Table of Contents

 Page

Background ÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖ.................. 3

Value of the Granite Canyon sampling site ÖÖÖÖÖÖÖÖÖÖÖ................... 3

Project goals ÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖ.................. 3

Installation and maintenance ÖÖÖÖÖÖÖÖÖÖÖÖÖÖ............................. 4

REINAS, Internet accessibility to the CT-probe data ÖÖÖÖ..ÖÖÖ.................. 5

Data processing ÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖ..Ö.................. 5

Preliminary processing (daily temperature) ÖÖÖÖÖÖÖÖÖÖÖ.................. 6

Reduction of "noise" frequencies ÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖ.................. 7

High-frequency systematic noise reduction ÖÖÖÖÖÖÖÖÖÖÖ.................. 7

Fast Fourier transform (fft) filter ÖÖ....ÖÖÖÖÖÖÖÖÖÖÖÖ.................. 10

Low frequency systematic noise reduction from independent measurements Ö....... 10

Comparison of sampling years ÖÖÖÖÖÖÖ...ÖÖÖÖÖÖÖÖ.................. 11

Power spectra ÖÖÖÖÖÖÖÖÖ.........ÖÖÖÖÖÖÖÖÖÖÖ.................. 13

Central California ocean seasons ........................................................... 14

Temperature / salinity relationships ÖÖÖÖÖÖÖÖÖ....ÖÖÖÖ.................. 16

Comparison to other environmental measurements ÖÖÖ....ÖÖÖÖ.................. 17

Conclusions and prospectus ÖÖÖÖÖÖÖÖÖÖÖÖÖ...ÖÖÖ.................. 17

References ÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖ..ÖÖÖÖÖÖ.................. 20

Appendix 1 ÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖ................... 22
Granite Canyon Temperature and Salinity Data 3

Background

Once-a-day measurements from shore

stations are among the few records of low-frequency oceanographic variability. At several

stations along the west coast of the United

States, decades of temperature data have been

collected by once-a-day "bucket" techniques

(SIO, 1998). These are adequate for some

analyses, if highly motivated volunteer observers are available (Reid et al., 1958; Roden,

1963; McGowan et al., 1998). However, it is

difficult to find careful observers that will continue over the decades of measurement needed

to monitor low-frequency ocean changes, e.g.

local manifestations of climate change due to

global warming. Consequently, it is important

that automatically recording instruments be used

in place of observers. In this case, the

observer's role changes from daily operator of

unsophisticated equipment to less frequent operator of sophisticated electronic equipment that

requires careful calibration and monitoring.

This Technical Memorandum is a report of the

ability of conductivity and temperature measuring probes (CT-probes) to operate continuously in sub-littoral (2-5 m below lowest tide)

conditions at Granite Canyon, California.

Value of the Granite Canyon

sampling site

Records of once-a-day temperature

measurements taken 5 to 30 times per month at

the California Department of Fish and Game

(CDF&G) Granite Canyon laboratory begin in

1971. Once-a-day salinity sample collection

was initiated in 1986 (SIO, 1998). When long

records are available, climate-scale changes in

physical processes and resulting biological activity such as fish stock recruitment are more

easily analyzed (Norton, 1987; Norton, 1999).

The Granite Canyon location, 11 km

north of Pt. Sur, is on the unprotected central

California coast. Measurements at this station

are less influenced by local heat and water exchanges that may confound shore station measurements made in harbors and bays (SIO,

1998). Nearly constant wave action and vigorous wind-forced ocean transport at Granite

Canyon (Breaker and Mooers, 1986) reduce the

 influence of local factors. Since there are no

major rivers within 150 km of Granite Canyon,

freshwater runoff would be expected to have

only transitory influence on temperature and

 salinity measurements. Temperature measurements made at Granite Canyon may be representative of areas encompassing more than

4,000 km2 of adjacent ocean (Breaker and

Mooers, 1986; Breaker and Broenkow, 1994;

Traganza et al., 1981).

The ocean record from Granite Canyon

is especially important because both temperature

and salinity measurements by standardized procedures are available. "Bucket" water samples

are obtained and saved in "poly-seal" bottles at

the same time sea temperature is measured.

These water samples are shipped to Scripps Institution of Oceanography where salinity is

measured using salinometers with accuracy

between .01 and .004 psu. Regular data reports for Granite Canyon and other shore stations along the west coast of the United States

are available from Scripps Institution of Oceanography (SIO, 1998).

Project goals

Since about 1992, greater requirements

on and reassignment of CDF&G personnel at

the Granite Canyon Laboratory have resulted in

reduction in frequency of once-a-day "bucket"

measurements. In March 1995 personnel from

the Pacific Fisheries Environmental Laboratory

(PFEL), in cooperation with the Real-Time Environmental Information Network and Analysis

System (REINAS) experiment of University of

California, Santa Cruz (Fernandez et al., 1996)

and the CDF&G installed a Sea Bird Electronics

(SBE)1

 Conductivity Temperature (CT) probe

to obtain high temporal frequency measurements and to gain experience in using these instruments in collecting high-quality time series

data at shore stations.

High-resolution records add dimension

to existing data sets for this site. The effectiveness of the once-a-day "bucket" measurements

in depicting the ocean environment can be assessed and the effects of missing intervals of

daily sampling (mid-1990s to present) can also

1 Use of copyrighted brand names does not represent endorsement by the National Oceanic and

Atmospheric Administration.
4 Granite Canyon Temperature and Salinity Data

be examined for accuracy. High-resolution CT

probe records provide continuous monitoring of

the ocean environment and resolve a more

extensive range of time scales than once-a-day

"bucket" measurements. "Bucket" measurements at Granite Canyon are always made during daylight hours. The CT measurements allow the once-a-day measurements to be compared to measurements made throughout the

daily cycle. Effects of tides and the daily solar

cycle can also be assessed and analyzed as the

higher frequency data become available.

Continuous high-resolution records are

used by oceanographers and meteorologists in

analyzing and predicting marine air-sea interactions such as those leading to the formation of

marine fog (Norton and Schacher, 1980). The

records may also find use in detecting and

monitoring El Niño warming events (Norton et

al., 1985; McGowan et al., 1998).

Electronic measurements allow the data

to be transmitted, automatically processed and

made available over the Internet via the

REINAS network (Fernandez et al., 1996).

Because of the sensitivity of temperature change

at Granite Canyon to regional forcing mechanisms such as wind forced upwelling (Breaker

and Mooers, 1986), real-time access to the data

could be useful in directing pollution prevention

and mitigation activities and possibly in ocean

search and rescue operations.

Installation and maintenance

The CT-probe is installed inside a

0.203 m inside diameter pipe which extends to

the bottom of a 10 by 20 m natural pool. The

pipe is slotted with 5 by 20 cm openings and is

one intake for the CDF&G laboratory sea water

supply. Within pipe installation allows relatively easy access to the instrument and does

not require SCUBA diving to insure secure installation. The sub-littoral pool is open to circulation at north and south ends. When ocean

swell greater than one to two meters breaks

over the westward rock barrier, mixing from

the seaward side is continuous. The pool is 5

to 7 m deep and the installed CT remains more

than 2.4 m below the sea surface (sub littoral).

Bathymetry seaward of the sampling site slopes

steeply from the littoral zone to more than 100

m within 2 - 3 km of shore. Access of ocean

water is not impeded by bays, promontories or

peninsulas. Sea breeze effects are minimized

by the steep aerial topography shoreward of the

site and winds generated by differential diurnal

heating are channeled parallel to the coast.

Changes in wind direction are frequently detected in the sea surface temperature within 12

hours. These temperature changes are similar

to those found at sea in the area of Pt. Sur and

along the central California coast (Breaker and

Mooers, 1986). However, the fixed subsurface temperature data have important differences from surface "bucket" temperatures, as

discussed below. Once-a-day “bucket” measurements are made within 3 - 4 m of the CTprobe location.

Positioning of the CT-probes inside the

pump intake pipe of the CDF&G laboratory sea

water supply system protects the probes from

objects - rocks, kelp, driftwood, carcasses and

other flotsam and jetsam - that may be tossed

about by breaking waves that will occasionally

exceed 6 m height. At the same time, the proximity to this turbulent environment promotes

exchange of water with the open sea. However,

installation at this location precludes attachment

of chemical anti-fouling devices to the CTprobe. As a consequence bio-fouling in the salinity cell leads to loss of its utility after a few

month’s deployment.

Four-lead cable connecting the CT to the

power supply and data decoder (SBE "Opto"

data and power interface box) ascends a cliff 30

m to a terminal box at the REINAS meteorological station, then 65 m to a building maintained by CDF&G. The cable is protected

within a flexible plastic conduit with 0.5 cm

wall thickness. This installation has been in

place since February 1995. Initial problems

with instrument grounding were solved by SBE

and REINAS engineers. Recording of useful

data began on March 31, 1995 with the model

1475 CT-probe. Appendix 1 lists all data files

collected from March 27, 1995 to August 7,

1998.

Conductivity and temperature were

measured with model 1475 and model 1441

SBE instruments. The model 1475 also records

hydrostatic pressure in decibars (herein expressed as water depth in meters) at each measurement cycle. In either case, temperature and

conductivity (converted to salinity with calibra-
Granite Canyon Temperature and Salinity Data 5

tion data) were recorded 30 to 120 times an

hour (0.5 to 2.0 min-1). Data are stored internally by the CT and may also be monitored using SBE-provided software and the "Opto" interface box. Cooperation with the REINAS

group allowed near real-time monitoring of CT

output over an Internet connection.

Periodically (5 to 13 months), the instruments were exchanged and the out-ofservice instrument was returned for factory

calibration. The model 1475 probe was installed for over 8 months before temporary failure of salinity function. The model 1441 probe

was deployed for more than 12 months during

1997 and 1998. However, in the latter case,

significant degradation in salinity measurement

was observed. Calibration and recalibration

procedures are the major maintenance costs of

the installation. Occasionally the deployed

probe was retrieved and the salinity cell cleaned

with medical swabs, Triton X100 detergent and

alcohol. It appears from subsequent analysis

that cleaning can be effective in restoring the

original measuring properties of the salinity

cell, depending on the nature and extent of biofouling.

REINAS, Internet accessibility to the

CT-probe data

REINAS engineers helped with initial

installation of the CT probe at Granite Canyon

and arranged for near real-time Internet display

and access to the CT data (Figure 1). REINAS

is an engineering research and development

program linking several local institutions. The

goal of REINAS is to design, develop and test

an operational prototype network for environmental data acquisition, management, and visualization (Figure 1).

The network gathers data in real-time

from standard oceanographic and meteorological instruments (including the Granite Canyon

CT-probe) plus continuous video and available

satellite images (Fernandez et al., 1996). Demonstrations of REINAS capability in graphical

display may be accessed on the Internet at:

http://csl.cse.ucsc.edu/projects/reinas/demos.html

Linking CT-probe data streams into the

REINAS network allows the CT-probe to be

monitored from any location with Internet

access. The REINAS network provides a prototype of how data from a variety of sources

might be collected, archived and made available

in the future (Fernandez et al., 1996). However, it has not been possible to rely on the

REINAS network as a sole data source because

a limited amount of development programming

has been done for each data collection node.

REINAS conversions of the CT-probe hexadecimal data files are available only for the

model 1475 CT and not for the CT lacking a

pressure sensor (model 1441) during the period

reported herein. In the current configuration the

REINAS system stores data at the data collection node that are also transferred by radio or

hard-wire link to the Computer Science Laboratory at the University of California at Santa

Cruz (Fernandez et al., 1996).

Occasional radio link failure accompanying local power loss and storage disk malfunction has caused CT data to be lost and degradation of the REINAS data set. Fortunately,

PFEL personnel have collected a complete series of data segments from the instruments by

frequent downloading from CT data storage

(Appendix 1). If, in the future, data segments

are lost at a time when the REINAS system is

fully functional, the data file may be obtained

from the REINAS archive.

Graphic displays available through the

REINAS Internet site for three data sensor

channels can be produced on temporal scales

ranging from hours to months. Temperature,

salinity and depth channels may be displayed

together or individually (Figure 1). When the

model 1475 CT-probe is installed it is possible

to check the status of each channel for accuracy

and responsiveness. The addition of the CTprobe to the REINAS systems creates a valuable tool for monitoring the marine environment

on the unprotected coast south of Monterey

Bay.

Data processing

The data are stored internally by the CTprobes. Model 1475 CT, which records scan

number, temperature, salinity and depth, will

store 42810 data cycles and model number

1441 CT, which records scan number, temperature, salinity, will store 65213 data cycles.
6 Granite Canyon Temperature and Salinity Data

Figure 1. Twelve hours of CT-probe data obtained during

an upwelling episode as displayed by the REINAS web

page "Demonstration" option. Upper panel shows recorded

salinity and the lower panel shows sea temperature for the

360 data points available. These data were sent from the

Granite Canyon laboratory by radio link and then put on an

Internet server at the University of California, Santa Cruz

(Fernandez et al., 1996). Noise spiking to lower salinity

shown after 2300 is discussed in the text.

Internally stored data files are periodically downloaded to a portable DOS-based

computer by PFEL and CDF&G personnel.

The data set from each download session is

called a "segment." Segments vary in length

from 3 to 70 days (Appendix 1).

Several factors go into making the segments different from one another. First, sensor

response characteristics changed as deployment

time increased. Second, the mechanical environment influenced the noisiness of some signals, particularly salinity. Third, the electrical

environment varied from segment to segment as

influenced by the 60 cycle/sec (Hz) power

source and possibly radio frequency interference. These differences have been accommodated in developing processing techniques that

can be applied uniformly to the entire data set.

The 41-month (1316 day) series sampled 30 hr-1 are cumbersome data sets within

the available computing environment. The record for a single year may exceed 20 megabytes

when date time data are included in each sample

cycle. For this reason segments and samples of

original data sets may be used in examples and

Figures.

Preliminary processing

(daily temperature)

SBE SEASOFT software was used to

monitor data and present early results. When

downloaded from the CT, the data are in hexadecimal form. One 12-character data word contains information about temperature, conductivity (16 characters to include depth in the

model 1475) and scan number. The scan number is the measurement cycle number starting

with 0000 for the first measurement cycle of the

segment. Time and date information are added

to header files at the beginning of each data

collection sequence and before each 1000 scan

cycles. Inaccuracies in CT time annotations

were found to be less than 1-2 minutes. Header

information is conveniently carried through all

processing done by SEASOFT software.

SEASOFT software adds additional information

to the header as processing proceeds (SBE,

1993).

Hexadecimal files were first converted,

using the SEASOFT DATCNV module, to

ASCII files showing header information, scan

number, temperature, salinity and depth (if

available). Data were averaged into 24 hr intervals, centered on 1200 PST using SEASOFT

BINAVG. SEASOFT BINAVG was also used

to convert files of data sampled at 30 second

intervals to 120 second spacing (see Appendix

1). In general there were few problems in this

method of processing, aside from incrementing

the date discrepancy caused by the leap day in

1996 and an occasional power fluctuation that

caused the instrument to cease recording data
Granite Canyon Temperature and Salinity Data 7

and sometimes commence again. On one occasion, before March 1995, CT memory reached

maximum capacity and recording stopped. In

terms of internal data recorded, the instrument

and SEASOFT software are well suited to preliminary processing of temperature and pressure

when extensive corrections are not needed.

After the SEASOFT conversion from hexadecimal to ASCII representation of temperature,

salinity and depth, the largest part of the data

presented in this report was processed using

MATLAB (MATLAB, 1994).

Reduction of "noise" frequencies.

Noise (signal variance or energy at

frequencies unrelated to the analysis) can be

treated as either quasi-random or systematic.

Quasi-random noise has apparently spurious

positive and negative excursions: data streams

are made more tractable by smoothing and filtering. Systematic noise (one-way spiking) will

be modified but may not be removed by

smoothing and filtering processes used routinely for quasi-random noise reduction. The

noise encountered can be further classified into

low-frequency (less than one hour in the present case) and higher frequency. Three approaches were taken in removing noise from the

raw data series. First, higher frequency systematic noise in salinity data was reduced with a

one way persistence filter (described below).

Second, wide-banded quasi-random noise in

temperature, salinity and pressure was reduced

with a low-pass fast Fourier transform (fft) filter (cut off = 1 hr). Third, after data decimation

from 30 to two samples per hour, low frequency systematic noise in salinity was reduced

by comparison to once-a-day bucket sampling.

Figures 2, 3 and 4 show before (upper) and after filtering (lower panels) for an April 1995

series.

High-frequency systematic noise

reduction

Temperature and salinity data were frequently characterized by single datum one-way

transients of more than 10 times the expected

standard deviation. If these spurious data points

are not removed, systematic offsets will be introduced into accepted smoothed series.

Figure 2. Processing of CT-probe temperature (upper panel) involved fast Fourier transform smoothing (see text) and

decimation from 30 to 2 samples per hour. The upper panel shows observed 30 samples per hour data and the lower

panel shows smoothed and decimated temperature data for April 1995. Similarity of traces suggest little need for additional processing.
8 Granite Canyon Temperature and Salinity Data

Figure 3. CT-probe salinity for April 1995. Systematic noise intervals occur near the 2nd, 8th and 18th of the month

(upper panel). The lower panel shows the data after "step" filter, fft smoothing, decimation and low- frequency adjustment using bucket measurements. Note that the downward spiking noise is removed by filtering and the entire curve is

displaced upward by the low frequency drift correction. The flat area during April 7th is a period where salinity values

lower than 32.2 were adjusted to 32.2. See text for additional details.

Figure 4. Processing steps converting observed (upper) to corrected (lower) pressure (dbar or depth in meters) were fft

filtering and decimation. Sea swell is shown by a thickening of the line in the upper panel. Note that the line thickening in this figure corresponds to downward spiking in Figure 3, suggesting a connection between swell and noise in

the salinity measurements.
Granite Canyon Temperature and Salinity Data 9

These transients, lasting one to 10 times the two

minute sampling rate, were most frequent in the

salinity channel where they were toward lower

salinity (Figures 1 and 3). Similar, but less frequent noise in the temperature channel was effectively eliminated by an fft filter (Figure 2). 

When high-frequency oscillations due to

sea swell increase in the pressure series, there is

corresponding increase in downward spiking in

the salinity channel (Figures 3 and 4). From

this and on site observations, it is reasonable to

conclude that one-way salinity spiking is caused

by bubbles being formed and forced down to

the level of the salinity sensor by breaking

waves. Bubbles within the conductivity cell reduce conductivity (and calculated salinity) of the

contained sea water volume (SBE, 1993).

 A multi-pass “step” or persistence filter

was developed to reduce systematic noise in the

salinity data (spiking to lower values). This

filter is based on the assumption that the coherent maximum values, shown in the upper panel

of Figure 3, most accurately reflect salinity

changes in the sub-littoral pool. The filter

works from the earlier to later salinity values

(S(1), S(2), .....S(n)....). Each sample, S(n),

is compared to the values that precede and follow it. The temporal range of comparison and

or replacement is the interval T. If the test

value, Vt, is less than the test values derived

from the data, then the mean or max of

...... S(n-2), S(n-1), S(n), S(n+1), S(n+2) ......

for interval, T, replaces the data value tested,

S(n). The T and Vt values were adjusted empirically to permit minimum degradation of

sample-to-sample variability in the 1995-1998

record. Comparison of upper and lower panels

in Figure 3 shows that when the persistence

filter procedure is combined with outlier removal and fft filtering, downward (and upward) spiking is significantly reduced. The five

discrete test and replacement processes used are

as described below. Each process

was designed to meet specific noise reduction

and down-stream processing requirements.

I. Salinity values exceeding 34 psu were replaced with the mean value of 140 samples

equally spaced around the test value (T = 280

min). The wide replacement range was used to

avoid data values (S(n)) characteristic of spiking to lower salinity. Data values above 34 psu

were rare (<0.01%) and by coherence considerations were outliers in the CT data. The origin of high-frequency spiking to higher salinity

is unknown. After process I two data sets

were used in further processing: the series

“sal”, which is progressively modified through

the next steps, and “rsal”, which is the “raw” or

unprocessed data set. Where possible, apparently bad values in “sal” were replaced with

values derived from “rsal.” These replacements

counter the tendency for progressively aliasing

the “sal” series through successive manipulations.

II. This process tests whether consecutive values differ by more than 0.2 psu (Vt). If (sal(n)

- sal(n+1)) is more than Vt, then sal(n+1) is

made equal to the maximum of “rsal” from n-3

to n+14 (T = 9 min.). This process removes

most of the spiking to lower salinity (Figure 3).

The process will not track precipitous value-tovalue declines and increases unless adjusted to

reach forward (n+14) for the maximum values

of the “rsal” data series. The forward reach is

minimized empirically. Vt might be increased

to minimize the span of T, but this would leave

larger negative offsets in “sal.” In the worst

case, there may be a 30-minute forward shift of

signal segments, half the decimated data’s Nyquist frequency.

III. This step flags outliers with a constant

value. Records from once-a-day “bucket”

measurements obtained during 1986 - 1997

show that salinity at this site is seldom less than

32.5 psu. To allow for exceptional salinity values, all values less than 32.2 psu were made

equal to 32.2 psu.

An example of step III processing is

shown for data from 7 - 8 April, 1995 (Figure

3). This process was added to flag values reasonably assumed to be incorrect and to keep

persistent out-of range values (< 32.2 psu)

from interfering with processing steps that depend on averaged “sal” values.

IV. This step modifies the “sal” series with

three passes that detect steps in consecutive

samples that increase “sal” more than 0.1

psu (Vt). If (sal (n+1) - sal(n)) is more than
10 Granite Canyon Temperature and Salinity Data

Vt, then “sal” is replaced with the mean of 30

consecutive values distributed around sample

number (n).

Process I was used for multi-point outlier groups. Step IV reduced the influence of

one, two and three consecutive excursions to

non coherently higher salinity, which represent

less than 0.01% of the data set. If these positive excursions are not removed, they will be

shifted to lower frequencies and by the maximizing steps that follow.

V. The final process aims at finer scale adjustment of values that are more than 0.03 psu (Vt)

below the local mean. Here the mean of 7

points about sample n is compared to a value

sal(n+1). If the value tested is more than Vt

lower than the mean, it is given the maximum

value of consecutive sample numbers, n, n+1,

n+2 and n+3, of “rsal.” This process corrects

some of the offset left by the relatively large

value of Vt needed in process II (0.2 psu). A

smaller Vt is needed in this step because the

“sal” series has less noise after the preceding

processes. Other filtering steps and sequences

of steps may be as effective in reclaiming the

salinity data as the ones discussed above.

Fast Fourier transform (fft) filter

An fft low-pass seventh-order Butterworth filter was developed and implemented in

MATLAB (MATLAB, 1994). Allowable band

pass attenuation was 3 decibels for frequencies

lower than 0.333 hr-1. After filtering in the

forward direction the filter was run through the

once-filtered data in the reverse direction to

produce zero-phase distortion. Forward-back

filtering minimizes start-up and ending transients. These filtering processes remove quasirandom high and low spiking from each channel [e.g. swell signatures from the depth (pressure) channel]. This fft filter was used for all

three channels (Figures 2, 3 and 4).

Tests made throughout the three-year

sampling period and comparison of pre- and

post- deployment factory calibration of the sensors indicate that the temperature and pressure

sensors are accurate to within 0.01 °C and 0.01

m, respectively. Temperature and depth data

were assumed to be accurate and received only

fft filtering. The complete decimated temperature record is shown in Figure 5 along with the

available bucket observations and an historical

mean derived from "bucket" measurements.

Low-frequency systematic noise reduction in salinity data from independent

“bucket” measurements

The CT-probe salinity data stream consistently drifted to lower values relative to

“bucket” measurements as a consequence of

the settling of algae and invertebrate larvae from

the ambient plankton. As organisms settle and

grow, the effective volume of the conductivity

cell is reduced and the new cell geometry will

result in recording of lower salinity because of

decreased conductivity in the vicinity of the

measuring electrodes (SBE, 1993). Stanton

(Department of Oceanography, Naval Postgraduate School, 833 Dyer Rd, Monterey, CA)

has observed that both the slope and intercept of

the calibration curve will change as biological

colonization occurs in the conductivity cell and

in the vicinity of the electrodes. Therefore, correction is needed to insure proper interpretation

of CT salinity records.

Herein, we use a correction to salinity

based on the composite drift observed between

electrode cleaning or refurbishing to recover

83% of the decimated salinity values. It is conservative to start with a linear approach and use

the knowledge gained in this study to work toward more effective reclamation of CT-probe

salinity series.

There were seven instances when the

instrument was replaced with a refurbished CT

or the conductivity cell of an in-place CT was

cleaned. The composite slope of daily difference between CT measured salinity and

“bucket” derived salinity (delta s) is shown in

Figure 6. The day’s “bucket” measurements

were taken to be between 0900 and 1300 hours

and the day’s CT measurement was a mean of

the measurements made during this interval. 

In correcting the decimated salinity,

each series was displaced (offset) by the intercept value of the individual linear fits to observed drift. Additional correction is added according to the composite linear fit shown in

Figure 6. Calculations leading to Figure 6

measure time in days, but the slope was used to

interpolate data corrections to 30 minute increments. Where concurrent “bucket” salinity cor-
Granite Canyon Temperature and Salinity Data 11

rections where not available, the average intercept was used with the composite linear fit

(Figure 6). Those parts of the corrected salinity

record that consistently diverged more than 0.3

psu from the “bucket” salinity were not “accepted” for further consideration in this report.

Note that fitting the composite of several

drift sequences with any curve will have difficulties because individual drift sequences have

different character. The fit is similar for first-

(L = linear), second- (P2), and third-degree

(P3) polynomials. Examination of Figure 6

shows that in the first 100 days the fit is balanced by different time dependent responses.

For instance, the drift response for cases shown

by triangles and circles will pull the fit down

and the response shown by cases repre-sented

by squares and asterisks pull the fit up. Consequently, none of the three fits provide an excellent match to observations in the 40 to 60 day

range. Increasing dispersion (scatter) of points

after the 80th day emphasizes the value of more

frequent and more thorough salinity cell cleaning (Figure 6). There may also be seasonal and

temperature related drift dependence that will

become more evident as drift information is accumulated from the CT-probes deployed at the

Granite Canyon site.

Comparison o f sampling years

Comparison of the mean annual thermal

cycle from historical "bucket" measurements,

available "bucket" measurements and CT probe

measurements allows several general observations. Regularity in the annual cycle is shown

in the CT, and concurrent "bucket" sampling

(Figure 5).

Figure 5. Temperature time series comparison of "bucket" (circles) and decimated CT series (fine line) for the period from

March 1995 through August 1998. Temperature is in °C. The simple linear regression between the two sets of values

(converted to 24 hr averages) gives an r of 0.89 to 0.95 depending on time period (r = 0.92 overall). "Bucket" measurements were made on about 40% of the days. Factory recalibration of CT-probes shows that the instruments maintain calibration within 0.01 °C during deployment. The heavy broken line gives a smoothed climatology based on monthly mean

"bucket" measurements for 1973 - 1994 (SIO, 1998).
12 Granite Canyon Temperature and Salinity Data

Interannual, annual and seasonal variability is clearly evident in magnitude and temporal position of maxima and minima shown in

Figures 5, 7, 8 and 9. As would be expected,

there is coherence between "bucket" and CT

temperature measurements (correlation coefficient, r = 0.92). "Bucket” sampling appears

adequate for low-frequency sampling. Higher

frequency detail is apparent in CT data series.

Persistent differences between CT and

“bucket” temperature measurements may be

traced to the diurnal cycle. The average

monthly “bucket” temperature is 0.4 - 0.5 °C

above the monthly CT average. This difference

may be primarily due to CT sampling throughout the diurnal cycle. "Bucket" temperatures

are always made during daylight hours. Spectral analysis shows a spectral peak at 1 cycle per

day (see below). Insolation of the sub-littoral

pool and surrounding ocean probably

causes day time “bucket” SSTs to be higher

than 24-hr mean CT temperatures.

 The 1997-1998 El Niño signal is

shown by 2 - 4 °C positive temperature anomalies from October 1997 through June 1998

(Figures 5, 8). Lesser positive anomalies span

from May 1997 through August 1998. The annual cycle was exaggerated and displaced: mean

maxima occur in October and the 1997 maxima

was in November. Minima for the climatological and measured temperatures during 1997

were in April and March, respectively. The difference between maxima and minima for 1997

was greater than the mean SST extreme and

greater than that observed in the other two years

of observation. CT and “bucket” measurements

during the 1997 - 1998 winter (Figure 5) show

that the amplitude of variations of 1-10 day period was 5% to 10% the amplitude of variation

found in the rest of the record.

Figure 6. Differences between "bucket" salinity and average CT salinity (delta-s) plotted against the number of days after

installation or cleaning (abscissa). Delta-s is the "bucket" salinity for day n minus average CT probe salinity between

0900 and 1300 hours for day n. Different symbols represent seven periods of salinity-cell drift monitoring. Points from

all drift sequences, measured from replacement or cleaning were used in curve fitting. Delta-s points for the first (circles)

and fifth drift series (squares) were displaced -0.29 and -0.70, respectively, to adjust for high intercept values. Derived low

frequency corrections from the linear fit (L) were used to adjust the decimated CT-probe salinity to obtain the ìcorrected

salinity.î Second (P2) and third degree (P3) polynomial fits to these data are shown by the solid and broken lines, respectively.
Granite Canyon Temperature and Salinity Data 13

Figure 7. Comparison of ìacceptedî CT salinity (line) and "bucket" salinity (symbols). The interval compared is the same

as for Figure 5. The corrected CT salinity is deleted where it consistently diverged more than 0.30 psu from the "bucket"

salinity. These divergent intervals are shown by straight lines connecting areas of normal variability. Eighty-three percent of the decimated values have been retained in the set of ìacceptedî salinity (line). The heavy broken curve shows historical annual cycles from monthly means of "bucket" sampling during 1973-1994 (SIO, 1998).

During 1997, the spring transition was the earliest observed during the 1995-1998 CT observations. 1996 was the coolest year of CT observations (Figures 5, 8 and 9).

Power spectra

An example of power spectral analysis

on 30 sample hr-1 temperature data during 90

days in 1995 is shown in Figure 10. The panels show identical spectra plotted against linear

(upper) and logarithmic (lower) scales.

A large portion of the energy is in the

lowest frequencies, indicating strong seasonal

forcing. Beginning at the low-frequency end of

Figure 10 (left), the most energetic peak is

found around 0.001 cycles per hour (cph) or

about a 42-day cycle. This maxima may be

aliased because the short data sequence analyzed. There is a triplet of peaks from about

0.0026 to 0.005 cph (16- to 8-day cycles).

Next, maxima are shown for 5.2- and 3.0- day

cycles (0.008 and 0.014 cph, respectively).

Three to 16-day cycles are evident in Figures 5

and 8. The peaks at 0.038 and 0.042 cph occur

at diurnal lunar tide and the diurnal solar cycles,

respectively. The relative strength of these signals suggest that the solar diurnal cycle was

more important than the diurnal tides. The importance of the solar cycle is also indicated by

the general difference in daily temperature between "bucket" and CT-probe temperatures.

Another series of maxima appear between .07 and .09 cycles per hour. These may

be harmonics of the maxima around 0.04 cph.
14 Granite Canyon Temperature and Salinity Data

The higher frequency peak at 0.084 cph appears

related to the semi-diurnal tides (Figure 10).

Several of these maximum frequencies are

shown in the power spectra of salinity data

from the same period (not shown).

Central California ocean seasons

 The CT-probe data from Granite Canyon

show the three oceanic seasons reported by

Skogsberg (1936) and Skogsberg and Phelps

(1946). These relationships were further discussed by Sverdrup et al. (1942) in a general

description of California coastal oceanography

and by Breaker and Broenkow (1994) and

Breaker and Mooers (1986) in their discussions

of interannual variability off the central California coast. Present terminology follows

Skogsberg and Phelps (1946). The upwelling

season is characterized by lower temperatures

and higher salinity (Figures 5, 7, 8 and 9). It is

the low temperature part of the year that may

last from mid-February (julian day or jd ~ 048)

to late August (jd ~237).The oceanic season is

from late August (jd ~ 238) to mid-November

(jd ~ 319). In the mean this period has the

highest temperatures as shown by Figures 5,

7, 8 and 9.

Figure 8. Comparison of pressure, accepted salinity (32-35 psu) and corrected temperature (5 - 15 °C) for the four years of

observation. Pressure (depth) is on a relative scale with total range of 0.3 m. Low frequency events are conspicuous in each

of the three parameters during each of the four years. All data segments have been smoothed by fft filtering.
Granite Canyon Temperature and Salinity Data 15

The oceanic season is a transitional period from a regime when the subtropical atmospheric high pressure system is well-developed

and coastal winds from the northwest are common to a period when the Aleutian low atmospheric pressure system has greater influence

(Skogsberg and Phelps, 1946; Bakun, 1973;

Norton et al, 1985; Norton et al., 1994). Figure 5 shows short periods of elevated ocean

temperatures occurring between late July (jd

~ 210) and late October (jd ~ 300) of 1995,

1996 and 1997. These are the periods of highest daily temperature during 1995 and 1996, but

in the 1997 El Niño year this warming period is

early and is seen as a local maximum rather than

an annual maximum.

The Davidson current season from midNovember until mid February (jd ~ 320 until

jd ~ 47), is characterized by northward coastal

current and deepening of the coastal thermostructure (Skogsberg, 1936, Reid et al., 1958;

Breaker and Mooers, 1986). Figures 5, 7 and

8 show relatively high temperatures and low

salinity during this period, when upwelling

events of 2-10 day duration may occur. The

Davidson current season ends when the spring

transition becomes evident (Figure 9).

Figure 9. Spring transitions for 1996, 1997, 1998 and partially for 1995 are compared using temperature series that have

been smoothed by an fft filter to show low frequency events (see text). The year's traces are successively offset 2°C upward. Downward pointing arrows show the apparent beginning of the spring transitions and the upward arrows show the

approximate end of these events. 
16 Granite Canyon Temperature and Salinity Data

During El Niño years (Figure 5, 8), the greatest

positive temperature anomalies and sometimes

the warmest annual temperatures are found

during the Davidson current period (Norton et

al., 1985; Breaker and Mooers, 1986; Nortonand McLain, 1994). An interesting feature of

the Granite Canyon SST series is that the lowest temperatures occur during the spring upwelling season in common with offshore temperatures (Skogsberg, 1936; Robinson, 1960).

The coolest temperatures at more protected

shore stations occur in the winter Davidson current season (SIO, 1998; Norton, personal observations at Monterey Wharf 2.).

Temperature/salinity relationships

Interpretation of time series from shore

station measurements is facilitated by an understanding of the source of the water measured.

A well-tested method of obtaining this information is to examine temperature/salinity (T/S) relationships (Sverdrup et al., 1942; Lynn and

Simpson, 1987; Norton and Crooke, 1994).

T/S relationships may be visualized by plotting

data pairs with increasing temperature on the

ordinate and increasing salinity on the abscissa

(Figure 11). In the present case the depth is

fixed and a representation of water source is

obtained from the position of the data points

(Sverdrup et al., 1942).

The importance of coastal upwelling in

determining the overall shape of the T/S scatter

is indicated by the convergence of values in the

lower part of the graph near 34.1 psu and 8-10

°C. This represents the water brought to the

surface during extreme upwelling conditions.

The triangular shape is similar to that seen in an

assembly of T/S points from vertical sampling

(Sverdrup et al., 1942).

The low salinity, left margin, of the

cluster indicates increase of temperature concomitant with decrease of salinity. This relationship reflects dominant on-offshore water

movement off the central California coast.

When there is upwelling, surface water is

pushed offshore and cooler, higher salinity

water comes to the surface. When upwelling

episodes end, the on-offshore slope characteristic of upwelling is relaxed and warmer, less

saline water from offshore enters the littoral

zone. These relationships are shown in Figure

8. For instance, the two temperature maxima

shown in July 1995 correspond to two minima

in the accepted salinity series. In Figure 11 the

points on the right of the cluster suggest processes that change temperature as much as 5 °C

while the salinity remains greater than 34 psu.

Figure 10. Two presentations of temperature power spectra.

The upper panel shows variability, or power, plotted on a

linear scale. The lower panel is identical except for a logarithmic ordinate. This is an fft transform of 90 days of 30

per hour temperature data obtained during March, April,

May and June 1995. The solar diurnal frequency is shown

by the peak at 0.042 cycles per hour.
Granite Canyon Temperature and Salinity Data 17

Figure 11. Plot of decimated data pairs of temperature and corresponding accepted salinity (T/S plot). Temperature increases on the ordinate and salinity increases on the abscissa. Curved dotted, diagonal lines show water density as

sigma-t.

Comparison to other environmental

measurements

CT-probe temperature was found to be

correlated with other environmental measurements from the central California coast. CT

temperature at Granite Canyon was correlated

(r = 0.62) with the standard upwelling index at

36°N (Bakun, 1973; Schwing et al., 1996).

Daily averaged CT temperature was correlated

(r = 0.63 and 0.55, respectively), with SST

from the Cape San Martin and Monterey Bay

NOAA, National Data Buoy Center buoys,

suggesting significant relationships. The relationships hold when the annual cycle is removed from the comparison. These comparisons with buoys moored 70 km to the south

and 50 km to the north, respectively, show

physical coherence between SST at Granite

Canyon and other locations along the central

California coast, confirming earlier results of

Robinson (1960) and Breaker and Mooers

(1986).

Conclusions and prospectus

Aside from the fact that it is better to

have measurements every day, a series of

pooled measurements provides a better representation of environmental changes than single
18 Granite Canyon Temperature and Salinity Data

daily measurements. We are currently obtaining 720 measurements per day. These pooled

measurements (by averaging or smoothing) are

better representations of daily temperature and

pressure. When sampling does not include

complete solar and tidal cycles, the observation

of lower frequency events may be biased. The

solar cycle varies from day-to-day and the extent of solar heating and the extent of mixing at

the time of a single measurement will vary. The

tidal cycle will also be aliased into the data

when measurements are made at a fixed time

each day. In addition, the high temporal resolution CT-Probe measurements allow analyses

of daily and higher frequency ocean events at

Granite Canyon.

Continuous records such as the ones

available from Granite Canyon can provide

background for all physical and biological

oceanographic studies conducted along the central California coast. It may be possible to distinguish between different types of coastal

ocean forcing using comparison of salinity,

temperature and sea level time series to standard

upwelling index products (Bakun, 1973), locally measured wind forcing (Fernandez et al.,

1996), ocean dynamic topography, large-scale

indices (Norton and McLain, 1994) and buoy

data. Additional studies may allow changes that

occur in the adjacent ocean volume to be interpreted as temporal variation at Granite Canyon.

Continuous, high-resolution data are important

in advancing these efforts. Near-real-time access to the data enhances its value in pollution

control, sampling trip planning, bio-toxin

monitoring, physical modeling and interpretation of ecological changes.

Deployment of additional CT-probes at

other locations on the central coast would also

enhance the utility of the Granite Canyon installation, particularly if each installation has

near-real-time access. Addition of dissolved

oxygen and fluorescence sensors to the CTprobe would improve its utility in biological

studies.

Marine plants and animals are sensitive

to temperature and major bio-geographic divisions correspond to regions of 1 - 4 °C temperature change (Brinton, 1981; Fields et al.,

1993). At a fixed shore station these discontinuities may be measured temporally rather than

spatially. Micro-nutrient increase and consequently biological productivity along the central

California coast corresponds to decreased ocean

temperature with such regularity that the primary (planktonic) productivity can be assessed

by an analysis of ocean temperature changes

(Traganza et al., 1981). Macro-algae (kelp)

growth and proliferation on the central California coast will be a function of temperature

changes reflecting nutrient variability. Important ecological processes involving several

commercial and recreationally important species

are linked to seasonal and interannual variability

in kelp forest production (Zimmerman and

Kremer, 1984; Tegner and Dayton, 1987;

Roughgarden et al., 1988).

An ongoing program combining daily

measurements and continuous CT-probe recording will optimize both recording methods.

The CT salinity sensor must be kept free of

contaminants to maintain calibration. Because

settling of algae and invertebrate larval stages

from the ambient plankton is continuous, necessary cleanliness of the salinity cell and electrodes is seldom possible for an installed instrument. Therefore, correction is needed to insure proper interpretation of CT salinity records. Once-a-day salinity measurements (as

done in the past) allow continuous calibration of

CT salinity and they allow rapid changes in CT

calibration to be detected (Figure 7). The highest quality records will be obtained when daily

salinity measurements are available.

Current plans call for CDF&G personnel to maintain the CT probe system at Granite

Canyon, with PFEL serving in a data processing and advisory capacity. CDF&G knowledge

of the relationship between species survivorship

and oceanic conditions will lead to a more ecological approach to management of marine resources as mandated by California Assembly

Bill AB1241.
Granite Canyon Temperature and Salinity Data 19

Acknowledgments

We would not have been able to complete this report without the help of Connie Fey of the

Marine Life Research Group, Scripps Institution of Oceanography, who provided the shore station

data needed to validate CT-probe functioning. George Boehlert, Director of the Pacific Fisheries

Environmental Laboratory, provided the support necessary to install the instruments, collect and

process the data and assemble this report. Art Stroud and Steven Cummings of the Pacific Fisheries Environmental Laboratory were extremely helpful in providing information and assistance in

using computing and graphing equipment and programs. Mike Donnelin and Scott Clark of the

California Department of Fish and Game have efficiently taken control of CT-probe operation.
20 Granite Canyon Temperature and Salinity Data

References

Bakun, A., 1973. Coastal upwelling indices, west coast of North America 1946-71, U. S. Dep.

Comm., NOAA Technical Report. NMFS SSRF 671, 103 pp.

Breaker, L. C. and C. N. K. Mooers, 1986. Oceanic variability off the central California coast,

Prog. Oceanog., 17:61-135.

Breaker, L. C. and W. W. Broenkow, 1994. The circulation of Monterey Bay and related processes, Oceanography and Marine Biology, Annual Review 32:1-65.

Brinton, E., 1981. Euphausiid distributions in the California Current during the warm-water

spring of 1977-78, in the context of a 1949-66 time series., California, Calif. Coop. Oceanic Fish.

Invest. (CalCOFI) Rep., 22:135-154.

Fernandez, D. M., P. E. Mantley, D. E. Long, E. Rosen and C. M. Wittenbrink, 1996.

REINAS: Real time environmental information network, Sea Technology, May, 23-47.

Fields, P. A., J. B. Graham, R. H. Rosenblatt and G. N. Somero, 1993. Effects of expected

global climate change on marine faunas, Trends in Ecology and Evolution, 8:361-366.

Lynn, R. J. and J. J. Simpson, 1987. The California current system: the seasonal variability of its

physical characteristics, J. Geophys. Res., 92:12947-12966.

MATLAB User's Guide, High-performance numeric computation and visualization software,

1994. The Math Works, Inc. Natick, Massachusetts.

McGowan, J. A., D. R. Cayan and L. M. Dorman, 1998. Climate-ocean variability and ecosystem response in the northeast Pacific, Science, 281:210-217.

Norton, J. G., 1987. Ocean climate influences on groundfish recruitment in the California current.

In Proceedings of the International Rockfish Symposium, October 20-22, 1986, pp. 73-98.

Alaska Sea Grant College Program, University of Alaska, Fairbanks, Alaska.

Norton, J. G., 1999. Apparent habitat extensions of dolphin-fish (Coryphaena hippurus) in response to climate transients in the California Current, In Biology and fishery of dolphin-fish and

related species (Scientia Marina Monograph), E. Massuti and B. Morales-Nin eds. (in press).

Norton, J. G., D. R. McLain, R. E. Brainard and D. M. Husby, 1985. El Niño event off Baja

and Alta California and its ocean climate context. In El Niño North: Niño effects in the eastern

subarctic Pacific Ocean, W. S. Wooster and D. L. Fluharty eds., pp 44-72. Washington Sea Grant

Program, University of Washington, Seattle.

Norton, J. G. and G. E. Schacher, 1980. The shipboard use of a low-level atmospheric thermograph in fog and stratus investigations, Jour. Applied Meteorology 19:224-229.

Norton, J. G., D. R. Cayan and D. R. Mclain, 1994. Near and distant connection of atmospheric

systems to ocean temperature change in the coastal California current region. In K. T. Redmond

and V. L.Tharp. Eds. Proceedings of the Tenth annual Pacific Climate (PACLIM) Workshop.

April 1993. California Department of Water Resources, Interagency Ecological Studies Program.

Tech. Rept. 36, pp. 93 - 105.
Granite Canyon Temperature and Salinity Data 21

Norton, J. G. and S. J. Crooke, 1994. Occasional availability of dolphin, Coryphaena hippurus,

to southern California Commercial Passenger Fishing Vessel Anglers: Observations and hypotheses, Calif. Coop. Oceanic Fish. Invest. (CalCOFI) Rep., 35:230-239, 1994.

Norton, J. G. and D. R. McLain, 1994. Diagnostic patterns of seasonal and interannual temperature variation off the west coast of the United States: Local and remote large scale atmospheric

forcing. J. Geophys. Res. 99:16,019-16,030.

Reid, J. L. , G. I. Roden and J. G. Wyllie, 1958. Studies of the California Current System, Calif.

Coop. Oceanic Fish. Invest. (CalCOFI) Rep. 6:27-57.

Robinson, M. K., 1960. The use of a common reference period for evaluating climatic coherence

in temperature and salinity records from Alaska to California, Calif. Coop. Oceanic Fish. Invest.

(CalCOFI) Rep. 8:121-130.

Roden, G. I.,1963. On statistical estimation of monthly extreme sea surface temperatures along the

west coast of the United States, J. Mar. Res. 21:172-190.

Roughgarden, J., S. Gaines and H. Possingham, 1988. Recruitment dynamics in complex life

cycles, Science 241:1460-1466.

SBE. SEA-BIRD ELECTRONICS, Conductivity, temperature, pressure recorder, Operating

manual, 1993. Sea-Bird Electronics, Inc. Bellevue, Washington.

Schwing, F. B., M. O’Farrell, J. Steger, K. Baltz, 1996. Coastal upwelling indices, west coast of

North America, U. S. Dep. Comm., NOAA Technical Memorandum. NMFS , NOAA-TMNMFS-SWFSC-231, 207pp.

SIO (Anon.), 1998. Surface water temperatures at shore stations, United States west coast

1995 -1998, University of California Scripps Institution of Oceanography, SIO Reference Series

1916-1998.

Skogsberg, T., 1936. Hydrography of Monterey Bay, California. Thermal conditions, 1929-

1933, Transactions of the American Philosophical Society 29, 152 pp.

Skogsberg, T. and A. Phelps, 1946. Hydrography of Monterey Bay, California. Thermal conditions, part II, 1934-1937, Proceedings of the American Philosophical Society 90:350-386.

Sverdrup, H. U., M. W. Johnson and R. H. Fleming, 1942. The Oceans, their physics, chemistry

and general biology, Prentice-Hall, Englewood Cliffs, New Jersey, 1087 pp.

Tegner, M. J. and P. K. Dayton, 1987. El Niño effects on Southern California kelp forest communities, Adv. Ecol. Res. 17:423-479.

Traganza, E., J. C. Conrad and L. C. Breaker, 1981. Satellite observations of a cyclonic upwelling system and giant plume in the California Current, in Coastal Upwelling, edited by

F. A. Richards, pp. 228-241, American Geophysical Union, Washington, D. C.

Zimmerman, R. C. and J. N. Kremer, 1984. Episodic nutrient supply to a kelp forest

ecosystem in Southern California, J. Mar. Res. 42:591-604.
22 Granite Canyon Temperature and Salinity Data

Appendix 1

DATA FILES FROM GRANITE CANYON CT (1995-1998)

This table lists downloaded segments for the March 1995 through August 1998 period, along with

the filenames used for the downloaded segments and the intervals covered by the segments. From

13 February through 16 March several download segments were made during testing and trouble

shooting. These early segments contain only short sections of useful information and are not

considered in this report.

- 1995 -

DOWNLOAD

DATE

SAMPLING

INTERVAL

INSTRUMENT

MODEL

NUMBER

BEGIN DATE

AND TIME

(PST)

END DATE

AND TIME

(PST)

DOWNLOAD

FILE NAME

PROCESS

NAMES

27 March 95 (30 sec) 1475 March 16, '95

1608

March 27, '95

0948

jgn1400.hex J15.CNV

jgn1404.cnv

gc_ctd_1.1995

4 Apr. 95 (30 sec) 1475 March 27

1137

April 4

1339

J1500.hex J154A.CNV

gn1504.cnv

gc_ctd_2.1995

10 Apr. 95 (30 sec) 1475 April 4

1439

April 10

1451

JGN1600.hex J1610A.CNV

jgn1604.cnv

gc_ctd_3.1995

- Begin analyzed record on March 31, 1995 (jd=90) -

25 Apr. 95 (30 sec) 1475 April 10

1606

April 25

0918

jgn1700.hex Jgn1700.cnv

jgn1704.cnv

gc_ctd_4.1995

3 May 95 (30 sec) 1475 April 25

1213

May 3

1401

jgn1800.hex JGN1800.cnv

jgn1804.cnv

gc_ctd_5.1995

11 May 95 (30 sec) 1475 May 3

1453

May 11

1231

JGN1900.hex jgn1904.cnv

gc_ctd_6.1995

19 May 95 (30 sec) 1475 May 11

1343

May 19

1441

JGN2000.hex jgn2004.cnv

gc_ctd_7.1995

30 May 95 (30 sec) 1475 May 19

1551

May 30

1449

JGN2100.hex jgn2104.cnv

gc_ctd_8.1995

8 June 95 (30 sec) 1475 May 30

1631

June 8

1115

JGN2200.hex jgn2204.cnv

gc_ctd_9.1995

- Change in sampling rate (30 sec. to 120 sec) -

15 June 95 (120 sec) or

(720/day)

1475 June 8

1251

June 15

1455

jgn2300.hex jgn2300.cnv

gc_ctd_10.1995

5 July 95 (120 sec) 1475 June 15

1522

July 5

1306

jgn2400.hex jgn2400.cnv

gc_ctd_11.1995

20 July 95 (120 sec) 1475 July 5

1351

July 20

0945

jgn2500.hex jgn2500.cnv

gc_ctd_12.1995
Granite Canyon Temperature and Salinity Data 23

DOWNLOAD

DATE

SAMPLING

INTERVAL

INSTRUMENT

MODEL

NUMBER

BEGIN DATE

AND TIME

(PST)

END DATE

AND TIME

(PST)

DOWNLOAD

FILE NAME

PROCESS

NAMES

20 July 95 (120 sec) 1475 --- --- jgn2600.hex jgn2600.cnv

(Note: monitor

cleaning of conductivity cell;

1-2 hour record

not included)

- Conductivity cell cleaned -

8 Aug. 95 (120 sec) 1475 July 20

1213

August 8

1337

jgn2700.hex jgn2700.cnv

gc_ctd_13.1995

28 Aug. 95 (120 sec) 1475 August 8

1421

August 28

1527

jgn2800.hex jgn2800.cnv

gc_ctd_14.1995

7 Sept. 95 (120 sec) 1475 28 August

1614

7 September

1540

jgn2900.hex JGN2900.CNV

gc_ctd_15.1995

13 Sept. 95 (120 sec) 1475 7 September

1704

13 September

1258

jgn3100.hex ---

13 Sept. 95 (15 sec) 1441 13 September

1350

13 September

1415

JGN3200.hex JGN3200.CNV

(Note: 1441

clock time

test# 1441 not

included in final data)

27 Sept. 95 (120 sec) 1475 7 September

1704

27 September

0945

jgn3300.hex JGN3300.CNV

gc_ctd_16.ctd

(Note: counter

uneven / cycle

drop out is

1258 to 1441

on 13 Sept.)

- Remove model number 1475 CTD-probe / Install model number 1441 CT-probe -

27 Sept. 95 (15 sec) 1441 September

1235

September

1357

jgn3400.hex JGN3400.CNV

(Note: install /

check; not

included in

final data)

 6 Oct. 95 (120 sec) 1441 27 September

1412

October 6

1226

JGN3500.hex JGN3500.CNV

gc_ctd_17.1995

20 Oct. 95 (120 sec) 1441 October 6

1329

October 20

1427

jgn3600.hex JGN3600.CNV

gc_ctd_18.1995

3 Nov. 95 (120 sec) 1441 October 20

1511

November 3

1114

JGN3700.hex

JGN3800.hex

(Note: 600

b/no error)

jgn3700.cnv

jgn3800.cnv

gc_ctd_19.1995

18 Nov. 95 (120 sec) 1441 November 3

1253

November 18

1239

jgn3900.hex jgn3900.cnv

gc_ctd_20.1995
24 Granite Canyon Temperature and Salinity Data

DOWNLOAD

DATE

SAMPLING

INTERVAL

INSTRUMENT

MODEL

NUMBER

BEGIN DATE

AND TIME

(PST)

END DATE

AND TIME

(PST)

DOWNLOAD

FILE NAME

PROCESS

NAMES

3 Dec. 95 (120 sec) 1441 November 18

1323

December 3

1337

jgn4000.hex jgn4000.cnv

gc_ctd_21.1995

15 Dec. 95 (120 sec) 1441 December 3

1428

December 15

1642

jgn4100.hex jgn4100.cnv

gc_ctd_22.1995

31 Dec. 95 (120 sec) 1441 December 15

1716

December 31

1404

jgn4200.hex JGN4200.CNV

gc_ctd_23.1995

- 1996 -

12 Jan. 96 (120 sec) 1441 December 15

1717

January 11

1049

JGN4400.hex JGN4400.CNV

gc_ctd_1

(Note: file

contains data

gap from last

upload)

3 Feb. 96 (120 sec) 1441 January 12

1501

February 3

1648

JGN4300.hex JGN4300.CNV

gc_ctd_2

(Note: file

numbers not

sequential)

5 Mar. 96 (120 sec) 1441 February 3

1755

March 5

1549

jgn4500.hex JGN4500.CNV

 gc_ctd_3

(Note: CT

record date

incorrect due

to 29 day (leap

year) February )

22 Mar. 96 (120 sec) 1441 March 5

1718

March 22

1513

03-22-96.hex 03-22-96.CNV

gc_ctd_4

5 April 96 (120 sec) 1441 March 22

1625

April 5

1316

04-05-96.hex 04-05-96.CNV

gc_ctd_5

 - Remove model number 1441 CT-probe / install model number 1475 CTD-probe -

30 April 96 (120 sec) 1475 April 5

1631

April 30

1541

04-30-96.hex 04-30-96.CNV

gc_ctd_6

(Note: record

includes data

dropout)

24 May 96 (120 sec) 1475 April 30

1710

May 24 

1341

05-24-96.hex 05-24-96.CNV

gc_ctd_7

15 June 96 (120 sec) 1475 May 24

1504

June 15

1411

06-15-96.hex 06-15-96.cnv

gc_ctd_8

4 July 96 (120 sec) 1475 June 1

1524

July 4

0946

07-04-96.hex 07-15-96.cnv

gc_ctd_9
Granite Canyon Temperature and Salinity Data 25

DOWNLOAD

DATE

SAMPLING

INTERVAL

INSTRUMENT

MODEL

NUMBER

BEGIN DATE

AND TIME

(PST)

END DATE

AND TIME

(PST)

DOWNLOAD

FILE NAME

PROCESS

NAMES

1 Aug. 96 (120 sec) 1475 July 7

1056

August 1

1244

08-01-96.hex 08-01-96.CNV

gc_ctd_10

- Cleaning of conductivity cell not entirely effective -

2 Sep. 96 (120 sec) 1475 August 1

1510

September 2

1514

09-02-96.hex 09-02-96.CNV

gc_ctd_11

30 Sep. 96 (120 sec) 1475 September 2

1657

September 30

1426

09-30-96.hex 09-30-96.CNV

gc_ctd_12

18 Oct. 96 (120 sec) 1475 September 30

1613

October 18

1022

10-18-96.hex 10-18-96.CNV

gc_ctd_13

- Clean conductivity cell -

22 Nov. 96 --- --- --- --- --- Note: Unable to

establish

communications;

Opto box nonfunctional.

13-27 November: data lost from jd=318 (683) to jd=331 (696);

Opto interface box damaged by power surge

29 Nov. 96 (120 sec) 1475 October 18

11:44:46

--- bust.hex 11-29-96.CNV

gc_ctd_14

(Note: record

lost, logging

stopped on 12th)

28 Dec. 96 (120 sec) 1475 November 29

1802

December 28

1540

12-28-96.hex

[28dc.96]

12-26-98.CNV

gc_ctd_15

(Note: replace

Opto interface

box)

- 1997 -

20 Jan. 97 (120 sec) 1475 Dec. 28, '96

1721

Jan. 20, '97

1542

20JN97.hex 01-20-97.cnv

gc_ctd_1.1997

13 Feb. 97 (120 sec) 1475 Dec. 28, '96

1720

Feb. 13, '97

1745

2-13-97.hex 02-13-97.cnv

gc_ctd_2.1997

(Note: file

02-13-97.cnv

contains above

record)

12 Mar. 97 (120 sec) 1475 February 13

2034

March 12

0906

03-12-97.hex 03-12-97.cnv

gc_ctd_3.1997
26 Granite Canyon Temperature and Salinity Data

DOWNLOAD

DATE

SAMPLING

INTERVAL

INSTRUMENT

MODEL

NUMBER

BEGIN DATE

AND TIME

(PST)

END DATE

AND TIME

(PST)

DOWNLOAD

FILE NAME

PROCESS

NAMES

17 April 97 (120 sec) 1475 March 12

1048

April 17

1647

041797.hex 041797.cnv

gc_ctd_4.1997

14 May 97 (120 sec) 1475 April 17

1905

May 17

0814

05-14-97.hex 05-14-97.cnv

gc_ctd_5.1997

- Remove model number 1475 CTD-probe / install model number 1441 CT-probe -

5 June 97 (120 sec) 1441 May 14

1157

June 5

1514

06-05-97.hex 06-05-97.cnv

gc_ctd_6.1997

(Note: second

start at 18th

record)

1 July 97 (120 sec) 1441 June 5

1626

 July 1

1451

07-01-97.hex 07-01-97.cnv

gc_ctd_7.1997

5 Aug. 97 (120 sec) 1441 July 1

1608

August 5

1440

08-05-97.hex 08-05-97.cnv

gc_ctd_8.1997

20 Aug. 97 (120 sec) 1441 August 5

1303

August 20

1445

08-20-97.hex 08-20-97.cnv

gc_ctd_9.1997

28 Sept. 97 (120 sec) 1441 September 28

1427

August 20

1543

09.28.97.hex 09-28-97.cnv

gc_ctd_10.1997

8 Nov. 97 (120 sec) 1441 September 28

1731

November 8

1524

110897g.hex 110897G.cnv

gc_ctd_11.1997

27 Dec. 97 (120 sec) 1441 November 8

1753

December 27

1546

12-27-97.hex

12.hex

12.CNV

gc_ctd_12.1997

- 1998 -

2 March 98 (120 sec) 1441 December 27

1810

March 2

1230

gc980302.hex gc980302.cnv

gc_ctd-1.1998

3 May 98 (120 sec) 1441 March 2

1534

May 3

1435

03d05m98.hex 03d05m98.cnv

gc_ctd_2.1998

6 June 98 (120 sec) 1441 May 3

1707

June 6

1732

06d06m98.hex gc_ctd_3.1998

06d06m98.cnv

16 June 98 (120 sec) 1441 June 6

1900

June 16

1107

16d06m98.hex 16d06m98.cnv

gc_ctd_4.1998

- Remove model number 1441 CT-probe / install model number 1475 CTD-probe -

- CDF&G takes control of equipment and “field” work -

23 June 98 (120 sec) 1475 June 16

1535

June 23

1013

23d06m98.hex 23d06m98.cnv

gc_ctd_5.1998

13 July 98 (120 sec) 1475 June 23

1104

July 13

1332

13d07m98.hex 13d07m98.cnv

gs_ctd_6.1998

7 Aug. 98 (120 sec) 1475 June 13

1605

Aug. 7

1005

07d08m98.hex 07d08m98.cnv

gc_ctd_7.1998