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Physical Oceanographic Observationsfrom the Resolute 1995 Ice Camp,

Barrow Strait, April/May 1995

by

G. Crawford and L. Padman

Oregon State University

MARILYN POTTS GUIN LIBRARY

HATFIELD MARINE SCIENCE CENTER

OREGON STATE UNIVERSITY

NEWPORT, OREGON 97365

College of Oceanic & Atmospheric SciencesOregon State University

Corvallis, OR 97331-5503

Data Report 163COAS Reference No. 97-1

February 1997

PHYSICAL OCEANOGRAPHIC OBSERVATIONS FROM THERESOLUTE 1995 ICE CAMP, BARROW STRAIT,

APRIUMAY 1995

Greg Crawford and Laurie Padman

College of Oceanic and Atmospheric SciencesOregon State University104 Ocean Admin. Bldg.

Corvallis, OR 97331-5503

2/7/97

Sponsor: Office of Polar Programs, National Science Foundation

Grants: DPP-9224303 and OPP-9530916

Data Report #163

COAS Reference No. 97-1

1

PROJECT SUMMARY

A multidisciplinary oceanographic research program was carried out by US and Canadian

investigators in the spring of 1995 in the Canadian Arctic, near Lowther Island in Barrow Strait. The

program, referred to here as Resolute 95 (or Res95), had a variety of objectives, including detailed

examination of the mechanisms responsible for vertical mixing, and assessing the relative

importance of nutrient and light limitation on algal growth under ice.

This report focuses on analysis of the observational component conducted by Dr. Laurie

Padman (Oregon State University). The observational data set discussed here includes nearly-

continuous profile measurements of currents, temperature, salinity and turbulence at a fixed location.

Calibrations and data processing are described and observations are summarized. .

2

TABLE OF CONTENTS

1. OVERVIEW 4

2. MOORING MEASUREMENTS 4

MICROSTRUCTURE PROFILER MEASUREMENTS3 6.

4. ADCP MEASUREMENTS 9

APPENDIX: CALCULATION OF DISSIPATION RATES 12

LIST OF TABLES 17

LIST OF FIGURES 18

3

Oceanographic Measurements in Resolute 1995 Crawford and Padman (Oregon State U.)

1. OVERVIEW

The study site was located around 74° 27.398N, 97° 15.788' W, in Barrow Strait in the

central Canadian Arctic Archipelago (Figure 1.1). The locations of various instrumented sites within

the camp itself are shown in Figure 1.2. Table 1 provides a summary of the Res95 instrumentation,

including those maintained by other investigators. The instruments discussed in detail in this report

are: temperature and salinity sensors mounted at various depths on a mooring line; a downward-

looking, 300 kHz, narrow-band acoustic doppler current profiler (ADCP) mounted just below the

ice surface; and a profiler (RSVP) measuring temperature, conductivity and velocity shear

microstructure. Figure 1.3 shows time lines for each of these instruments, depicting periods of good,

calibrated data. [Throughout this report, time is given in decimal day-of-year (where 00:00 UT on

January 1, 1995 corresponds to t=1.0).]

Figure 1.4 shows the position of the two hydroholes inside the main science hut. One hole

was used to mount the ADCP, the other for the RSVP, CTD and bottle casts. All depths are

referenced to the ocean-ice interface. In this region the bottom of the ice was very smooth,

consisting of undeformed, first-year, land-fast ice. Large rafts of multi-year, landfast ice were

observed to the northeast of the study site, as well as along the coast of Lowther Island (see Figure

1.5). Water depth at the main science hut was 152m, while depths at other instrumented sites varied

from 151 to 165 m.

A set of CD-ROMs have been generated containing raw and processed forms of the data

described in this report. File names in this report correspond to file names on the CDs.

2. MOORING MEASUREMENTS

Three Seabird SBE CTD sensors and eight Alpha-Omega miniature data recorder (MDR)

temperature sensors were installed on a 3/16" kevlar cable, which was moored to the ice and held

taut with a 50 lb. anchor weight; depths of the sensors are given in Table 2. The mooring was fully

deployed around 23:30 UT, April 26, 1995 (year day 116.9792) and recovered around 15:00 UT,

4


May 18, 1995 (year day 138.625). All of the moored sensors were set to sample at one minute

intervals. One thermistor (MDR-107) failed very early in the experiment.

The thermistors were calibrated in December 1994 in Oregon State University's large, slowly

drifting temperature bath (with a drift rate of about 2x 10-3 °C per minute) over the desired

temperature range (-2.5 to 2°C). A frequently-calibrated Seabird standard (SBE-544) is used to

provided absolute temperature. The Seacat (T, C) sensors (including SBE-544) were calibrated by

Seabird Electronics in March 1994.

In order to estimate noise levels for temperature (T) and conductivity (C), we examined the

power density spectra for each sensor. At high frequencies the spectra flatten out, which we attribute

to this frequency band being dominated by noise. Assuming that the spectral level in the noise region

represents white noise that extends from zero to the Nyquist frequency, we can obtain the rms noise

level. Table 3 provides estimates of the rms noise level for each of the thermistors, and Table 4

provides noise level estimates for both the conductivity cells and for the derived salinity. We expect

the true noise level for sensors of one type to be similar: the increase in nns noise level with depth

for T suggests that, even at high frequencies, true signal is responsible for much of the power spectral

density at greater depths where variations in T are more pronounced.

Two versions of the mooring temperature and salinity data have been retained. The first

version is the full calibrated data with a 1 minute sampling interval. The second version is a low-

pass-filtered (phase-preserving, net 8th-order Butterworth filter, with a 1 hour cutoff period) data set

which has been subsampled to a 1/2 hour sampling interval. Figures 2.1 and 2.2 show overlays of

selected mooring temperatures, and all salinity time series, respectively. Figure 2.3 shows a plot of

temperature as a function of depth and time. Figure 2.4 and Figure 2.5 show examples of raw,

filtered, and filtered/subsampled data sets for temperature and salinity, respectively. In both figures,

we plot the time series and spectra (in two different forms) for the raw, filtered, and

filtered/subsampled data in order to show how the processing affects the characteristics of the data

sets. The spectra in these figures were calculated with the PSD function in MatlabTM (which uses

Welch's averaged periodogram method; see Oppenheim and Schafer [ 1975] and Little and Shure

[1993]). We used 8192 Fourier coefficients for the unfiltered and filtered data, and 273 coefficients

for the filtered/subsampled data, these choices leading to essentially the same number of degrees of

freedom for the spectral averages for the three spectra. It can be seen from these figures that the low

frequency information in the unfiltered data is well-preserved in the filtered, subsampled data.

5


Two of the MDR units on the mooring line also recorded pressure (see Table 2) and indicated

no measurable swing of the mooring line. Another sensor, operated by McGill University (G.

Ingram, P.I.), was placed on the seabed to measure tides and bottom water temperature. Figure 2.6

shows time series plot of those data.

3. MICROSTRUCTURE PROFILER MEASUREMENTS

Profiles of temperature, conductivity, and velocity shear were measured using the OSU Rapid

Sampling Vertical Profiler (RSVP). The RSVP, as configured for Res95, is very similar to the

version described by Robertson et al. [1995]. The instrument is designed to fall quickly and without

appreciable vibration through the water column. At the beginning of an RSVP profile measurement,

the profiler is at rest. The RSVP is then released and accelerates under gravity to a terminal velocity

of roughly 1.2-1.3 ms 1, which is determined by buoyancy elements and drag brushes. The profiler is

arrested at a predetermined depth determined by the length of instrument cable made available.

Figure 3.1 shows an example of a typical drop speed profile.

The RSVP sampling strategy was to alternate between profiling frequently for roughly 25

hours (generally to a depth of about 125 m), then pausing for about 23 hours. This strategy was

designed within manpower constraints to provide frequent data through two M2 tidal periods every

two days through a complete spring/neap tidal cycle. Each profile generated a data set identified by a

profile i.d. (also referred to as "drop number"). Each 25-hour collection of profiles is identified as a

"batch". Preliminary tests were carried out between April 25 and April 30; the data from this period

have been dubbed'batch 0'. Batch 1 through 9 denote sets of profiles collected between April 30

(year day 120) and May 17 (year day 137), spanning a total period of 18 days, or a little more than

one spring-neap cycle (see Figure 2.6). The sampling frequency was usually set to 256 Hz and the

terminal fall speed of the probe was usually about 1.2 - 1.3 ms 1, which led to a typical sampling

interval of about 5 mm (although none of the sensors are actually able to resolve down to this scale,

i.e. all data are oversampled). The start time and date for each drop, along with other related

information, is provided in a data file called `dropsum.tab'.

As a part of the RSVP calibration procedure, each profile data set was plotted on a computer

screen and examined visually to identify obvious problems or unusual circumstances; a 'quality code'

was ascribed to each profile, denoting the apparent integrity of the recorded data channels. In

6


particular, RSVP data files were flagged as 'bad' (data quality code=2) under the following

circumstances: data file was missing or empty; data file was very short; sampling frequency was less

than 256 Hz; pressure (and therefore depth) did not increase during data collection, so the file did not

represent a 'drop'; the temperature channel was clearly bad. Table 5 describes the code values and

their interpretation. The quality codes for all the drop files are presented in Table 6; Table 7 presents

a data summary of the RSVP batches. In addition, a comment file ('DropNotes.txt') was also

developed which describes an assessment of the drop file data sets.

In total, 1231 drop data files were generated. Of these, 1064 appear to have good temperature

and conductivity profiles; 995 of these data sets occur in batches 1-9. In all of the drop files except

one, data from shear probe S2 (the second of the two shear probes on the instrument) werehighly

corrupted, possibly due to a grounding problem with the S2 data channel. However, Si (first shear

probe) gave good results in almost all the drop profiles. In all, 1046 drop profiles have good

temperature, conductivity and shear data (see Tables 6 and 7).

Two separate forms of processed data files are generated for each valid RSVP drop file. One

consists of 8-point (i.e., 1/32 second) averages of depth, temperature, conductivity, and shear; the 8-

point data retain most of the frequency response available in the thermistor and shear sensors. The

second type of processed data are 256-point (i.e. one second, or roughly 1.2m) block averages of

depth, temperature, conductivity, salinity, and dissipation rate. For data channels with 'bad' values,

the associated measurements in the processed data sets are 'flagged' by setting them to a standard

value of 999.99.

The RSVP temperature and conductivity laboratory calibrations are less accurate and stable

than calibrations for the moored Seabird CTDs and MDR units. Consequently, in order to improve

the absolute accuracy of the RSVP measurements, we first compared mean RSVP and mooring

temperature profiles over each batch. The results showed that the RSVP temperatures based on

laboratory calibrations were systematically colder than the mooring temperatures. We examined the

temperature differences in a variety of ways, including histograms and scatterplots as a function of

depth and of mooring temperature. Based on these comparisons, we have added a constant offset of

+0.007°C to the RSVP temperatures. This offset is incorporated in the calibrated data files (which

are generated by the calibration program, `newcalibrat.f'). Figure 3.2 shows a typical comparison of

the batch-averaged temperature profile determined from the mooring, uncorrected RSVP

7


temperatures, and corrected RSVP temperatures. The RSVP temperature correction clearly improves

the comparison against the mooring.

We have also compared batch-averaged conductivity profiles from the RSVP and the moored

CTDs. The RSVP conductivities are consistently higher than the moored values. The differences at

7m and 30m depth are fairly well-represented by a constant offset of -0.24 mS cm -1 (equivalently,

mmho.cm"1). The differences at 15m are somewhat higher, but the CTD sensor at this depth is in the

halocline, and the differences may be attributed to a depth offset of only 2m between the moored

CTD sensor and the RSVP pressure measurements. Consequently, we have incorporated a uniform

correction of -0.24 mS cm1 to the RSVP conductivities. Figure 3.3 shows a typical comparison of

the batch-averaged conductivities from the moored CTDs and corrected and uncorrected RSVP

profiles. Again, the RSVP correction clearly improves the comparison against the mooring data.

It is well-known that the response time of the RSVP conductivity cell is somewhat slower

than the response time of the RSVP thermistor, owing in large part to the flushing time and the

thermal inertia of the cell (c.f. Lueck and Picklo [1990]; Morison et al. [1994]). This effect leads to

a time delay between temperature and conductivity sampling of the same water depth, which can

lead to significant errors in salinity calculations. This problem was noted during recent studies in the

Antarctic (e.g., Robertson et al. [1995]), where temperature variations generally play a much greater

role than salinity in setting conductivity. However, in the present data set, salinity variations play a

dominant role in setting conductivity: temperature effects are almost negligible due to the small

overall change in T throughout the water column. After careful examination of the RSVP

temperature and conductivity data, we found it unnecessary to compensate for any slight time delays

between the sensors. Salinities and densities were then derived using the standard formulas.

During a period of roughly one hour on May 11 (day 131), a cross-calibration test was

carried out using the RSVP profiler, mooring sensors, and a Seabird CTD from McGill University

(G. Ingram, pers. comm.). The CTD profile began at 20:14 UT; one RSVP profile began at 20:44

and another began at 21:09. Figure 3.4 (a) shows a comparison of temperature profiles from the

McGill CTD and the two RSVP profiles; the minimum and maximum temperatures observed

between 20:14 and 21:09 at each thermistor on the mooring are also shown. There is clearly some

variability among all three of the continuous profiles, but most of this is likely due to internal wave

activity and tidal advection of horizontal property gradients. Figure 3.4 (b) shows a comparison of

salinities from the same instrumentation. The results suggest there is still a systematic, finite offset

8


of roughly 0.04 to 0.06 psu between the McGill salinity and the RSVP and mooring salinity. (A

fixed depth offset of about 10 in can also account for the differences in the deep portion of the

salinity profile, but then the salinity differences in the upper portion of the water column become

unrealistic). At this stage we do not attempt to correct for this difference, but we note that the offset

appears to be nearly independent of depth.

The temperature and conductivity measurements are essentially independent of RSVP fall

speed of the RSVP, however the shear measurements and inferred dissipation rates are not. In

practice, we use the fall speed to determine the valid depth range for shear and dissipation estimates

as follows: we define the first valid depth is the first depth at which the profiler fall speed is greater

than 1.0 ms-1; the last valid depth is the next depth at which the profiler speed is greater than 1.5 ms -1

or less than 0.8 ms-1. Figure 3.5 shows the valid depth range for shear and dissipation rateestimates

for each RSVP profile, organized by batch number.

Examples of shear time series and wavenumber power spectra are shown in Figures 3.6 and

3.7. Under the assumption of a frozen turbulence field (Taylor's hypothesis), we can relate the cyclic

frequency, f, to a scalar wavenumber in the (vertical) profiling direction, k, through the fall speed, w:

kZ =2af

(1)W

Since the fall speed is fairly constant (w-1.25ms 1) for the depths of interest, the relationship

between kZ and f is effectively linear.

Values of the energy dissipation rate, e, are estimated from the shear spectra using an iterative

integration technique. The details of this method, as applied to the RSVP data from Res95, are

presented in the Appendix.

Summary plots of the RSVP data for the nine batches are shown in Figures 3.8 - 3.16. The

plotted measurements include temperature (T), salinity (S), buoyancy frequency (N) and energy

dissipation rate (E).

4. ADCP MEASUREMENTS

A 317 kHz RDI narrow-band ADCP operating in high-power mode (AC power provided

externally) was installed in a downward-looking orientation in a hydrohole at the SW corner of the

9


main science hut (Figure 1.4). The transducers were set in a convex pattern with a 30° beam angle,

and were mounted in a square sea chest, with the four beams directed along the diagonals of the

chest (see Figure 1.4). Transducer beam 3 (see RD Instruments [ 1991 ]) was determined to be

directed 3 degrees North of Gourdeau Point on Lowther Island, so the long axis of the science hut

was oriented 48 degrees North of Gourdeau Point. The depth of the transducer head. is 1.8m below

the mean water surface, and recorded depths are corrected to the surface accordingly. ADCP data

were logged both internally and on the hard drive of an IBM-compatible computer. Acoustic

backscatter levels were also recorded by the ADCP, but have not yet been examined in detail.

However, it is known that backscatter data do provide a useful alternative view of the vertical motion

associated with higher-frequency internal waves in the main pycnocline.

A timing problem occurred with the instrument during the experiment, which regularly shut

down data logging at midnight UT every day. This led to the generation of short data gaps, and a

total of 45 ADCP data files being generated. Table 8 summarizes the ADCP times and instrument

settings for these 45 data files. The first available data starts at 16:23 UT, April 25, 1995 (year-day

115.6826) and the last available record corresponds to 03:55 UT, May 18 (year-day 138.1632). Ping

repetition period was fixed at 0.4 seconds; the number of pings averaged for velocity estimates was

varied between 140 and 300; pulse width (and hence bin width) was varied between 2m and4m, as

specified in the setup software. Correction to the depth bins was later made using estimates of the

speed of sound profile derived from RSVP data. Figure 4.1 shows the average speed of sound

profile from all valid RSVP profiles collected during the experimental period. Sound speed over the

range of valid velocity data varied from about 1436.5 ms 1 to 1441 ms-1. We have chosen a mean

sound speed of 1439.2 ms-1 to relate the binned ADCP data to depths. Errors in the depths

associated with ignoring sound speed profile variation is limited to less than 4 cm. Good ADCP

profile data were retrieved consistently to at least 120 in. The mean sound speed at the transducer

head was about 1436.5 ms-1; this value is used in the conversion of Doppler-shifted frequency

estimates to velocity estimates [RD Instruments, 1991 ].

The ADCP initially records data from all four transducer heads. We took these data and

determined velocity components in beam coordinates, as defined by RD Instruments. The velocity

component along the beam 1 - beam 2 axis (referred to as v12) is within a few degrees of being

aligned with the north-south direction, and the component along the beam 3 - beam4 direction (v34)

is very nearly aligned west-east. We therefore associate the east-west velocity, v, , as vX = - V34

10


(since beam 3 points nearly west) and the north-south velocity, vy, as Vy =V12- Vertical velocity, vz,

is generally low and comparable in magnitude to the error velocity estimate, verr. However, there are

several short periods where vZ is much larger than ve1l, and thus appears to represent a true vertical

velocity. Figs. 4.2 - 4.5 show examples of the ADCP velocity components (vs, vy, vz, and veer,

respectively) at four selected depths.

The various velocity files were low-pass filtered (using a phase-preserving, net 8"'-order low-

pass Butterworth filter, with 1 h cutoff period), subsampled to half-hourly intervals, and re-

formatted. Tidal current analysis was then carried out on the entire available time series using the

algorithms of Foreman [ 1993]. The length of the time series allowed for 18 different tidal

constituents to be evaluated. Table 9, 10, 11 and 12 provide the tidal analysis results over the water

column resolved by the ADCP (5.5 in to 114.2 in, at roughly 4 in intervals) for the K1, 01, M2 and

S2 constituents, respectively; Tables 13, 14, 15, and 16 present the analysis results for all 18

constituents at 9.3, 28.0, 50.5, and 99.2 in depth, respectively. These analyses include the mean

current, shown in the Tables as Z0. We also used the Foreman algorithms to output the time series

of analyzed tidal currents for the measurement period with a one-hour time interval. Figures 4.6, 4.7,

4.8 and 4.9 show comparisons of the low-passed horizontal velocity components and the velocities

reconstructed from the tidal analysis at 9.3, 28.0, 50.5 and 99.2 m depth, respectively.

Acknowledgments: We wish to thank the staff of the Polar Continental Shelf Project at Resolute for

providing logistical support and Walt Waldorf, Miles McPhee, Guy Millette, Paul Peltola, and Zeus

Kerravala for providing technical support. Greta Reynolds and Rick Guritz of the Alaska SAR

Facility, University of Alaska Fairbanks, provided the SAR image data. This project was funded by

the National Science Foundation (DPP-9224303, and OPP-9530916).

11


APPENDIX: CALCULATION OF DISSIPATION RATES

For homogeneous, isotropic turbulence, the energy dissipation rate, c, is related to the integral

of the vertical shear spectrum, according to

00

2v f cp(kk )dkk

0

(Al)

where v is the kinematic viscosity, cp(kk) is the power spectrum of measured turbulent shear, au'/az

(where z is in the vertical [profiling] direction, kZ is a wavenumber component in the z direction, and

u' is the turbulent velocity component in a fixed horizontal direction, (i.e., tangential to z); see also

Tennekes and Lumley [1972]). In practice, one is usually limited to evaluation of the spectrum over

a finite range of wavenumbers, due to a number of constraints (e.g. finite sampling, noise levels,

anisotropic behavior at low, buoyancy-influenced, wavenumbers). We can rewrite (Al) as

Er(k',k2) (A2)

where

g(k,,k2)

k2

En(k,,k2,£) =15

v f (p (kz)dkk

k,

(A3)

is a partial estimate of t, and

k2

f (p (kk)dkk

k,g(k,,k2,£) CIO

(A4)

f sp (kk )dkk

0

represents the fraction of the total variance of the turbulent shear captured within the spectral band

[kt,k2]. In other words, g represents a correction factor for estimation of e from fr,, (note that, since

is a function of F-, so is g).

For isotropic turbulence, the theoretical shear spectrum has a universal form, sometimes

referred to as the Nasmyth spectrum, given by

4,

12

Oceanographic Measurements in Resolute 1995

T, = kr2(EV5)ll4G2

where

ks =(EV-3)114

Crawford and Padman (Oregon State U.)

(A5)

(A6)

is the characteristic (Kolmogorov) wavenumber and G2 is a nondimensional shape function. Oakey

[1982] provides tabulated values of G2 (derived from the data of Nasmyth [1970]) at specific values

of k Iks, where k = k/2it is the cyclic wavenumber; in Table Al, we re-write those data values in the

more standard notation, G2 (k / k,) = G2 (k l k,) / 27r. The spectrum tot is peaked, with the peak

occurring at about 0.lks. As E increases, the spectral energy levels increase and the peak shifts to

higher wavenumbers.

Following equations Al-A6, we define two more functions: a theoretical partial estimate of

dissipation rate (based on Nasmyth spectra), en,, given by

k2

E,P(k,,k2,E) = 21

v f cp,(k,)dkk (A7)

k,

and the associated theoretical fractional variance function, gt, given by

k2

f cpt(k,)dkk

k, Etngt(k,,k2,E)=00

f tp,(k,)dkZ

0

r -

(A8)

Figure A.1 shows plots of the cumulative integration of the tpt , normalized to the total

variance of the spectrum, for a variety of values of E. Values of E that are most commonly observed

in the stratified ocean are in the range10"9<£<10"5 m2s 3, the lower limit being due to noise levels of

shear probes and the upper limit being set by the spatial response of shear probes. For this range of s,

most of the contribution to the total variance in the shear spectrum occurs at wavenumbers between

about 10 mt and 400 m 1. Indeed, for e - 10-9 - 10-8 m2s 3, most of the energy appears at

wavenumbers less than 100 m-1. Figure A.2 shows examples of gt , as a function of e, obtained by

integrating (pt over two different wavenumber bands: [k1,k2] = [12 m-' , 320 m-' ] and

13


[k1,k2] _ [12 m t, 80 m' ]; Figure A.3 shows gt as a function of a , for the same wavenumber

bands. These latter curves allow us to recover E from a particular measure of Etr and (k1, k2) using

(A.2).

We assume the measured spectrum, rp,, is well-represented by

Y'm = T, +T., (A9)

where con is the noise spectrum, over a range of wavenumbers associated with the inertial subrange

and down to viscous dissipation scales. One can therefore also calculate an observationally-

determined partial estimate of E, denoted by E,np, from

15 k2 15Emp(k,,k21E) = 2 V f (m(kz)dkz = v

k,

k2 k2

f t'p, (kz )dkz + f cpn (kz )dkz

k, k,

(A 10)

In regions with high energy in the shear signal (e.g., Figure 3.6), the peak location and the shape of

the measured shear spectra is well-represented by the Nasmyth spectrum (cpm - (pt). In regions with

low shear energy (e.g., Figures 3.6 and 3.7), the peak is harder to pick out of the background noise

and there is a lot of noise at the higher end of the spectrum which is not related to the theoretical

spectrum.

As mentioned in Section 3, the profiler fall speed is generally very steady at about

w=1.25 m s t, so the vertical wavenumber kZ and frequency f are linearly through (1). The measured

shear spectra suggest that a lower bound off1=2 Hz (k1 - 12 m-1) is reasonable and allows us to get a

spatial (vertical) resolution of as small as 1.25 m; for conditions of moderate to high turbulence,

noise in the data does not contribute significantly to the spectra below frequencies of about 64 Hz

(k2.-320 m1), while for low turbulence conditions the noise can play a significant part in the variance

and therefore may lead to overestimates of the true shear variance and, hence, E.

While we do not have a detailed model or measurements of the noise spectrum, we seek to

minimize the contribution of spectral noise to our estimates of E (thereby reducing the noise floor of

those estimates) while at the same time preserving good estimates of E; we also wish to eliminate

shear values that arise through sensor impact with bugs, ice crystals and other particles in the water

column, which lead to data spikes. In order to do so, we have adopted the following procedure.

First, the shear data are divided into 256-point (1 second) blocks. For each block, despiking is

performed by identifying shear values greater than three standard deviations from the mean shear

value of that block and setting those values to zero. This despiking process is carried out twice. The

14


number of points that are rejected by the despiking algorithm is rarely a significant fraction of the

original block of 256 points, hence no correction is made to the estimated variance to compensate for

rejected points.

An adaptive integration scheme is then applied to each valid block. First, the measured shear

(wavenumber) power spectrum, cpm, for a 256 point (1 second) block is determined using a FFT, the

mean fall speed over the block period, and from (1). The lower bound on spectral integration is

fixed at f1=2 Hz, while the upper bound is first initialized to f2=16 Hz; the equivalent bounds on the

wavenumbers k1 and k2 are also determined (1). The algorithm calculates a partial estimate of

dissipation rate, £,,,p(kl, k2) from (A10), then estimates gm(kl, k2, E,,,p) and E by assuming (Qm"'O and

spline-interpolating Emp to predicted values of F -,p inferred from (A7). If the estimated value of gm is

less than a minimum threshold (taken as g, = 0.75), then the estimate of E is rejected and the upper

bound of integration is increased incrementally by 4 Hz. The procedure is then repeated until the

algorithm detects that at least 75% of the predicted shear variance is captured within the bounds of

integration (i.e. gm>_ ge). The associated dissipation rate estimate is then accepted (N.B., a maximum

value of f2 = 64 Hz was used, although the algorithm always converged to an acceptable limit before

this limit was reached). Based on the distributions of e that are found in the least energetically-

mixing regions, we determine that the noise floor for E estimates is about 2x 10-9 m2s"3.

Figure A.4 shows an example of a profile of E for a set of measurements with both high and

low shear variance regions. Three different estimates of E are displayed, all three of which use the

same, fixed low frequency for integration, f, =2 Hz; the first method uses f2=16 Hz, the second uses

f2=64 Hz, and the third uses our adaptive scheme for f2. All three methods correct for the finite

spectral bandwidth using an estimate of g(kl, k2, E), where k, and k2 are computed fromf1 andf2 from

(1) using the average fall speed w over each 256 point (1 second) vertical bin. It can be seen that, for

the high shear regions, the results from the adaptive scheme closely match those derived from the

f2=64 Hz case; for the low shear regions the adaptive scheme estimates of E match the f2=16 Hz case

and are generally lower than estimates based onf2=64 Hz (which would include more noise

contribution) as expected. Figure A.5 shows another energy dissipation profile determined from the

adaptive scheme, along with the associated value of f2 at each depth.

15


REFERENCES

Foreman, M.G.G., 1993. Manual for Tidal Currents Analysis and Prediction. Pacific MarineScience Report 78-6. Institute of Ocean Sciences, Sidney, B.C. Canada. 66pp.

Little, J.N., and L. Shure, 1993. Signal Processing Toolbox User's Guide. The Mathworks, Inc.,Natick, Mass.

Lueck, R.G., and J. J. Picklo, 1990. Thermal inertia of conductivity cells: Observations with a Sea-Bird cell. J. Atmos. Oceanic Technol., 7, 741-755.

Morison, J., R. Andersen, N. Larson, E. D'Asaro, and T. Boyd, 1994. The correction for thermal-lageffects in Sea-Bird CTD data. J. Atmos. Oceanic Technol., 11, 1151-1164.

Nasmyth, P., 1970. Oceanic turbulence. Ph.D. thesis, Institute of Oceanography, University ofBritish Columbia, 69 pp.

Oakey, N., 1982. Determination of the rate of dissipation of turbulent energy from simultaneoustemperature and velocity shear microstructure measurements. J. Phys. Oceanogr., 12, 256-271.

Oppenheim, A.V., and R.W. Schafer, 1975. Digital Signal Processing. Prentice-Hall.RD Instruments, 1991. Self-contained Acoustic Doppler Current Profiler (SC-ADCP) TechnicalManual. RD Instruments, San Diego.

Robertson, R., L. Padman, and M. D. Levine, 1995. Fine structure, microstructure, and verticalmixing processes in the upper ocean in the western Weddell Sea. J. Geophys. Res., 100 (C9),18,517-18,535.

Tennekes, H., and J. L. Lumley, 1972. A First Course in Turbulence. The MIT Press, Cambridge,Mass., 300 pp.

16


LIST OF TABLES

Table 1. Summary of oceanographic instrumentation deployed during Resolute 95.

Table 2. Moored instrument summary. Variables include temperature (T), conductivity (C), andpressure (P).

Table 3. Moored thermistor noise levels (inferred from observed temperature spectra).

Table 4. Moored conductivity and salinity noise levels (inferred from observed spectra).

Table 5. RSVP drop file quality codes (following the format developed by R. Robertson).

Table 6. Quality codes for RSVP profiles. The first column in each row gives the profile W.number for the first profile of each group of twenty profiles; the next twenty columns (given ascomma-separated values) indicate the quality code for profile number and the next nineteenprofiles in sequential order (thus, for the first row above, 0001 refers to RSVP profile # 0001,and the following 20 comma-separated values indicate the quality code for RSVP profiles #0001-0020, respectively. See Table 5 for interpretation of the code values.)

Table 7. RSVP batch drop summary.

Table 8. Summary of ADCP settings.

Table 9. Tidal analysis results for K1 tidal constituent, from 5m to 115m depth. Angle ofinclination denotes the clockwise rotation of the major axis relative to east. Positive values of theminor axis indicate counterclockwise rotation of the tidal component; negative values indicateclockwise rotation.

Table 10. Same as Table 9, but for 01 tidal constituent.

Table 11. Same as Table 9, but for M2 tidal constituent.

Table 12. Same as Table 9, but for S2 tidal constituent.

Table 13. Entire 18-component tidal analysis for 9.3 in depth bin.

Table 14. Same as Table 13, but for 28.0 in depth bin.



Table A-1. Discrete values of the universal shape function for the shear spectrum (after Oakey[ 1982] and Nasmyth [ 1970]). The data have been re-written from Table Al in Oakey [ 1982] in termsof wavenumber instead of cyclic wavenumber.

17


LIST OF FIGURES

Figure 1.1a: Map of the Canadian Arctic Archipelago. The Res95 experimental site is in BarrowStrait, in the center of the archipelago. A finer-scale view of the region immediately surrounding thecamp is shown in Figure 1.1b (following page).

Figure 1.1b: Map of the central Barrow Strait region, showing more detail in the area indicated by abox in Figure 1.la. Bathymetric contours in (b) are given in meters. The Res95 camp is locatedaround 74° 27.398' N, 97° 15.788'W, southeast of Lowther Island.

Figure 1.2: Locations of primary instrumented sites at the Res95 camp.

Figure 1.3: Time lines of good, calibrated data for each of the instrument packages discussed in thisreport.

Figure 1.4: A schematic showing the location of the two hydroholesinside the main science tent

and the orientation of the transducers.

Figure 1.5: A portion of a synthetic aperture radar (SAR) image, obtained by the ERS-1 satellite onMay 2, 1995 (year day 122) showing the study site. The image (which has been rotated so that thetop of the page is in the northward direction) consists of 8 bit pixels, corresponding to uncalibratedbackscattered intensity. Pixel resolution is roughly 100 m by 100 m. Lowther Island is clearlyidentifiable. The ice camp was located on land-fast first-year ice; the medium gray masses along the

coast of Lowther Island and to the northeast of the study site represent land-fast, multi-year ice (SARimage data provided by G. Reynolds, Alaska SAR Facility, University of Alaska Fairbanks [data take

i.d. EI/S/19860.01; image i.d. 183735200]).

Figure 2.1: Moored temperature time series from selected depths (125, 75, 25, 7 m). Samplinginterval is one minute.

Figure 2.2: Moored salinity time series from the three CTDs (30, 15, 7 m). Sampling interval is

one minute.

Figure 2.3: Mooring temperature as a function of depth and time.

Figure 2.4: Temperature data from MDR 106 (50 m depth). Top panel shows the entiretemperature time series. Middle panel displays the log-log plots of the power spectral density, PSD,of the raw time series (blue), the low-pass-filtered time series (green), and the low-pass-filtered,subsampled time series (red). Bottom panel shows same data as the middle panel, plotted here as the

frequency times the PSD on a log-linear scale. Filter cutoff period is 1 h; raw sampling interval is 1

min.; time interval for subsampled data is 30 min. See text for more details on the filtering,subsampling, and spectral estimation.

Figure 2.5: Salinity data from SBE 40 (30 m depth). Top panel shows the entire salinity timeseries. Middle panel displays the log-log plots of the power spectral density, PSD, of the raw timeseries (blue), the low-pass-filtered time series (green), and the low-pass-filtered, subsampled time

18


series (red). Bottom panel shows same data as the middle panel, plotted here as the frequency timesthe PSD on a log-linear scale. Filter cutoff period is 1 h; raw sampling interval is 1 min.; timeinterval for subsampled data is 30 min. See text for more details on the filtering, subsampling, andspectral estimation.

Figure 2.6: Time series of measurements from the McGill sensor mounted on the seabed: (a) waterlevel (height of water above the sensor); (b) bottom water temperature.

Figure 3.1: Fall speed profile for drop number 180. The profiler is seen to quickly accelerate to itsterminal velocity of about -1.25 ms-t (a negative value here implies descent) and to continue to fall atabout that speed throughout the water column. The profiler is quickly arrested at the end of theprofile near 110 m depth.

Figure 3.2: Sample comparison of time-averaged temperature profiles from the mooring (opencircles), the uncorrected RSVP data (dashed line) and the corrected RSVP data (solid line),evaluated over the entire period of batch 2 (day 122.6347 to 123.6669). The RSVP averages arederived from the 256-point `block' averages and have been bin-averaged in 1 m depth bins.

Figure 3.3: Sample comparison of time-averaged conductivity data from the mooring (open circles),the uncorrected RSVP data (dashed line) and the corrected RSVP data (solid line), evaluated overthe entire period of batch 2 (day 122.6347 to 123.6669). The RSVP averages are derived from the256-point `block' averages and have been bin-averaged in 1 m bins.

Figure 3.4a: Comparison of temperature data during cross-calibrationrun on May 11 (year day131). The dotted line is from the McGill CTD at 2014 h; the solid line is from the RSVP profiler at2044 h; the dashed line is from the RSVP at 2109; open circles identify the minimum and maximumvalues observed at the mooring between 2014 h and 2109 h.

Figure 3.4b: Comparison of salinity data during cross-calibration run on May 11 (year day 131).The dotted line is from the McGill CTD at 2014 h; the solid line is from the RSVP profiler at 2044h; the dashed line is from the RSVP at 2109; open circles identify the minimum and maximumvalues observed at the mooring between 2014 h and 2109 h. The results suggest there is a nearlyuniform offset between the McGill salinity and the RSVP mooring salinity, corresponding to roughly0.04 to 0.09 psu. No attempt has been made at this stage to correct for this difference.

Figure 3.5a: Depth range of valid RSVP data vs. RSVP drop number for Batches 0 and 1.

Figure 3.5b: Depth range of valid RSVP data vs. RSVP drop number for Batches 2 and 3.

Figure 3.5c: Depth range of valid RSVP data vs. RSVP drop number for Batches 4 and 5.

Figure 3.5d: Depth range of valid RSVP data vs. RSVP drop number for Batches 6 and 7.

Figure 3.5e: Depth range of valid RSVP data vs. RSVP drop number for Batches 8 and 9.

19


Figure 3.6: Shear time series and frequency spectra for RSVP Drop 653. (a) Time series of shearfrom shear channel S 1, with times plotted relative to the beginning of data collection for that profile.Two short, 256-point (1 second) data segments are selected, representing high and low regions ofshear variance (labeled A and B, respectively). Drop speed was about 1.15 ms-1 and very stable overmost of the profile; A corresponds to about 32 m and B to 87 m depth. (b) Wavenumber powerspectra for time series A (thick line) and B (thin line), plotted on a log-log scale as kZ toM (ks) vs. kZ.No spectral averaging is performed here; note that this is not an energy-preserving plot, but doesallow visualization over a very broad dynamic range. Dashed lines show theoretical Nasmyth spectrafor different orders of magnitude of the dissipation rate, ranging from E = 10"9 to 10-5 m2s 3. Atwavelengths greater than about 320 m-1 (denoted by a vertical line; f -- 64 Hz), the spectra drop offsharply due to the frequency characteristics of the shear probe and data collection scheme. In the lowdissipation measurements, much of the energy greater than 80 m-1 is probably due to electronic noiseand profiler motion and vibrations.

Figure 3.7: Similar to Figure 3.6, but for RSVP Drop 1184; data segments A and.B correspond to10 m and 93 m depth, respectively; drop speed was steady at about 1.20 ms-1.

Figure 3.8: Stack plot summary of RSVP profile data for batch 1. Panels represent (from top tobottom), temperature (T, in °C), salinity (S, in psu), buoyancy frequency (N, in cycles/hour), anddissipation rate (as loglo[E], with E in m2s"3).

Figure 3.9: Same as Figure 3.8, for batch 2.








Figure 4.1: Average sound speed profile (solid line), as determined from the RSVP data. Thedashed lines represent plus or minus one standard deviation.

Figure 4.2: Time series of raw, ADCP-derived measurements of eastward (v,,) velocity at specifieddepths: (a) 9.3 m; (b) 50.5 m; (c) 99.2 m. The reduction in high-frequency variability between day122 and day 127 is primarily a consequence of a longer pulse width and an increased number ofsamples per ensemble (see Table 8).

Figure 4.3: Same as for Figure 4.2, but for northward (vy) velocity.

20


Figure 4.4: Same as for Figure 4.2, but for vertical (v2) velocity.

Figure 4.5: Same as for Figure 4.2, but for the error velocity (VeTC).

Figure 4.6: Comparison of low-frequency velocities (solid lines) and reconstructed velocities(dashed lines) from tidal analysis at 9.3 m depth: (a) eastward component; (b) northward component.Time interval shown for the plotted data is 1 hour; time range is limited to a 5 day section for ease ofcomparison.

Figure 4.7: Same as for Figure 4.6, but for 28 m depth.

Figure 4.8: Same as for Figure 4.6, but for 50.5 m depth.


Figure A.1: Cumulative integration of Nasmyth shear spectra, qpt, normalized to the total shearvariance, for several values of dissipation rate, E. Integrations were carried out numerically, based onvalues of G2(k/k,) given by Oakey (1982). For the range of £ typically found in the ocean(10-1<F<10-5 m2s-3), most of the spectral energy occurs at wavenumbers between about 12 mt and320 m-1; for £=10-9-10-8 m2s-3, most of the energy occurs between 12 in-' and 80 m 1.

Figure A.2: Estimates of gt, the fraction of the variance in the Nasmyth shear spectrum, captured ina fixed spectral wavenumber band [k1i k2], as a function of dissipation rate, E. Two differentwavenumber bands are shown: [k1, k2] = [12 m 1, 80 m f] and [k1, k2] = [12 m1, 320 m"1].

Figure A.3: Estimates of gt, the fraction of the variance in the Nasmyth shear spectrum, captured ina fixed spectral wavenumber band [k1, k2], as a function of the partial estimate, -tp. Two differentwavenumber bands are shown: [k1, k2] = [12 m 1, 80 in-] and [k1, k2] = [12 m-' 320 m-']. Ahorizontal line denotes the minimum threshold of gt = 0.75 required for determining observationalestimates of £ from integrations of observed shear spectra (see Appendix).

Figure A.4: Comparison of energy dissipation profile estimates for RSVP drop number 1184 forthree algorithms with different high-frequency cutoff values: f2 = 16 Hz (thin solid line), f2 = 64 Hz(dashed line), and a variable f2 (from the adaptive method; thick solid line). All three methods usethe same low-frequency cutoff, fl = 2 Hz, and make corrections for energy not included in thespectral range of integration (see Appendix).

Figure A.5: (a) Dissipation profile for RSVP drop number 1184, obtained using the adaptivemethod; (b) associated high frequency cutoff value, f2, used by the method. The minimum thresholdvalue of f2 = 16 Hz is clearly identified. When the energy levels in the shear spectra are high, thealgorithm integrates to higher frequencies (wavenumbers) to get a better estimate of the shearvariance.

21


Instruments Location Sample Interval Principal Investigator300 kHz Narrow-Band

ADCPMain Science Hut 1 min x (2-4) m Padman (OSU)

600 kHz Narrow-BandADCP

Marsden ADCPIgloo

1 min x 1 m Marsden (RMC)

600 kHz Broad-BandADCP

McGill ADCP Igloo 10 s x I m Ingram (McGill)

RSVP MicrostructureProfiler

Main Science Hut 15 min for 25 h,every 48 h (see text)

Padman (OSU)

Temperature /Conductivity Mooring

Padman Mooring 1 min Padman (OSU)

Turbulence Frame McPhee Shelter 1 s McPhee/Padman

S4 Current Meters S4 East andS4 West

5 min Ingram (McGill)

Aanderaa T-C recorders Main Science Hut 1 min In ram (McGill)Aanderaa Tide Gauge McGill ADCP tent 30 min In ram (McGill)

Chemistry, radiation, andice

Biology Camp variable Cota (Old Dominion)

Table 1. Summary of oceanographic instrumentation deployed during Resolute 95.

22


Depth belowice (m)

Sensor ID Variables

2 MDR-103 T7 SBE-43 T,C10 MDR-112 T15 SBE-41 T,C20 MDR-109 T25 MDR-116 P,T

30 SBE-40 T,C50 MDR-106 T75 MDR-101 T100 MDR-107 (did not work)125 MDR-100 P,T

130 50 lb. lead weight N/A

Table 2. Moored instrument summary. Variables include temperature (7),conductivity (C), and pressure (P).

Sensor ID SensorDepth

Spectral Noise Level(oC2-hr)

Rms Noise Level (°C)

MDR-103 2 1 x 10-7 2 x 10-3

SBE-43 7 6 x 10-8 1 x 10-3

MDR-112 10 2 x 10-7 3 x 10-3

SBE-41 15 2 x 10-7 3 x 10-3

MDR-109 20 2 x 10-7 3 x 10-3

MDR-116 25 2 x 10-7 3 x 10-3

SBE-40 30 4 x 10-7 4 x 10-3

MDR-106 50 4 x 10-7 4 x 10-3

MDR-101 75 8 x 10-7 5 x 10-3

MDR-107 100 (did not work) (did not work)

MDR-100 125 6 x 10-7 4 x 10-3

Table 3. Moored thermistor noise levels (inferred from observedtemperature spectra).

23


Sensor ID Conductivity Salinity

Spectral Noise Level([mS/cm]2hr)

Rms NoiseLevel (mS/cm)

Spectral Noise Level([ su]2hr)

Rms NoiseLevel (psu)

SBE-43 1 x 10-6 6 x 10-3 2 x 10-6 8 x 10-3

SBE-41 1 x 10-6 6 x 10-3 2 x 10-6 8 x 10-3

SBE-40 2 x 10-7 3 x 10-3 1 x 10-6 6 x 10-3

Table 4. Moored conductivity and salinity noise levels (inferred from observed spectra).

RSVP DropFile Quality

Code

Description

0 file not evaluated (temporary status)1 all data channels good

2 bad drop file3 C (conductivity) channel bad4 S 1 (shear) channel bad

5 S2 (shear) channel bad

6 S 1 and S2 channels bad

7 C, Si and S2 channels bad

Table 5. RSVP drop file quality codes (following the format developed by R. Robertson).

24


Profile Quality CodesI.D. (20 consecutive profiles)

0001: 2,2,2,2,2,2,2,6,6,2,2,2,2,2,2,2,2,2,2,2,0021: 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,5,2,0041: 2,2,2,2,6,2,2,6,2,2,2,2,2,2,2,2,2,2,2,2,0061: 4,2,4,4,4,4,6,2,4,6,2,2,2,2,2,4,4,2,4,2,0081: 2,4,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,0101: 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,5,5,5,0121: 5,5,5,5,5,2,5,5,5,5,5,5,5,5,5,5,5,2,5,5,0141: 2,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0161: 5,5,5,5,5,5,5,2,5,5,2,5,5,5,5,5,5,5,5,5,0181: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,2,0201: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,2,5,0221: 5,5,5,5,5,5,5,5,5,5,5,5,5,2,5,5,5,5,5,5,0241: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0261: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0281: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,2,2,2,2,0301: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0321: 5,5,5,5,5,5,5,5,5,2,5,5,5,5,5,2,5,5,2,2,0341: 5,6,5,5,6,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0361: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0381: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0401: 5,5,5,5,5,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,0421: 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,5,5,5,5,5,0441: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0461: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0481: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,2,5,5,5,5,5,0501: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0521: 5,5,5,5,5,2,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0541: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0561: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0581: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0601: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,


Profile Quality Codes

I.D. (20 consecutive profiles)

0621: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,2,0641: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0661: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0681: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0701: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0721: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0741: 5,5,5,5,5,5,5,5,5,5,2,2,5,5,5,5,5,5,5,5,0761: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0781: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0801: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0821: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,2,5,0841: 5,5,5,5,5,5,5,5,5,5,5,5,5,2,5,5,2,2,5,5,0861: 2,5,5,5,5,5,5,5,5,2,5,5,5,5,5,2,2,5,5,5,0881: 5,5,5,5,5,5,5,5,5,5,5,2,5,5,5,5,5,5,5,5,0901: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0921: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0941: 5,5,5,5,5,5,5,5,5,5,5,5,2,5,5,5,5,5,5,5,0961: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,2,2,5,5,5,0981: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,1001: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,1021: 5,5,5,5,5,5,5,5,2,2,5,5,5,5,5,5,5,5,5,5,1041: 2,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,1061: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,1081: 5,5,5,5,5,5,5,5,2,2,5,5,5,5,5,5,5,5,5,5,1101: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,1121: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,1141: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,1161: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,1181: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,1201: 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,1221: 5,5,5,5,5,5,5,5,5,5,5

Table 6. Quality codes for RSVP profiles. The first column in each row gives the profile W.number for the first profile of each group of twenty profiles; the next twenty columns (given ascomma-separated values) indicate the quality code for profile number and the next nineteenprofiles in sequential order (thus, for the first row above, 0001 refers to RSVP profile # 0001,and the following 20 comma-separated values indicate the quality code for RSVP profiles #0001-

0020, respectively. See Table 5 for interpretation of the code values.)

25


BatchNumber

Number ofDrop Filesin Batch

Number ofGoodt

Drop Filesin Batch

FirstGoodt

Drop i.d.in Batch

Time of FirstGoodt Drop

i.d. (yearday)

LastGoodt

Drop i.d.in Batch

Time of LastGoodt Drop

W. (yearday)

0 170 67 8 116.0575 170 120.0822

1 126 122 172 120.4724 296 121.7066

2 113 101 301 122.6347 405 123.6669

3 116 89 436 124.9901 525 126.0531

4 114 113 527 126.6181 639 127.6666

5 111 110 641 128.6175 750 129.6664

6 106 102 753 130.0442 856 131.0825

cross-comparisons

4 2 859 131.8644 860 131.8813

7 115 109 862 132.5396 975 133.7291

8 113 108 978 134.4483 1088 135.5207

9 143 141 1091 136.4865 1231 137.5167

Total 1231 1064 - - - -

Table 7. RSVP batch drop summary.

t 'Good' here indicates that there are, at a minimum, good profiles of temperature and conductivity in the data set.

26


ADCP FileNumber

File Start Time File End Time Number ofEnsembles

Pulse Rep.Rate (x10-2 s)

Number ofSamples per

Ensemble

Number ofBins

PulseLength (m)

[approx]

1 04/25 16:23:00 04/25 16:44:49 22 40 150 60 2

2 04/25 17:05:35 04/25 18:45:35 101 40 140 60 2

3 04/25 19:10:10 04/25 23:58:10 289 40 140 60 2

4 04/26 01:09:22 04/26 17:48:22 1000 40 140 60 2

5 04/26 19:37:01 04/26 23:58:01 262 40 140 60 2

6 04/27 00:44:51 04/27 11:30:51 647 40 140 60 2

7 04/2711:51:00 04/2718:01:00 371 40 140 60 2

8 04/27 18:06:09 04/27 23:58:09 353 40 140 60 2

9 04/28 00:20:01 04/28 12:31:01 732 40 140 60 2

10 04/28 12:53:14 04/28 22:30:14 578 40 140 60 2

11 04/28 12:53:14 04/28 23:57:14 665 40 140 60 2

12 04/29 00:30:13 04/29 01:25:13 56 40 140 60 2

13 04/29 01:50:41 04/29 12:54:41 665 40 140 60 2

14 04/29 13:08:29 04/29 15:12:29 125 40 140 60 2

15 04/29 15:22:35 04/29 23:58:35 517 40 140 60 2

16 04/30 00:37:01 04/30 23:58:01 1402 40 140 60 2

17 05/0100:39:01 0510118:05:01 1047 40 140 60 2

18 05/01 18:30:28 05/0123:58:28 329 40 140 60 2

19 05/02 00:36:15 05/02 01:54:15 79 40 140 60 2

20 05/02 02:12:09 05/02 13:01:59 322 40 300 36 4

21 05/02 14:12:00 05/02 23:57:04 290 40 300 36 4

22 05/03 00:00:46 05/03 00:33:09 17 40 300 36 4

23 05/03 00:53:02 05/03 12:59:48 360 40 300 36 4

24 05/03 13:12:58 05/03 23:56:44 319 40 300 36 4

25 05/04 00:39:56 05/04 12:56:50 365 40 300 36 4

26 05104 13:07:56 05104 23:57:47 322 40 300 36 4

27 05/05 00:31:55 05/05 14:13:50 407 40 300 36 4

28 05/05 14:33:55 05/05 23:56:43 279 40 300 36 4

29 05/06 01:15:57 05/06 12:54:23 346 40 300 36 4

30 05/06 13:05:55 05/06 23:57:47 323 40 300 36 4

31 05/07 00:15:54 05/07 12:49:00 373 40 300 36 4

32 05/07 13:07:55 05/07 23:57:55 651 40 140 72 2

33 05/08 00:25:43 05/08 13:13:43 769 40 140 72 2

34 05/08 13:22:08 05/08 23:58:08 637 40 140 72 2

35 05/09 00:01:50 05/09 23:58:50 1438 40 140 72 2

36 05/10 00:17:35 05/10 23:58:35 1422 40 140 72 2

37 05/1100:16:41 05/11 23:58:41 1423 40 140 72 2

38 05/12 00:21:43 05/12 23:58:43 1418 40 140 72 2

39 05/13 00:13:41 05/13 23:58:41 1426 40 140 72 2

40 05/14 00:10:40 05/14 23:58:40 1429 40 140 72 2

41 05/15 00:08:39 05/15 23:58:39 1431 40 140 72 2

42 05/16 00:52:37 05/16 23:58:37 1387 40 140 72 2

43 05/17 00:00:34 05/17 23:58:34 1439 40 140 72 2

44 05/18 01:37:14 05/18 01:58:14 22 40 140 72 2

45 05/18 03:12:38 05/18 03:55:38 44 40 140 72 2

Table 8. Summary of ADCP settings.

27


Depth(m)

Major AxisLength (mm/s)

Minor AxisLength (mm/s)

Angle ofInclination (de g.)

G(de)

G+(de)

G-(de g)

5.5 54 -3 15.3 145 129.7 160.4

9.3 51 -6 7.8 141.7 133.9 149.6

13 47 -5 6 140.7 134.8 146.7

16.8 51 -2 7 143.6 136.6 150.5

20.5 53 -1 9.6 145.5 135.9 155.1

24.3 55 -1 8.3 143.5. 135.3 151.8

28 60 -3 10.8 142.3 131.6 153.1

31.8 61 -7 11.4 141.4 130 152.8

35.5 59 -8 12.1 140.1 128 152.2

39.3 57 -6 11.8 141.5 129.6 153.3

43 56 -3 11.7 143.4 131.8 155.1

46.8 56 0 12.4 142.8 130.5 155.21

50.5 54 2 13.8 141.6 127.8 155.41

54.3 52 3 13 141.4 128.4 154.4

58 51 4 13.1 140.7 127.7 153.8

61.8 50 5 12.7 139.3 126.6 152

65.5 50 7 12.7 137.1 124.4 149.9

69.3 51 6 11 134.9 123.9 145.9

73 52 6 10.4 132.7 122.3 143

76.8 52 6 11.6 131.2 119.6 142.7

80.5 52 6 12.7 131.3 118.6 144

84.3 51 7 16.1 131.3 115.2 147.5

88 50 7 18.1 130.2 112.2 148.3

91.7 49 8 19.7 127.7 108 147.4

95.5 49 10 20.3 125.1 1104.9 145.4

99.2 49 11 20.6 122.8 1102.3 143.4

103 49 12 20.8 122 1101.2

106.7 49 11 22.6 122.9 1100.3 145.61

110.5 48 11 27.3 127.8- 100.5 155.1

114.2 47 10 33.6 T3 3.9 1100.3 167.41

Table 9. Tidal analysis results for K1 tidal constituent from 5 m to 115 m depth. Angle ofinclination denotes the clockwise rotation of the major axis relative to east. Positive values of theminor axis indicate counterclockwise rotation of the tidal component; negative values indicateclockwise rotation.

28

142.7


Depth(m)




G(de)

G+(de)

G-(de g)

5.5 19 0 5.6 105.5 100 111.1

9.3 20 -4 173.1 280.4 107.3 93.5

13 23 -2 170.7 283 112.3 93.7

16.8 23 -3 2.2 102.31 100.1 104-51

20.5 24 -7 172.4 284.7 112.3 97.1

24.3 26 -6 175.9 286.81 110.9 102.7

28 26 -8 179.7 288.71 108.9 108.4

31.8 26 -8 4 109.91105.9 113.9

35.5 25 -5 5.9 106.6 100.7 112.5

39.3 24 1 7.2 105.7 98.5 112.9

43 22 7 6 101.2 95.3 107.2

46.8 23 7 1.1 93.7 92.7 94.8

50.5 23 5 177.8 273.3 95.5 91.1

54.3 26 4 177.2 274.3 97.2 91.5

58 29 3 178.5 273.4 94.9 91.9

61.8 31 1 1.6 92.2 90.6 93.8

65.5 31 1 4.9 90.3 85.4 95.3

69.3 31 1 7.8 90.8 83 98.6

73 31 0 10.2 91.8 81.6 102

76.8 30 2 12.2 93.4 81.3 105.6

80.5 29 3 14.5 93.2 78.7 107.6

84.3 29 3 14.4 93.5 79.1 107.9

88 29 2 14.6 93.2 78.5 107.8

91.7 31 2 15 93.3 78.3 108.4

95.5 32 2 14.4 94.8 80.4 109.3

99.2 33 1 15.6 97.8 82.1 113.4

103 33 1 17.6 98.9 81.3 116.5

106.7 33 1 20.1 97.2 77.1 117.4

110.5 33 2 25.1 96.3 71.1 121.4

114.2 34 1 27.8 97.4 69.6 125.2

Table 10. Same as Table 9, but for 01 tidal constituent.

29


Depth(m)




G(de)

G+(de)

G-(de g)

5.5 63 32 5 27 22.1 32

9.3 75 22 4.5 27.1 22.6 31.6

13 99 -6 178.1 201.4 23.3 19.4

16.8 118 -23 179.4 207.3 27.9 26.8

20.5 121 -24 4.6 32 27.5 36.6

24.3 111 -14 13.2 37 23.8 50.2

28 95 2 23.6 43.8 20.2 67.4

31.8 85 16 30.4 50 19.6 80.4

35.5 77 24 32.8 53.1 20.3 86

39.3 73 27 33 54.3 21.3 87.4

43 71 27 32.2 54.2 22 86.4

46.8 70 28 29.2 53 23.7 82.2

50.5 69 29 24.5 48.2 23.7 72.7

54.3 68 27 18.8 42.6 23.8 61.4

58 71 25 14.1 37.7 23.6 51.7

61.8 73 23 12.1 36.4 24.3 48.5

65.5 74 21 13.7 36.5 22.8 50.3

69.3 74 21 14.5 37.1 22.6 51.6

73 76 20 15.9 38.4 22.5 54.3

76.8 78 18 18.6 40.6 22 59.2

80.5 79 17 21.3 42.6 21.2 63.9

84.3 80 16 24.2 43.8 19.6 68

88 80 17 25.4 44.7 19.3 70.1

91.7 79 18 27 45.6 18.6 72.6

95.5 78 20 28.2 46.7 18.4 74.9

99.2 76 22 29 47.4 18.3 76.4

103 72 25 30.5 49.1 18.5 79.6

106.7 68 27 32.9 51.4 18.5 84.2

110.5 63 30 38.2 55.9 17.7 94.2

114.2 58 33 46.7 63.7 16.9 110.4

Table 11. Same as Table 9, but for M2 tidal constituent.

30


Depth(m)



Angle ofInclination (de .)

G(de)

G+(de)

G-(de g)

5.5 29 12 56 111.8 55.8 167.8

9.3 36 10 38.9 97.1 58.1 136

13 40 4 35.6 95.4 59.7 131

16.8 28 14 24.9 84.7 59.8 109.7

20.5 36 4 173.9 235.9 61.9 49.8

24.3 44 -7 171.3 232.4 61.2 43.7

28 50 -10 172.5 233.9 61.4 46.4

31.8 46 -5 0.1 60.4 60.3 60.4

35.5 41 1 14.4 74.2 59.8 88.5

39.3 40 3 26.8 84.9 58.1 111.8

43 39 3 31.5 89.2 57.6 120.7

46.8 40 1 32.3 88.3 56 120.6

50.5 41 1 29.9 85.6 55.8 115.5

54.3 42 1 26.7 82.4 55.8 109.1

58 42 0 23.9 78.2 54.3 102.2

61.8 42 1 21.3 74.5 53.2 95.8

65.5 43 0 19.5 70.5 51 90

69.3 43 1 18.1 69.1 51 87.2

73 43 2 17 67.8 50.8 84.7

76.8 43 3 14 67.3 53.3 81.3

80.5 43 4 12.3 67.8 55.5 80.1

84.3 42 5 13.1 70.7 57.6 83.8

88 42 6 15 74 59 89

91.7 42 6 18.8 76.9 58.1 95.7

95.5 40 8 23.4 81.3 57.9 104.7

99.2 36 9 26.8 83.6 56.8 110.4

103 33 12 28.7 85.2 56.5 113.9

106.7 29 14 32 88.4 56.5 120.4

110.5 25 16 33.5 89.4 55.9 122.9

114.2 22 18 39.8 94.4 54.5 134.2

Table 12. Same as Table 9, but for S2 tidal constituent.

31


Name ofTidal

Constituent

Frequency Major Axis or AxisLength(mm/s)

Angle ofInclination

(de g)

G(deg)

G+(deg)

G-(deg)

ZO 0 31 0 47.7 360 312.3 47.7

MSF 0.002822 17 -11 42.2 301.5 259.2 343.7

01 0.038731 20 -4 173.1 280.4 107.3 93.5

K1 0.041781 51 -6 7.8 141.7 133.9 149.6

M2 0.080511 75 22 4.5 27.1 22.6 31.6

S2 0.083333 36 10 38.9 97.1 58.1 136

M3 0.120767 6 -4 142.8 162.7 19.8 305.5

SK3 0./25/14 5 2 14.4 189.8 175.4 204.2

M4 0.161023 10 -7 126.1 283.4 157.3 49.5

MS4 0.163845 5 -3 88.2 42.2 314 130.4

S4 0.166667 5 -3 29.6 114.2 84.6 143.8

2MK5 0.202804 3 2 141.4 285.5 144.2 66.9

2SK5 0.208447 3 -1 116.8 172.7 55.9 289.6

M6 0.241534 2 -1 139.4 233.4 94.1 12.8

2MS6 0.244356 2 1 5.7 26.1 20.5 31.8

2SM6 0.247178 3 0 160.5 284.5 124 85.1

3MK7 0.283315 3 -1 168.7 311.4 142.7 120.2

M8 0.322046 3 0 131.9 302.8 170.9 74.7

Table 13. Entire 18-component tidal analysis for 9.3 m depth bin.

32

(cph) Length


Name ofTidal

Constituent

Frequency Major Axis Minor Axis Angle ofInclination

(de g)

G(deg)

G+(deg)

G-(deg)

ZO 0 37 0 44 180 136 224

MSF 0.002822 22 -11 12.5 359.7 347.2 12.2

01 0.038731 26 -8 179.7 288.7 108.9 108.4

Ki 0.041781 60 -3 10.8 142.3 131.6 153.1

M2 0.080511 95 2 23.6 43.8 20.2 67.4

S2 0.083333 50 -10 172.5 233.9 61.4 46.4

M3 0.120767 7 -5 138.2 359.7 221.5 137.9

SK3 0./25/14 13 -6 3.9 221.6 217.6 225.5

M4 0.161023 11 -4 109 65.9 317 174.9

MS4 0.163845 7 -5 83 125.9 43' 208.9

S4 0.166667 3 -1 166.7 97.6 290.9 264.3

2MK5 0.202804 7 -2 146.4 120.1 333.7 266.5

2SK5 0.208447 2 0 33.2 181.4 148.2 214.7

M6 0.241534 4 -2 123.4 233.4 110 356.8

2MS6 0.244356 2 -1 152.4 247.4 95 39.8

2SM6 0.247178 3 0 151.9 354.3 202.4 146.1

3MK7 0.283315 6 -4 129.8 212.4 82.6 342.2

M8 0.322046 2 -1 164.2 120.8 316.5 285

Table 14. Same as Table 13, but for 28.0 m depth bin.

33

(cph) Length Length


Name ofTidal

Constituent

Frequency Major AxisLength(mm/s)

Minor AxisLength(mm/s)

Angle ofInclination

(de g)

G(deg)

G+(deg)

G-(deg)

ZO 0 56 0 36.9 180 143.1 216.9

MSF 0.002822 30 -3 37.9 37.1 359.2 74.9

01 0.038731 23 5 177.8 273.3 95.5 -91.1

K1 0.041781 54 2 13.8 141.6 127.8 155.4

M2 0.080511 69 29 24.5 48.2 23.7 72.7

S2 0.083333 41 1 29.9 85.6 55.8 115.5

M3 0.120767 4 -3 129.6 92 322.3 221.6

SK3 0./25/14 8 -5 146.3 206.9 60.7 353.2

M4 0.161023 8 -6 134.3 119.9 345.6 254.3

MS4 0.163845 10 -6 112.5 194.4 81.9 307

S4 0.166667 2 -1 129.2 9.5 240.4 138.7

2MK5 0.202804 3 -1 119.3 54.8 295.5 174.2

2SK5 0.208447 3 -1 110.5 114 3.5 224.5

M6 0.241534 3 -1 74.5 42.8 328.3 117.4

2MS6 0.244356 5 -3 101.2 87.9 346.7 189.1

2SM6 0.247178 3 -1 120 129.4 9.4 249.4

3MK7 0.283315 1 1 167.2 107.8 300.6 275

M8 0.322046 1 0 166.9 134.6 327.7 301.5


34

(cph)


Name ofTidal

Constituent

Frequency(cph)

Major AxisLength(mm/s)

Minor AxisLength(mm/s)

Angle ofInclination

(de&)

G(deg)

G+(deg)

G-(deg)

ZO 0 36 0 34.9 180 145.1 214.9

MSF 0.002822 13 -5 55.7 42.5 346.8 98.1

01 0.038731 33 1 15.6 97.8 82.1 113.4

KI 0.041781 49 11 20.6 122.8 102.3 143.4

M2 0.080511 76 22 29 47.4 18.3 76.4

S2 0.083333 36 9 26.8 83.6 56.8 110.4

M3 0.120767 4 -3 155.3 230.2 74.9 25.5

SK3 0./25/14 4 1 69.7 161.8 92.1 231.5

M4 0.161023 4 -3 73.9 358.6 284.7 72.4

MS4 0.163845 6 -3 120.6 40.6 279.9 161.2

S4 0.166667 3 0 39.6 58.3 18.7 97.9

2MK5 0.202804 4 -2 33.4 31.8 358.4 65.2

2SK5 0.208447 1 0 77.3 86.6 9.3 164

M6 0.241534 2 0 36.8 317 280.2 353.9

2MS6 0.244356 3 -2 95.9 333.7 237.8 69.6

2SM6 0.247178 2 1 3.9 242.9 239 246.7

3MK7 0.283315 2 -1 103.2 144.4 41.2 247.6

M8 0.322046 1 0 86.3 239.5 153.2 325.8


35


k/ks G2(k/S)1.78 x

10"3

8.4211 x 10-23.16x10" 1.018x10-15.62 x 10"3 1.236 x 10"

1.00x10 1.497x10"1.78x10" 1.811x10"3.16x 10 2.196x 105.62 x 10-2 2.677 x 10"1.00 x

10"1

3.664 x 10"'1.78 x 10-1 3.463 x 103.16x10 2.185x10"5.01x10 -8.400 x 1

7.92 x 10-1 2.136 x 10"1.00 9.80 x 101.26 3.96 x 10"1.58 1.61 X 10-3


Table A-1. Discrete values of the universal shape function for the shear spectrum (after Oakey[ 1982] and Nasmyth [ 19701). The data have been re-written from Table Al in Oakey [ 1982] in termsof wavenumber instead of cyclic wavenumber.

36

ViscountMelville Sound

I ,--1 S

VictoriaIs.

NORTHIWEST TERRITORIES

FoxeBasin

Figure 1.1a: Map of the Canadian Arctic Archipelago. The Res95 experimental site is inBarrow Strait, in the center of the archipelago. A finer-scale view of the regionimmediately surrounding the camp is shown in Figure 1.1b (following page).

750

740

IntrepidPassage

Lowther

+00' (o' Island(

RUSSELLISLAND

Garrett I.

PEELSOUND

CORNWALLISISLAND

GriffithIsland

BARROW STRAIT

SOMERSETISLAND

Figure 1.1b: Map of the central Barrow Strait region, showing more detail in the areaindicated by a box in Figure 1.1a. Bathymetric contours in (b) are given in meters. TheRes95 camp is located around 74° 27.398' N, 97° 15.788' W, southeast of Lowther Island.

LOWTHER ISLANDICE CAMP

April, May 1995

Surveyed byL. Guy Millette

#3 Transducer30 North of

Goudeau Pt.

Gourdeau Point

S4 55° co

aepui 103111

0 50

meters

Gourdeau Point

Main Science Hutdepth 152 m

o McPhee FrameLiving tent 13k

camp benchmark

(c) Camp Position:Reference

74°27.381' N97°15.772' W

WGS 84

Biology Camp

McGill ADCPo

depth 158 m

Gourdeau Point

sducet A,(., ;%U PV`-"#3TCa

W L.P. mooring

GQ ac`sMarsden ADCP 280

A saesP Jce?l

depth 158 m Ma

11Z

S4

depth 151 m

S4 orientation

Gourdeau Point (0°)

Figure 1.2: Locations of primary instrumented sites at the Res95 camp.

WAS

140115 120 125 130 135

Resolute Data Summary

RSVP

1111111 11/11/1111ADCP

MOORING

Year Day

Figure 1.3: Time lines of good, calibrated data for each of the instrument packagesdiscussed in this report.

/3/N

RSVP/CTD/Bottles Main

2 0 043

-10 A D C P

Scribe Mark

GourdeauPt.

ScienceHut

Figure 1.4: A schematic showing the location of the two hydroholes inside the mainscience tent and the orientation of the transducers.

Figure 1.5: A portion of a synthetic aperture radar (SAR) image, obtained by the Elks-1 satelliteon May 2, 1995 (year day 122) showing the study site. The image (which has been rotated so thatthe top of the page is in the northward direction) consists of 8 bit pixels, corresponding touncalibrated backscattered intensity. Pixel resolution is roughly 100 in by 100 in. Lowther Islandis clearly identifiable. The ice camp was located on land-fast first-year ice; the medium graymasses along the coast of Lowther Island and to the northeast of the study site represent land-fast, multi-year ice (SAR image data provided by G. Reynolds, Alaska SAR Facility, Universityof Alaska Fairbanks [data take i.d. EI/S/19860.01; image W. 183735200]).

-1.4

-1.45

-1.5

-1.55

-1.6

-1.65

-1.7

-1.75

-1.85

-1.3

-1.35

Res95 Moored Thermistor Time Series - Selected Depths

11 120 125 130 135 140Year Day

Figure 2.1: Moored temperature time series from selected depths (125, 75, 25, 7 m).Sampling interval is one minute.

125m

75m

25m

7m

LI

—I

32.4

32.2

32

31.8Cl)a

31.4

31.2

Res95 Moored CTD Salinity Time Series

31L115 120 125 130 135 140

Year Day

Figure 2.2: Moored salinity time series from the three CTDs (30, 15, 7 m). Samplinginterval is one minute.

8

10

12

1

T (°C)-1.40

-1.45

-1.50

-1.55

-1.60

-1.65

-1.70

-1.71

-1.72

-1.73

=1.74

-1.75

-1.76125 130 135

Day-of-year (UTC: 1995)

Figure 2.3: Mooring temperature as a function of depth and time.

140

icy-3 102

120 125 130 135

yI I

I

102

MDR-106 (50m) - Temperature Data Comparisons

a)

TO -1.6a)CLEmF-

-1.8L115

100

fl.U0105

00

10 10

10-2 10-1

10-2 10-1 100 101Frequency (cph)

Figure 2.4: Temperature data from MDR 106 (50 m depth). Top panel shows the entiretemperature time series. Middle panel displays the log-log plots of the power spectraldensity, PSD, of the raw time series (blue), the low-pass-filtered time series (green), andthe low-pass-filtered, subsampled time series (red). Bottom panel shows same data as themiddle panel, plotted here as the frequency times the PSD on a log-linear scale. Filtercutoff period is 1 h; raw sampling interval is 1 min.; time interval for subsampled data is30 min. See text for more details on the filtering, subsampling, and spectral estimation.

Julian Da

100

10-10

00 1

Year Day

100 101 102

10-3 10 ' 10

32.4

-

U)0-

10-2

SBE-40 (30m) - Salinity Data Comparisons

125

10'

102 10-1

100f (cph)

Figure 2.5: Salinity data from SBE 40 (30 in depth). Top panel shows the entire salinitytime series. Middle panel displays the log-log plots of the power spectral density, PSD,of the raw time series (blue), the low-pass-filtered time series (green), and the low-pass-filtered, subsampled time series (red). Bottom panel shows same data as the middlepanel, plotted here as the frequency times the PSD on a log-linear scale. Filter cutoffperiod is 1 h; raw sampling interval is 1 min.; time interval for subsampled data is 30min. See text for more details on the filtering, subsampling, and spectral estimation.

raw (no filter)

filtered

filtered/decimated

Res95: McGill Water Level and Bottom Water Temperature

120 125 130Year Day

135 140

Figure 2.6: Time series of measurements from the McGill sensor mounted on theseabed: (a) water level (height of water above the sensor); (b) bottom water temperature.

Res95 RSVP Drop 180: Fall Speed Profile

-20

-40

E

-60am0

-80

-100

-120`-1.5 -1.4 -1.3 -1.2 -1.1 -1 -0.9 -0.8 -0.7 -0.6 -0.5

Speed (m/s)

Figure 3.1: Fall speed profile for drop number 180. The profiler is seen to quicklyaccelerate to its terminal velocity of about -1.25 ms -1 (a negative value here impliesdescent) and to continue to fall at about that speed throughout the water column.' Theprofiler is quickly arrested at the end of the profile near 110 in depth.

Mean Temperature Profile - Batch #20

10

20

60

70

80-1.75 -1.74 -1.73 -1.72 -1.71 -1.7 -1.69 -1.68 -1.67 -1.66 -1.65

Temperature (C)

Figure 3.2: Sample comparison of time-averaged temperature profiles from the mooring (opencircles), the uncorrected RSVP data (dashed line) and the corrected RSVP data (solid line),evaluated over the entire period of batch 2 (day 122.6347 to 123.6669). The RSVP averages arederived from the 256-point `block' averages and have been bin-averaged in I m depth bins.

Mean Conductivity Profile - Batch #2

25 25.4 25.6 25.8Conductivity (mS/cm)

26 26.2

Figure 3.3: Sample comparison of time-averaged conductivity data from the mooring (open circles),the uncorrected RSVP data (dashed line) and the corrected RSVP data (solid line), evaluated overthe entire period of batch 2 (day 122.6347 to 123.6669). The RSVP averages are derived from the256-point `block' averages and have been bin-averaged in 1 m bins.

Temperature Intercomparisons, Year Day 131

-1.7 -1.6 -1.55Temperature (C)

-1.5 -1.45 -1.4

Figure 3.4a: Comparison of temperature data during cross-calibration run on May 11 (year day131). The dotted line is from the McGill CTD at 2014 h; the solid line is from the RSVP profiler at2044 h; the dashed line is from the RSVP at 2109; open circles identify the minimum.and maximumvalues observed at the mooring between 2014 h and 2109 h.

Salinity Intercomparisons, Year Day 131

31.6 31.8 32 32.2Salinity (psu)

32.4 32.6 32.8

Figure 3.4b: Comparison of salinity data during cross-calibration run on May 11 (year day 131).The dotted line is from the McGill CTD at 2014 h; the solid line is from the RSVP profiler at 2044h; the dashed line is from the RSVP at 2109; open circles identify the minimum and maximumvalues observed at the mooring between 2014 h and 2109 h. The results suggest there is a nearlyuniform offset between the McGill salinity and the RSVP mooring salinity, corresponding to roughly0.04 to 0.09 psu. No attempt has been made at this stage to correct for this difference.

Depth Range vs. Drop Number, Batch #00

E -50

a0-100

-150

-150

20 40 60 80 100 120


140

180 200 220 240 260 280

160

Figure 3.5a: Depth range of valid RSVP data vs. RSVP drop number for Batches 0 and 1.


E -50

.rCLa)

a-100

-150'---' I I I I I I I I I I

300 310 320 330 340 350 360 370 380 390 400


E -50

-150420 440 460 480 500 520

Figure 3.5b: Depth range of valid RSVP data vs. RSVP drop number for Batches 2 and 3.

Depth` Range vs. Drop Number, Batch #4

TI

-1501 f - I I I I I 1 I I I 1

530 540 550 560 570 580 590 600 610 620 630


E -50

0a)

a-100

-150 I I I 1 I i I 1 I I 1

650 660 670 680 690 700 710 720 730 740 750

Figure 3.5c: Depth range of valid RSVP data vs. RSVP drop number for Batches 4 and 5.


E -50

-150760 770 780 790 800 810 820 830 840 850


E -50

-150" 1

860 880 900 920 940 960

Figure 3.5d: Depth range of valid RSVP data vs. RSVP drop number for Batches 6 and 7.

0

'. lDepth Range vs. Drop Number, Batch #8

0

E -50

tQ.a)c -100

-150980 990 1000 1010 1020 1030 1040 1050 1060 1070 1080


E -50

CLa)

o -100

-1501100 1120 1140 1160 1180 1200 1220

Figure 3.5e: Depth range of valid RSVP data vs. RSVP drop number for Batches 8 and 9.

Res95 RSVP Drop 653: Shear Time Series and Spectral Examples

2

U10 20 30 40

Tim50 (s)60 70 80 90 100

e

100

102

E9_10-4

106

100101

102kz(m-1)

103

Figure 3.6: Shear time series and frequency spectra for RSVP Drop 653. (a) Time seriesof shear from shear channel S 1, with times plotted relative to the beginning of datacollection for that profile. Two short, 256-point (1 second) data segments are selected,representing high and low regions of shear variance (labeled A and B, respectively).Drop speed was about 1.15 ms-' and very stable over most of the profile; A correspondsto about 32 m and B to 87 m depth. (b) Wavenumber power spectra for time series A(thick line) and B (thin line), plotted on a log-log scale as kZ cpM (kk) vs. kZ. No spectralaveraging is performed here; note that this is not an energy-preserving plot, but doesallow visualization over a very broad dynamic range. Dashed lines show theoreticalNasmyth spectra for different orders of magnitude of the dissipation rate, ranging from E= 10-9 to 10-5 m2s-3. At wavelengths greater than about 320 m-1 (denoted by a vertical line;f - 64 Hz), the spectra drop off sharply due to the frequency characteristics of the shearprobe and data collection scheme. In the low dissipation measurements, much of theenergy greater than 80 m-1 is probably due to electronic noise and profiler motion andvibrations.

Res95 RSVP Drop 1184: Shear Time Series and Spectral Examples

1 I I I

0 10 20 30 4050

60(s)Time

100 101 102k,(m-')

70 80 90 100

103

Figure 3.7: Similar to Figure 3.6, but for RSVP Drop 1184; data segments A and B correspond to10 m and 93 m depth, respectively; drop speed was steady at about 1.20 ms-1.

i

--r ------------- T120.7 120.9 121.1 121.3

Year Day

Figure 3.8: Stack plot summary of RSVP profi e data for batch(from top to bottom), temperature (T, in °C), sal nity (S, in psu),in cycles/hour), and dissipation rate (as logio[e], with a in mesa)

r

" 4-

Res95 RSVP Batch 1 Summary

0-1.5

E -40 0N -80

F-

-1.7-120

120.5 120.7 120.9 121.1 121.3 121.5 121.70 33

-- -40E 32 OLN -80 (/)

-120 31

120.5 120.7 120.9 121.1 121.3 121.5 121.70 20

- -40E Q

10

N -80 z

-120 0

120.5 120.7 120.9 121.1 121.3 121.5 121.70 -6

-40E

N

0rn0-80 -8

-120120.5 121.5 121.7

1 1. Panels representbuoyancy frequency (N,

_TiL 1;:-ThStJ*iluiirnr--J Res95 RSVP Batch 2 Summary

0

-40-1.5

E1 6N -80

- .

-1.7-120

122.7 122.9 123.1 123.3 123.50 33

-, -40 ME 32 Q-N -80 U)

-120 31

122.7 122.9 123.1 123.3 123.50 20

-, -40E

10N -80 z

-120 0122.7 122.9 123.1 123.3 123.5

0 -6

-40 w

E O_

0)N -80 0-8

-120

122.7 122.9 123.1 123.3 123.5Year Day


9z t8'9l

521931

931

931


0

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E -1.6U

N -80 ~-1.7

-120

125.2 125.4 125.6 125.80 33

-, -40 ME

N32 a-80 Cl)

-120 31

125.4 125.6 125.80 20

-- -40E

N10

-80 z

-120 0125.2 125.4 125.6

0 -6

-40E O

Nrn0-80 -8

-120125 125.2 125.4 125.6

Year Day


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-1.0F--80

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126.7 126.9 127.1 127.30 33

-40E

32N -80 U)

-120 31126.7 126.9 127.1 127.3 127.5

0 20

-, -40E

10N -80 Z

-120 0126.7 126.9 127.1 127.3 127.5

0 -6

-40E 0

0)N -80 0-8

-120126.7 126.9 127.1 127.3 127.5

Year Day


PT


0

-1.5- -40

N -80-1.7

-120128.7 128.9 129.1 129.3 129.5

0 33

-40E un32 aN -80 U)

-120 31

128.7 128.9 129.1 129.3 129.50 20

-, -40E

10o

N -80 z

-120 0

128.7 128.9 129.1 129.3 129.50 -6

-- -40 wE O

0)N -80 0-8

-120128.7 128.9 129.1 129.3 129.5

Year Day


N

9 ,06 G


0

-1 5E -40 .

N -1 6-80 .

-1 7-120 .

130.1 130.3 130.7 130.90

33

-40

32 0.N -80

U)

-12031

130.1 130.30

20

-400.

10"' -80 Z

-120 0130.1 130.3

0 -6-40 w

0CIE-80 -8 0

120130.1 130.3 130.5

Year Day130.7 130.9


9'eC l

££l

N

B

££L


0

-1.5-40 U

-1.6-80

-1.7120

132.6 132.8 133.2 133.4 133.60 33

-- -40E

32N -80 U)

-120 31

132.6 132.8 133.2 133.4 133.60 20

- -40E

10Q

N -80 z

-120 0132.6 132.8 133.2 133.4 133.6

0 -6

-40E 0

rnN -80 -8 0

-120

132.6 132.8 133 133.2Year Day

133.4


(w)z

(w)z


0

-- -40E

N -80

-1.5

-1.6

-1.7-120

134.7 134.9 135.10 33

-40

32Cl)

-80

120 31134.5 134.7 134.9 135.1

0 20

-40CL

10-80 z120 0

134.5 134.7 134.9 135.1 135.3 135.50 -6

w-40E 06N -80 0-8

-120134.5 134.7 134.9

Year Day135.1 135.3 135.5


________

-!_____________________


0

-40E

N -80

-1.5

-1.6

-1.7-120

136.5 136.7 136.9 137.1 137.3 137.50 33

-40E 32 Q-N -80

-120 31

136.7 136.9 137.1 137.3 137.50 20

-40 0E 10 yN -80 z

-120 0

136.9 137.1 137.3 137.50 -6

-40 OE CM

0N -80 -8

-120136.5 136.7 136.9 137.1 137.3 137.5

Year Day


-

-40

-80

Averaged Speed of Sound Profile from All Valid RSVP Profiles0

-20

E

-60aN0

-100

-11436 1437 1438 1439 1440 1441 1442

Speed of Sound (m/s)

Figure 4.1: Average sound speed profile (solid line), as determined from the RSVP data.The dashed lines represent plus or minus one standard deviation.

120

120

125 130

130

135 140

140

120 135 140

Res95: ADCP-Raw Eastward Velocity Component, vX50

x>

-50115

50

x>

-50'115

50

125 135

-50'115 125 130

Year Day

Figure 4.2: Time series of raw, ADCP-derived measurements of eastward (v,,) velocityat specified depths: (a) 9.3 m; (b) 50.5 m; (c) 99.2 m. The reduction in high-frequencyvariability between day 122 and day 127 is primarily a consequence of a longer pulsewidth and an increased number of samples per ensemble (see Table 8).

50

50

Res95: ADCP Raw Northward Velocity Component, vy

-50115

50

0

-50 L--115

(a)

(b)

(c)

120 125 130 135

120 125 130 135

140

140

-50'115 120 125 130 135 140

Year Day

Figure 4.3: Same as for Figure 4.2, but for northward (vy) velocity.

1

i

I I -

q

- i4.i -Ref'.. Z.' `l

I I

20

-20115

20

-20115

20

CO

EU

N

0

(a)

(b)

(c)

C

Res95: ADCP Raw Vertical Velocity Component, vz

120 125 130 135

120 125 130 135

140

140

-20115 120 125 130 135 140

Year Day

Figure 4.4: Same as for Figure 4.2, but for vertical (vi) velocity.

Res95: ADCP Raw Error Velocity Component, very20

0

-20115

20

0

-20 L-115

20

0

(a)

120 125 130 135 140

(b)

120 125 130 135 140

(c)

-20'115 '120 125 130 135 140

Year Day

Figure 4.5: Same as for Figure 4.2, but for the error velocity (verr).

1

fib)

y-----------------I

ADCP Velocities: Low Frequency and Tidal Reconstruction (9.3 m)20

10

10

-30120 120.5 121 121.5 122 122.5 123 123.5 124 124.5 125

20

10

0E0

-20Low Frequency

- - Tidal Analysis

-30120 120.5 121 121.5 122 122.5 123 123.5 124 124.5 125

Year Day

Figure 4.6: Comparison of low-frequency velocities (solid lines) and reconstructedvelocities (dashed lines) from tidal analysis at 9.3 m depth: (a) eastward component; (b)northward component. Time interval shown for the plotted data is 1 hour; time range islimited to a 5 day section for ease of comparison.

I

(b)

ADCP Velocities: Low Frequency and Tidal Reconstruction (28 m)20

10

-3020120.5 121 121.5 122 122.5 123 123.5 124 124.5 125

20

10

Low Frequency- - Tidal Analysis

-3120120.5 121 121.5 122 122.5 123 123.5 124 124.5 125

Year Day

Figure 4.7: Same as for Figure 4.6, but for 28 m depth.

/ 1

VVI --' V/1

I

ADCP Velocities: Low Frequency and Tidal Reconstruction (50.5 m)20

10

E 00x -10

120.5 121 121.5 122 122.5 123 123.5 124 124.5 125

20

10

CO

E 0U

-10

L F-20

ow requency

- - Tidal Analysis

-3120120.5 121 121.5 122 122.5 123 123.5 124 124.5 125

Year Day


TTZT

(b)

I

4-

ADCP Velocities: Low- Frequency and Tidal Reconstruction (99.2 m)20

10

-3020120.5 121 121.5 122 122.5 123 123.5 124 124.5 125

20

10

Low Frequency- - Tidal Analysis

-3120120.5 121 121.5 122 122.5 123 123.5 124 124.5 125

Year Day


'-00

N6

6

Normalized Cumulative Integration of Nasmyth Shear Spectra

4-0c

0.40CZi

Figure A.1: Cumulative integration of Nasmyth shear spectra, cp,, normalized to the total shearvariance, for several values of dissipation rate, E. Integrations were carried out numerically, based onvalues of G2(k/kc) given by Oakey (1982). For the range of e typically found in the ocean(10-9<F<10-5 m2s-3), most of the spectral energy occurs at wavenumbers between about 12 m-1 and320 m-1 ; for E=10-9-10-8 m2s"3, most of the energy occurs between 12 m-1 and 80 m-1.

rl

1I

7

II

Ii

gt(k 1,k2,c) for fixed k1 and k2

0.8

0.6

C4N

0.4

[k1,k2] = [12m -1,320m

[k1,kz] = [12m -1,80m -1 ]

0.2

0-10

10109 108 107 106 105

10-4

s(m2s-3)

Figure A.2: Estimates of g,, the fraction of the variance in the Nasmyth shear spectrum, captured ina fixed spectral wavenumber band [ki, k2], as a function of dissipation rate, E. Two differentwavenumber bands are shown: [k1, k2] = [12 m'', 80 m'] and [kI, k2] = [12 m', 320 m"'].

1

gt(k-,,k2,E tP ) for fixed k, and k2

.11

' [k,,k2] = [12m '1, 320m -1 ]

0.8

°'0.4

0.2

[k,,k2] = [12m -1, 80m -1 ]

1011 1010 109 108 10' 106 10510-4

£tP (m2 s-3)

Figure A.3: Estimates of g,, the fraction of the variance in the Nasmyth shear spectrum,captured in a fixed spectral wavenumber band [k1, k2], as a function of the partialestimate, E,p. Two different wavenumber bands are shown: [k1, k2] _ [12 m , 80 m-'] and[k1, k2] = [12 m 1, 320 m-1]. A horizontal line denotes the minimum threshold of gt = 0.75required for determining observational estimates of c from integrations of observed shearspectra (see Appendix).

6

N

I

Res95 RSVP Drop #1184: Dissipation Algorithm Comparison

-20

-40

E

0

J

-80

-100

2-16 Hz

- - 2-64 Hzadaptive

-110-10 109 108107 106

Dissipation Rate (m^2/s^3)

Figure A.4: Comparison of energy dissipation profile estimates for RSVP drop number1184 for three algorithms with different high-frequency cutoff values: f2 = 16 Hz (thinsolid line),f2 = 64 Hz (dashed line), and a variable f2 (from the adaptive method; thicksolid line). All three methods use the same low-frequency cutoff, f, = 2 Hz, and makecorrections for energy not included in the spectral range of integration (see Appendix).

0

-40

0

-20 -20

-40

E E

W -60 - -60Q Qm a.0 0

-80 -80

-100 -100

-12010_1°10-8

10-6Dissipation Rate (m^2/s^3)

-120' -I

'

10 20 30 40 50High Frequency Cutoff (Hz)

Figure A.5: (a) Dissipation profile for RSVP drop number 1184, obtained using theadaptive method; (b) associated high frequency cutoff value, f2i used by the method. Theminimum threshold value of f2 = 16 Hz is clearly identified. When the energy levels in theshear spectra are high, the algorithm integrates to higher frequencies (wavenumbers) toget a better estimate of the shear variance.

gc 856 no.163 )ceanic and atmospheric sciences 0l(j

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