les données SAR en CP dans leur flux de travaux opérationnels, une fois la MCR lancée.

Sea Surface Wind Retrievals from SIR-C/X-SAR Data: A Revisit

The Geophysical Model Function (GMF) XMOD1 provides a linear algorithm for sea surface wind field retrievals for the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR). However, the relationship between the normalized radar cross section (NRCS) and the sea surface wind speed, wind direction and incidence angles is non-linear. Therefore, in this paper, XMOD1 is revisited using the full dataset of X-SAR acquired over the ocean. We analyze the detailed relationship between the X-SAR NRCS, incidence angle and sea surface wind speed. Based on the C-band GMF CMOD_IFR2, an updated empirical retrieval model of the sea surface wind field called SIRX-MOD is derived. In situ buoy measurements and the scatterometer data of ERS-1/SCAT are used to validate the retrieved sea surface wind speeds from the X-SAR data with SIRX-MOD, which respectively yield biases of 0.13 m/s and 0.16 m/s and root mean square (RMS) errors of 1.83 m/s and 1.63 m/s.

Self-Consistency of Marine Surface Wind Vectors Observed by ASCAT

Marine surface wind vectors observed by the Advanced Scatterometer on the MetOp-A satellite are evaluated by assessing their self-consistency. Global statistics on wind speeds and directions were calculated from the data for a period of one year. The wind speed histograms exhibited a clear dependence on the cross-track wind vector cell (WVC) location, which corresponds to the incidence angle. This trend was reflected in the higher order statistics (standard deviation, skewness, and kurtosis) of the wind speed distribution. The histograms of the wind directions relative to the satellite flight direction clearly showed systematic errors relative to the antenna beam directions. The number density of the wind directions exhibited a systematic pattern relative to the antenna beam directions, and the pattern varied with wind speed and cross-track WVC location. These systematic errors in the wind speed and direction may affect the divergence/convergence and rotation of the wind field. The results of this study suggest the need for further refinements of the wind retrieval algorithms and the C-band geophysical model function. It was also confirmed that the evaluation technique based on the statistical distributions of scatterometer-derived vector winds is effective for identifying systematic errors in the wind speeds and directions.

Cross-Polarized Synthetic Aperture Radar: A New Potential Measurement Technique for Hurricanes

We present an empirical C-band Cross-Polarization Ocean (C-2PO) model for wind retrievals from synthetic aperture radar (SAR) data collected by the RADARSAT-2 satellite. The C-2PO model relates normalized radar cross section (NRCS) in cross polarization to wind speed at 10-m height. This wind retrieval model has the characteristic that it is independent of wind direction and radar incidence angle but is quite linear with respect to wind speed. To evaluate the accuracy of the proposed model, winds with a resolution on the scale of 1 km were retrieved from a dual-polarization SAR image of Hurricane Earl on 2 September 2010, using the C-2PO model and compared with CMOD5.N, the newest available C-band geophysical model function (GMF), and validated with collocated airborne stepped-frequency microwave radiometer measurements and National Data Buoy Center data. Results suggest that for winds up to 38 m s−1, C-2PO has a bias of −0.89 m s−1 and a root-meansquare error of 3.23 m s−1 compared to CMOD5.N, which has a bias of −4.14 m s−1 and an rms difference of 6.24 m s−1. Similar results are obtained from Hurricane Ike, comparing wind retrievals from C-2PO and CMOD5.N with H*Wind data. The advantage of C-2PO over CMOD5.N and other GMFs is that it does not need any external wind direction and radar incidence angle inputs. Moreover, in the presently available quad-polarization dataset, C-2PO has the feature that the cross-polarized NRCS linearly increases even for wind speeds up to 26 m s−1 and reproduces the hurricane eye structure well, thereby providing a potential technique for hurricane observations from space.

Marine wind speed retrieval from RADARSAT-2 dual-polarization imagery

New regression models for the retrieval of marine wind speeds from RADARSAT-2 dual-polarization images and results of the comparative analysis of these models with the C-band geophysical model function CMOD_IFR2 are presented. In the two new models, synthetic aperture radar (SAR) co-polarization (VV) and cross-polarization (VH) radar cross-sections, instrument noise floor, and antenna beam incidence angle were used as independent variables. In addition, one of the models also included wind direction input. To build and test the empirical relationships between wind speed and RADARSAT-2 parameters, we created a database containing 570 samples of ocean buoy wind speed observations collocated and coincident with the information obtained from SAR images. The models were tested on independent wind speed data reaching up to 40 knots. The CMOD_IFR2 was also tested on the same data. Analysis of the test results proved a higher accuracy of the new regression models, including the model without wind direction, as compared with CMOD_IFR2, which uses wind direction information. This means that the degraded accuracy of the SAR wind retrieval model without input of the wind direction can be compensated for by using cross-polarization backscatter information. The models were validated through current buoy and image data, provided by the quasi-operational Wind Information Processing System (WIPS). The developed models have been integrated into and are currently functioning within WIPS (at the Meteorological Service of Canada).

Ocean Surface Wind Speed of Hurricane Helene Observed by SAR

Abstract The hurricanes can be detected by many remote sensors, but synthetic aperture radar (SAR) can yield high-resolution (sub-kilometer) and low-level wind information that cannot be seen below the cloud by other sensors. In this paper, an assessment of SAR capability of monitoring high-resolution hurricane was conducted. A case study was carried out to retrieve ocean surface wind field from C-band RADARSAT-1 SAR image which captured the structure of hurricane Helene over the Atlantic Ocean on 20 September, 2006. With wind direction from the outputs of U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) model, C-band geophysical model functions (GMFs) which describe the normalized radar cross section (NRCS) dependence on the wind speed and the geometry of radar observations (i.e., incidence angle and azimuth angle with respect to wind direction) such as CMOD5 and newly developed CIWRAP models have been tested to extract wind speed from SAR data. The SAR retrieved ocean surface winds were compared to the aircraft wind speed observations from stepped frequency microwave radiometer (SFMR). The results show the capability of hurricane wind monitoring by SAR.

Validation of Backscatter Measurements from the Advanced Scatterometer on MetOp-A

Abstract The Advanced Scatterometer (ASCAT) on the Meteorological Operational (MetOp) series of satellites is designed to provide data for the retrieval of ocean wind fields. Three transponders were used to give an absolute calibration and the worst-case calibration error is estimated to be 0.15–0.25 dB. In this paper the calibrated data are validated by comparing the backscatter from a range of naturally distributed targets against models developed from European Remote Sensing Satellite (ERS) scatterometer data. For the Amazon rainforest it is found that the isotropic backscatter decreases from −6.2 to −6.8 dB over the incidence angle range. The ERS value is around −6.5 dB. All ASCAT beams are within 0.1 dB of each other. Rainforest backscatter over a 3-yr period is found to be very stable with annual changes of approximately 0.02 dB. ASCAT ocean backscatter is compared against values from the C-band geophysical model function (CMOD-5) using ECMWF wind fields. A difference of approximately 0.2 dB below 55° incidence is found. Differences of over 1 dB above 55° are likely due to inaccuracies in CMOD-5, which has not been fully validated at large incidence angles. All beams are within 0.1 dB of each other. Backscatter from regions of stable Antarctic sea ice is found to be consistent with model backscatter except at large incidence angles where the model has not been validated. The noise in the ice backscatter indicates that the normalized standard deviation of the backscatter values Kp is around 4.5%, which is consistent with the expected value. These results agree well with the expected calibration accuracy and give confidence that the calibration has been successful and that ASCAT products are of high quality.

Comparison of C-Band Scatterometer CMOD5.N Equivalent Neutral Winds with ECMWF

Abstract This article describes the evaluation of a C-band geophysical model function called C-band model 5.N (CMOD5.N). It is used to provide an empirical relation between backscatter as sensed by the spaceborne European Remote Sensing Satellite-2 (ERS-2) and Advanced Scatterometer (ASCAT) scatterometers and equivalent neutral ocean vector wind at 10-m height (neutral surface wind) as function of scatterometer incidence angle. CMOD5.N embodies a refit of CMOD5, a C-band model function, which was previously derived to obtain nonneutral surface wind, in such a way that its 28 tunable coefficients lead, for a given backscatter observation, to an enhancement of 0.7 m s−1 in wind speed. The value of 0.7 m s−1 is chosen to be independent of wind speed and incidence angle, and it incorporates the average difference between neutral and nonneutral wind (∼0.2 m s−1) and for a known bias of CMOD5 (∼0.5 m s−1) when compared to buoy wind data. The quality of the CMOD5.N fit is successfully tested for the Active Microwave Instrument (AMI) scatterometer on ERS-2 and ASCAT instrument on Meteorological Operational-A (MetOp-A) for July 2007 and January 2008. ASCAT and ERS-2 wind speed obtained from CMOD5.N compares well on average with operational neutral wind from the European Centre for Medium-Range Weather Forecasts (ECMWF). In comparison with nonneutral wind, the local, seasonally dependent biases between scatterometer and ECMWF model are reduced. Besides effects introduced by sea state, orography, and ocean currents, a residual stability-dependent bias between scatterometer and neutral wind remains, which is likely connected to a nonoptimality in the ECMWF boundary layer formalism that is reported in the literature.

Double Structure of the Wind Jet through the Tsushima Strait

We have investigated the northeasterly/southwesterly wind jets blowing through the Tsushima Strait from two case studies. Using high-resolution winds derived from SAR, we have presented the detailed structure of wind in the strait. The general ∞ow is generally close to geostrophic wind in the strait, inferring from the seal level pressure flelds. Wind jets are induced by two channels and by the terrestrial gap at the center of the Tsushima Island. The wind jets are clearly separated from the coastlines. The Tsushima Strait is a generic term indicating the sea area between the Korean Peninsula and the Japanese archipelago, with the Japanese islands of Honshu to the east, Kyushu to the south and the Goto Islands to the southeast (Figure 1). In the center of the strait, a slender island, the Tsushima Island is located along the strait. This island principally consists of two mountainous islands. The Tsushima Island divide the strait into eastern and western channels; the width and maximum depth are 140km and 110m in the eastern channel, and 40km and 200m in the western channel, respectively. Both channels connect the East China Sea and the Japan Sea. From these geographical conditions, the Tsushima Strait is one of the most important sea areas where the continuous and intense monitoring researches are required from oceanographic and meteorological point of views as well as marine security point of view. Extensive previous studies have investigated the Tsushima Strait hydrography by considering wind efiects on it. However, higher-resolution and wider-area wind observations are required for better understanding of the oceanographic and meteorological environment because of the complex coastal topography of the region. This is because few studies pay attention to the formation of wind jets in the strait, wind jet structures, and the role of the Tsushima Island on the formation of the wind jets. These are open issues at the present stage. The purpose of this paper is to investigate the wind blowing through the Tsushima Strait by using high-resolution satellite wind measurements. We look into the evolution and distribution of the wind jets during representative time periods and illustrate the contribution of the Tsushima Island to the wind jet formation. Speciflc questions we would like to address are: First question is typical structures of the wind jets found in the Tsushima Strait. When the wind blows through the Tsushima Strait in southwest-northeast direction, strong winds are formed. Second, what are the roles of the Tsushima Island on the formation of the wind jets? 2. DATA We analyze wind flelds derived from two SARs. They are the European Space Agency (ESA) Environmental Satellite (ENVISAT) Advanced Synthetic Aperture Radar (ASAR) and the Cana- dian RADARSAT-1. Both SARs operate at C-band (5.3GHz). While RADARSAT operates in horizontal (HH) polarization, ENVISAT/ASAR operates in HH or vertical (VV) polarization. In this study, we use wide-swath or ScanSAR mode products. That is, the ENVISAT/ASAR Wide- swath mode images covers an area of approximately 500 £ 500km, with a pixel size of 75m. The RADARSAT ScanSAR Narrow mode image covers an area of approximately 300 £ 300km, with a pixel size of 25m. Wind speed maps are derived from the ENVISAT/ASAR and RADARSAT images by applying SAR wind retrieval by using CMOD IFR2 scatterometer model function (1) and wind direction from objective analysis data (GPV: Grid Point Data). In cases of HH polarization images, a polarization ratio conversion factor (2) is applied. While the C-band geophysical model function is originally developed for VV polarized radar cross section, the polarization ratio conversion factor enables to convert it to HH polarized radar cross section. It has been shown by numerous studies that wind speeds can be retrieved from ENVISAT/ASAR (3) and RADARSAT-1 (4) with a root mean square error of less than 2m/s and with negligible bias.