Wind waves in the North Atlantic from ship navigational radar: SeaVision development and its validation with Spotter wave buoy and WaveWatch III

20 Wind waves play an important role in the climate system, modulating the energy exchange between the ocean and the atmosphere and effecting ocean mixing. However existing ship-based observational networks of wind waves are still sparse limiting therefore the possibilities of validating satellite missions and model simulations. In this paper we present data collected on three research cruises in the North Atlantic and Arctic in 2020 and 2021 and the SeaVision system for measuring wind wave characteristics over the open ocean with a standard marine navigation X-band radar. Simultaneously 25 with SeaVision wind wave characteristics measurements we also collected data 2 The dataset can be further used for validation of satellite missions and regional wave model experiments. Our study shows the potential of ship navigation X-band radars (when assembled with SeaVision or similar systems) for the development of a new near-global observational network providing a much larger amount of wind wave observations compared to e.g. Voluntary Observing Ship (VOS) data and research vessel campaigns.

important role into the Earth' climate system specifically in the air-sea interaction processes and energy exchange between the ocean and the atmosphere. In this paper we present the SeaVision system for measuring wind waves' parameters in the 40 open ocean with navigational marine X-band radar and prime data collection from the three research cruises in the North Atlantic (2020 and 2021) and Arctic (2021). Simultaneously with SeaVision observations of the wind waves we were 45 collectingcollected data in the same locations and time with Spotter wave buoy and running WaveWatch III model over our domains. Measurements with SeaVision were quality controlled and validated by comparison with Spotter 50 wave buoy data, in addition we run and WaveWatch III experiments for the domains of research cruises.. Observations of the wind waves with navigational X-band radar are in agreement among these three sources of data, with the best agreement for wave 55 propagation directions. The dataset that supports this paper consists of significant wave height, wave period and wave energy frequency spectrum from both SeaVision and Spotter buoy avaiable through the PANGAEA repository (Gavrikov et al., 2022) at 60 https://doi.pangaea.de/10.1594/PANGAEA.939620. The dataset can be used for validation of satellite missions as well as model outputs. One of the major highlights in this study is potential of all ships navigating into the open ocean and equipped with X-105 in air-sea interaction processes and energy exchange between the ocean and the atmosphere. At the same time, the history of building a robust global and regional datasets for assessment of the wind waves climatology and dynamics revealed that the wave 110 fields are always hard to measure both remotely and in situ with sufficient temporal and spatial resolutions to cover global and regional domains (comparing with e.g. air temperature or sea surface temperature). investigating alternative sources of massive wind wave data remains a challenge. In this respect ship navigation radars represent an option whose potential, especially in open ocean regions, is not yet explored to a full extent. Here we present the results of the development and validation of the SeaVision system for wind wave observations in the open ocean using 130 standard navigation marine X-band radars which allows for real time monitoring of wind wave characteristics along the commercial ship tracks.
Applicability of the navigation radars for measurements of the wind wave characteristics was first noted by Young et al. (1985). Radar images of the ocean surface, known as sea clutter, are generated by the Bragg scattering (Crombie, 1955) of the electromagnetic signal by the ripples on the ocean surface produced by the wind. Being emitted from the radar, an 135 electromagnetic signal reaches the ocean surface and further, being reflected by ripples on the ocean surface, is received back by the radar antenna when the ocean surface is rough enough (i.e. ripples are developed). Under a wind speed > 3 m/s and waves height > 0.5 m the surface waves field becomes detectable on the radar image of the sea clutter (Hatten et al., 1998;Hessner and Hanson, 2010). Time sequences of these images are further analyzed for estimating of wind wave characteristics. The associated retrieval procedures can be based on various approaches, which include signal-to-noise ratio 140 derived from the image spectrum (Nieto-Borge et al., 1999;Neito-Borge et al., 2008;Seemann et al., 1997), statistical analysis of the island-to-trough ratio on the sea clutter images (Buckley and Alter, 1997;Buckley and Alter, 1998), analysis of the image texture (Gangeskar, 2000), wavelet technique (Huang and Gill, 2015), the least square approach (Huang et al., 2014) and shadowing analysis (Gangeskar, 2014;Liu et al., 2015). Methodologies may also be based on the combination of these methods with the use of artificial neural networks (Vicen-Bueno et al., 2012 This may also include the analysis of the 145 Doppler shift of the received radar signal that is based on the well-defined relationship between orbital velocities and wave height for linear gravity waves (Plant, 1997;Plant et al., 1987;Johnson et al., 2009;Hwang et al., 2010;Hackett et al., 2011;Chen et al., 2019). There are many aspects of the sea clutter radar images analysis: Nieto Borge and Guedes Soares (2000) for example proposed an approach considering superpositions of swell and wind sea components, that allows to derive wind waves and swell contributions to the total wave field, along with directional characteristic. There are also attempts to use 150 images of the sea clutter revealed from X-band radars for estimating the current-depth profiles with a Eulerian approach (Campana et al., 2017), to retrieve wind speed and wind direction (Chen et al., 2015;Dankert and Horstmann, 2007;Dankert et al., 2003;Vicen-Bueno et al., 2013) and to derive surface characteristics (Senet et al., 2001).
On this basis several commercial systems such as WaMoS II (http://www.oceanwaves.de), SeaDarQ (Greenwood et al., 2018) and WaveFinder (Park et al., 2006) were developed. The most widely used system nowadays is WaMoS II (software 155 and hardware details provided in Reichert at al., 1999) is focused on the operational monitoring of the sea state (wind waves and surface currents) and operational management of oil platforms and ships using nautical X-band radars. In combination with other sources of the data (altimetric wave radar, vessel hydrodynamic simulator) wind waves estimates from navigational radar can be used managing security of the offshore systems, assessing ship fatigue due to mechanical environmental influence (Drouet et al., 2013) or for the real-time prediction of ship rolling (Hilmer and Thornhill, 2015). 160 Natalia 26.6.2022 13:16 Удалено: The methodology of the navigational 210 marine radar adaptation for measurements of the wind waves characteristics was announced by (Young et al., 1985). The r…adar images of the ... [2] Natalia 26.6.2022 13:25 Удалено: the …his basis of these studies and ... [3] We present the design and pre-proccesing methodology of the SeaVision system along with the dataset collected during 215 three research cruises (Fig. 1). SeaVision was developed in collaboration between the Shirshov Institute of Oceanology of the Russian Academy of Sciences (IORAS, https://ocean.ru/) and the Joint stock company "Marine Complexes and Systems" ("MC&S" J.S.C., https://www.mcs.ru/). SeaVision is developed in the basis of the sea ice monitoring system with navigational marine radar -IceVision (https://ice.vision/en). The pilot version of SeaVision was tested and validated in two North Atlantic cruises in 2020 and 2021 and in the Arctic cruise in 2021 (Fig. 1). The major advantage of the presented 220 dataset is the provision of the co-located Spotter wave buoy data with SeaVision records at almost 50 locations and outputs of WaveWatch III (WW3) model experiments forced by ERA5 reanalysis (Hersbach et al., 2020) for the corresponding domains. We present in this study the SeaVision system and dataset of the measurements of the wind waves in the open ocean and its comprehensive analysis.
The paper is organized as follows. In the Section 2 we provide details of research cruises, technical specifications of the 225 SeaVision system, data collection and analysis principles as well as the description of the WW3 model setup. Section 3 presents the results of the analysis and validation of the SeaVision dataset against Spotter buoy data and comparison with WW3 model output. The concluding section 4 summarizes the results and discusses the perspectives of the use of ship navigation radars for a massively enhanced collection of wind wave information in the open ocean.

Data collection and analysis 230
We provide definition of all parameters in the published dataset in Appendix C.  245 Figure 1 demonstrates ship tracks of three research cruises, during which wind wave data were collected. Research cruises were carried out by IORAS research vessels (R/Vs) "Academik Sergey Vavilov" and "Academik Ioffe". Table 1 provides a general information about the cruises and detailed information on the coordinates and dates and is provided in Appendix A.

Ship cruises
The two cruises in the subpolar North Atlantic (Figure 1a, b) were focused on the regular survey of the 59.5°N oceanographic cross-section and cross-sections in the Denmark Strait (Verezemskaya et al., 2021). During these cruises the 250 R/V makes full-depth CTD profiling. The distances between the hydrographic stations vary from ~30 km in the open ocean to a few km near the East Greenland coast with time allocated for each station (ship is drifting) varying from 2 to 6 hours.
Between the stations the R/V travels at a speed of approximately 6 to 10 kn. During the cruise of R/V "Academik Ioffe" in the Kara Sea ( Figure 1c) stations were somewhat shorter in time (2-3 hours). During all cruises wave observations were carried out after completing hydrographic profiling. For operating solely SeaVision the R/V position was strictly stationary 255 being controlled by bow and stern thrusters of the R/V. When SeaVision was used together with the free drifting Spotter buoy, the thrusters were off to provide also free drifting of the R/V. This allowed for measurements of the background wave field by both SeaVision and Spotter bouy. At each station we first released the Spotter buoy with a supplementary floating buoy dumping cable vibrations. Such design allows for maintenance of at least 300 m distance between the buoys and the R/V. Next, both buoys were in the free-floating mode for at least 30 min during which the recording was performed by both Удалено: along with other regular deep ocean observations. All three cruises were carried out by Shirshov Institute of Oceanology of the Russian 275 Academy of Sciences (IO RAS) within the governmental program of regular ocean observations. In particular, two cruises in the North Atlantic (Figure 1a,b) are related to regular deep ocean observations at the 59.,5°N (Verezemskaya et 280 al., 2021;Falina et al. 2007;Gladyshev et al. 2018Gladyshev et al. , 2019Sarafanov et al. 2008Sarafanov et al. , 2018 and the Arctic expedition is a part of the IO RAS "Floating University of IORAS" program (Stepanova, 2018). In addition to the regular deep ocean observations in 285 these cruises we were collectingcollected data from navigational radar with the newly developed SeaVision system and simultaneously carrying out observations with Spotter buoy (https://www.sofarocean.com/products/spotter).

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During At all "stations" research vessels were driftingdrifted during wave data collection (from 30 minutes to 2 hours) with its engines in neutral position to provide conditions for Spotter buoy wave observations in the free floating mode.

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SeaVision and the Spotter buoy ( Figure 4, top panel). Then both buoys were pulled back onboard. The Spotter buoy measured vertical and horizontal displacements starting from its release until getting back onboard. After completing measurements at each station only the data recorded during the free-floating mode were used for the joint analysis of SeaVision and Spotter buoy records. During all SeaVision and Spotter buoy measurements standard meteorological parameters were measured using onboard the meteostation. 300

Ship navigation radar signal retrieval and preprocessing
Development of the SeaVision system was based on a commonly accepted approach of the recording and analysis of the sea clutter images. Using a similar approach to commercial systems such as WaMoS II (http://www.oceanwaves.de), SeaDarQ 310 (Greenwood et al., 2018) and WaveFinder (Park et al., 2006) were developed. These commercial systems provide customers with their original software and hardware (sometimes including the X-band radar itself). In our approach we are focused on the development of an independently operating and low cost system compatible with the existing navigation radars with which ships are already equipped.
Research vessels Academik Sergey Vavilov (r/v ASV) and Akademik Ioffe (r/v AI) are equipped with the standard navigation 315 X-band radar JRC JMA-9110-6XA and JMA-9122-6XA. Technical details of radar transmission and backscatter characteristics are given in Table 2. Both radars operate at 9.41 GHz frequency (wavelength ~3 cm), and are equipped with a 6 feet antenna with the directional horizontal resolution of 1.2° (Table 2). Radars can optionally operate at the pulse lengths of 0.08 µs, 0.25 µs, 0.5 µs, 0.8 µs, 1.0 µs. For our purposes we used the smallest possible pulse length of 0.08 µs (at the socalled "short-pulse" mode -SP1) providing the highest possible resolution of the image (thus the best resolution of the ocean 320 surface). Our X-band radars are characterized by a 3.18 cm wave length of the emitted electromagnetic waves ( Table 2). The pulse length is the emission time of the wave beam, thus the number of the emitted waves and the area of the reflection at the ocean surface (defining spatial resolution) increase with increasing pulse length.
The SeaVision system (Fig. 2) is connected to the radar via splitter. It provides digitizations and further recording of the directionally stabilized (northward) radar sea clutter image resulting from each single full turn of the radar antenna. By doing 325 this, SeaVision converts the sea clutter image into a digital format with further recording the data onto the external storage.
SeaVision is also connected to the ship navigation package and simultaneously records geographical coordinates from GPS, speed over ground (SOG) and course over ground (COG). Each full turn of antenna results in ASCII file (~16 MB) consisting of the 4096x4096 matrix (1.875 m discretization at 4096 beam directions) representing the sea clutter digitized image with GPS information, SOG and COG in the file header. These files are further consolidated and converted into 330 NetCDF format at the post-processing stage. Natalia 21.6.2022 14:43 Удалено: For our purposes we used the shortest possible pulse length of 0.08 µs (at so-called "shortpulse" mode -SP1), that is equivalent to a 12 m angular spatial resolution.

Figure 2: SeaVision integration to the ship's navigational equipment together with an example of the series of the geographically stabilized (northward) sea clutter images, one for each antenna turn (right column). Image of the JRC 360
radar scanner (top left) is taken from the http://www.jrc.co.jp/eng/index.html.

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After the sea clutter images are collected and digitized, the next step is the postprocessing focused on the computation of significant wave height (H s ), wave period ( !! ), wave energy spectrum ( ! ) and wave direction ( ! ). Here we provide a short condensed description of the algorithm with the full details given in Appendix B. The subset collected at each station ( Fig. 1) consists of 20 minutes SeaVision record, which is equivalent to at least 540 images of the sea clutter (27 antenna full turns per minute for JRC JMA-9110-6XA radar). 375 The methodology for estimation of wind wave characteristics relies on a a well established Fourier Transform (FT) technique (Nieto-Borge and Guedes Soares, 2000;Borge et al., 2004, Borge et al., 2008. For each station preprocessing of the data begins from the choice of the processing squared area (squared area of 720×720 m). For now we locate the processing area visually by taking the area of the most apparent wave signal at the image and requiring this area to be deviated from the ship by 300 m to avoid a potential impact of the ship on the wave field and the effects of the reflection 380 and modulation of the radar signal by the ship superstructure. When the processing area is selected, we consolidate the data captured in this area from all 540 images for the further analysis. Note that data initially sampled in the polar coordinates are re-gridded at this step to the Cartesian grid of 384x384 grid points with 1.875 m spatial resolution for each subset.
The sequence of 540 matrixes with 384×384 grid points each is then split into 16 sectors (22.5 o width each). Further, to obtain the directional spectra estimates, we transformed the data into a 3D spectral domain by using FT and applying the 385 Welsh method with a half-width overlapping Hanning window (Fig. 3). This returns for each sector the three-dimensional spectrum !!,!"#$% ( ! , ! , ), where = /2 is the frequency (Hz) and is the angular frequency, ! and ! (rad/m) are the components of the wave vector ! , ! . Then for each sector we capture the spectrum power within the band along the line satisfying the linear dispersion relation for ocean waves (Fig. 3): where k is the wave number (rad/m), g is gravity (m/s 2 ), U is the surface velocity (m/s) which includes surface current velocity and ship drift, and is the angle between the wave vector and velocity vector . This procedure is applied to the bands corresponding to the first and the second spectral harmonics (see Appendix B for the definition of band width). The spectral power outside the bands for the two harmonics is assumed to be a background speckle-noise ( !"#$%&# ) (Kanevsky, 395 2008). Integrated spectral power outside of the bands matching the wave dispersion relation (1) is further used for estimation of the signal-to-noise ratio (SNR) as described in Appendix B and outlined in many works (Nieto-Borge et al., 1999;Hessner et al., 2002;Young et al 1985, Nieto-Borge and Guedes Soares 2000, Ivonin et al. 2016. Following Nieto-Borge et al. (1999,2004) SNR is then converted to significant wave height !,!"#$%&%'( using the linear regression equation: Удалено: At this stage we locate the processing area by visual choice of the most apparent wave signal on the images and minimal distance from the ship of 300 m (to avoid potential impact of the ship 420 to the wave field and illumination of the radar signal by the ship). After choosing the area we create the dataset for the further analysis by sampling the same squares from each image (one antenna turn). Data sampled in the polar coordinates were regridded to 425 the Cartesian grid resulting in 384x384 pixels dataset array (with 1.875 m spatial resolution) for each station.
Natalia 26.6.2022 14:44 Удалено: The sequence of these images is then transformed to the 3D spectral domain using fast 430 Fourier transform (FFT, Fig. 3) where A and B are empirical calibration coefficients which are individual for each radar. In this study these coefficients were computed by fitting a linear regression (2) to the significant wave height measured by the Spotter wave buoy. Derived numerical values of A and B coefficients are given in Table 2 for both X-band radars. Wave period !!",!"#$%&%'( was estimated conventionally using zeroth and first spectral moments: 435 where !,!"#$%&%'( is the estimate of the wave energy spectrum from SeaVision: where !,!"#$%&%'( is the estimate of the wave energy spectrum from SeaVision: !,!"#$% , thus being the estimate of significant wave height using the raw sea clutter image before calibration.

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To calibrate and validate SeaVision wave observations we performed simultaneous measurements with the Spotter wave buoy (https://www.sofarocean.com/products/spotter) in the locations shown in Figure 1 and specified in Table A1. Once the ship is drifting at the location of the measurements, the Spotter buoy was deployed and started move away from the ship.
Note that the ship drift is always faster compared to that of the buoy, thus the distance between the buoy and the ship was progressively increasing. When the distance between the ship and the buoy reached at least 300 m, the "free floating" mode 460 of SeaVision and Spotter buoy operation was initiated for at least 30 minutes as described in section 2.1. The longest free floating mode time period at some stations reached up to 1.5 hours. To ensure homogeneity of the analysis we used 20minute segments from "free floating" mode time series for further computations of significant wave height, wave spectra and directional moments following Raghukumar et al. (2019) -the surface elevations  variance in the frequency range of the wind waves. Further use wave parameters derived from the Spotter buoy as a "ground 500 truth" for the calibration of SeaVision data and derivation of A and B calibration coefficients in (2) (

Meteorological data
During all cruises the AIRMAR WeatherStation 220WX was installed on the main ship mast at 30 m height above the sea.
The weather station provided an output consisting of standard output parameters (barometric pressure, wind speed and direction, air temperature and relative humidity). Wind characteristics were recalculated from the relative wind to the true 510 wind in real-time mode.
Natalia 26.6.2022 15:25 Удалено: More details on calculation of the mean wave direction, directional spread, wave directional spectrum and other parameters on the basis of the Spotter time series can be found in (Raghukumar et  Удалено: calibration and estimation of the radar calibration coefficients A and B, these coefficients are further used to rescale SeaVision wave energy spectrum to match buoy spectrum with least squares.

WaveWatch III model experiment 540
We run WaveWatch III (WW3DG, version 6.07, WW3) spectral wave model forced by ERA5 reanalysis (Hersbach et al., 2020) over the domain and the time period of the research cruises (Table 3).. The experiments were performed for the outer domain at 0.1° spatial and 1-hr temporal resolution and for the inner domain with 0.03° (~1 km) resolution (see Table 3).
The outer domain solution was used for setting lateral boundary conditions for the inner domain. These experiments returned 545 two -dimensional wave spectra co-located with SeaVision and Spotter buoy observations. In the WW3 experiments we used the ST6 parameterization (Bababin, 2006;Bababin, 2011;Rogers et al., 2012;Zieger et al., 2015) for wave energy input and dissipation and the discrete interaction approximation (DIA) scheme for nonlinear wave interactions . This WW3 setting is close to that used in Sharmar et al. (2021) for the global wind wave hindcasting.

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Validation of SeaVision data was provided for wind speeds from 2 to approximately 20 m/s -1 and for significant wave heights from few tens of centimeters to 4.2 meters. Figure 5 demonstrates the results of the intercomparison of significant wave height (H s ) estimates retrieved from SeaVision data and those measured by Spotter buoy and simulated with WaveWatch III. The H s differences 'Spotter minus SeaVision' (Fig. 5a) and 'WW3 minus SeaVision' (Fig, 5b) are plotted as a function of wind speed recorded by the ship weather station (Table A1). Table 4 provides comparative estimates of 560 differences in H s for the three cruises. On average WW3 yields lower wave heights than SeaVision H s by 28 cm, while the agreement between SeaVision and Spotter buoy data is better with H s measured by Spotter being 9 cm higher than retrieved from SeaVision. For low wind speeds SeaVision tends to underestimate H s up to 50 cm and for moderate and strong winds Natalia 26.6.2022 15:32 Удалено: parameters: barometric pressure, wind speed and direction, air temperature and relative 565 humidity. Wind characteristics were recalculated from apparent wind to true wind in real-time. to reconstruct two-dimensional wave spectra comparable with SeaVision and Spotter buoy observations. Start and end dates of the experiments were collocated in time with dates of the research cruises. For wave energy input and dissipation we 580 use ST6 parameterization (Bababin, 2006;Bababin, 2011;Rogers et al., 2012;Zieger et al., 2015) and the discrete interaction approximation (DIA) scheme for nonlinear wave interactions  for the higher wind speeds. This effect can be due to better ripples development on the ocean surface during higher winds affecting the signal to noise ratio (Formula 1). the analysis shows an overestimation of SeaVision H s compared to buoy and model data. This can be explained by better 600 developed ripples (affecting the signal to noise ratio) at the ocean surface under stronger winds. We also identified two locations (2901 and 2937, see Table A1) for which the differences between the Spotter buoy data and SeaVision reach more than 1 m (for 5 and 13 m/s winds). Weather conditions for these two cases were not associated with severe weather and H s values were in the range between 1.5 and 2 m. However, in both cases we recorded a strong drift of the vessel due to the local current that potentially impacted the angle of the electromagnetic signal reflection from the 610 surface and hence affected the accuracy of the radar images. Thus, strong ship drift may influence the SeaVision results and the data collected under strong ship drift should be considered with caution. These cases, in the future, can be identified by analysis of speed over ground (SOG parameter).  (Fig. 6). There is no robust evidence of the dependence of the magnitude or sign of H s and T m01 differences on the magnitude of parameters themselves. 620 We also note that both SeaVision and Spotter show higher waves and slightly longer periods compared to WW3 (Fig. 6). We Natalia 24.6.2022 20:30 Удалено: At the same time there are two stations (2901 and 2937 see Table A1) where this difference reaches almost 100 cm (between 59 and 132 m/s winds), examinations of weather conditions at these stations revealed that there were not any special 705 weather conditions and observations were carried for Hs between 1.5 and 2 m, however there was a strong drift of the vessel due to the local current that potentially influenced the angles of electromagnetic signal reflection from the surface and hence affected 710 the accuracy of the radar images. For the cases of the strong drift of the vessel and other non-standard situations in the open ocean we will collect more data and investigate into these differences. In Table  4 we provide average differences of Hs for three 715 expeditions.
Natalia 27.6.2022 21:46 Удалено: note however, that simulated wind waves with WW3 strongly depend on the atmospheric forcing (choice of reanalysis). 730 Difference in climatological mean values over the North Atlantic obtained with WW3 but with different forcing functions can reach few tens of centimeters (Sharmar et al. 2021). WW3 (b,d)  Удалено: and between Overall, the analysis of significant wave heights among these three sources of data (Spotter, SeaVision and WW3) shows that the highest H s values are measured by the Spotter buoy, lowest are simulated by WW3, with SeaVision being in between. These results are intuitively correct as wave buoys measure the actual elevations of ocean surface, SeaVision provides a proxy of local wave conditions from image analysis (thus imposing averaging over the domain) and is not expected to be as accurate as wave buoy data. 750 Figure 7 shows comparisons of wave directions along with corresponding H s values (simplified approximation of directional spectra) for six stations (see Table A1). Generally all three data sources demonstrate very good agreement on directions (differences in waves direction do not exceed 10°) with corresponding wave height estimates being underestimated in model simulations as already mentioned above (Figures 5 and 6). 755  Table A1).  Figure 7 for six stations (see Table A1). It is important to notice that all three sources of the data: SeaVision, Spotter buoy and WW3 demonstrate higher agreement in estimates of 770 the waves directions (from) than in Hs or Tm01Ts. The difference in waves direction does notdoesn't exceed 10°.

Figure 6: Scatterplots of the significant wave height (H s ) and wave period (T m01 ) revealed by SeaVision and measured by Spotter (a,c) as well as revealed by SeaVision and simulated with
We also performed comparisons of SeaVision and Spotter H s estimates with satellite altimeter missions (Figures 8, 9). Figure  775 8 shows overpasses of all available satellite tracks of Jason-3, CFOSAT, Sentinel-3A, Sentinel-3B, SARAL and HaiYang-2B which are suitable for comparisons with our dataset. Altimeter data were used for comparisons when they satisfied two conditions: an overpass was within 2° latitude and within ±30 minutes from the measurement time (Table A1). In total we selected 20 cases that satisfied these conditions.  (Table A1).
The average H s for these 20 locations measured by satellite altimeters is 1.47 m, with Spotter buoy is 1.38 m and SeaVision 785 giving 1.26 m. There is a general agreement for most stations among these three sources of data and differences do not exceed 50 cm except for two cases: stations 2937 and 2901, where H s is underestimated by SeaVision comparing to Spotter and altimeter by more than 100 cm. These two outliers were already mentioned above ( Figure 5) and large differences were c b a attributed to a very strong drift of the ship for these locations.  Table A1.

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To open a new avenue for widely needed broad-scale high-quality observations of ocean wind wave estimates we used a conventional navigation X-band ship radar equipped with a SeaVision recorder and software package and here present the evaluation of the instrument package for measuring wind wave parameters and comparing them with in-situ observations and model results. The data were collected on three cruises in the subpolar North Atlantic and in the Kara Sea. All SeaVision records were co-located with in-situ Spotter buoy measurements used for validation. We demonstrate an overall agreement 800 of the estimates of significant wave height and wave period measured by SeaVision with Spotter buoy measurements and with simulations with the WW3 spectral wave model. Estimates of significant wave height between SeaVision, WW3 and Spotter buoy are in a better agreement than those for the wave periods. In the ranges of H s up to 4.2 m the average difference between the Spotter buoy and SeaVision is 9 cm for H s , while WW3 simulations are higher than SeaVision H s by 28 cm. We note, however, that comparisons with WW3 should be considered with caution, as the model results are significantly 805 dependent on the choice of forcing function (atmospheric reanalysis). SeaVision tends to underestimate mean wave periods by ~0.5 s compared to the Spotter buoy while the differences in periods with WW3 simulations may amount to more than 2 sec. Also, a very good agreement was found for the wave directions whose spread across all three data sources does not exceed 10°.  (Figures 8, 9). Figure 8 shows overpasses of all available satellite tracks of Jason-3, CFOSAT, Sentinel-3A, Sentinel-3B, SARAL and HaiYang-2B which are suitable for 815 comparisons with our dataset. Altimeter data were used for comparisons when they satisfied two conditions: an overpass was within 2° latitude and within ±30 minutes from the measurement time (Table A1). In total we selected 20 cases that 820 satisfied these conditions. Natalia 26.6.2022 16:31 Отформатировано: Подстрочный A newly developed SeaVision system for digitizing and recording of the analog signals from navigation radars and further quantitative estimation of wind wave characteristics promises to enhance massive observations of wind waves over the open ocean. SeaVision is currently mounted onboard two R/Vs operated by IORAS, but in 2022 five more IORAS R/Vs will be 825 supplied with SeaVision systems. Data records will become operationally available at an open source web page. In 2023 we also plan to develop a portable and cheap version of SeaVision that can be easily mounted on any ship with navigational radar operating in the open ocean, on the platform, lighthouse or any coastal infrastructure. After further validation SeaVision can be easily upgraded to incorporate all post-processing procedures into the internal software package that will make it possible for commercial ships on which the system is installed to provide real-time reporting of wind wave 830 parameters though the Global Telecommunication System (GTS). Theoretically the estimated data flow is formally one estimate per 2-3 seconds (1 full turn of the radar antenna). Even with a reporting frequency once per minute the potential of the SeaVision data flow overestimates the current VOS data flow by hundred times. Contrasting to exiting commercial systems for wind waves monitoring with navigational marine radars, such as WaMoS II (http://www.oceanwaves.de), SeaDarQ (http://www.seadarq.com/) and WaveFinder (Park et al., 2006), SeaVision is focused on the use of information of 835 conventional navigation ship radars representing potentially a low cost alternative. Wide use of such a system at commercial ships can drastically increase the amount of sea state observations available to users, including National Meteorological Offices using this information as data assimilation input for NWP models and reanalyses.
The Global Climate Observing System (GCOS) and associated Global Ocean Observing System (GOOS) are considering sea state to be a critical climate variable highly demanded by global observing modules. We hope that SeaVision with its 840 perspective to provide exceptionally high global coverage with on-line wave measurements will meet this urgent demand and help to satisfy GCOS given its mandate for systematic observations under the UN Framework Convention on Climate Change (UNFCCC), including also GCOS and GOOS responsibilities under the Subsidiary Body for Scientific and Technological Advice (SBSTA) and the Subsidiary Body for Implementation (SBI).

Data availability
Datasets that contains significant wave height, wave period, wave direction, wave energy frequency spectrum, meteorological data and other related parameters from both SeaVision and the Spotter buoy at the locations of every station 850 ( separation of the swell and wind waves at this stage of the SeaVision development. We plan to include this procedure into the next studies. At the same time, we provide one dimensional spectrum that potentially allows to see first and seconds peaks associated with winds waves and swell (an example is shown in Figure 4b). Users interested in the analysis of the raw 855 Natalia 26.6.2022 15:59 Удалено: In this study we present the dataset of the observations of the wind waves collected during three research cruises (two in the North Atlantic and on in the Arctic) on the basis of usage navigational X-band marine radar and wave buoy Spotter.

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Nowadays there is still exists gap in the in situ observational network for the wind waves, at the same time Wwinds waves is are crucially important dynamical components of the interaction between the ocean and the atmosphere and play important 865 role into the climate system, however in situ observational network for the wind waves is still sparse. We also present a newly developed SeaVision system for digitizing and recording of the analogous marine radar signal and further analysis of 870 the data to obtain wind waves' parameters such as significant wave height, wave period and wave energy spectruma. The potential usage of the dataset is validation of the satellite missions and outputs from the wave models.

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Natalia 26.6.2022 16:00 Удалено: We demonstrate an overall agreement of the estimates of significant wave height and wave period on the basis of SeaVision with the same estimates simultaneously measured by the wave buoy Spotter and modelled by WW3 spectral wave 880 model. At the same time estimates of the significant wave height between WW3, Spotter and SeaVision are in a better agreement than estimates of the wave period. Within the Hs up to 4.2 m and Ts up to 10 s the average difference between SeaVision Spotter 885 and Spotter SeaVision buoy is 3 9 cm for Hs, while for the Spotter WW3 minus WW3 SeaVision this difference is -287 cm, meaning underestimation of wave heights by WW3 comparing to SeaVision and slight (9 cm) underestimation of wave height by .

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SeaVision comparing to Spotter buoy. SeaVision has a tendency (relatively to Spotter) to overestimate underestimate mean period by 0.5 s while WW3 both overestimates and underestimates wave periods by up to 2.,5 s (regression coefficient with 895 SeaVisionpotter is only 0.7663, Fig. 6). The best agreement among three sources of the data is in estimation of wave directions (Fig. 7), the difference doesn't exceed 10°.
... [15] radar dataset or in the wave characteristics in the locations were measurements were carried out only with SeaVision are welcome to request access from Alexander Gavrikov (gavr@sail.msk.ru).

Appendix A: List of the locations (stations) of the wind waves measurements during three research cruises 905
The curve associated with the second harmonic is clearly seen in Figure 3. The rest of the signal lying in the spectral domain outside the bands associated with dispersion curves and attributed to speckle-noise (Kanevsky, 2009) is needed to be properly quantified. This depends on the algorithm used for the quantification of bands associated with dispersion relation 935 curves. Speckle-noise is used for normalization of the radar spectrum and removing the impulse power impact on the radar signal modulations by the sea waves (Kanevsky, 2009). The 2D normalized spectrum !,!!,!"#$ ( , ) of the signal at each wavenumber k can be calculated as: where the speckle frequency is: Then the full image spectrum !,!,! ( ) needs to be filtered to obtain the power corresponding to the band capturing the first 945 !,! harmonic for the direction n: Here k !,! is the dispersion relation (1) solution for the first harmonic !,! ( !,! ) = 2 and ∆k is related to the size of the processing area (720 m) as ∆k = 0.02 ≈ 2 • 2π/720 (rad/m). Similarly for the second harmonic ω !,! we obtain: where k !,! is the dispersion relation (B1) solution for the second harmonic !,! ( !,! ) = 2 .
The total power !,! falling in the bands along dispersion relation curves yields: Given that this procedure is applied to all 16 sectors of the image (see section 2.2.2), the omnidirectional image frequency 955 spectrum !"#$% can be derived as follows: Further integration over the frequency domain returns the zeroth moment !,!"#$% of the !"#$% spectrum: which provides us with the estimate of SNR being: ≡ !,!"#$% + 1.
Formally, considering the !!"#$,! spectrum as a modulation analog of the real sea wave spectrum, ! , the zeroth 965 moment m !,!"#$% can be further converted to the magnitude of signal modulations !"#$% on the radar image which stands as a provisional measure of H s : !"#$% = 4 !,!"#$% (B.9) Further the transform of the omnidirectional SeaVision image frequency spectrum !"#$% to the sea wave frequency 970 (wave energy) spectrum !,!"#$%&%'( visible by SeaVision is performed by applying the standard technique described in section 2.2.2 and resulting in Eq. (2) returning significant wave height H !,!"#$%&%'( estimate based on the radar calibration coefficients A and B along with estimate for the wind wave period (4) derived from the zeroth and the first moments of the spectrum.

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Appendix C: Definition of all the parameters in the manuscript and dataset.

Competing interests 990
The authors declare no conflict of interests.
Vika Grigorieva and Igor Goncharenko of Shirshov Institute of Oceanology for their help with setting up the hardware for radar signal digitization and useful advice. We thank Takaya Uchida at Université Grenoble Alpes for final proofreading of the manuscript.