Observational evidence of supercooling and frazil ice formation throughout the water column in a coastal polynya in the Sea of Okhotsk

Continental Shelf Research 196 (2020) 104072

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Observational evidence of supercooling and frazil ice formation throughout the water column in a coastal polynya in the Sea of Okhotsk Masato Ito a, *, Yasushi Fukamachi b, c, Kay I. Ohshima a, b, Kunio Shirasawa a a

Institute of Low Temperature Science, Hokkaido University, Sapporo, Japan Arctic Research Center, Hokkaido University, Sapporo, Japan c Global Station for Arctic Research, Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo, Japan b

A R T I C L E I N F O

A B S T R A C T

Keywords: Frazil ice Supercooling Coastal polynya Ice production Sea of okhotsk Acoustic Doppler current profiler

This paper examines underwater frazil ice formation in a coastal polynya. In a coastal polynya, the seawater near the ocean surface can become supercooled due to intense atmospheric cooling. Supercooled water sinks deeper under turbulent conditions, resulting in frazil ice formation in the water column. For the winter of 2002–2003, mooring measurement with an Acoustic Doppler Current Profiler (ADCP), an Ice-Profiling Sonar (IPS) and a conductivity-temperature recorder was conducted off the east coast of Sakhalin in the Sea of Okhotsk with the water depth of 33 m. IPS-derived ice draft data showed several polynya periods lasting for 1–2 weeks, associated with strong offshore winds. During these polynya periods, the ADCP acoustic backscatter strength was enhanced throughout the water column, accompanying in-situ and/or potential supercooling. This is evidence of under­ water frazil ice formation associated with supercooling. Our data indicate that ice divergence/convergence, caused by the combination of wind and tidal forcing, results in a diurnal cycle of underwater frazil ice formation. According to a heat budget analysis, the contribution of frazil ice production to the total ice production during the winter is estimated to be at least 60% of mass. Based on the mooring data, this study shows that frazil ice formation occurs throughout the water column in a polynya, resulting in effective ice production.

1. Introduction A coastal polynya is a region of open water and newly formed sea ice in a pack ice area. Offshore sea ice transport by persistent wind and/or ocean current causes latent heat polynyas to open. In a latent heat polynya, the ocean surface is exposed to a cold atmosphere without a thick ice cover acting as a heat insulator, and hence heat loss from the ocean to atmosphere and subsequent ice production are much larger than those in surrounding pack ice areas. When sea ice forms (or nu­ cleates) and grows, the saline water, called brine, is drained from the ice crystal lattice. Persistent brine rejection in a coastal polynya generates dense shelf water which can be a source component of North Pacific Intermediate Water in the Sea of Okhotsk (Talley, 1991; Yasuda, 1997; Yamamoto-Kawai et al., 2004) and Antarctic Bottom Water in the Southern Ocean (Morales Maqueda et al., 2004; Ohshima et al., 2016). Sea ice production in a polynya is highest when the open water surface is maintained. According to some laboratory experiments (e.g. Ushio and Wakatsuchi, 1993; Smedsrud, 2001), this mechanism can occur when frazil ice forms in the water column due to sinking of

supercooled water under turbulent conditions. Frazil ice is comprised of small ice crystals with size on the order of μm – mm which forms initially in the ocean (Martin, 1981). In a polynya, the seawater near the ocean surface can become supercooled by severe cooling. Supercooled seawater can sink deeper under turbulent conditions with strong winds because it is denser than underlying water. This results in underwater frazil ice formation. On the other hand, under calm conditions, sheet ice such as nilas is formed. For the former case, the open water surface is maintained for a long time because frazil ice is suspended in the water column due to ocean turbulence in addition to offshore transport of newly formed ice by winds. Thus, this mechanism leads to very effective ice production. In-situ oceanic observations under sea ice have been limited due to the harsh polar ocean/meteorological conditions. In addition, the measurements of supercooling and suspended frazil ice are challenging because the level of supercooling in the ocean is comparable to the instrumental uncertainty and the methods of frazil ice detection have not been well established. Thus the details of underwater frazil ice for­ mation associated with supercooling have not been well understood.

* Corresponding author. E-mail address: [email protected] (M. Ito). https://doi.org/10.1016/j.csr.2020.104072 Received 21 March 2019; Received in revised form 11 January 2020; Accepted 1 February 2020 Available online 4 February 2020 0278-4343/© 2020 Elsevier Ltd. All rights reserved.

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Recent observational studies have revealed the occurrence of supercooling and subsequent frazil ice formation in the ocean. In Arctic coastal polynyas, supercooling phenomena on the order of 10 mK have been reported (e.g. Drucker et al., 2003; Skogseth et al., 2009; Dmi­ trenko et al., 2010, 2015; McPhee et al., 2013; Ito et al., 2015). The maximum supercooling of 37 mK was measured by Skogseth et al. (2009) at the edge of an active polynya in Storfjorden, Svalbard. They also observed drifting frazil ice at the ocean surface. In regions adjacent to ice bodies with large draft such as icebergs and ice keels, supercooling can occur due to the freezing point lowering with depth. Seawater in contact with such an ice body at great depths is cooled to a lower freezing point than freezing point at the surface, as well as freshened by meltwater supply. This acts to move the seawater parcel up towards the ocean surface where it becomes supercooled. Lewis and Perkin (1983) referred to this process as an ice pump. They explained that supercooling observed north of Svalbard was due to an ice pump generated by large ice keels. In the perennial sea ice region adjacent to the Ross Ice Shelf, near Antarctica, supercooled water was observed beneath the sea ice (e.g. Leonard et al., 2006, 2011; Mahoney et al., 2011; Gough et al., 2012). This water mass is cooled through contact with the bottom of an ice shelf. Through the ice pump, platelet ice is generated at the bottom of sea ice or ice shelf (e.g. Langhorne et al., 2015). Recent in-situ observations suggest that frazil ice suspended in the water column can be detected by acoustic instruments such as an upward-looking sonar and an Acoustic Doppler Current Profiler (ADCP). For the former, Drucker et al. (2003) and Ito et al. (2015) showed that the acoustic signals of underwater frazil ice from the surface down to a depth of ~15 m can be detected with an upward-looking sonar in the St. Lawrence Island polynya and Barrow coastal polynya, respectively. For the latter, although an ADCP is mainly used to obtain the vertical profile of the current, it records the acoustic backscatter strength throughout the water column simultaneously. ADCP backscatter strength can be enhanced by suspended frazil ice, as reported in McMurdo Sound (Leonard et al., 2006) and the Laptev Sea coastal polynya (Dmitrenko et al., 2010). Based on the in-situ observations described above, the occurrences of supercooling and subsequent frazil ice formation in the polar oceans have been revealed. However, the details of underwater frazil ice for­ mation process such as its duration and contribution to the total ice production are still not well understood. The Sea of Okhotsk is the southernmost sizable sea ice area in the Northern Hemisphere, located northwest of the Pacific Ocean (Fig. 1). Initial sea ice production occurs over the Northwest shelf in November, and then the sea ice region spreads toward the south. Sea ice extent reaches a maximum in late February or early March when 50–90% of this sea is covered with sea ice, and sea ice completely melts by June (Cavalieri and Parkinson, 1987). During winter, coastal polynyas are formed over the north/northwestern shelves and off the eastern Sakhalin coast (the Sakhalin polynya; see Fig. 2 for its location) due to the prevailing cold northwesterly monsoon. These polynyas contribute to the sea ice production in this sea significantly, as reported by the studies using satellite data (Martin et al., 1998; Nihashi et al., 2009, 2012; Kashiwase et al., 2014). Shcherbina et al. (2004) and Fukamachi et al. (2009) reported potential and in-situ supercooling in the North­ west polynya and the Sakhalin polynya, respectively, based on mooring data. In the region ~200 km north of the Sakhalin polynya (triangles in Fig. 1), suspended frazil ice was detected from the surface to a depth of ~30 m in a pack ice edge area under windy conditions by bottommounted ADCPs (Ito et al., 2017), even though polynyas did not form in this region. This fact and the report of supercooling by Fukamachi et al. (2009) imply the occurrence of active frazil ice production in the Sakhalin polynya. Fukamachi et al. (2009) examined the brine rejection in the Sakhalin polynya using the mooring data, but they did not focus on the supercooling event and frazil ice production. In this study, we

Fig. 1. The region around the Sea of Okhotsk. Bathymetry from the General Bathymetric Chart of the Oceans (GEBCO). The circle and cross denote the mooring site and ERA-Interim data grid point closest to the mooring site, respectively. The triangles denote the mooring sites for the winter of 1999–2000 described by Ito et al. (2017). The inset shows the location of the Sea of Okhotsk wherein the box denotes the enlarged portion.

re-analyze these mooring data along with the satellite and meteorolog­ ical data focusing on supercooling and frazil ice production, and then investigate the process of underwater frazil ice production in the polynya and its impact on the total ice production. 2. Data and methods 2.1. Mooring observation An experiment using two bottom taut moorings was conducted in the Sea of Okhotsk at 52.72� N, 143.57� E located ~18 km off the east Sakhalin coast with a water depth of ~33 m (circle in Fig. 1). These moorings were deployed separately with a separation distance of ~120 m to avoid possible acoustic interference. They were deployed on 27 December 2002 and recovered on 12 June 2003. One mooring was equipped with an ADCP (RD Instruments Workhorse Sentinel 300 kHz) and a conductivity-temperature recorder (C-T recorder: SeaBird SBE-37 MicroCAT), and another was equipped with an IPS (ASL Environmental Sciences, IPS4 420 kHz). All the instruments were moored at a depth of 24 m. The details of this observation are described in Fukamachi et al. (2009). An ADCP measures the vertical profile of the ocean current and the acoustic backscatter strength, called the echo amplitude. For this observation, the ADCP cell length and sampling interval were set to 2 m and 20 min, respectively. The deepest cell was 19–21 m. The accuracy and the dynamic range of the echo intensity are �1.5 dB and 80 dB, respectively. The wave length of the acoustic pulse (or ping) is ~5 mm. The accuracy of the ADCP speed is better than 0.01 m s 1. The C-T recorder measured the conductivity (converted to salinity) 2

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Fig. 2. The spatial distributions of the ice thickness derived from the AMSR-E data (Nihashi et al., 2009) with the spatial reso­ lution of ~12 km off the east coast of the northern Sakhalin. Open water, thick ice and land areas are shown by blue, gray and khaki, respectively. The black cross denotes the mooring site. The inset shows the thick­ ness distribution around Sakhalin and the box indicates the enlarged area. The date and time for each panel are shown in the local time (UTC þ 9h). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

and the water temperature with a sampling interval of 20 min. The ac­ curacy of the salinity and the temperature are 4 � 10 3 and 2 mK, respectively. Pre-deployment calibration was carried out before the observation. An IPS emits an acoustic pulse and detects a return pulse back­ scattered by the ocean surface or the ice bottom using the same trans­ ducer. The travel time of the ping is converted to the range between the transducer and scatterer automatically using a constant sound speed of 1460 m s 1 (ASL Environmental Science, 2004). This is called the range data. Sound speed was calibrated on the basis of range data during open water periods without large waves in order to calculate ice draft (Fukamachi et al., 2009). Fukamachi et al. (2009) generated the ice draft data using these range data along with the other data in the Sakhalin polynya. We used these ice draft data for this study. Although the range (draft) data was sampled with an interval of 1 s, the average within the ADCP ensemble time (150 s) for every 20 min was used in this study. The pulse length of the ping is 0.1 m, hence the ice draft data contains at least

an error of 0.05 m. The water pressure was also measured by the IPS with an accuracy of 1.26 � 102 Pa (0.0126 dbar). Note that the IPS used for the observation in Sakhalin polynya did not record the backscatter strength from the water column and thus we cannot use the IPS data to detect underwater frazil ice. 2.2. ADCP acoustic backscatter data The acoustic pulse emitted from the transducer propagates in the water column and is scattered by targets such as frazil ice, zooplanktons, sedimentary particles, fishes and air bubbles at depth. The ADCP uses the same transducer to transmit and receive the acoustic wave. The energy or the acoustic pressure of the received pulse is amplified and converted to 8-bit digitized electric voltage amplitude (in counts), called the echo amplitude, by the instrument. The echo amplitude cannot be used to compare the backscatter strength at different depths and times. This is because the propagating acoustic wave loses energy due to the 3

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geometric spreading of the wave and sound absorption by the water and the energy of emitted pulse depends on the battery power. Hence we use the volume backscatter strength, called SV (in dB), which is the target strength per unit volume. SV is calculated as follows by the sonar equation (Deines, 1999), SV ¼ kc(E - Er) þ 2αR þ 10log10(TxR2) – 10log10L – 10log10Wt þ C,

Kimura (1995) as follows, QSW ¼ (A – 0.5CL2)QSWC,

where A ¼ 0.865, CL is the cloud cover. The long wave radiation is estimated empirically for the Sea of Okhotsk as follows (Ohshima et al., 2006),

(1)

QLW ¼ εσT4s (B1 þ B2ew)(1 – δLCL) þ 4εT4S(Ts – Ta),

where kc ¼ 0.45 (dB counts 1) is the conversion coefficient, E is the echo amplitude (counts), Er is the received noise (counts), α is the attenuation coefficient (dB m 1), R is the range between the target and the trans­ ducer (m), Tx is the transducer temperature (K), L is the acoustic pulse length (m), Wt is the transmit power (W) and C ¼ 143.5 (dB). The received noise, Er, is derived from the echo amplitude before the deployment and it is 42 counts for our case. The pulse length, L, is 1.0 m for the entire observational period. Tx and Wt are recorded by the in­ strument for every measurement. The attenuation coefficient, α, is determined from the sum of the terms of the acoustic absorption by seawater and scattering/absorption by suspended materials. As in the previous studies (e.g. Hoitink, 2004), the latter effect was ignored and α is assumed to 0.069 dB m 1 (Deines, 1999).

The freezing point of seawater, Tf, depends on the salinity, S, and the water pressure, Pw. This is calculated using the UNESCO algorithm (Fofonoff and Millard, 1983), (2)

where a1 ¼ 0.0575 (� C), a2 ¼ 1.710523 � 10 3 (� C), a3 ¼ 2.254996 � 10 4 (� C) and b ¼ 7.53 � 10 8 (� C Pa 1). The freezing point derived from Eq. (2) contains an uncertainty of �2 mK. Seawater which is below its freezing point at depth is in-situ super­ cooled. According to Eq. (2), the freezing point decreases at a rate of ~7 mK per 10 m depth. This fact means that if in-situ supercooled water sinks deeper into the water column, its temperature would be above the freezing point at depth. Considering this pressure dependence of the freezing point, potential supercooling is defined as water that has a potential temperature below its freezing point at the ocean surface, Tf (S, 0). Potentially supercooled water becomes supercooled if it is raised adiabatically to the surface, even though it is not necessarily super­ cooled at depth. The instrumental uncertainties of in-situ and potential supercooling in this study are at least �5 mK, considering the accuracy of the temperature, salinity and pressure measurements (see section 2.1) and the uncertainty of Eq. (2). The detail of this error estimation is described in Ito et al. (2015).

2.5. Satellite data The Advanced Microwave Scanning Radiometer-EOS (AMSR-E) data were used to show sea ice conditions in the Sea of Okhotsk. The AMSR-E observes the region in the Sea of Okhotsk twice a day on average. The ice concentration is derived from the enhanced NASA Team (TN2) algo­ rithm (Markus and Cavalieri, 2000). The ice thickness is estimated from the algorithm using the brightness temperatures from vertically and horizontally polarized channels at 36.5 GHz (Nihashi et al., 2009). The estimation error is ~0.05 m for thickness �0.2 m. The spatial resolution of these data is ~12 km. Note that these satellite-derived ice thickness data are not used to calculate the heat budget in this study, considering their lower temporal and spatial resolutions with respect to the mooring data.

2.4. Meteorological data and heat budget at the surface For the meteorological data (2-m air and dew point temperature, 10m wind speed, sea surface pressure and cloud cover), we used the Eu­ ropean Centre for Medium-Range Weather Forecast Interim Re-analysis (ERA-Interim) data. The spatial and temporal resolutions are 0.75� � 0.75� and 6 h, respectively. The data at the grid point closest to the mooring site (52.50� N, 144.00� E) were used (cross in Fig. 1). The heat budget at the ocean or ice surface, Q, is expressed as follows, Q ¼ (1 – αsolar)QSW þ QLW þ QLH þ QSH,

(5)

where ε ¼ 0.99 is emissivity at the ocean or sea ice surface, σ ¼ 5.67 � 10 8 is the Stefan-Boltzman coefficient (W m 2 K 2), B1 and B2 are 0.254 and 4.9 � 10 3, respectively, ew is the vapor pressure (Pa), Ts and Ta are the surface and air temperature (K), respectively, and δL ¼ 4.27 � 10 3 � latitude þ 0.5036. Sensible and latent heat fluxes, QSH and QLH, are calculated using the bulk formulae, following Ohshima et al. (2006). We assume two surface conditions for the calculation: complete open water and entirely ice-covered surface. These conditions are determined from the method described in section 4.1 using a combination of IPSderived ice draft and ADCP-derived SV. For the open water case, αsolar ¼ 0.06 and Ts ¼ Tf ~271.35 K ( 1.8 � C) are assumed. For the ice covered surface, we assume that the total, ice and snow thickness are h, hi and hs (h ¼ hi þ hs), respectively. The heat budget can be calculated assuming the energy balance between the conductive heat flux through the ice, F, and incoming heat flux, Q, at the surface. The conductive heat flux, F, is represented as F ¼ κ(Tb – Ts), where κ is the bulk conductivity, Tb ¼ Tf ~ 271.35 K is the temperature at the ice bottom. The bulk conductivity, κ, is given by κ ¼ κiκs/(κihs þ κihi), where κi ¼ 2.03 and κs ¼ 0.31 W m 1 K 1 are the conductivities of ice and snow. We assume the presence of snow cover on the ice for the case of ice draft, di, > 0.19 m (hi > 0.2 m). Toyota et al. (2000) showed a linear correlation between snow and ice thickness of hs ¼ 0.2hi in the Sea of Okhotsk. The total thickness, h, is estimated under an assumption of isostasy using ice and snow densities of 920 and 350 kg m 3. The ice surface albedo is assumed to be 0.27, 0.36 and 0.7 for the total thickness of �0.1, 0.1–0.2 and >0.2 m, respectively (Nihashi et al., 2012). For the calculation of the heat budget in this study, we assume that incoming shortwave radiation is only absorbed and reflected at the surface, and ignore the penetrative solar energy into the ocean for simplicity. The heat budget is calculated every 20 min corresponding to the timing of ADCP measurement using linearly interpolated ERAInterim data.

2.3. Supercooling of seawater

Tf (S, Pw) ¼ a1S þ a2S3/2 þ a3S2 þ bPw,

(4)

3. Results

(3)

3.1. Overview of ADCP high-backscatter events

where αsolar is the surface albedo, QSW is the shortwave radiation, QLW is the long wave radiation, QLH is the latent heat flux and QSH is the sen­ sible heat flux. Here, positive values correspond to downward (incoming) flux inputting energy into the water column. The shortwave radiation for the clear sky case, QSWC, is calculated from an empirical formula (Zillman, 1972). Cloud effect on shortwave radiation is represented by an empirical formula described by Kim and

In this subsection, we overview the underwater conditions derived from the mooring data, along with the meteorological data and satellitederived surface ice conditions. Fig. 3a shows the time series of the IPSderived ice draft at the timing of ADCP measurement. For the 2002–2003 winter, we can identify several periods of continuous open 4

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Fig. 3. Time series of the mooring and meteorolog­ ical data during the period from 27 December 2002 to 31 March 2003. (a) Ice draft obtained by the IPS (Fukamachi et al., 2009). The orange bars indicate the periods of polynya (ice thickness � 0.2 m). (b) The wind vector (blue) and speed (navy), and air temperature (pink) derived from the ERA-Interim data. (c) Ice draft obtained by the IPS (black shade) and the vertical profiles of the volume back­ scatter strength, SV, obtained by the ADCP. Note that SV in the uppermost two cells (gray shade) were not shown because it always high due to the backscatter by the ocean surface or ice bottom. The orange and light-blue bars indicate the periods of polynya and underwater frazil ice detection, respectively. (d) The water temperature at the depth of 24 m relative to the freezing point at the same depth (blue), the po­ tential temperature relative to the freezing point at the surface (red) and salinity at the depth of 24 m (gray). The light-blue shade indicates regions of po­ tential or in-situ supercooling. (e) The heat budget at the surface (blue) and the shortwave radiation (or­ ange). The negative value indicates oceanic cooling by the atmosphere. (f) The vertical profiles of the north-south component of the ocean current. (g) The vertical profiles of the east-west component of the current. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

water and/or thin ice (hi � 0.2 m), shown by orange bars above panels 3a and 3c, as described in Fukamachi et al. (2009). The offshore (westerly or northwesterly) winds with a speed around 10 m s 1 during these periods (Fig. 3b) imply the opening of the Sakhalin polynya including the region around the mooring site due to offshore transport of sea ice. Fig. 2 shows typical examples of distributions of thin ice thick­ ness derived from the AMSR-E data. The Sakhalin polynya appeared episodically (Fig. 2a, b, 2d, 2g, 2h, 2k and 2l), and the mooring site (cross) was located in the northern part of the polynya. In particular, an open water area spread widely around the mooring site on 28 December, 8 January, 16 February and 26 March (Fig. 2a, b, 2h and 2l). The periods when IPS-derived ice draft show open water or thin ice with the thick­ ness �0.2 m correspond well to the occurrences of the polynya. Coin­ ciding with the periods of thick ice cover revealed by the IPS (Fig. 3a), the polynya was absent around the mooring site on 13 and 26 January, 9 February, 3 and 5 March 2003 (Fig. 2c, e, 2f, 2i and 2j). The heat loss from the surface to the atmosphere associated with the polynya forma­ tion was up to 300–600 W m 2 (Fig. 3e), indicating intense sea ice production. Colors in Fig. 3c denote the time series of the vertical profiles of the volume backscatter strength, SV, derived from the ADCP data. Note that SV in the two cells below the surface (the depth range of 0–3 m) shown

by gray shade was quite high due to the backscatter/reflection at the ocean surface or the ice bottom, and thus it is not shown. These ranges correspond to the ocean-air or ocean-ice boundary, and the data in these ranges cannot be used for characterizing underwater conditions. During the polynya periods, strong SV of 70 to 60 dB was detected throughout the water column, as indicated by light blue bars above panel 3c. The backscatter strength of these acoustic signals was stronger in shallower depths, suggesting that its acoustic sources originate from the near-surface layer. In addition, potential supercooling of 10–15 mK occurred at a depth of 24 m simultaneously (red line in Fig. 3d). For short periods, the water became in-situ supercooled (blue line in Fig. 3d), although the level of supercooling of <10 mK is almost com­ parable to the instrumental uncertainty. The wind speed during periods with surface-intensified acoustic signals reached up to 15 m s 1 and its direction was northwesterly (Fig. 3b). These windy conditions likely generated the heavy turbulence in the ocean. Based on these data, we can interpret that the scatterers of the strong surface-intensified signals are frazil ice crystals suspended in the water column. Potential acoustic scatters other than frazil ice include marine or­ ganisms such as zooplanktons, air bubbles and re-suspended sediment. In general, zooplankton move to the ocean bottom during the day and return to the surface during the night (e.g. Petrusevich et al., 2016). 5

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During mid-May – June after sea ice retreat, SV vertical profiles showed such a diurnal cycle of vertical migration. However, such acoustic sig­ nals cannot be identified in Fig. 3c for most of the winter period. These observations suggest that zooplankton are not the acoustic target generating those signals. The surface-intensified acoustic signals were not detected after sea ice retreat even during strong wind periods (not shown). This indicates that these signals were likely not caused by air bubbles. Finally, the possibility of upward transported bottom sediment as the main scatterer is also rejected because these acoustic signals should have been intensified toward the bottom (Ito et al., 2017). Considering all of the above, we can propose, again, that underwater frazil ice is most likely the source of the surface-intensified SV detected during open water or thin ice periods. Frazil ice signals were detected at the deepest ADCP cell (central depth of 20 m) as shown in Fig. 3c. The depth at which frazil ice forms cannot be determined solely from our data. The following two situations can be considered. One is that frazil ice forms at greater depths due to sinking of supercooled water, and another is that frazil ice is transported to a greater depth from shallower depths by wind stirring and convec­ tion. In the coastal region off Sakhalin, the mixed layer can thicken down to >100 m due to strong convection generated by intense atmo­ spheric cooling (winter mixing) (Ohshima et al., 2006). Thus, potential supercooling at a depth of 24 m indicates the possibility of in-situ supercooling at shallower depths where the freezing point is higher. This suggests that detected frazil ice was formed at those shallower depths. On the other hand, according to the model simulation by Mat­ sumura and Ohshima (2015), potential supercooling at greater depth can occur because frazil ice formed near the ocean surface can be transported deeper where it melts due to the freezing point depression and can cool the surrounding seawater down to its local freezing point, which leads to a potentially supercooled water column at depth. This is also a possible process of observed potential supercooling. The acoustic signals of underwater frazil ice were observed over 1–2 weeks (Fig. 3c) during the polynya periods. This implies that frazil ice formed and suspended in the water column for 1–2 weeks under the windy turbulent conditions and that the open water surface persisted without ice cover. Thus, we can interpret that our data show the occurrence of the most effective ice production in the polynya. In fact, the ocean heat loss (Fig. 3e) reached up to 600 W m 2 and remained high during the periods when underwater frazil ice was detected as shown by light blue bars in Fig. 3c. The contribution of frazil ice pro­ duction to the total sea ice production will be discussed in section 4.1. Underwater frazil ice signals showed different patterns through the winter. During the polynya period of 27–31 December 2002, frazil ice was detected throughout the water column persistently. During the polynya periods of 7–21 January and 12–21 February 2003, a diurnal

pattern was observed. For 5–6 and 25–26 March, short periods associ­ ated with in-situ supercooling and underwater frazil ice were detected. In the following subsections, we examine these different patterns individually. 3.2. Persistent underwater frazil ice formation—a polynya event in December Fig. 4a and b shows the time series of ice draft and the vertical profiles of SV during the period from 27 December 2002 to 1 January 2003, respectively. Ice draft is also shown in Fig. 4b as a black shade. The mooring was deployed on 27 December. The IPS data show that open water persisted over this period (Fig. 4a) and the AMSR-E data also show that the Sakhalin polynya was active during this period (Fig. 2a). The mooring site was located in the newly formed ice (thin ice) area with thicknesses < 0.1 m (Fig. 2a). ADCP backscatter data (Fig. 4b) show frazil ice signals with SV of 70 to 55 dB throughout the water column over the polynya period. During this period, the potential temperature at a depth of 24 m was 10–15 mK below the surface freezing point and the water temperature was only ~10 mK above the in-situ freezing point (Fig. 4c). This fact suggests that in-situ supercooling persisted at shallower depths. Thus, it is highly likely that the open water was maintained and an ice cover did not form over a five day period owing to underwater frazil ice formation associated with supercooling. From ~21:00 on 30 December to ~10:00 on 31 December, SV increased throughout the water column (Fig. 4b). This is probably caused by an increase in the number and/or volume of underwater frazil ice because SV is related to these quantities theoretically (Greenlaw, 1979). During this period, the wind speed nearly reached 20 m s 1, which is the maximum during the 2002–2003 winter, and its direction was northwesterly (Fig. 3b). This severe wind likely induced strong wind stirring. However, this wind increase was compensated by the increase of the air temperature by ~10 K (Fig. 3b), so that the ocean heat loss did not change significantly. Hence, it is likely that the total frazil ice pro­ duction did not change significantly either. Here, we suggest two possible reasons why the total volume of underwater frazil ice increased as follows. First, the enhanced wind stirring transports more frazil ice from the surface down into the water column. It can also bring larger frazil crystals with larger buoyancy deeper into the water column. Second, more supercooled water can sink down due to the enhanced wind stirring and subsequently more frazil ice forms in the water col­ umn. In any case, for underwater frazil ice production (production in­ cludes both formation and growth), the wind speed can be a more important factor than the heat budget at the ocean surface and the air temperature. Fig. 4. Time series of the mooring data from 27 December 2002 to 1 January 2003. (The longer tics indicate 0:00 LT.) (a)Sea ice draft derived from the IPS data. (b) Sea ice draft derived from the IPS data (black shade) and the vertical profile of SV derived from the ADCP data. The uppermost two cells are shaded because the data were not available. The orange and light blue bars represent the polynya periods (total thickness � 0.2 m) and underwater frazil ice detection, respectively. (c) The water tem­ perature at the depth of 24 m relative to the freezing point (blue line) at the same depth and the potential temperature relative to the freezing point at the surface (red line). The light-blue shade indicates re­ gions of potential supercooling. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

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in the case of December (Fig. 4) described in section 3.2, underwater frazil ice signals show a diurnal cycle, i.e. the signals only appeared at night and disappeared during the day. The mechanism of this diurnal cycle will be examined in section 4.2. Note that this diurnal pattern is different from that of zooplankton migration, as described in section 3.1. Water at the depth of 24 m was potentially supercooled for almost all of the polynya periods (Fig. 5b and d). Moreover, several in-situ supercooling events were detected around midnight in the period of 7–11 January, although the supercooling of <5 mK is the same level as the instrumental uncertainty (Fig. 5b). Such low temperatures indicate frazil ice formation from supercooled water at depth. For these polynya periods, the water temperature also changed diurnally. This diurnal temperature cycle occurred simultaneously with that of SV. The water temperature decreased from the evening through the dawn and increased after sunrise. The diurnal amplitude of the water temperature during the polynya period in February (~20 mK) is larger than that in January (~10 mK). While the potential temperature varied within the range mostly below the freezing point at the surface in January, it often reached above the freezing point at the surface in the afternoon in February. In spite of these differences, the depth and duration of frazil ice detection shown in the SV were almost the same in both cases (Fig. 5a and c). Thus, the presence of potential supercooling is not likely the direct factor controlling the diurnal cycle of underwater frazil ice formation. The mechanism of the diurnal frazil ice formation and temperature change will be discussed in sections 4.2 and 4.3, respectively.

After the night of 31 December, underwater frazil ice was not detected by the ADCP (Fig. 4b). At that point, the wind direction changed to northeasterly (onshore) from northwesterly (Fig. 3b). This wind could possibly cause the accumulation of frazil ice at the surface near the coast. According to the ice draft data (Fig. 4a), ice thickness increased gradually around the end of the polynya period. This suggests that the phase of sea ice production changed from frazil ice formation in the water column to growth of accumulated frazil (or grease ice), consolidation to thin ice and subsequent thermal growth. 3.3. Diurnal cycle of frazil ice formation —polynya events in January and February Fig. 5 shows the time series of ice draft, the vertical profile of SV and the water temperature during the period of 6–24 January 2003 (Fig. 5a and b) and 11–25 February 2003 (Fig. 5c and d). Ice draft data indicate thin ice and open water during periods starting from 7 January and 11 February (black shade in Fig. 5a and c). The wind direction changed to northwesterly/westerly (offshore) around 7 January and 13 February (Fig. 3b). The AMSR-E derived ice thickness data show the presence of the Sakhalin polynya including the region around the mooring site during the periods of 7–12, 15–23 January and 12–24 February (Fig. 2b, d, 2g and 2h). A wide open water area expanded from the nearshore to offshore regions on 8 January and 16 February (Fig. 2b and h). Ac­ cording to the AMSR-E data, the Sakhalin polynya disappeared on 13 and 14 January (Fig. 2c). On the other hand, the ice draft data indicate open water or thin ice persisted over this time (Fig. 5a). Thus, for 13–14 January a thin ice region likely formed around the mooring site locally with a spatial scale less than the resolution of the satellite data (<~12 km). According to ADCP backscatter data for these polynya periods, strong acoustic signals of frazil ice were detected throughout the water column soon after the polynya opened (Fig. 5a and c). However, unlike

3.4. The short term underwater frazil ice formation associated with in-situ supercooling —high-backscatter events in March Fig. 6a shows the time series of ice draft (black shade) and the ver­ tical profiles of SV (color) during 4–6 March 2003. Thick ice with drafts of 3–10 m covered the mooring site mostly until morning on 6 March

Fig. 5. Similar to Fig. 4b and c, except for the periods of (a and b) 6–24 January 2003 and (c and d) 11–25 February 2003. The light-blue shade of panel 5b indicates regions of potential or in-situ supercooling. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) 7

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Fig. 6. Similar to Fig. 5a and b, except for the periods of (a and b) 4–6 and (c and d) 25–27 March 2003.

before the polynya began to form. On the other hand, IPS data also showed short periods of open water around 0:00 and 4:00–9:00 LT on 5 March. We use the local time (LT) hereinafter. According to the AMSR-E ice thickness and concentration data, the polynya or thin ice area was absent around the mooring site on 4 and 5 March (Fig. 2i) and the ice concentration was >90% (not shown). These facts indicate that open water detected by the IPS on 5 March was likely small leads or openings between ice floes. The wind direction changed from northwesterly to northeasterly around 3 March (Fig. 3b). The wind speed exceeded 10 m s 1 (Fig. 3b). This wind could advect sea ice offshore leading to open water. The heat loss from the ocean to the atmosphere was up to 560 W m 2 associated with the presence of open water (Fig. 3e). At these times, potential supercooling occurred (Fig. 6b). During the later open water period (4:00–9:00 on 5 March), in particular, in-situ supercooling up to 8 mK occurred at a depth of 24 m (Fig. 6b). At the same times of in-situ supercooling, SV was enhanced to quite high values � 60 dB throughout the water column (Fig. 6a). When in-situ supercooling reached the maximum value (5:40 on 5 March), SV reached the maximum for the observational period simultaneously (Fig. 6a and b). Considering these facts that the increase in SV well corresponded to insitu supercooling and occurred during an open water period, the strong acoustic backscatter throughout the water column was undoubtedly caused by underwater frazil ice. Potential supercooling was enhanced from ~0:00 on 5 March for a few hours before the detection of under­ water frazil ice (Fig. 6a and b). If observed potential supercooling were due to cooling by latent heat absorption of melting frazil ice that has been transported down from the surface, as proposed by Matsumura and Ohshima (2015), then frazil ice should have appeared at depths before the occurrence of potential supercooling. Thus, this fact suggests that frazil ice was produced throughout the water column associated with sinking of supercooled water due to strong wind stirring by the wind with speed �10 m s 1 (Fig. 3b). During 25–31 March, the AMSR-E ice thickness data showed that the Sakhalin polynya was formed around the mooring site, and open water

occupied most of the polynya except the region near the offshore edge (Fig. 2l). This open water was maintained for the entire polynya period (not shown). Although the IPS-derived ice draft data also showed continuous open water during this period, thick ice floes with thick­ nesses up to ~5 m were detected episodically on 29 and 30 March (Fig. 3a). Fig. 6c and d shows the time series during the former part of this polynya period (25–27 March). Around noon on 25 March, SV values up to ~ -50 dB were seen from the ocean surface down to a depth of 16 m just after the polynya opening (Fig. 6c). The wind speed during this period was up to ~16 m s 1 (Fig. 3b). While atmospheric conditions were similar to those during other high-backscatter events, these SV signals are higher than those for other frazil ice events. The water temperature at a depth of 24 m was ~0.1 K higher than the freezing point. Moreover, in late March the heat budget was positive (heating) during the day (Fig. 3e) due to the shortwave radiation although the air temperature was lower than the freezing point of seawater (Fig. 3b). Hence, the ocean was heated by the shortwave radiation. These facts indicate the contribution of scatterers other than frazil ice such as air bubbles or marine organisms to surface-intensified acoustic backscatter. In-situ supercooling as large as 5 mK occurred (comparable to the instrumental uncertainty) before sunrise at 4:40–6:40 on 26 March (Fig. 6d). Acoustic signals with SV around ~ -60 dB were detected throughout the water column simultaneously (Fig. 6c). The heat budget at the surface returned to negative (cooling) as large as ~200 W m 2 after sunset (Fig. 3e). Thus, the acoustic backscatter strength was likely enhanced by suspended frazil ice in this case. In Fig. 6c, there were periodic SV signals of ~ -70 dB oscillating in the depth range between near the bottom during the day and near the surface during the night on 26–27 March. These acoustic signals were likely due to the diurnal vertical migration of zooplankton. Thus, it is likely that the backscatter from suspended frazil ice and zooplanktons overlapped near the surface before sunrise on 26 March.

8

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4. Discussion

underwater frazil ice. However, as in the case on 24 January, SV from thick ice was also larger than 75 dB (Fig. 7a and b). These indicate that SV at 3–5 m � 75 dB was likely caused by underwater frazil ice or thick solid ice. To distinguish the backscatter from these two targets, we use ice draft data obtained by the IPS. The simplest way to distinguish these two targets is that acoustic targets are regarded as underwater frazil ice only for the periods of open water (draft ¼ 0). However, the layer of frazil ice accumulated at the surface is a potential source of high acoustic backscatter, and this layer can be detected as the underwater part of solid ice by sonars (Drucker et al., 2003). Although there has been only a few field measurements of accumulated frazil or grease ice, Martin and Kauffman (1981) and Smedsrud and Skogseth (2006) reported thick­ nesses of these layers of >1 m and 0.7 m in Arctic polynyas, respectively. Taking these facts into account, we conclude that the surface was open water and frazil ice was suspended in the water column for the case of SV at 3–5 m � 75 dB and draft � 1m (Case 1 in Fig. 8). For the case of draft > 1m together with SV at 3–5 m � 75 dB, the acoustic backscatter was assumed to be due to thick ice which covered the mooring site (Case 4). When solid ice with thickness � 1m covered the mooring site and frazil ice was not present in the water column, SV at 3–5 m is expected to be less than 75 dB and thus the ice condition is categorized as Cases 3 or 4 as described below. Next, we consider the conditions without frazil ice in the water column, i.e. SV at 3–5 m is less than 75 dB. If ice draft is 0 m, then we determine that the surface is open water (Case 2). Otherwise the surface is assumed to be covered with solid sea ice with thickness h. The cases of h � 0.2 m and >0.2 m correspond to Case 3 (thin ice cover) and Case 4 (thick ice cover), respectively. This method to categorize the ice condition is summarized in the flow chart shown in Fig. 8. Based on the estimated ice condition categorized as the four cases above, we calculated surface heat budget and subsequent sea ice pro­ duction during the period from 27 December 2002 (deployment day) to 31 March 2003. Details of the calculation are described in section 2.4. Here, open water is assumed for Case 1 and 2. During the winter of 2002–2003, we have 6780 data points with a time interval of 20 min based on the ADCP data. The results for Cases 1–4 are summarized in Table 1. Total ice production at the mooring site is 4.47 m. The contri­ butions of underwater frazil ice production (Case 1) and thermal growth (Case 3) to the total ice production are 60% (2.69 m) and 26% (1.18 m), respectively. On the other hand, the number of Case 1 data points is roughly comparable to that of Case 3. For Case 2, underwater frazil ice production may occur near the surface (depth < 3 m) where SV data are not available. Thus, we expect that the contribution of underwater frazil ice production to the total ice production is actually larger than 60%.

4.1. The impact of underwater frazil ice production on total ice production In this subsection, we estimate the ice production from the heat budget at the surface and assess the contribution of underwater frazil ice production to total ice production. We assume that water temperature remained at the freezing point, and latent heat associated with ice production balances the heat flux from the ocean to atmosphere. Hence, sea ice production per unit area equivalent to thickness, ΔH (m), for a short period, Δt (s), is represented using the heat budget at the surface, Q (W m 2), as LiρiΔH ¼ -QΔt, where Li ¼ 335 � 103 J kg 1 is a latent heat of fusion, ρi ¼ 920 kg m 3 is the density of ice. Heat budget, Q, is obtained from Eq. (3) in section 2.4, using the meteorological conditions defined from the linearly interpolated ERA-Interim data. We carry out an ice production calculation assuming four different ice and ocean conditions as follows. Case 1: the open water surface with underwater frazil ice. Case 2: the open water surface without under­ water frazil ice. Case 3: thin ice cover (h � 0.2 m) without underwater frazil ice. Case 4: thick ice cover (h > 0.2 m) without underwater frazil ice. These conditions are categorized by the following method based on the SV from the ADCP and ice-draft data from the IPS. We judge the presence of underwater frazil ice using a combination of SV at 3–5 m (the shallowest bin of the valid backscatter data) and IPSderived ice draft. At first, we focus on the former (SV). Fig. 7 shows the time series of the SV vertical profiles and values at 3–5, 11–13 and 19–21 m during the high-backscatter event during 6–24 January. During this period, diurnal acoustic signals of frazil ice were detected as mentioned in section 3.3. When strong acoustic signals of frazil ice penetrated from the surface into the water column (Fig. 7a), SV at depth was larger than 80 to 75 dB (Fig. 7b–d). Thus, the SV value of 75 dB can be considered as a conservative threshold of backscatter from

Fig. 7. Time series of (a) ice draft derived from the IPS data (black shade) and the vertical profiles of SV (color) and SV at the depth of (b) 3–5, (c) 11–13 and (d) 19–21 m during the period of 6–24 January 2003. Black dashed lines in (a) show the depths of 4, 12 and 20 m. Dashed lines in (b), (c) and (d) denote 75 dB. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 8. The flow chart of the algorithm to categorize conditions of sea ice production using SV derived from the ADCP data and sea ice draft derived from the IPS data. 9

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Table 1 Ice production from 27 December 2002 to 31 March 2003. Case1: underwater frazil ice. Case 2: open water without underwater frazil ice. Case 3: thin solid ice with total thicknesses �0.2 m. Case 4: thick solid ice with total thicknesses >0.2 m. Case 1. Frazil ice 2. Open water 3. Thin ice 4. Thick ice Total

Number of data

Ice production

(counts)

(%)

(m)

(%)

2048 560 2270 1902 6780

30 8 34 28 –

2.69 0.43 1.18 0.17 4.47

60 10 26 4 –

Toyota et al. (2004) reported that granular texture occupies ~65% of the total ice thickness of the first year ice in the southern Sea of Okhotsk, based on the combined analysis of ice structure and stable isotopic composition. In the Sea of Okhotsk, sea ice is transported southward by the northwesterly monsoon and southward East Sakhalin Current (Simizu et al., 2014). A part of the first year ice in the southern Sea of Okhotsk originates from the Sakhalin polynya and is transported southward. The contribution of underwater frazil ice production esti­ mated from our study is comparable to that estimated from ice samples. 4.2. The mechanism of diurnal cycle of underwater frazil ice formation During the polynya periods in January and February, underwater frazil ice signals clearly showed the diurnal pattern as described in section 3.3 (Fig. 5a and c). To our knowledge, such a phenomenon has not been reported previously. In section 4.1, we described the method to determine the presence of underwater frazil ice from a combination of SV and ice draft. Using this method along with the ocean current and atmospheric conditions, we examine a mechanism of the diurnal pattern of underwater frazil ice in this subsection. Fig. 9a and b shows the time series of SV at 3–5 m and incoming shortwave radiation at the surface at the mooring site during 6–23 January 2003, respectively. Gray shade in each panel of Fig. 9 shows the periods when frazil ice was detected in the water column. Underwater frazil was detected only during the night except for 21 January. How­ ever, episodes of underwater frazil ice relative to sunrise and sunset are not uniform within the polynya period (Fig. 9b). In addition, the heat budget at the surface was always negative (i.e. cooling) during day and night throughout the period and as low as 600 W m 2 (Fig. 3e). Thus, it is unlikely that the shortwave radiation solely explains the diurnal cycle of underwater frazil ice formation. Frazil crystals formed in the water column float toward the surface slowly due to their buoyancy. Then, frazil ice is accumulated at the surface, forming grease ice as a slurry of water and ice. Because grease ice damps out the wave and swell, as the layer of grease ice increases, the dominant ice production becomes thermal crystal growth, and finally grease ice begins to consolidate (Martin and Kauffman, 1981). During offshore transport of sea ice, floating frazil ice diverges offshore and open water is maintained. As a result, underwater frazil ice formation associated with supercooling can persist. On the other hand, when the offshore ice transport is weakened or changed onshore-ward, frazil ice tends to converge at the surface. Afterwards, frazil ice cannot be readily formed in the water column. Fig. 9c shows the time series of the east­ ward (offshore-ward) component of ice drift obtained from the ADCP bottom track data. Offshore ice drift tends to be faster and slower during night and day, respectively. This diurnal pattern corresponds to that of underwater frazil ice formation. The sea ice drift is forced by the wind and ocean current. In the case of the Sea of Okhotsk, wind-forced ice drift is with a speed and turning angle of 1.6% and 17.6� to the left of the wind, respectively (Simizu et al., 2014). Winds were mostly from the northwest with the speeds of 7–10 m s 1 during the polynya period (Fig. 9d). Thus, winds persistently

Fig. 9. Time series of the mooring and meteorological data during the period of 6–23 January. (a) SV at 3–5 m. (b) Incoming shortwave radiation at the surface. (c) The east-west component of the ice drift derived from the ADCP bottom track data. (d) The stick-diagram of the wind. (e) The east-west component of the ice drift forced by the wind. (f) The east-west component of the current at 3–5 m. Gray shade denotes the periods when underwater frazil ice was detected.

transport sea ice offshore-ward with a speed of 0.1–0.2 m s 1, as shown in Fig. 9e. In contrast, the eastward component of the current at 3–5 m was dominated by diurnal variability (Fig. 9f). This is because diurnal coastally trapped waves are generated over the Sakhalin shelf (Ono et al., 2008; Ono and Ohshima, 2010). During the polynya period in January, the eastward component of the tidal current was positive (i.e. offshore-ward) during night and negative (i.e. onshore-ward) during day and its absolute value was comparable to that of the wind-forced ice drift (Fig. 9e and f). Underwater frazil ice was mostly detected in the period of offshore tidal current. This can be explained as follows. During night, both the wind and tidal forced ice drifts were offshore-ward, and then frazil ice was advected towards offshore. Whereas during day, because the offshore wind forced drift is balanced with onshore tidal drift, frazil ice was accumulated within the polynya. Thus, the diurnal cycle of sea ice divergence/convergence by the tidal current is considered to be the main driver of the diurnal cycle of underwater frazil ice formation. During the polynya event in December, frazil ice was detected throughout the water column continuously over five days, as described in section 3.2 (Fig. 4b). During this period, the tidal current was slower because of the neap tide (Fig. 3f and g), and the winds were from northwest with the speeds up to 15 m s 1 (Fig. 3b). The ice drift induced by the wind was much stronger than that by the tidal current. Thus, the floating frazil ice was persistently transported offshore and the accu­ mulation of frazil ice was prevented. On the other hand, the polynya periods in January and February corresponded to periods of spring tides (Fig. 3f and g), and wind speeds of 7–10 m s 1 were weaker than those in December (Fig. 3b). Thus, the ice drift induced by the wind was com­ parable to that by the tidal current, and a diurnal cycle of underwater frazil ice formation appeared in association with the diurnal cycle of sea 10

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ice transport and the resultant ice divergence/convergence.

Although γ actually varies with the ice condition, we use this constant value for simplicity. The red lines in Fig. 10a and b are the calculated temperatures using Eq. (7). The initial value is set to the temperature at sunrise. The tem­ perature increase, ΔT, is calculated during the day. The upper and lower sides of orange shade in Fig. 10a and b denote the calculated tempera­ tures for clear and fully-cloud covered sky conditions, respectively. Considering the range between these two extreme sky conditions, the calculated temperature based on our assumptions is comparable to the observed one (black lines in Fig. 10a and b), indicating that the diurnal temperature variability is controlled by the penetrative shortwave ra­ diation. The calculated values based on the cloud cover derived from the ERA-Interim (red lines in Fig. 10a and b), however, mostly underesti­ mate the observed temperature increase. This suggests that the cloud cover of ERA-Interim data is potentially higher than the actual value. On the other hand, our calculation overestimates the observed temperature increase for the case of fully-covered sky on 13 January and 23–24 February. During these days, the ocean was covered with solid ice (Figs. 2c and 3a), and this ice probably reduced the penetration of solar energy. The water temperature decreased after sunset. During night, super­ cooled water sinks down and then frazil ice forms again associated with the eastward (offshore) current. Then, the oceanic heat loss cools the entire water column due to strong mixing. According to Fig. 10a, the daily lowest temperatures were recorded just before sunrise for most of the polynya periods. On the other hand, this temperature drop was minimal on 12–13 January and 22–24 February. This is likely because a solid ice cover weakened the ocean mixing. The penetrative shortwave radiation affects the short term vari­ ability such as diurnal water temperature cycle, as described above. However, its contribution to the total ice production over winter is less than 5% in mass according to our heat budget analysis. Hence, we ignored the penetrative shortwave radiation for the heat budget analysis for simplicity in section 4.1.

4.3. Diurnal oscillation of water temperature Fig. 10a and b shows the time series of the water temperature at 24 m measured by the C-T recorder during the periods of 6–23 January and 12–24 February 2003, respectively. These time series reveal the diurnal temperature oscillation with a magnitude of the order of 10 mK during the polynya periods. The water temperature clearly increased/decreased during day/night. This temperature oscillation occurred even when the zonal current direction was mostly westward on 13–14 January (Fig. 9f). Thus, the temperature change for these polynya periods is likely related to shortwave radiation, unlike the case of diurnal frazil ice cycle described in section 4.2. Incoming shortwave radiation can penetrate into the water column, while other heat fluxes, the long wave radiation, latent and sensible heat fluxes, cool or heat only the surface. Therefore, the penetrative solar energy can directly warm the water column even under a negative heat budget at the surface (i.e. cooling). Here, we examine this effect quan­ titatively. The penetrative shortwave radiation at depth z, I(z), is calculated by, I(z) ¼ γI0exp(z/Hγ),

(6)

where I0 ¼ (1 – αsolar)QSW and γ are the irradiance and the transmittance of the solar energy at the surface, respectively, and Hγ is the e-folding depth scale for the penetration of irradiance. The transmittance, γ, de­ pends on the surface condition. When grease or solid ice covers the ocean surface, the heat loss from the ocean to the atmosphere is converted to the latent heat of ice “growth”, not to “formation”. In this case, water temperature beneath sea ice does not change due to heat loss at the upper surface. Thus, the penetrative shortwave radiation is the only factor that controls the temperature of the water column other than advection. Assuming that the water temperature and its increase, ΔT, by the penetrative shortwave radiation over a short period, Δt, are vertically uniform due to wind stirring, then ΔT is estimated as, ΔT ¼ Δt(γI0/cpHρSW)

5. Concluding remarks This paper examines the process of sea ice production in a coastal polynya based on moored ADCP, IPS and C-T recorder data obtained in the Sakhalin polynya in the Sea of Okhotsk, along with satellite and meteorological data. During the opening of this polynya under turbulent conditions, potential/in-situ supercooling was recorded. At the same time, the acoustic backscatter strength obtained by the ADCP was enhanced throughout the water column. These observations indicate that supercooled water sunk deeper into the water column, leading to

(7)

where cp ¼ 4.2 � 103 J kg 1 K 1 and ρsw are the specific heat at constant pressure and the density of seawater, respectively, and H is the water depth. Conditions of sea ice production are judged by the method described in section 4.1. The period, Δt, is set to 1200 s (20 min), the time interval of the ADCP measurement. H is set to the water depth at the mooring site (33 m). ρSW is assumed to be a constant value of 1025 kg m 3. According to Murtugudde et al. (2002), γ for open water is 0.47.

Fig. 10. Time series of the water temperature at 24 m during the periods of (a) 6–23 January 2003 and (b) 12–24 February 2003. Black and red lines are measured and computed water temperatures, respectively. Orange shading denotes the range of temperature increase from fully-covered to clear sky conditions. (For inter­ pretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) 11

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frazil ice formation at depth. The heat loss from the ocean to atmosphere was kept at high values of up to 300–600 W m 2 when underwater frazil ice was persistently detected. This process is very effective at sustaining high heat loss and subsequent ice production in the absence of creating ice cover at the surface. We introduced a method to estimate the condition of sea ice pro­ duction based on the ADCP and IPS data, and calculated the ice pro­ duction by a heat budget analysis based on the estimated condition. Cumulative total ice production over the winter at the mooring site is estimated to be 4.47 m, in terms of ice thickness. Of this 4.47 m, cu­ mulative frazil ice production is estimated to be 2.69 m. Hence, frazil ice production contributes to more than the half of total ice production. Satellite data reveal that open water and thin ice regions were present over a wide area rather than a narrow area around the mooring site during polynya periods. These facts indicate the important role of un­ derwater frazil ice formation in ice production in this polynya. We also revealed that sea ice offshore/onshore transport and resul­ tant ice divergence/convergence have a significant effect on underwater frazil ice formation. Diurnal tidal currents dominate in the region of observation. During spring tides, the offshore/onshore component of ice drift showed a diurnal pattern, induced by the wind and tidal current, resulting in a diurnal cycle of sea ice production. According to the in­ crease and decrease in offshore ice transport, floating frazil ice could diverge and converge at the surface, respectively. When the ice transport is offshore-ward, the water at the surface can be supercooled and sink deeper, and then frazil ice can be formed throughout the water column. In contrast, when the ice transport is onshore-ward, frazil ice accumu­ lates at the surface. In this phase, underwater frazil ice formation does not occur. We cannot specify the size and concentration of suspended frazil ice from our present data, although these are likely key factors in the ice production process in any coastal polynya. In the future, in-situ obser­ vations by multi-frequency acoustic instruments and/or sampling frazil ice may enable us to identify these properties of underwater frazil ice, as in the cases of some river observations (Richard et al., 2011; Ghobrial et al., 2013; Marko et al., 2015).

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Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements The ERA-Interim product was provided by ECMWF (http://apps. ecmwf.int/datasets/). The AMSR-E data were provided by the Na­ tional Snow and Ice Data Center (NSIDC), University of Colorado (htt p://nsidc.org/data/). The thin ice thickness data were provided by Sohey Nihashi. We are indebted to Anatoliy M. Polomoshnov, Ervin Kalinin, Masao Ishikawa, Toru Takatsuka, and Takaharu Daibo for their logistical supports. This work was supported by Grant-in-Aid for Japan Society for the Promotion of Science (JSPS) Research Fellow 16J04868 from Japanese Ministry of Education, Science, Sports, Culture and Technology (MEXT), Japan, and Grants-in-Aids for Scientific Research 15403008, 17540405 and 17H01157 from MEXT. We also thank two anonymous reviewers for valuable comments on the manuscript. References ASL Environmental Sciences, 2004. Ice ProfilerTM Operators Manual for Model IPS4. 3. ASL Environ. Sci. Inc., Sidney, B. C., Canada. Cavalieri, D.J., Parkinson, C.L., 1987. On the relationship between atmospheric circulation and the fluctuations in the sea ice extents of the Bering and Okhotsk seas. J. Geophys. Res. Oceans 92 (C7), 7141–7162. https://doi.org/10.1029/ JC092iC07p07141.

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