OSOcean ScienceOSOcean Sci.1812-0792Copernicus PublicationsGöttingen, Germany10.5194/os-12-433-2016Turbulence observations in the Gulf of Trieste under moderate wind forcing
and different water column stratificationFalcieriFrancesco Marcellofrancesco.falcieri@ve.ismar.cnr.ithttps://orcid.org/0000-0002-9759-6714KanthaLakshmiBenetazzoAlvisehttps://orcid.org/0000-0002-9535-4922BergamascoAndreaBonaldoDavideBarbariolFrancescoMalačičVladoSclavoMauroCarnielSandrohttps://orcid.org/0000-0001-8317-1603Istituto di Scienze Marine – Consiglio Nazionale delle
Ricerche, Venice, ItalyColorado Center for Astrodynamical Research – University
of Colorado, Boulder, CO, USANational Institute of Biology, Marine Biology Station,
Piran, SloveniaFrancesco Marcello Falcieri (francesco.falcieri@ve.ismar.cnr.it)11March201612243344917July201514August201521December201517February2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://os.copernicus.org/articles/12/433/2016/os-12-433-2016.htmlThe full text article is available as a PDF file from https://os.copernicus.org/articles/12/433/2016/os-12-433-2016.pdf
The oceanographic campaign CARPET2014 (Characterizing Adriatic Region Preconditionig EvenTs), (30 January–4 February 2014) collected the very first turbulence data in the
Gulf of Trieste (northern Adriatic Sea) under moderate wind (average wind
speed 10 m s-1) and heat flux (net negative heat flux ranging from 150
to 400 W m-2). Observations consisted of 38 CTD (Conductivity, Temperature, Depth) casts and 478
microstructure profiles (grouped into 145 ensembles) with three sets of yoyo
casts, each lasting for about 12 consecutive hours. Averaging closely
repeated casts, such as the ensembles, can lead to a smearing effect when in
the presence of a vertical density structure with strong interfaces that can
move up or down between subsequent casts under the influence of tides and
internal waves. In order to minimize the smearing effect of such
displacements on mean quantities, we developed an algorithm to realign
successive microstructure profiles to produce sharper and more meaningful
mean profiles of measured turbulence parameters.
During the campaign, the water column in the gulf evolved from well-mixed to
stratified conditions due to Adriatic waters intruding at the bottom along
the gulf's south-eastern coast. We show that during the warm and relatively
dry winter, the water column in the Gulf of Trieste, even under moderate wind
forcing, was not completely mixed due to the influence of bottom waters
intruding from the open sea. Inside the gulf, two types of water intrusions
were found during yoyo casts: one coming from the northern
coast of the Adriatic Sea (i.e. cooler, fresher and more turbid) and one coming from the open
sea in front of the Po Delta (i.e. warmer, saltier and less turbid). The two
intrusions had different impacts on turbulence kinetic energy dissipation
rate profiles. The former, with high turbidity, acted as a barrier to
wind-driven turbulence, while the latter, with low sediment concentrations
and a smaller vertical density gradient, was not able to suppress downward
penetration of turbulence from the surface.
Introduction
Turbulence and associated processes are gaining a broader interest within
the ocean sciences community for their fundamental role in many ocean
phenomena (Gargett, 1997; Thorpe, 2005). Because of their importance in
issues such as ocean mixing, energy transfer, dissipation or dispersion of
nutrients and pollutants, a better understanding of turbulent processes is
paramount for ocean sciences. While turbulence observations have become more
common in recent years there is still a need to collect more data sets for
use in the analysis of mixing in the water column, and to improve turbulent
mixing parametrization in numerical ocean models (Carniel et al., 2012).
The Gulf of Trieste (GoT henceforth) is a small and shallow bay (maximum
depth less than 30 m) located in the north-eastern corner of the Adriatic Sea
(Fig. 1). It is generally classified as a region of freshwater influence
(ROFI; Simpson et al., 1993) due to intense riverine discharges and undergoes a
marked seasonal variability. The GoT hydrodynamics are driven by winds (Bora
and Sirocco), tides, buoyancy effects of the Isonzo River plume and
exchanges of water masses with the Adriatic Sea. The north-easterly Bora
generates a cyclonic circulation in the northern Adriatic and pushes surface
waters out of the GoT, inducing a compensating inflow of open-sea waters
near the bottom (Malačič et al., 2012). The inflow/outflow transport
is governed by topographic control of the wind-driven circulation (Csanady,
1982). During Sirocco winds, however, the water masses at the surface are driven
to the northern shore of the Adriatic Sea between Venice and Trieste, where
they bifurcate in front of the GoT. The eastern part of the flow turns right
and enters the GoT along its northern coastline, while the western part
turns left and contributes to the coastal current flowing towards the Venice
lagoon (Malačič et al., 2012).
(Left panel) location of the CARPET2014 stations inside the GoT.
Red dots denote CTD stations; green circles MSS stations, red and blue
squares MSS yoyo sites from Y01 and Y02/Y03, respectively, yellow dot points
out
the VIDA buoy. The insert shows the location of the Adriatic Sea inside the
Mediterranean Sea. (Right panel) stations of the entire CARPET2014 cruise.
Red dots show locations of CTD casts, black rectangle marks the area of the
CTD casts considered representative of open-sea waters (see Fig. 4), the
green circle shows the station used as Y02 and Y03 casts end points.
The Isonzo River plume, during windless conditions, occupies the surface of
the northern GoT with inertial motions near the river outlet, while along
the frontal line that embraces the plume's bulge there is a
quasi-geostrophic motion with a convergence zone (Malačič et al.,
1996). Due to vertical mixing of the surface fresh water with seawater
across the halocline, this plume induces an inflow of water masses near the
bottom of the GoT (Malačič and Petelin, 2001). The annual mean flow
rate of the Isonzo River was about 90 m3 s-1 from 1998 to 2005
(Comici and Bussani, 2007), but different estimates, varying by a factor of
3 from this value, can also be found in the literature. In January–February,
the monthly mean flow rate ranged from 1 to 351 m3 s-1, with 41 m3 s-1 on average (Comici and Bussani, 2007)
during the 1998–2005 period. In 2014, the Isonzo River experienced a period
of strong discharges, with February 2014 average discharge rising to 547 m3 s-1. During the sampling period inside the GoT, the mean
discharge was 868 m3 s-1 with maximum and minimum values of
1768 and 327 m3 s-1, respectively (according to data
collected from the hydro-meteorological service of Friuli–Venezia Giulia,
Servizio Idrometeorologico – Protezione Civile Friuli Venezia Giulia). Those unusually large discharge rates have an effect on the surface density
structure, which in turn affects near-surface turbulence characteristics.
Turbulence measurements in the Adriatic Sea are scarce and scattered. To our
knowledge, a very limited number of papers dealing with this topic have been
published in the literature. Peters and Orlić (2005) presented the first
measurements of turbulence in the Adriatic Sea with a set of 32 casts in the
central basin collected in May 2003 within the framework of the
DOLCEVITA (Dynamics of Localized and Eddy Variability in the Adriatic)
project. During the collection period, wind forcing was weak and the water
column generally well stratified with a shallow mixed-layer depth. The
authors found small values for the turbulent kinetic energy (TKE)
dissipation rates in the upper mixed layer. Peters et al. (2007) reported a
second set, collected in February 2003 also within the DOLCEVITA project in
the shallow northern Adriatic under strong winds, intense cooling and a
well-mixed water column. Their main findings highlight different
contributions of surface forcing and bottom friction on the TKE dissipation
rate profiles. At both study sites, the main contribution to turbulence
generation was found to be mechanical and buoyancy effects were small.
Carniel et al. (2008) discussed two sets of repeated observations in the
southern Adriatic Sea in front of the Gargano peninsula during the March
2006 DART06A (Dynamics of the Adriatic in real time) cruise. Their study revealed layered thermohaline staircase
structures that originated from double diffusive convection. During the
DART06B cruise (August 2006), Carniel et al. (2012) collected a total of
more than 300 casts, which allowed them to describe the upper oceanic mixed
layer under a series of different meteorological conditions (different wind
forcing, night-time convection and strong insolation).
All of the studies cited above deal almost exclusively with the surface
mixed layer and only Peters et al. (2007) discuss the role of the bottom boundary on turbulent dissipation rates. This means that
the interaction between surface and bottom turbulence has only been
described briefly in the Adriatic Sea.
In this study a sub-set of observations will be described, which were collected during
the CARPET2014 (Characterizing Adriatic Region Preconditionig EvenTs) campaign on-board the R/V Urania in the northern Adriatic Sea
between 29 January and 10 February.
Observations and data processing
The CARPET2014 data set (Benetazzo et al., 2015) was collected between
30 January and 10 February 2014 in the northern Adriatic Sea.
In this work only the data collected inside the GoT will be discussed
(Fig. 1).
Turbulence measurements were made with two microstructure profilers (MSS 90;
Prandke et al., 2000), which were allowed to free fall until they hit the sea floor.
This operational procedure permitted collection of observations very close
(8 cm from the bottom) to the sea floor. During the cruise, 818 casts were
made at 104 stations, 554 with a MSS profiler owned by ISMAR-CNR (Istituto di Scienze Marine – Consiglio Nazionale delle Ricerche) and 264
with one owned by the Slovenian National Institute of Biology (NIB-MBP, National Institute of Biology – Marine Biology Station Piran). At
each station, three to five profiles were measured, which were then averaged
to obtain a mean profile representative of the water column during sampling.
We will refer to these profiles as ensemble casts.
Among all the stations, three were in yoyo mode, i.e. a series of repeated
casts in a fixed location with the R/V either at anchor or keeping the
position dynamically. A yoyo series is helpful in studying the temporal
evolution of the water column at a given location, but at the loss of
synoptic and spatial information. The three yoyo casts (Y01, Y02 and Y03)
were made at two stations close to each other in the deepest part of the GoT
(blue squares in right panel of Fig. 1) with a sampling rate of 30 min
(specifics of each set are reported in Table 1). During the last part of
Y03, the sampling rate was increased to every 15 min.
The temperature and salinity measurements from the two MSS probes were
calibrated against CTD (Conductivity, Temperature, Depth) observations by pairing the first cast of each MSS
ensemble to its spatially and temporally closest CTD. Of all possible
pairings, only those that were closer than 1000 m and taken less than 15 min apart were considered. In order to have an optimal cross-calibration, all profiles with a stratified water column were ignored (i.e.
those profiles that presented a salinity range higher than 0.3 or a
temperature range higher than 0.5 ∘C). This was necessary because
in the presence of a thermocline or halocline, even a small vertical
displacement (due to interface oscillations) between casts could result in
measures of different values at the same depths and hence errors in
calibration.
The bias, root mean squared error (RMSE) and percentage root mean squared
error (PRMSE) of each pair were computed, and all profiles with PRMSE less
than 1 % were used to compute each sensor bias. Results are shown in
Table 2.
Among all the profiles collected by the ISMAR probe, 73 pairs satisfied the
spatial and temporal proximity criteria and 21 were selected for cross-calibration based on vertical stratification criteria. The NIB probe had 60
pairs, with 28 of those eligible for calibration. For all profiles the bias
and RMSE are very low, almost at the precision limit of each sensor, and
PRMSE values are therefore small. The only sensor that shows a significant
BIAS (-0.2418) is the salinity sensor on the ISMAR profiler, which was
therefore corrected for later computations.
The two microstructure profilers acquired data at 1024 Hz to allow for the
collection of observations every 0.0011 m (given an average fall speed of 0.6 m s-1). Both probes were equipped with a standard CTD sensor (pressure,
temperature and conductivity), two shear sensors and a fast temperature
for the water column microstructure. Shear data from both profilers were
used to determine the turbulent kinetic energy dissipation rate using
(Gregg, 1987; Peters et al., 2007)
ε=7.5νdudz2,
where du/dz is the velocity shear and ν is the kinematic viscosity. Details
of the protocol used for data processing can be found in Prandke et al. (1998); the algorithm used to minimize the smearing effect of interface
observations is given in Appendix A.
In addition to the microstructure profiles, ancillary observations include
104 CTD, current measurements made with a downward looking hull-mounted ADCP (Acoustic Doppler Current Profiler, RDI workhorse 75KHz), acoustic bin size set to
4 m with a blank interval of 5 m and first bin centred at 7 m), and
meteorological forcing acquired by the R/V Urania weather station and by the Slovenian coastal observatory VIDA buoy. During selected periods 3-D sea-surface
wave-field measurements were made with a Wave Acquisition Stereo System
(WASS; Benetazzo et al., 2012) mounted on the port side of the R/V bridge
about 8 m above mean sea level.
Bias, root mean square error (RMSE) and percent RMSE computed for
the ISMAR and NIB MSS probes compared to CTD measurements.
Compared to the climatological mean, the winter of 2013–2014 can be
considered dry and warm, with January 2014 and the period of the CARPET2014
cruise being anomalously warm and moist. During the campaign, a warm and
moist air mass was flowing from the south-east (northern African coast) over
the northern Adriatic region while, at the same time, a cold air mass was
flowing from the eastern part of the European continent towards the northern
Adriatic Sea.
Atmospheric and sea-surface observations and fluxes collected from
the R/V Urania (left panels) and VIDA buoy (right panels). (a) Air (red) and sea
(blue) temperature time series; (b) wind speed (light green) and wind
direction (black); (c) net (blue line), latent (light blue) and sensible
(orange) heat fluxes computed with the COARE algorithm and buoyancy flux
(magenta); (d) wind stress (cyano), Monin–Obukhov length (black) and Stokes
drift (dark green). Given that the maximum depth of the GoT is 25 m,
Lmo is shown up to -250 m depth to provide a clearer representation of
the water column. Lmo values can be as low as -1200 m during calm
periods. Vertical dashed lines show the yoyo cast collection time.
Bottom currents and values from CTD casts at surface and bottom are
shown inside the GoT for 30 January (top panels), 31 January
(central panels) and 4 February (bottom panels). Panels on the left
column show the ADCP bottom cell currents; red arrows are observations taken
during rising tide, blue arrows during falling tide. Temperature (second and
third columns) and salinity (fourth and fifth columns) values are shown for
surface (0 and 2.5 m) and bottom layers (last 2.5 m of cast) inside the GoT.
Atmospheric data, sea-surface temperature and salinity were recorded
throughout the cruise by the R/V Urania's ship-borne weather station (located
about 10 m a.s.l.) and by a thermistor and a salinometer mounted on
the R/V's hull, about 2 m b.s.l. (Fig. 2, left panel). The
latter had a bias of 0.2 when compared to CTD data and hence its
measurements used for computation of fluxes were corrected accordingly. The
R/V Urania sailed in the GoT and did not hold a fixed position, and therefore, in
order to have a complete representation of the atmospheric conditions, the
ship-borne weather observations need to be supplemented by a fixed
observation point. Data collected from the Slovenian coastal observatory
VIDA were also used for computation of fluxes (Fig. 2, right panel). The
VIDA buoy is anchored at a depth of 22 m about 2.3 km off the coast in front
of Piran (https://www.nib.si/mbp/en/buoy/general). Atmospheric
observations and fluxes computed using the two data sets show strong
similarity, and therefore their merged analysis can be considered to be
representative of the atmospheric conditions over the whole GoT during the
campaign. The small-scale variations in R/V Urania's data set can be ascribed to a
higher sampling rate (one record per minute) with averages over 10 min
intervals used for flux computations, compared to the 30 min averages for
the VIDA buoy data set.
At the beginning of observations, easterly Bora was turning to a south-east
Sirocco (∼ 10 m s-1) that lasted for 2 days until the
night of 2 February, when it turned back to a Bora with an average wind
speed of 10 m s-1 with peaks of 16 m s-1 (Fig. 2b);
during the Sirocco event, three calm periods were recorded with weak winds
from the north. Air temperature showed a similar pattern with lower values
during Bora (between 5 and 8 ∘C) and a warmer one during Sirocco
(up to 14.5 ∘C). The three calm periods can also be seen in air
temperature, with sudden drops of about 5 ∘C. Throughout the
cruise, sea-surface temperature was rather constant around 11.5 ∘C with an increasing trend toward the end of the operations
(Fig. 2a). The ship-borne observations showed a stronger variability with respect
to the VIDA ones due to the R/V's positional changes within the GoT. Analogous
behaviour was also seen in sea-surface salinity (not shown).
(Left panel) θ–S plot of all CTDs and MSSs (both ISMAR and
NIB) casts (light grey for the northern Adriatic and dark grey for the GoT).
The green and red dots are the MSS-ISMAR and MSS-NIB ensemble means for Y02
and Y03, respectively, light colour for surface values and dark colour for
bottom ones. The green circle indicates the bottom waters observed at the
entrance of the GoT on 30 January that are the end point for Y02
bottom waters; red circles point to deep waters outside the GoT on 4 January
considered as the end point of Y03 bottom water. The black square
encompasses values in bottom waters in the centre of the North Adriatic Sea.
Locations of end points are shown in Fig. 1. The profiles of the cast
leading to the end points are shown in light blue. (Right panel) θ–S
plot for Y02 and Y03. Colour scale shows turbidity FTUs (formazin turbidity units) as measured by the
back scatterometer mounted on the MSS ISMAR probe.
Figure 2 also shows the heat fluxes (panel c) and wind stress (panel d in
cyan) computed using the COARE algorithm (Coupled Ocean-Atmosphere Response Experiment; Fairall et al., 2003), from on-site observations (sea-surface temperature and salinity, air temperature,
pressure and humidity) and from short- and long-wave radiation. The radiation
fields were derived from an implementation of the Coupled Ocean Wave and
Sediments model over central Europe with a 7 km horizontal resolution
(Ricchi et al., 2016).
The net heat flux was always negative at both sites, with a heat loss from
the ocean to the atmosphere always higher than 150 W m-2 during Bora
events (peaks of just over 400 W m-2 at Urania and 350 W m-2 at VIDA).
During Sirocco events, fluxes were generally smaller, with heat losses of
around 100 W m-2. It is noteworthy that on the one hand the latent heat
flux was always negative, but on the other hand, sensible heat flux turned
positive during Sirocco due to air temperature being higher than the sea-surface temperature. During the three calm periods, a drop in wind speed and
air temperature, below the sea-surface temperature, resulted in a switch in
the sensible heat flux direction.
The buoyancy flux at the surface (Fig. 2d) was obtained following
Shay and Gregg (1984, 1996) as
Jb=gρwαCpJt+βSLE(1-S)Jl,
where the first term inside brackets represents the heat buoyancy flux,
computed from the net heat flux (Jt), the thermal expansion coefficient
(α=-2.16×10-4∘C-1) and the sea water
specific heat (Cp=3.98×103 J K-1 kg-1); the second term
is the evaporative buoyancy flux computed from the latent heat flux
(Jl), the haline contraction coefficient (β=0.79), the latent
heat of evaporation (LE=2.6×106 J kg-1) and sea-surface
salinity expressed as concentration. The convention used for heat and
buoyancy fluxes in this study is that negative/positive fluxes correspond to
losses/gains from/to the ocean to/from the atmosphere. In the case of
buoyancy, this means that a negative Jb corresponds to a loss of
buoyancy from the ocean to the atmosphere (i.e. water is getting less dense)
with a stabilizing effect on the water column, while positive Jb
indicates a gain of buoyancy (i.e. water becoming more dense) and hence a
destabilizing effect on the water column.
Hydrological conditions and water mass structure
The hydrological conditions in the GoT during CARPET2014 are the result of
the forcing described in Sect. 2.1, a combination of wind-driven
circulation during the two prevalent winds (Bora and Sirocco), with inertial
oscillations in offshore areas during times of wind shifts from one type to
another and during periods of calm between windy episodes.
Weather and ship logistical constraints did not permit a synoptic
hydrological survey of the entire GoT; hence, different parts of the basin
were covered each day. In order to give a rough overview of the
hydrodynamics of the GoT, surface (from 0 to 2.5 m) and bottom (last 2.5 m of cast) temperature and salinities collected on 30 and 31
January, as well as 4 February from CTD casts, are shown in Fig. 3 along
with the bottom currents measured by the hull-mounted ADCP.
The overall picture that emerges from Fig. 3 is a bottom circulation with
waters incoming from the open sea along the south-eastern coast and flowing
out along the north-western coast (left panels). The same pattern is common to
both tidal intervals, during rising (blue arrows in Fig. 3 left panels) and
falling (blue arrows in Fig. 3, left panels) tides, with the latter
showing weaker currents. The intervals of rising and falling tides have been
defined from the pressure values recorded by the bottom-mounted ADCP located
at the VIDA buoy. The apparently incoherent vectors close to the coast can
be explained by the influence of the coastline and the shallow topography
on the local currents. Each plot shows a 24 h collection of data over a
relatively small area, and may also include small-scale variations.
Temperature and salinity distributions (Fig. 3) are in agreement with the
general picture of warmer and saltier bottom waters entering the southern
part of the GoT and cooler and fresher waters confined to the northern part.
The low surface salinity values in the northernmost part and in front of
Trieste (Fig. 3, right panels) are the result of the influence of the
Isonzo and Timavo discharges (Fig. 1, left panel), respectively. It is of
interest that on 4 February, the easternmost stations were warmer and
saltier throughout the water column than those on 30 January. This
cooling of the water column was due to the steady negative heat flux between
Y02 and Y03 (Fig. 2).
The θ–S (potential temperature–salinity) plot (Fig. 4),
computed from both CTD and MSS data, helps in the identification of the
water masses that were present in the GoT and in the northern Adriatic Sea
during the campaign. Inside the GoT (dark grey dots in Fig. 4), the water
temperature was lower than that outside of the basin (light grey dots in
Fig. 4), due to the moderate negative net heat flux throughout the cruise
(ranging between -150 and -400 W m-2) and the shallow bathymetry of the
GoT. Apart from the Isonzo River mouth and the inner part of the gulf,
salinity values are comparable to (or slightly smaller than) the rest of the
Adriatic Sea. By looking at Y02 and Y03 casts (red and green dots), it is
possible to highlight the different origins of part of their bottom waters.
More specifically, Y02 presents deep waters (dark green in the left panel of
Fig. 4), whose θ–S values are directed towards an end point (green
circle in the left panel of Fig. 4, location shown in Fig. 1, right
panel) close to the density isoline 1029 kg m-3, which is compatible with
northern Adriatic coastal waters (i.e. fresher, cooler and more turbid
waters) observed right outside the GoT on 30 January. On the other hand, Y03 θ–S values of bottom waters have an end point
(red circle in left panel of Fig. 4, location shown in Fig. 1 right
panel) typical of the open basin, slightly warmer, saltier and cleaner
waters (Fig. 4, right panel). Moreover, in the case of the Y03 end point, its
characteristics are similar to the open-sea bottom waters in front of the Po
Delta (black rectangle in the left panel) during periods of low discharges
(Falcieri et al., 2013). The slight misalignment of those θ–S points
with respect to the Y03 end point can be explained by their position being
close to the influence of the Po River plume. Both end points are
located over the same station but were recorded 4 days apart, the first
one on 31 January and the second one on 4 February.
The wave field over the GoT was assessed from data collected by the WASS
system on the R/V and at the VIDA buoy. A total of four WASS acquisitions, each
of roughly 15 min, were collected between 12:05 and 14:32 UTC of
3 February, right before Y03, and resulted in an average significant
wave height (Hs) of 0.8 m, period (Tm) of 3.9 s and wave length of 23 m.
During the acquisition the wind forcing was stable, with a mean wind speed
of 14 m s-1 and direction of about 75∘ N (typical of Bora
wind).
To cover a longer part of the study period, the wave and wind data collected
at the VIDA buoy were used. The wave spectrum E(f) of each sea state at the buoy
was represented by the JONSWAP spectrum (Hasselmann et al., 1973). This assumption
is consistent with the spectrum computed from the R/V with the WASS
observations. A further verification of this is that the Hs and Tm computed at
VIDA with JONSWAP (given the wind speed and fetch length) are close to those
directly observed. This spectrum, which models the distribution of wave
energy in deep water fetch-limited sea states, was used to compute the
Stokes drift (Us) following Hasselman (1970) as
Us(z)=∫0∞1g(2πf)3Efexp-2g2πf2zkdf,
where z is the vertical coordinate positive upwards, g the gravitational
acceleration, f is the frequency in Hz and k is the unit vector in the wave
propagation direction. During the period under investigation, fetch-limited
and deep-water conditions occurred from 2 February 2014 at 00:00 UTC
to 4 February 2014 at 12:00 UTC, as moderate and persistent Bora winds
were blowing over the Gulf of Trieste (Fig. 2). A further verification of
this approach is given by the fact that the Stokes drift computed from the
WASS spectrum (0.06 m s-1) is in good agreement with the value computed
at VIDA (0.05 m s-1) using the JONSWAP spectrum. The Us time series (dark green line in Fig. 2d, right side) closely follows the wind stress with values ranging
from 0.01 to 0.07 m s-1.
Turbulence scaling
Ocean turbulence is generated and enhanced by different processes such as
the shear stress at the sea surface or the bottom, buoyancy fluxes and
unstable stratification, breaking and motion of surface and internal waves
and wave–current interactions (Burchard et al., 2008; Thorpe, 2005; Kantha
and Clayson, 2004). In this study the observed TKE dissipation rate profiles
will be compared to their forcing with a similarity scaling approach (Peters
et al., 2007) to highlight discrepancies between the theoretical and the
observed profiles, identify the dominant forcing and show the role of
buoyancy interfaces in suppressing turbulence in the water column.
Turbulence generated by surface wind stress obeys a law of the wall scaling
below the wave-influenced surface region (D'Asaro, 2014; Thorpe,
2005) as
εs=u∗3kz,
where k=0.4 is the von Kàrmàn constant, z is the distance from the sea
surface and u∗ is the friction velocity given by
u∗=τaρ12
where τa is the wind stress computed with the COARE algorithm
from wind speed at 10 m height and ρ is the surface water density
computed from the R/V's hull-mounted instruments. This scaling is valid for
the surface layer either under calm sea conditions or below a depth at which
turbulence generation by wave breaking or wave–current interactions becomes
insignificant (Burchard et al., 2008; Thorpe, 2005).
The law of the wall approach is also valid for turbulence generated by
bottom shear stress above a few centimetres thick viscous layer. As for the
wind stress-generated turbulence, the TKE dissipation rate near the sea
floor can be scaled as
εb=u∗b3kh,
where h is the distance from the sea floor and u∗b the bottom
friction velocity given by
u∗b=τbρ1/2
in which the bottom shear stress (τ∗b) is computed with a non-linear function of the depth-averaged velocity with a quadratic bottom drag
law computed as
τb=ρCDu2,
where ρ is the local water density, u the average bottom current speed
as recorded by the downward looking ADCP and CD=0.003 is the
bottom drag coefficient (Peters et al., 2007). In the case of Y02 and Y03,
current observations are the average of the cells that span from 13 to 17 m depth, roughly 8 m above the sea floor. Hence, the bottom stress here
computed needs to be regarded as just a rough estimation.
It is common to assume that the dissipation rate due to buoyancy in the
surface mixed layer is uniform and equal to εb=cJb. The value of the constant c is trivial to define and different figures
have been proposed ranging from c=0.25 for the surface upper bound and c=0.4 under strong pycnoclines (Kantha, 1980) to c=0.6 (Shay and Gregg,
1996; Peters et al., 2007). Here the latter parameterization will be used.
The wave contribution to turbulence in the surface layer is a more complex
topic since it consists of three different processes: wave breaking, Stokes
production and the development of Langmuir circulation. In the case of wave
breaking, the contribution to TKE is generally confined to a depth of the
order of the significant wave height and is dissipated rapidly in less than
four wave periods (Anis and Moum, 1995; Kantha and Clayson, 2004; Paskyabi
and Fer, 2014). Stokes production can be a large contribution to TKE, Kantha
(2010; see also Kantha and Clayson, 2004 and Kantha et al., 2010) estimated
that its magnitude can be of the same order of conventional shear-generated
TKE and can extend deep into the water column where the shear generated by
Stokes drift is still significant. Langmuir circulation can extend
vertically down to the mixed-layer depth (Grant and Belcher, 2009; Teixeira
and Belcher, 2010).
In the collected data set not all the information is available to
fully investigate and scale the role of waves in turbulence generation. To
give a general description of the relationship between different turbulence
forcings, we adopt a regime diagram (Li et al., 2005) as modified by Belcher
et al. (2012). The diagram is constructed by plotting the Langmuir number
versus the ratio of the buoyancy and wave-forced turbulence. The Langmuir
number La (McWilliams et al., 1997) represents the ratio between the wind and
wave-forced TKE production and is computed as
La=u∗Us1/2,
where Us is the Stoke drift velocity. La=0.35 (McWilliams et al., 1997) or La=0.4 (Belcher et al., 2012) are common values for well-developed sea and
show a dominance of Langmuir circulation over wind-forced production. The
transition between those two regimes can be set for La=0.7 (Belcher et
al., 2012). The second ratio is computed h/LL, where h is the mixed layer depth and LL is the Langmuir stability
length:
LL=-w∗LJb,
where Jb is the buoyancy flux as computed in Sect. 2.1 and w∗L is the
scaling for wind and wave-forced turbulence (Kantha and Clayson 2000, Kantha et al., 2010):
w∗L=u∗2Us1/3,
where Us is the Stokes drift computed as described in Sect. 2.2.
Yoyo casts and turbulence observations
Microstructure profiles were collected form a free-falling profiler and
hence the surface layer (roughly 2 m) was lost. Moreover, the usual
practice in processing microstructure casts is to ignore depths up to twice
the vessel draft in order to avoid contamination from the turbulent ship
wake. However, TKE dissipation profiles will be shown cutting off only the
first 5 m (roughly the vessel draft) because, even if noisy and not
scaling well with the available forcing, data collected from 5 to 10 m can
still give some information on the magnitude of the surface TKE production
and on its transfer to deeper layers of the shallow GoT.
Regime diagram of turbulence forcing computed at the VIDA buoy from
2 February (14:30 UTC) to 4 February (12:00 UTC). Green and orange
squares represents values before and after the Y03, red marks are the values
for the ensembles shown in Fig. 9. The horizontal dashed line indicates
the demarcation between convection dominated turbulence and shear stress
dominated one; the vertical dashed line shows demarcation between
conventional wind stress-driven turbulence and Stokes production-driven one.
In the CARPET2014 data set the observed TKE dissipation scaled as expected
with the exception of a surface layer that can reach as deep as 10 m
(as TKE dissipation rate profiles in Fig. 9 will show), this mismatch can
be attributed to the complex forcing of surface turbulence. Figure 5 shows
the regime diagram of turbulence forcing at the VIDA buoy computed every half an
hour. A reduced time series (from 2 February 00:00 UTC to 4 February
12:00 UTC) had to be chosen since it was the only period covered by
the shipborne WASS observations, used to verify the JONSWAP spectrum, and of
almost constant wind forcing. Up to the end of Y03 (3 February at
12:00 UTC, green squares in Fig. 5) turbulence generation was dominated by
wave forcing with some contribution from wind shear and a growing importance
of buoyancy (the ratio h/LL is slowly increasing). The orange squares
represent values between the end of Y03 and 4 February at 12:00 UTC
and show a progressive weakening of all forcing with buoyancy decreasing
to a lesser extent and hence defining a dominance of convection in TKE
generation.
The regime diagram of Fig. 5 gives, as a general picture, a condition in
which the role of buoyancy in TKE generation changes significantly
(h/LL varies between 0.16 to 7.95), reaching a quasi-dominance after
Y03. Instead the values of La present much smaller variations (between 0.47
and 0.55), meaning that the relative contribution of wind and waves is
almost constant throughout observations with a stronger role of the latter.
During the following analysis, we will show the similarity scaling for wind
shear and buoyancy but not for waves, due to the fact that no wave field
observations were collected during the yoyo casts. Moreover, using the probe
in a free-falling configuration we do not have information on the layer
under direct influence of wave TKE production. Similarly not enough
observations were collected to describe the eventual insurgence of Langmuir
circulation. Hence, as will be discussed for Fig. 9, there is a significant disagreement between the observed profiles and the similarity
scaling for the upper 10 m; this can be explained by the role of waves and
wave–current interaction in generating and distributing turbulence. In this
work we focus on the role of bottom intrusions with different turbidity in
suppressing turbulence and hence we leave a thorough description of the surface condition to future studies.
Hovmöller diagrams for Y01: (a) wind stress and buoyancy flux
during the Y01, (b) temperature profiles, (c) salinity profiles, (d) turbidity
profiles in FTU, (e) turbulent kinetic energy dissipation rate in logarithmic
scale (contours spaced in log of 1 W kg-1). Red dashed lines show the
time of collection of the Y01 casts reported in top panels of Fig. 8.
Y01 ADCP currents: second (top panel) and third (bottom panels)
cells of Y01 ADCP currents. The cell centres are located at 13 and 17 m below sea surface; cell width is 4 m. Black lines show current direction in
degrees (due north) and green lines show current magnitude in m s-1.
Red dashed lines show the time of collection of the Y01 casts reported in
top panels of Fig. 8.
Similarity scaling of turbulent kinetic energy dissipation rate
(ε) for four representative casts for each yoyo, Y01 top
panels, Y02 central panels and Y03 bottom panels. For each cast the
observed TKE dissipation rate is shown (ε, thick red line), and the
turbulence generated by surface wind stress (εs, green
line), bottom shear stress (εsb, blue line) and buoyancy
flux (εb, magenta vertical dashed line).
Yoyo cast Y01 was located in a shallower part of the GoT closer to the coast
(Fig. 1, red square in left panel). It presented a completely mixed water
column with no visible stratification, just a small increase in
temperature (less than 0.2 ∘C) and a decrease in salinity (about
0.1) toward the end of the yoyo series (Fig. 6). During sampling, surface
salinity (well over 37) shows no influence from the Isonzo River; turbidity
levels, however, were significantly high, in the range of 22.6 to 23.5 FTU.
TKE dissipation rate profiles showed high values near the sea surface, which
progressively decreased to values of the order of 10-6 W kg-1 near
the bottom, with one exception being the cast Y01-05 (fifth ensemble of yoyo
Y01) in which ε values were high throughout the water column.
ADCP-measured currents (Fig. 7, lower panel green line) showed generally
low bottom currents of magnitudes below 0.1 m s-1 with an increase
toward the end of observations to values smaller than 0.2 m s-1. This
can be explained by the change in tidal regime from falling to rising tide
and is also reflected in the ε profiles that show an increase
near the sea floor for the last ensembles of the series. The shallower cell
(Fig. 7, upper panel green line) presents a similar condition, with two
peaks of magnitude just less than 0.2 m s-1 but without an increasing
trend during sampling. Current directions (Fig. 7, black lines) are more
complex, with dominant direction from the east for the surface cell, and
from the south-west for the bottom cell.
Hovmöller diagrams of Y02 (left) and Y03 (right). Panels
shows (a) wind stress (cyan) and buoyancy flux (magenta), (b) temperature
profiles (grey contours are spaced 0.1 ∘C), (c) salinity profiles
(grey contours are spaced 0.1), (d) turbidity profiles in FTU (grey contours
are spaced 1 FTU) and (e) turbulent kinetic energy dissipation rate in
logarithmic scale (contours spaced in log of 1 W m-2). Red dashed lines show the time of collection of the yoyo casts reported in Fig. 8.
The TKE dissipation rate profiles support the measurements just described and
are in agreement with the local forcing (Fig. 8). In the case of Y01-01
and Y01-07, both characterized by strong wind forcing, a surface layer of
about 8 m in which TKE dissipation rates fall to 10-6 W kg-1 can
be identified, while near the sea floor, the bottom shear stress did not
influenced the TKE dissipation rate much. The Y01-08 ensemble was collected
under weak winds and the surface layer, with marked TKE dissipation rate drop,
was shallower (just 5 m). The last ensemble of the series (Y01-11) was
collected during rising tide with bottom currents up to 0.2 m s-1 and
moderate wind stress. This is reflected in the TKE dissipation rate profile
with a decrease in depth in the first 10 m and then a marked increase in
the last 5 m, due to the influence of turbulence generated by the bottom
shear stress. In all casts, the contribution of buoyancy-generated
turbulence is weak (εb, magenta dashed line in Fig. 8)
since the buoyancy flux is low and the Monin–Obukhov length scale is very
large (negative), larger than the local sea floor depth (Fig. 2d).
Y01 profiles show that in the absence of water column stratification, the
ε profile is mostly defined by the surface wind and bottom
stresses.
Yoyo casts Y02 and Y03 were located at the same site (Fig. 1, blue square)
but roughly 2 days apart from each other and present significant
differences in both water column structure and ε profiles. The
water column during Y02 (Fig. 9) was always stratified, at the beginning
of the casts with colder and fresher waters at the surface (consistent with
the influence of the Isonzo River discharges, as hinted by high turbidity),
then with warmer and saltier intrusion near the sea floor. Higher suspended
sediment concentrations were observed at the bottom at the beginning and
towards the end of the yoyo. Apart from the surface layer, the TKE
dissipation rate was generally low from mid-depths to the sea floor with
values almost at noise level (ε values lower than 10-8 W kg-1), but increased by 2 orders of magnitude around 18:00 UTC
on
1 February and then decreased again to very low values. ADCP currents
(Fig. 10) at bottom (ADCP cell 3 centred at 13 m depth, lower panel) and
mid-depths (ADCP cell 2 centred at 9 m depth, top panel) were similar, with
water flowing to the north-east (current speed up to 0.2 m s-1) during a
rising tide up to around 20:00 UTC. Once the tidal phase changes to falling
tide, currents turn toward the south-east, with an abrupt change in the bottom
layer, and drop to values below 0.05 m s-1.
In contrast to the Y01 data set, the Y02 ensembles had a more complex behaviour
due to the presence of surface stratification, the incoming water bottom
intrusion and the change in tidal character. Casts Y02-01 and Y02-04 (Fig. 8, middle panels) had a similar water column structure, with fresher and
cooler waters at the surface and more turbid waters near the sea floor. The
surface wind stress was weak during both casts and a steep drop of
ε to values below 10-6 W kg-1 can be seen around 7 m depth. Below this depth, the two ε profiles diverge due to
different bottom current velocities. In Y02-01, ε falls to
noise level due to a slower bottom current (and hence low bottom shear
stress). In
contrast, Y02-04 was characterized by higher wind stress with a TKE
dissipation rate significantly higher, reaching values above 10-6 W kg-1 with a profile that closely follows the εsb. In
the second half of the yoyo series, wind speed increased up to values around
10 m s-1, which results in a deepening of the ε drop from 7 to 10 and 15 m in Y02-06 and Y02-10, respectively. Y02-06 has a bottom
current velocity close to that of Y02-04 but ε reaches lower
values at the bottom due to the damping effect of the incoming water mass
intrusion.
A more extreme case of an abrupt drop in TKE dissipation rate near the sea
floor was Y02-10, in which ε reached noise levels just 5 m above the sea floor. This was the result of a concurrence of two factors. On
the one hand, a sudden drop in bottom current velocity can be related to the
change in the tidal character (that results in a lower εsb). On the other hand, a different water mass (warmer, saltier and
with high concentrations of suspended sediments) intruded in the bottom
layer and acted as a physical barrier to the propagation of wind-generated
turbulence to the bottom part of the water column. The turbulence generated
by buoyancy flux was low throughout Y02 with the exception of the first
ensembles, as shown by the small Monin–Obukhov length (Fig. 2).
Y03 (Fig. 9, right panels) presented a water column cooler and fresher
than Y02 with values closer to Y01. No surface salinity stratification was
observed as a result of the strong Bora winds that pushed the Isonzo plume
out of the GoT along its northern shore and enhanced vertical mixing to a
point in which the water column was completely mixed (i.e. Y03-07).
Moreover, the Isonzo discharges during Y03 presented a decrease in magnitude
from the flood event (mean discharge 500 m3 s-1) lasting between
noon of 3 February and 4 February. During Y03 two intrusions
were observed near the bottom, one right at the beginning of the series
ending at about 16:00 UTC and one starting around 00:00 UTC and lasting for
the remaining part of the yoyo. Even though those intrusions involve water
masses of similar temperature and salinity, they were significantly
different in turbidity, with the first intrusion carrying more suspended
sediments than the second one. This can be partially attributed to current
speed and direction, with the first intrusion flowing south-west at
velocities higher than 0.1 m s-1 and the second one due east at a much
lower speed (Fig. 10), with water properties consistent with an open-sea
origin as shown in Fig. 5. It is of interest to note the abrupt change in
current direction around 00:00 UTD right at the beginning of the second
intrusion, which also points toward a different origin of this water mass.
Y03 TKE dissipation rates were generally higher than those of Y02 throughout
the series. Y03-01 had a stratified water column with gradients across the
pycnocline similar to those of Y02-10, with a mixed surface layer and with
intruded turbid and dense water at the bottom. Below the mixed surface layer,
the ε value dropped to almost 10-8 W kg-1 at the top
of the intrusion (20 m) and then abruptly rose back to values of the order
of 10-6 W kg-1 as a consequence of high bottom currents (Fig. 8). In the case of Y03-07, there is no intrusion and the water column is
fully mixed, so that the ε profile after decreasing in the
surface layer stayed around 10-6 W kg-1 also near the sea floor
(i.e. no significant influence of εsb). In the second part
of the yoyo series (Y03-18 and Y03-20), the intruding water mass in contrast
to Y03-01 and Y02-10, was not enhanced by a high suspended sediment load and
hence the TKE dissipation rate was still damped by density interface but to
a lesser degree than in the other cases.
Summary and discussion
Between the end of January and the first week of February 2014, during a
period of high river discharges and moderate wind forcing, we were able to
make the very first microstructure measurements in the Gulf of Trieste (Fig. 8, middle panels, and Fig 9, left panels).
These observations, along with CTD casts, ADCP currents and meteorological
measurements, provided a comprehensive picture of the effect of different
forcing and water masses on the penetration of turbulence from its source
regions and on mixing in the water column.
The CARPET2014 data set analysis shows a winter circulation inside the GoT
driven mostly by wind, tides and the Isonzo River plume. As expected, a
significant correlation was found between the bottom circulation, and the
wind and tidal forcing. During strong wind periods, such as during Y02 or
the beginning of Y03, bottom currents increased in magnitude, while during
weaker winds, such as the beginning of Y02 and the end of Y03, they tended
to decrease. Near the sea floor, two types of bottom water intrusions were
identified: the first one coming from the northern Adriatic coastal area
during Y02 and the second one from the open sea in front of the Po Delta
during Y03. Those intrusions present similar densities but different
physical properties (i.e. temperature and salinity) and suspended sediment
concentration. Moreover, their arrival in the GoT followed periods dominated
by different wind forcing, mostly Scirocco for the first intrusion and Bora
for the second.
Apart from the surface layer, the TKE dissipation rates follow the
similarity scaling for wind stress-generated turbulence and for the one due
to bottom shear stress near the sea floor (Fig. 8). Buoyancy-driven
turbulence under those conditions proved to be generally insignificant, as
shown by the Monin–Obukhov length scale being generally greater than the
sea floor depth.
Second (top panel) and third (bottom panels) cells of ADCP
currents. The cell centres are located at 13 and 17 m below sea surface;
cell width is 4 m. Black lines show current direction (due north) and green
lines show current magnitude in m s-1. Left panels show Y02, right
panels Y03. Red dashed lines show the time of collection of the yoyo casts reported in Fig. 8.
The ε profiles of Fig. 8 and the water column properties
shown in Figs. 6 and 9 can help in defining a general description of the
impacts of density interfaces on the TKE dissipation rate in the water
column.
Well-mixed water column: the TKE dissipation rate profile, below the surface
layer, is solely defined by its forcing. Examples of this are the Y01
ensembles, in which the ε profiles closely follow the scaling
both in the middle of the water column and at depth (Fig. 8, top panels),
and the Y03-07 ensemble, which presented an almost constant TKE dissipation
rate below the surface layer.
Surface stratification: in presence of a stronger surface density interface
(i.e. casts Y02-01 and Y02-04), turbulence is confined to the shallow surface
layer with low ε values in the rest of the water column, whether
bottom currents are low (Y02-01) or with an increase in ε in
presence of strong bottom currents (Y02-04). It is noteworthy that in both
cases the bottom turbidity was high but not able to damp turbulence in the
absence of a density interface.
Dense bottom intrusion with turbidity gradient: when a turbidity gradient is
also present at a density interface the damping effect on turbulence is
significantly enhanced as in Y02-06, Y03-02 and Y02-10. In the first two
ensembles an increase of ε was observed due to a strong bottom
current, which was not present during Y02-10, hence the sudden drop of O(2)
in ε just below the density and turbidity interface.
Dense bottom intrusion without any turbidity gradient: the presence of a
density interface at the bottom produces a gradual damping of turbulence
(Y03-18 and Y03-20). In this case, there is no significant difference in
turbidity between the intrusion and the ambient waters and hence
ε is decreased but to a lesser degree than in the previous
case.
The general picture that can be drawn from these results is that the water
column structure (both the presence of buoyancy and suspended sediments
gradients) plays a fundamental role in defining the TKE dissipation rate,
not only inside the water column but also in the proximity of the sea floor.
In the specific case of the GoT, under moderate wind forcing, the presence
of the intruding Adriatic waters can be a significant limitation on complete
mixing of the water column.
The traditional approach in processing microstructure profiles calls for
averages of repeated casts (when logistically feasible three or more) at
each station, to reach statistical significance and increase the accuracy.
The averaging produces meaningful results for the mean profiles and yields
quantities more representative of the turbulence in the water column.
However, cases in which the water column has strong stable density
interfaces moving up and down are exceptions. In those cases, turbulence and
other parameters differ from one cast to another in their vicinity. In the
CARPET2014 data set, changes in the interface depth between casts were as
much as 4 m. This means that by averaging measured quantities at fixed
depths over consecutive profiles, the averages get smeared, and hence
characterized by smoother gradients and broader peaks. To avoid this, an
ad hoc algorithm was developed using the central profile of each ensemble as
reference and realigning sections of the remaining profiles to it. The mean
profile was then obtained by averaging the central profile with the
realigned sections. The step-by-step procedure applied to two consecutive
vertical profiles, is as follows:
One profile is chosen as the reference (Fig. A1a, cyan) and the
other as the one to be realigned (Fig. A1a, black).
Starting from the surface, the correlation coefficients are computed for a
progressively longer section, until the full profiles (i.e. surface to
bottom) are accounted for. Starting from the surface, the section with the
maximum correlation value is considered as a “surface layer” that does not
need to be shifted. In Fig. A1c, its lower limit is the horizontal
red line.
The root mean square error for the remaining parts of the profiles is then
computed with a 5-point moving window (Fig. A1c black line) and the
maximum peaks are found (Fig. A1c red dots). If the two peaks are
closer than 10 points to each other, just the largest one is considered. The
10-point window was chosen because in a sensitivity test (not shown), it
proved to be the most efficient in separating the two peaks. The two peaks
are then used to identify the sections to realign. The limit of each section
is set at the mid-point between two peaks (red line, in Fig. A1c).
Each section of the profile to be realigned is then correlated to the
reference profile shifting it from +20 to -20 points. The shift with
maximum correlation is then taken as the needed shift. In Fig. A1d,
the reference profile is in cyan, the one to be shifted in black and the
shifted sections are in red.
The process is repeated for each successive cast at the station and then the averages are computed over the new shifted profiles and the reference one. The final result of the process is shown in Figure A1e and A1f.
Figure A1 also presents the same plots but for ε.
The method described above offers a more meaningful vertical distribution of
the TKE dissipation rate, by taking into account the vertical oscillations
of the pycnocline, since turbulence is extinguished in the vicinity of
strongly stable interfaces. As a consequence, in the vertically shifted
profiles, the peaks in the TKE dissipation rate are much clearer and better
represent the shape of the observed profiles. The peaks are just above the
thermocline. In general, when more than one cast is collected at a station,
the most conservative assumption is to consider the central profile as the
reference one for the water column structure. Other profiles over the cycle
are then realigned with respect to the reference profile to obtain the TKE
dissipation rate caused by vertical shear, uncontaminated by the zero values
right at the interface.
(a) Original temperature profiles used in the realignment
algorithm: reference in cyan, profile to be realigned in black. (b)
Correlation coefficient computed for progressively longer segments starting
form surface. The black vertical line is the 0.95 correlation threshold and
the red circle the maximum correlation. (c) Root mean square error
between the two profiles; red dots identify peaks. Black horizontal lines
divide the segments used for realignment. (d) The realigned segments
(thin red lines) above the two original profiles. Panels (e) and (f) show the
mean profile for temperature and turbulent kinetic energy dissipation rates
computed using the original profiles (cyan) and the realigned ones (black).
Acknowledgements
The authors thank CNR-UPO for having granted R/V Urania ship time, and the vessel crew for their kind cooperation is thanked for their kind cooperation. CARPET2014 campaign was
supported by the Flagship Project RITMARE – The Italian Research for the Sea
– coordinated by the Italian National Research Council and funded by the
Italian Ministry of Education, University and Research within the National
Research Program 2011–2013. This work was also supported by the FP7 project
COCONET (grant agreement no: 287844) of the European Commission.
Edited by: J. Wolf
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