In this contribution the wind jet dynamics in the northern margin of the
Ebro River shelf (NW Mediterranean Sea) are investigated using coupled
numerical models. The study area is characterised by persistent and
energetic offshore winds during autumn and winter. During these seasons, a
seaward wind jet usually develops in a
Coastal areas are often characterised by highly variable and heterogeneous wind, wave and current conditions, which make the numerical prediction of the meteo-oceanographic processes difficult. For instance, wind jets induced by orographic effects present strong spatial wind field variability due to the orographic characteristics (e.g. Shimada and Kawamura, 2006; Zhai and Bower, 2013). Due to the persistence in wind intensity and direction, these regions are preferential sites for the installation of offshore wind farms (Nunalee and Basu, 2014). In the case of coastal regions, the resultant offshore winds decisively influence the exchange of water mass and material along the shelf/slope (Jordà, 2005; Barton et al., 2009). Despite the relatively limited fetch in the wind jet region, the wave height can be relevant, interacting with bimodal features (Shimada and Kawamura, 2006). In this sense, several contributions have highlighted the influence of variable wind conditions in relatively small-scale areas (such as wind jet), influencing wind–wave generation (Shimada and Kawamura, 2006; Bolaños-Sanchez et al., 2007; Alomar et al., 2014) or modifying ocean circulation patterns (Csanady, 1980; Zhai and Bower, 2013; Schaeffer et al., 2011; Klaić et al., 2011).
Localisation map
In coastal zones the air–sea momentum transfer presents a high complexity due to the dependence of wind intensity on ocean surface roughness. The relevance of the atmospheric bottom roughness increasing due to waves has been investigated in recent years (Janssen, 1989; Janssen and Viterbo, 1996; Lionello et al., 1998; Taylor and Yelland, 2001; Oost et al., 2002; Drennan et al., 2003). In this sense, advanced computational tools allowed for the feedback of meteo-oceanographic momentum and heat transfer to be addressed numerically (Warner et al., 2010; Zambon et al., 2014). Warner et al. (2010) developed a fully coupled numerical system (COAWST: Coupled Ocean–Atmosphere–Wave–Sediment Transport) to investigate the impact of storms on coastal systems. Using COAWST, Olabarrieta et al. (2012) and Renault et al. (2012) proved numerically that the wave-induced ocean surface roughness is a key parameter in the air–sea momentum transfer. Under severe storm conditions (hurricanes and cyclones), this parameter influences the spatial and temporal evolution of the meteo-oceanographic variables. Other recent examples that use a fully numerical model to investigate the air–sea interaction and its effect on oceanographic processes are found in Nelson and He (2012) and Drews (2013).
The case of the Ebro River shelf (NW Mediterranean Sea; see Fig. 1) is characterised by a strong, dry and usually cold wind that blows from the north-west through the Ebro valley. The westerly wind, greatly affected by the orography, is channelised into a limited band, forming a wind jet (Jansà, 1985; Spanish Ministry of Energy, 2014). The synoptic situation is related to an anticyclone in the Bay of Biscay and a low-pressure area in the Mediterranean Sea (Riosalido et al., 1986; Font, 1990; Martín-Vide, and Olcina, 2001; Cerralbo et al., 2015). Offshore wind is more usual and intense during autumn and winter, when larger atmospheric pressure gradients take place and cause stronger winds with an advection of cold air, but a small atmospheric pressure difference along the Ebro valley is sufficient to initiate wind during any season (Riosalido et al., 1986; Cerralbo et al., 2015).
The objective of this contribution is to describe the meteo-oceanographic processes associated with a wind jet developing at the northern margin of the Ebro River shelf. This work provides insight into wind jets in an orographically complex region, such as the Ebro delta shelf, describing the main wind, wave and current patterns and the feedback relative to the air–sea momentum transfer in terms of wave-induced ocean surface roughness. After the introduction (Sect. 1), in Sect. 2 (Methods) we describe the study area, the COAWST model implementation and the wind jet event selected to investigate in detail the meteo-oceanographic dynamics. Then, in Results (Sect. 3) we show the most relevant meteo-oceanographic processes observed and a detailed skill assessment of the fields modelled, comparing them with a set of available data (i.e. in situ observations and remote-sensing products). Also, the feedback in the air–sea momentum transfer in terms of wave-induced ocean surface roughness is investigated with a set of coupled simulations testing different air–sea momentum transfer formulations. Afterwards, we discuss (Sect. 4) the relevance and particularities of the dynamics of the wind jet area in terms of waves, winds and currents, comparing with previous investigations. The implications of the wind–wave coupling in terms of the wind resource assessment are highlighted. We close with the Conclusions (Sect. 5).
The meteorological patterns over the NW Mediterranean Sea exhibit sharp
gradients associated with the topographic control on synoptic fluxes
(Jansà, 1985; Martín-Vide and Olcina, 2001). Regional wind analysis
reveals strong and persistent cross-shelf winds. A channelisation effect
associated with the Ebro valley triggers north-westerly winds (called
The Ebro River delta is located immediately to the south of the wind jet
region, and the average annual river discharge ranges between 300 and
600 m
Oceanographic investigations in the Ebro River region were focused primarily on the outer shelf and slope dynamics of the southern margin (Font, 1990; Palanques et al., 2002; Salat et al., 2002; Jordà, 2005) with relevant eddy activity (Redondo et al., 2013). The circulation in these regions is dominated by the inertial band, with a relevant signal of the slope current associated with the regional northern current northern or Liguro–Provençal–Catalan current (Jordà, 2005). Observational analyses have revealed that the inner and mid-shelf (less than 50 m water depth) dynamics in the Ebro shelf are characterised by a strong influence of the frictional component of the flow (Jordà, 2005; Grifoll et al., 2015). Furthermore, the regional response to wind jets is not clear due to the complex bathymetry and the spatial variability of the wind jet. Durand et al. (2002) and Mestres et al. (2003) showed that the effects of the salinity river plume are important only near the river mouth (of the order of 10 km offshore from the river mouth).
As a part of large effort to collect physical data and implement numerical tools for the assessment of offshore wind energy potential, a buoy was moored in the northern margin of the Ebro shelf where the wind jet develops (see Fig. 1). The buoy was moored 3.1 km from the coast at 43.5 m bottom depth, measuring wind, waves and water currents for 1 year. A TRIAXYS directional wave sensor mounted on the moored buoy was used to record statistical wave spectra parameters. Wind speed and direction were measured at 4 m height every 10 min using an ultrasonic wind sensor (Gill Instruments) for 1 year (November 2011 to November 2012). Water currents were measured with a SonTek acoustic Doppler current profiler (ADCP) at 500 kHz every hour using 20 vertical layers (layer depth was 2 m). The mooring period covered more than 1 year (from November 2011 to December 2012).
Additionally, satellite-measured winds were used for the numerical model
validation. Sea wind intensity and direction were obtained from the National
Climatic Data Center (NCDC-NOAA;
The COAWST modelling system (Warner et al., 2010) was used in this study. COAWST relies on the three-dimensional (3-D) ocean modelling ROMS (Regional Ocean Modeling System; see Haidvogel et al., 2000), the phase-averaged wave model SWAN (Simulating WAaves Nearshore; see Booij et al., 1999), the non-hydrostatic meteorological model WRF (Weather Research and Forecasting; Skamarock et al., 2005) and the sediment transport module CSTMS (Community Sediment Transport Modeling System; Warner et al., 2008). The ocean model ROMS is a free-surface, terrain-following numerical model, which resolves the 3-D Reynolds-averaged Navier–Stokes (RANS) equations using hydrostatic and Boussinesq approximations. The WRF model (advanced research WRF version) is a non-hydrostatic, quasi-compressible atmospheric model with a variety of physical parameterisations of sub-grid-scale processes for predicting meso- and microscales of motion. The SWAN model solves the wave action balance equation simulating wind generation and propagation in deep and coastal waters. The modelling system COAWST includes the coupler Model Coupling Toolkit (MCT; Jacob et al., 2005) for the transmission and transformation of the physical variables using a parallel computing approach. The COAWST system also allows for the exchange of data fields on different grids using the Spherical Remapping Interpolation Package (SCRIP; Jones, 1999) to compute the interpolation weights.
The largest wave domain (mesh O1) covers the western Mediterranean Sea, which is considered large enough to capture the wave generation in the study area. The SWAN model implementation used amends the underestimation in the wave growth rates reported by Alomar et al. (2014) and Rogers et al. (2003) in a low- and medium-frequency energy spectrum. The measure adopted was introduced by Pallares et al. (2014) and consists in modifying the whitecapping dissipation term (see Appendix A1).
The largest water circulation domain (mesh O3) is nested into the daily
MyOcean-MEDSEA product (Tonani et al., 2009), with a horizontal resolution
of
The atmospheric model is nested into the ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-Interim reanalysis product considering four downscaling meshes – M1, M2, M3 and M4 with resolutions of 27, 9, 3 and 1 km, respectively – to obtain suitable grid resolution for the complex orography of the region (see Fig. 1). The WRF implementation uses a Mellor–Yamada–Nakanishi–Niino (MYNN) level 2.5 planetary boundary layer scheme. The nesting strategy consists of a set of different downscaling meshes (Fig. 1c and Table 1). The ocean–atmospheric–wave online coupling was implemented in the finer domain (mesh O4 for the wave and circulation model, and mesh M4 for the meteorological model) where the scale of the coupling process due to cross-shelf winds may be more evident in the results. In this case, air–sea coupled effects are included considering the Taylor and Yelland formulation (Taylor and Yelland, 2001), for the ocean surface roughness modification due to the wave effect, and vortex force for the wave effects on currents (Olabarrieta et al., 2012).
Resolution (in km) of the different domains/meshes used in the nested system as a function of each numerical model and regional scale covered. In parentheses the mesh name in Fig. 1 is shown.
As we noted in the introduction, the air–sea momentum transfer presents
high complexity due to the relation of wave characteristics and the
ocean surface roughness, which in turn affect the wind field. In order to
investigate the air–sea momentum transfer in the wind jet, a set of
simulations have been designed applying different air–sea momentum
transfer formulations included in the COAWST modelling system. The
sensitivity tests pursue an evaluation of the “coupling” effects on two
principal variables involved in the air–sea momentum transfer: wind
intensity (
Regional chart of the mean sea level pressure (hPa) during 21 May at 06:00 UTC (representative of the synoptic situation during the selected cross-shelf wind event). Data source: ERA-Interim global reanalysis from ECMWF. Arrows represent the wind field.
We select a cross-shelf wind event in order to characterise in detail the meteo-oceanographic dynamics of the wind jet. The episode selected for the sensitivity tests lasted from 19 to 23 March 2012. The synoptic situation during the selected episode corresponds to a typical offshore wind event induced by atmospheric pressure differences (see Fig. 2). A high-atmospheric-pressure area is centred over the North Atlantic Ocean, with the anticyclonic edge affecting part of the Iberian Peninsula. The low pressure is located in the centre of Europe. In this situation the cross-shore winds in the Ebro delta zone are intensified. The sequence of wind field modelled in the Catalan coast mesh during the wind jet period is characterised by a rise of wind intensity during the 20 and 21 May, leading to a wind jet in the northern margin of the Ebro delta (see daily-averaged wind intensity in Fig. 3). Then, the cross-shore winds remain strong during 22 May, decreasing during the 23 May 2012.
The skill assessment of the model is carried out for different meshes in
function with the spatial coverage of the observations. Modelled winds during the
simulation period reproduce the main wind directions previously reported in
the study area. Offshore wind prevails throughout the year, intercalated
with southerly winds during spring and summer (i.e. sea breeze). The
adjustment of the wind time series into a Weibull distribution is used to
evaluate the statistical inter-comparison between wind observations
(measured from the buoy and satellite) and the 3 km WRF model results (mesh M3).
Blended Sea Winds were used from the NOAA/NCDC SeaWinds project which
contain 6-hourly globally gridded, high-resolution ocean surface vector
winds and wind stresses on a global 0.25
Statistics for the comparison between buoy measurements and model
outputs.
In Fig. 6, time series comparing the results obtained from the coupled
SWAN model (mesh O3) and the buoy measurements (see position in Fig. 1)
are shown. The time series comparison corresponds to the significant wave
height (
Sequence of the wind jet intensity on 4 days for a wind jet event in the domain of the Catalan coast. The quiver is shown for each of the three points. Results obtained for COAWST at mesh M3 are plotted.
Weibull distribution adjustment for the wind velocities regarding the duration for the entire 12 months analysed.
Wind components (top panels: east–west top; bottom panels: north–south) from the satellite gridded product for the study area (top panels) and from the results of the meteorological model (mesh M1). The figure corresponds to 1 January 2012 at 12:00 UTC.
Time series of the significant wave height (m), the mean wave
period Tm
Numerical wave spectra for two different instants at the observational point: without wind jet event (left panel: 2 March 2012) and during wind jet event (right panel: 21 March 2012).
Along-shelf (left panels) and cross-shelf (right panels) velocity observed (top panels)
and modelled (bottom panels) during May 2012 (in m s
Figure 7 (right panel) shows a snapshot of the waves' directional spectra during the
wind jet period selected at the measuring point; the results reveal the
tendency to develop bimodal directional spectra due to the co-existence of
sea and swell waves. Directional spectra presents a peak around
315
The water circulation observed at the buoy is characterised by an alignment
of the flow following the isobaths. The principal component analysis of the
flow for the observed depth-averaged currents reveals an angle similar to
the coastline orientation (
The skill assessment of the numerical results in terms of current (water
velocity) was carried out following a similar scheme to the one used for
winds and waves. The numerical model validation with ADCP observations shows
an acceptable level of agreement according to the comparison for the wind
jet event. For instance, Fig. 8 shows a noticeable agreement between the
observed and modelled currents in the water column for both along- and
cross-shelf components. In addition, Table 2 presents the error statistics
for the depth-averaged velocity measurements compared with the numerical
model results for the wind jet event. Skill assessment is better in
depth-averaged along-shelf flow in comparison to cross-shelf (e.g.
The spatial water circulation modelled during the wind jet event (21 May)
is shown in Fig. 9 for two different depths: sub-surface (2m water
depth) and intermediate (50 m water depth) for O3 mesh. Depth-averaged
velocities are also presented in Fig. 9. The surface current modelled at
1 km (mesh O3) and 250 m (mesh O4) grid resolution presents a relatively
homogeneous offshore direction qualitatively that is well correlated with
the spatial distribution of the wind intensity. In this case, the surface
current is seldom affected by topographic features such as the Ebro
delta. Consistent with Fig. 8, at deeper layers the flow direction turns
onshore, resulting in a two-layer flow in which the current intensity is
lower than that of the surface layer (Fig. 9, centre panel). The depth-averaged
flow is small due to the balance between the sheared two-layer flow;
however, a flow component slightly appears that is aligned with the isobaths
in the deeper areas of the continental shelf. Related to that, a clear
signal of the slope current is observed in the results at
Modelled circulation at
Wind intensity (left panels) and significant wave height (right panels) for the wind jet energetic event for the observational (top panels) and control (bottom panels) points.
The wind intensity and the significant wave height during the selected wind
jet event for the four simulations are shown in Fig. 10 (for the control
and observational points shown in Fig. 1). Comparing the numerical results
and the observations (Fig. 10, upper panels), all the numerical
simulations reproduce the wind intensity and the significant wave height
with a similar level of agreement. The uncoupled (CHK) and coupled
simulations (e.g. T–Y, OOST and DRE) only present differences in the
numerical outputs during the joint occurrence of strong winds and wave peaks
in the control point. Waves and wind intensity numerical results at the
observational point do not present significant changes among the four
simulations due to the limited fetch conditions, which means lower
significant wave height in comparison to the control point. During the calm
period (at beginning and end of the wind jet event) the differences among
the four simulations are inappreciable. Numerical coupled results do not
present better agreement at the observational point than the uncoupled mode
results. Comparing the error statistics for the observational point among
the three coupled numerical simulations, we cannot assure which formulation
ensures a better skill assessment (Table 3). At the control point the magnitude
of the wind intensity and the significant wave height is larger for the
uncoupled simulation (CHK) in comparison to the coupled simulations (Fig. 10,
bottom panels). Maximum differences of 3 m s
Statistics for the comparison between buoy measurements and model
outputs.
The shape of the wind jet modelled is benefited by the high-resolution meshes used in our investigation. According to our results, the wind jet approximately covers an area of 50 km width offshore. This area is in agreement with the wind intensity atlas provided by the Spanish Ministry of Energy (see Fig. 11) obtained from a long-term reanalysis product (15 years using the MASS model). In this sense, high-resolution meshes used in this investigations (i.e. 1 and 3 km grid resolution) are suitable for an accurate wind jet modelling. As it was pointed out by Alomar et al. (2014) and Cerralbo et al. (2015), the relevance of winds in the ocean response in terms of waves and currents justifies the high-resolution in the modelling investigations in the Ebro delta region.
Our results have shown an acceptable representation of the bimodal structure of the significant wave height and support the conclusions highlighted by Alomar et al. (2014), who note that a high spatial resolution of the wind field is required to represent an acceptable numerical wave field in very limited fetch conditions. The occurrence of bimodal wave features may also have different implications: the first one is that, because of the spatial resolution, the local north-westerly wind that produced the second peak of spectra may not have been detected in previous investigations (Sánchez-Arcilla et al., 2008; Alomar et al., 2014). The second implication is related to the momentum transfer: several authors have highlighted that under mixed wave-train conditions the ocean surface roughness may increase appreciably (Sánchez-Arcilla et al., 2008). Also, the wave modelling deserves to be mentioned particularly with regard to the good fit of wave results in comparison to previous investigations (Bolaños-Sanchez et al., 2007; Sánchez-Arcilla et al., 2008). Statistical errors were reduced significantly due to the young sea developed in the wind jet region likely thanks to the modification of a parameter relative to whitecapping dissipation (Pallares et al., 2014). In particular, smaller root mean square errors were obtained in the mean wave period variable, which presented large uncertainty (Bolaños-Sanchez et al., 2007; Sánchez-Arcilla et al., 2008; Alomar et al., 2014).
Wind atlas annual mean wind speed at 30 m height from a reanalysis product (source: Spanish Ministry of Energy, 2014).
As we noted in the Results section, the water circulation pattern showed differential behaviour for the long-term water circulation in comparison to the wind jet event. For the long-term circulation and in the shallow region, the frictional response prevails, with the along-shelf flow variability being larger than the cross-shelf flow, similar to other investigations in the inner and mid-shelf (see review in Lentz and Fewings, 2012; Grifoll et al., 2013). However, a different picture occurs during the wind jet event. In this case a characteristic surface current is high correlated to the offshore wind. According to the numerical outputs and in situ observations shown in Fig. 8, a deeper onshore flow, opposing the surface layer flow offshore, is developed. This flow is relatively weak due to the prevalence of the along-shelf component that increases offshore. These circulation patterns are consistent with other investigations (e.g. Horwitz and Lentz, 2014; Fewings et al., 2008; Dzwonkowski et al., 2011) where a well-developed two-layer flow due to intense cross-shelf winds tends to occur when the turbulent layers overlap (water depth in the inner shelf is of the order of metres to tens of metres according to Lentz and Fewings, 2012). In the mid- and outer shelf, the flow tends to be oriented in the along-shelf direction due to the prevalence of the regional response to the wind jet and the slope current. In this sense, the frictional adjustment time due to the wind (inversely proportional to the depth) varies in the continental shelf section and may be of the order of days in the mid-/outer shelf (Csanady, 1982). As a consequence, the expected response at deeper layers will also be dependent on processes acting at larger scales than the wind jet (i.e. baroclinic forcing, mesoscale activity) such as the slope current signal observed at 50 m water depth and depth-averaged currents in the numerical results (Fig. 9). The along-shelf flow in the inner shelf is presumably influenced by the regional response to the wind jet at the stratification in the water column and the barotropic pressure gradient adjustment due the spatial wind variability. These factors play an important role in the resultant water circulation pattern and its variability deserves additional numerical efforts and extended local wind and sea level information. For instance, Oey et al. (2004) and Liu and Weisberg (2012) include extended measurements to investigate the water circulation's response to spatial wind and the particular role of the barotropic pressure gradients. Finally, it is worth noting that the interaction between offshore winds and regional circulation was filtered in previous investigations in the region (Font, 1990; Salat et al., 2002; Jordà, 2005).
Several investigations have found the importance of the sea state in the
impact on the air–sea momentum flux; in particular the calculations based
on the Charnock constant underestimated the air–sea momentum transfer
(e.g. Janssen and Viterbo, 1996; Drennan et al., 2003), which can be
significant under mixed seas (Sanchez-Arcilla et al., 2008). In the northern
margin of the Ebro delta and during the wind jet, no relevant differences
were found when comparing the significant wave period and the wind intensity
between the numerical model and observations for the observational point. During
calm periods, the averaged conditions prevail over energetic events, so the
feedback of the air–sea momentum does not show significant differences.
The detailed analysis of 21–22 May event showed
significant differences between the coupled and uncoupled cases for
significant wave height and wind intensity offshore of the wind jet
(e.g. control “offshore” point). When we compare the coupling numerical results
(i.e. T–Y, OOST and DRE) versus CHK results, we observe that the wind
intensity at the control point is affected significantly by the sea state
during the energetic event. For the coupling simulations the wind intensity
is reduced due to the increasing wave-induced ocean surface roughness. This
behaviour is consistent with other coupling atmosphere–ocean
investigations under a high level of meteorological energy (e.g. Olabarrieta
et al., 2012). In parallel, the wave field is modified by the feedback
between wave and wind stress. During the energetic wind event selected,
Differences in the primitive variables between the coupled and uncoupled
simulations during particular energetic events are relatively small in terms
of wind intensity and significant wave height. Furthermore, the assessment
of the wind energy resource is relevant in this region with a high potential
for wind farm installation due to the large and persistent wind intensity
and the relatively large spatial extension of the continental shelf. A
simple way to estimate turbine power from wind intensity is based on the
idealised machine of blade diameter (
The wave-limited fetches and the persistent offshore winds represent particular ocean–atmosphere conditions never investigated before from a full-coupling perspective; only energetic cyclogenesis activity and extreme conditions have been recently modelled and investigated (e.g. Warner et al., 2010; Olabarrieta et al., 2012; Renault et al., 2012; Zambon et al., 2014; Ricchi et al., 2016) where also the heat transfer plays a relevant role in the air–sea coupling. In the mentioned cases, extreme modelled waves and wind benefitted from the use of full-coupling systems. Our case only presents comparable energetic conditions during a very short period of time; however, the cubic relationship between the potential wind energy and the wind intensity may justify, for engineering purposes, the use of coupled formulations between wind and waves. Further observational campaigns and the future use of high-resolution remote-sensing products (e.g. Sentinel-1 and Sentinel-3; Torres et al., 2012; Malenovsky et al., 2012) will benefit the numerical results and extended physical investigations in such a complex process as wind jet, in particular the role of the air–sea transfer formulations. Our results are also relevant in that they may be useful for further physical investigations in similar domains where the wind jets control the ocean–atmosphere dynamics (Jiang et al., 2009; Barton et al., 2009; Shimada and Kawamura, 2006).
Wind jet events, investigated using numerical modelling and both in situ and remote-sensing data, present particular conditions in meteo-oceanographic variables in the northern margin of the Ebro delta. A fully coupled meteo-oceanographic numerical model was implemented, with a good level of agreement in terms of waves, currents and wind fields measured. The numerical results reveal a spatially varying wind pattern, forming a well-limited wind jet. The water current velocity pattern during wind jet is well correlated with the wind intensities in the surface layer. However, in deep layers the flow becomes complex, and other processes of larger temporal and spatial characteristic scales affect the water circulation. The wave modelling during the wind jet event is characterised by the development of bimodal wave spectra: local wave generation due to wind jet and waves propagated from the open sea. Numerical results from sensitivity tests have shown the relatively small relevance of air–sea transfer formulations considering the significant wave height for the ocean surface roughness estimation. Furthermore, the accurate estimation of the wind energy resource may be benefitted by the coupled numerical modelling. The characteristics of the meteo-ocean variables during the wind jet in the northern Ebro delta may be useful for understanding processes in similar domains under severe cross-shelf wind conditions.
Pallares et al. (2014) performed numerical experiments that aimed to
improve the numerical wave predictions in semi-enclosed bays, modifying the
dissipation terms in the wave energy balance equation. For this purpose two
whitecapping formulations are considered in SWAN, obtained from the
pulse-based model of Hasselmann (1974) reformulated in terms of wave number
(the WAMDI group, 1988):
In SWAN the previously mentioned coefficients are obtained by adjusting the
energy balance for idealised wave growth conditions (fully developed wind
seas in deep water), despite the wave growth in semi-enclosed domains with
highly variable wind fields differing considerably from those idealised
conditions. As a result of a calibration process in the NW Mediterranean
Sea, which led to a reduction of the wave forecast errors mainly present in
the wave period, the coefficients selected for the wind jet region were
The standard bottom roughness length scale is expressed as a function of the
Charnock coefficient (
The authors are thankful to Joan Puigdefàbregas (LIM/UPC, Barcelona), Joaquim Sospedra (LIM/UPC, Barcelona) and Jordi Cateura (LIM/UPC, Barcelona) for the data acquisition. The research leading to these results and data acquisition received funding from Mestral (CTM-2011-30489), Neptune (KIC project 006-2012-R01-IREC-OFF-AERO), Hareamar/Dardo (ENE2012-38772-C02-02), Rises-AM (GA603396), iCOAST project (ECHO/SUB/2013/661009) and MINECO and FEDER who fund Plan-Wave (CTM2013-45141-R). Edited by: J. von Hardenberg Reviewed by: two anonymous referees