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Sea Surface Roughness Observed by High Resolution Radar

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".

Deadline for manuscript submissions: closed (31 December 2018) | Viewed by 54798

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Special Issue Editors

Dr. Atsushi Fujimura

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Guest Editor

Marine Laboratory, University of Guam, Mangilao, GU 96923, USA
Interests: plankton ecology; harmful algal bloom; biogeochemistry; remote sensing; biophysical interactions; coastal oceanography; computational fluid dynamics; coral reef ecology
Special Issues, Collections and Topics in MDPI journals

Dr. Susanne Lehner

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Guest Editor

German Aerospace Center, Muenchner Strasse 20, 82234 Wessling, Germany
Interests: ocean remote sensing; synthetic aperture radar; severe weather; tropical cyclones; ocean waves

Dr. Alex Soloviev

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Guest Editor

Nova Southeastern University, 8000 N. Ocean Dr., Dania Beach, FL 33029, USA
Interests: near-surface of the ocean; hurricane physics; computational fluid dynamics; remote sensing; coastal ocean; circulation marine and environment engineering

Dr. Xiaofeng Li

E-Mail Website
Guest Editor

NCWCP - E/RA3, 5830 University Research Court, College Park, MD 20740, USA
Interests: AI oceanography; big data; ocean remote sensing; physical oceanography; boundary layer meteorology; synthetic aperture radar imaging mechanism; multiple-polarization radar applications; satellite image classification and segmentation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are happy to invite you to submit a paper to Remote Sensing for a Special Issue, “Sea Surface Roughness Observed by High Resolution Radar”, which cooperates with the 2018 Ocean Sciences Meeting (https://agu.confex.com/agu/os18/preliminaryview.cgi/Session28340).

Using various radar frequencies, resolutions, and modes of polarization, sea surface features have been analyzed by many research groups, bringing together very different datasets, thus allowing for new insights in small-scale processes at a larger areal coverage.

This Special Issue aims at investigating sea surface features detected by high spatial resolution radars, such as synthetic aperture radar (SAR). Such sea surface features include, but are not limited to: Upwelling, oceanic fronts, coastal processes on reefs, lee waves, swell, wind shadows, wind rolls, internal structures of tropical cyclones, oil seepage and natural slicks, internal waves, and turbulent effects due to wakes. We especially welcome studies on turbulent features at the air–sea interface at a resolution finer than 10 m, with a combination of remote sensing, in situ, and modeling techniques.

Thank you for your time and consideration.

Related References

Gebhardt, C.P.; Bidlot, J-R.; Gemmrich, J.; Lehner, S.; Pleskachevsky, A.; Rosenthal, W. Wave observation in the marginal ice zone with the TerraSAR-X satellite. Ocean Dyna. 2016, 66, 839–852.
Pleskachevsky, A.; Rosenthal, W.; Lehner, S. Meteo-marine parameters for highly variable environment in coastal regions from satellite radar images. ISPRS J. Photo. Remote Sens. 2016, 119, 464–484.
Ressel, R.; Frost, A.; Lehner, S. A neural network based classification for sea ice types on X-Band SAR images. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2015, 8, 3672–3680.
Lehner, S.; Pleskachevsky, A.; Bruck M. High resolution satellite measurements of coastal wind field and sea state. Int. J. Remote Sens. 2012, 33, 7337–7360.
Lehner, S.; Schulz-Stellenifleth, J.; Schättler, B.; Breit, H.; Horstmann, J. Wind and wave measurements using complex ERS-2 SAR wave mode data. IEEE Trans. Geosci. Remote Sens. 2000, 38, 2246–2257.
Lehner, S.; Horstmann, J.; Koch, W.; Rosenthal, W. Mesoscale wind measurements using recalibrated ERS SAR images. J. Geophys. Res. Oceans. 1998, 103, 7847–7856.

Dr. Atsushi Fujimura
Dr. Susanne Lehner
Dr. Alex Soloviev
Dr. Xiaofeng Li
Guest Editors

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Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

Radar
Sea surface roughness
Air-sea interaction
SAR

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Published Papers (12 papers)

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Editorial

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3 pages, 151 KiB

Open AccessEditorial

Sea Surface Roughness Observed by High Resolution Radar

by Atsushi Fujimura, Susanne Lehner, Alexander Soloviev and Xiaofeng Li

Remote Sens. 2019, 11(17), 2026; https://doi.org/10.3390/rs11172026 - 28 Aug 2019

Cited by 4 | Viewed by 2588

Abstract

Changes in the sea surface roughness are usually associated with a change in the sea surface wind field [...] Full article

(This article belongs to the Special Issue Sea Surface Roughness Observed by High Resolution Radar)

Research

Jump to: Editorial

20 pages, 6451 KiB

Open AccessArticle

Extension of Ship Wake Detectability Model for Non-Linear Influences of Parameters Using Satellite Based X-Band Synthetic Aperture Radar

by Björn Tings, Andrey Pleskachevsky, Domenico Velotto and Sven Jacobsen

Remote Sens. 2019, 11(5), 563; https://doi.org/10.3390/rs11050563 - 7 Mar 2019

Cited by 30 | Viewed by 4601

Abstract

The physics of the imaging mechanism underlying the emergence of ship wakes in Synthetic Aperture Radar (SAR) images has been studied in the past by many researchers providing a well-understood theory. Therefore, many publications describe how well ship wakes are detectable on SAR under the influence of different environmental conditions like sea state or local wind, ship properties like ship speed or ship heading, and image acquisition parameters like incidence angle or satellite heading. The increased imaging capabilities of current satellite SAR missions facilitate the collection of large datasets of moving vessels. Such a large dataset of high resolution TerraSAR-X acquisitions now enables the quantitative analysis of the previously formulated theory about the detectability of ship wakes using real data. In this paper we propose an extension of our wake detectability model by using a non-linear basis which allows consideration of all the influencing parameters simultaneously. Such an approach provides new insights and a better understanding of the non-linear influence of parameters on the wake detectability and their interdependencies can now be represented. The results show that the non-linear, interdependent influence of the different influencing parameters on the detectability of wakes matches well to the oceanographic expectations published in the past. Also possible applications of the model for the extraction of missing parameters and automatic for wake detection systems are demonstrated. Full article

(This article belongs to the Special Issue Sea Surface Roughness Observed by High Resolution Radar)

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21 pages, 8475 KiB

Open AccessArticle

A Wind Speed Retrieval Model for Sentinel-1A EW Mode Cross-Polarization Images

by Yuan Gao, Changlong Guan, Jian Sun and Lian Xie

Remote Sens. 2019, 11(2), 153; https://doi.org/10.3390/rs11020153 - 15 Jan 2019

Cited by 17 | Viewed by 4910

Abstract

In contrast to co-polarization (VV or HH) synthetic aperture radar (SAR) images, cross-polarization (CP for VH or HV) SAR images can be used to retrieve sea surface wind speeds larger than 20 m/s without knowing the wind directions. In this paper, a new wind speed retrieval model is proposed for European Space Agency (ESA) Sentinel-1A (S-1A) Extra-Wide swath (EW) mode VH-polarized images. Nineteen S-1A images under tropical cyclone condition observed in the 2016 hurricane season and the matching data from the Soil Moisture Active Passive (SMAP) radiometer are collected and divided into two datasets. The relationships between normalized radar cross-section (NRCS), sea surface wind speed, wind direction and radar incidence angle are analyzed for each sub-band, and an empirical retrieval model is presented. To correct the large biases at the center and at the boundaries of each sub-band, a corrected model with an incidence angle factor is proposed. The new model is validated by comparing the wind speeds retrieved from S-1A images with the wind speeds measured by SMAP. The results suggest that the proposed model can be used to retrieve wind speeds up to 35 m/s for sub-bands 1 to 4 and 25 m/s for sub-band 5. Full article

(This article belongs to the Special Issue Sea Surface Roughness Observed by High Resolution Radar)

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11 pages, 4456 KiB

Open AccessArticle

Group Line Energy in Phase-Resolved Ocean Surface Wave Orbital Velocity Reconstructions from X-band Doppler Radar Measurements of the Sea Surface

by Andrew J. Kammerer and Erin E. Hackett

Remote Sens. 2019, 11(1), 71; https://doi.org/10.3390/rs11010071 - 2 Jan 2019

Cited by 5 | Viewed by 3655

Abstract

The wavenumber-frequency spectra of many radar measurements of the sea surface contain a linear feature at frequencies lower than the first order dispersion relationship commonly referred to as the “group line”. Plant and Farquharson, showed numerically that the group line is at least partially caused by wave interference-induced breaking of steep short gravity waves. This paper uses two wave retrieval techniques, proper orthogonal decomposition (POD) and FFT-based dispersion curve filtering, to examine two X-band radar datasets, and compare wave orbital velocity reconstructions to ground truth wave buoy measurements within the field of view of the radar. POD allows group line energy to be retained in the reconstruction, while dispersion curve filtering removes all energy not associated with the first order dispersion relationship. Results show that when group line energy is higher or comparable to dispersion curve energy, the inclusion of this group line energy in phase-resolved orbital velocity reconstructions increases the accuracy of the reconstruction. This increased accuracy is demonstrated by higher correlations between POD reconstructed time series with buoy ground truth measurements than dispersion curve filtered reconstructions. When energy lying on the dispersion relationship is much higher than the group line energy, the FFT and POD reconstruction methods perform comparably. Full article

(This article belongs to the Special Issue Sea Surface Roughness Observed by High Resolution Radar)

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15 pages, 6136 KiB

Open AccessArticle

Analysis on the Effects of SAR Imaging Parameters and Environmental Conditions on the Standard Deviation of the Co-Polarized Phase Difference Measured over Sea Surface

by Andrea Buono, Carina Regina De Macedo, Ferdinando Nunziata, Domenico Velotto and Maurizio Migliaccio

Remote Sens. 2019, 11(1), 18; https://doi.org/10.3390/rs11010018 - 21 Dec 2018

Cited by 19 | Viewed by 5106

Abstract

This study aimed at analyzing the effect of Synthetic Aperture Radar (SAR) imaging parameters and environmental conditions on the standard deviation of the co-polarized phase difference (

σ_{φ_{C}}

) evaluated over sea surface. The latter was shown to be an important [...] Read more.

This study aimed at analyzing the effect of Synthetic Aperture Radar (SAR) imaging parameters and environmental conditions on the standard deviation of the co-polarized phase difference (

σ_{φ_{C}}

) evaluated over sea surface. The latter was shown to be an important polarimetric parameter widely used for sea surface target monitoring purposes. A theoretical model, based on the tilted-Bragg scattering, is proposed to predict the behavior of

σ_{φ_{C}}

against incidence angle for different roughness conditions. Then, a comprehensive experimental analysis, based on the processing of L-, C- and X-band polarimetric SAR scenes collected over different test areas under low-to-moderate wind conditions and covering a broad range of incidence angle, was carried out to discuss the effects of sensor’s and environmental parameters on sea surface

σ_{φ_{C}}

. Results show that SAR imaging parameters severely affect

σ_{φ_{C}}

, while the impact of meteo-marine conditions, under low-to-moderate wind regime, is almost negligible. Those outcomes have significant relevance to support the design of effective and robust algorithms for marine and maritime applications based on

σ_{φ_{C}}

, including the detection of metallic targets (ships and offshore infrastructures as oil/gas platforms, aquacultures, wind farms, etc.) and polluted areas. Full article

(This article belongs to the Special Issue Sea Surface Roughness Observed by High Resolution Radar)

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15 pages, 7357 KiB

Open AccessArticle

Ocean Wind Retrieval Models for RADARSAT Constellation Mission Compact Polarimetry SAR

by Tianqi Sun, Guosheng Zhang, William Perrie, Biao Zhang, Changlong Guan, Shahid Khurshid, Kerri Warner and Jian Sun

Remote Sens. 2018, 10(12), 1938; https://doi.org/10.3390/rs10121938 - 2 Dec 2018

Cited by 7 | Viewed by 3331

Abstract

We propose two new ocean wind retrieval models for right circular-vertical (RV) and right circular-horizontal (RH) polarizations respectively from the compact-polarimetry (CP) mode of the RADARSAT Constellation Mission (RCM), which is scheduled to be launched in 2019. For compact RV-polarization (right circular transmit and vertical receive), we build the wind retrieval model (denoted CoVe-Pol model) by employing the geophysical model function (GMF) framework and a sensitivity analysis. For compact RH polarization (right circular transmit and horizontal receive), we build the wind retrieval model (denoted the CoHo-Pol model) by using a quadratic function to describe the relationship between wind speed and RH-polarized normalized radar cross-sections (NRCSs) along with radar incidence angles. The parameters of the two retrieval models are derived from a database including wind vectors measured by in situ National Data Buoy Center (NDBC) buoys and simulated RV- and RH-polarized NRCSs and incidence angles. The RV- and RH-polarized NRCSs are generated by a RCM simulator using C-band RADARSAT-2 quad-polarized synthetic aperture radar (SAR) images. Our results show that the two new RCM CP models, CoVe-Pol and CoHo-POL, can provide efficient methodologies for wind retrieval. Full article

(This article belongs to the Special Issue Sea Surface Roughness Observed by High Resolution Radar)

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22 pages, 37030 KiB

Open AccessArticle

Capabilities of Chinese Gaofen-3 Synthetic Aperture Radar in Selected Topics for Coastal and Ocean Observations

by Xiao-Ming Li, Tianyu Zhang, Bingqing Huang and Tong Jia

Remote Sens. 2018, 10(12), 1929; https://doi.org/10.3390/rs10121929 - 30 Nov 2018

Cited by 36 | Viewed by 5782

Abstract

Gaofen-3 (GF-3), the first Chinese spaceborne synthetic aperture radar (SAR) in C-band for civil applications, was launched on August 2016. Some studies have examined the use of GF-3 SAR data for ocean and coastal observations, but these studies generally focus on one particular application. As GF-3 has been in operation over two years, it is essential to evaluate its performance in ocean observation, a primary goal of the GF-3 launch. In this paper, we offer an overview demonstrating the capabilities of GF-3 SAR in ocean and coastal observations by presenting several representative cases, i.e., the monitoring of intertidal flats, offshore tidal turbulent wakes and oceanic internal waves, to highlight the GF-3’s full polarimetry, high spatial resolution and wide-swath imaging advantages. Moreover, we also present a detailed analysis of the use of GF-3 quad-polarization data for sea surface wind retrievals and wave mode data for sea surface wave retrievals. The case studies and statistical analysis suggest that GF-3 has good ocean and coastal monitoring capabilities, though further improvements are possible, particularly in radiometric calibration and stable image quality. Full article

(This article belongs to the Special Issue Sea Surface Roughness Observed by High Resolution Radar)

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18 pages, 4617 KiB

Open AccessArticle

Developing a Quality Index Associated with Rain for Hurricane Winds from SAR

by Hui Shen, Chana Seitz, William Perrie, Yijun He and Mark Powell

Remote Sens. 2018, 10(11), 1783; https://doi.org/10.3390/rs10111783 - 10 Nov 2018

Cited by 8 | Viewed by 4555

Abstract

Differences in synthetic aperture radar (SAR)-retrieved hurricane wind speeds from co-polarization and cross-polarization measurements are found to be correlated with rain rate. A quality index is proposed for the SAR-retrieved wind speed product to recognize heavy rain- affected areas by taking account of the different imaging mechanisms of the radar backscattering from the ocean surface via cross-polarization and co-polarization observations. A procedure is proposed to rectify wind retrievals in the rain-contaminated areas within the hurricane core, based on the theoretical physical profile for hurricanes. The effectiveness of the proposed methodology for heavy rain area recognition and wind speed reconstruction in the rain-affected areas is validated against step frequency microwave radiometer measurements from hurricane reconnaissance missions and the hurricane surface wind analysis product (HWIND). The quality flags provide confidence levels of hurricane surface winds from SAR, which together with the proposed method to correct wind retrievals in rain-contaminated areas, can contribute to improved operational applications of SAR-derived winds under hurricane conditions. Full article

(This article belongs to the Special Issue Sea Surface Roughness Observed by High Resolution Radar)

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18 pages, 6514 KiB

Open AccessArticle

Typhoon/Hurricane-Generated Wind Waves Inferred from SAR Imagery

by Lei Zhang, Guoqiang Liu, William Perrie, Yijun He and Guosheng Zhang

Remote Sens. 2018, 10(10), 1605; https://doi.org/10.3390/rs10101605 - 9 Oct 2018

Cited by 6 | Viewed by 4266

Abstract

The wide-swath mode of synthetic aperture radar (SAR) is a good way of detecting typhoon/hurricane winds with a cross-polarization mode. However, its ability to detect wind waves is restricted because of its spatial resolution and nonlinear imaging mechanisms. In this study, we use the SAR-retrieved wind speed, Sentinel-1 SAR wave mode and buoy data to examine fetch- and duration-limited parametric models (denoted H-models), to estimate the wave parameters (significant wave height H_s, dominant wave period T_p) generated by hurricanes or typhoons. Three sets of H-models, in total 6 models, are involved: The H-3Sec model simulates the wave parameters in 3 sections of a given storm (right, left and back); H-LUT models, including the H-LUTI model and H-LUTB model, provide a better resolution of the azimuthal estimation of wind waves inside the storm by analyzing the dataset from Bonnie 1998 and Ivan 2004; and the third set of models is called the H-Harm models, which consider the effects of the radius of the maximum wind speed r_m on the wave simulation. In the case of typhoon Krovanh, the comparison with wave-mode measurements shows that the duration-limited models underestimate the high values for the wind-wave H_s, while the fetch models’ results are more accurate, especially for the H-LUTI model. By analyzing 86 SAR wave mode images, it is found that the H-LUTI model is the best among the 6 H-models, and can effectively simulate the wind-wave H_s, except in the center area of the typhoon; root mean square errors (rmse) can reach 0.88 m, and the coefficient correlation (R²) is 0.86. The H-Harm models add r_m as an additional factor to be considered, but this does not add significant improvement in performance compared to the others. This limitation is probably due to the fact that the data sets used to develop the H-Harm models have only a limited coverage range, with respect to r_m. Applying H-models to RADARSAT-2 ScanSAR mode data, we compare the retrieved wave parameters to collected buoy measurements, showing good consistency. The H-LUTI model, using a fetch-limited function, does the best among these 6 H-models, whose rmse and R² are 0.86 m and 0.77 for H_s, and 1.06 s and 0.76 for T_p, respectively. Results indicate the potential for H-models to simulate waves generated by typhoons/hurricanes. Full article

(This article belongs to the Special Issue Sea Surface Roughness Observed by High Resolution Radar)

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21 pages, 8766 KiB

Open AccessArticle

Comparison of C-Band Quad-Polarization Synthetic Aperture Radar Wind Retrieval Models

by He Fang, Tao Xie, William Perrie, Guosheng Zhang, Jingsong Yang and Yijun He

Remote Sens. 2018, 10(9), 1448; https://doi.org/10.3390/rs10091448 - 11 Sep 2018

Cited by 16 | Viewed by 4907

Abstract

This work discusses the accuracy of C-2PO (C-band cross-polarized ocean backscatter) and CMOD4 (C-band model) geophysical model functions (GMF) for sea surface wind speed retrieval from satellite-born Synthetic Aperture Radar (SAR) images over in the Northwest Pacific off the coast of China. In situ observations are used for comparison of the retrieved wind speed using two established wind retrieval models: C-2PO model and CMOD4 GMF. Using 439 samples from 92 RADARSAT-2 fine quad-polarization SAR images and corresponding reference winds, we created two subset wind speed databases: the training and testing subsets. From the training data subset, we retrieve ocean surface wind speeds (OSWSs) from different models at each polarization and compare with reference wind speeds. The RMSEs of SAR-retrieved wind speeds are: 2.5 m/s: 2.11 m/s (VH-polarized), 2.13 m/s (HV-polarized), 1.86 m/s (VV-polarized) and 2.26 m/s (HH-polarized) and the correlation coefficients are 0.86 (VH-polarized), 0.85(HV-polarized), 0.87(VV-polarized) and 0.83 (HH-polarized), which are statistically significant at the 99.9% significance level. Moreover, we found that OSWSs retrieved using C-2PO model at VH-polarized are most suitable for moderate-to-high winds while CMOD4 GMF at VV-polarized tend to be best for low-to-moderate winds. A hybrid wind retrieval model is put forward composed of the two models, C-2PO and CMOD4 and sets of SAR test data are used in order to establish an appropriate wind speed threshold, to differentiate the wind speed range appropriate for one model from that of the other. The results show that the OSWSs retrieved using our hybrid method has RMSE of 1.66 m/s and the correlation coefficient are 0.9, thereby significantly outperforming both the C-2PO and CMOD4 models. Full article

(This article belongs to the Special Issue Sea Surface Roughness Observed by High Resolution Radar)

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10 pages, 3483 KiB

Open AccessArticle

Symmetric Double-Eye Structure in Hurricane Bertha (2008) Imaged by SAR

by Guosheng Zhang and William Perrie

Remote Sens. 2018, 10(8), 1292; https://doi.org/10.3390/rs10081292 - 15 Aug 2018

Cited by 5 | Viewed by 3780

Abstract

Internal dynamical processes play a critical role in hurricane intensity variability. However, our understanding of internal storm processes is less well established, partly because of fewer observations. In this study, we present an analysis of the hurricane double-eye structure imaged by the RADARSAT-2 cross-polarized synthetic aperture radar (SAR) over Hurricane Bertha (2008). SAR has the capability of hurricane monitoring because of the ocean surface roughness induced by surface wind stress. Recently, the C-band cross-polarized SAR measurements appear to be unsaturated for the high wind speeds, which makes SAR suitable for studies of the hurricane internal dynamic processes, including the double-eye structure. We retrieve the wind field of Hurricane Bertha (2008), and then extract the closest axisymmetric double-eye structure from the wind field using an idealized vortex model. Comparisons between the axisymmetric model extracted wind field and SAR observed winds demonstrate that the double-eye structure imaged by SAR is relatively axisymmetric. Associated with airborne measurements using a stepped-frequency microwave radiometer, we investigate the hurricane internal dynamic process related to the double-eye structure, which is known as the eyewall replacement cycle (ERC). The classic ERC theory was proposed by assuming an axisymmetric storm structure. The ERC internal dynamic process of Hurricane Bertha (2008) related to the symmetric double-eye structure here, which is consistent with the classic theory, is observed by SAR and aircraft. Full article

(This article belongs to the Special Issue Sea Surface Roughness Observed by High Resolution Radar)

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17 pages, 4052 KiB

Open AccessArticle

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

by Sander Rikka, Andrey Pleskachevsky, Sven Jacobsen, Victor Alari and Rivo Uiboupin

Remote Sens. 2018, 10(5), 757; https://doi.org/10.3390/rs10050757 - 15 May 2018

Cited by 22 | Viewed by 5443

Abstract

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. Full article

(This article belongs to the Special Issue Sea Surface Roughness Observed by High Resolution Radar)

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