NOAA Technical Memorandum OAR PMEL-119

Calibration procedures and instrumental accuracies for

ATLAS wind measurements

H.P. Freitag1, M. O’Haleck1,2, G.C. Thomas1,2, and M.J. McPhaden1

1Pacific Marine Environmental Laboratory

7600 Sand Point Way NE

Seattle, WA 98115-6349

2Joint Institute for the Study of the Atmosphere and Ocean (JISAO)

University of Washington

Box 351640

Seattle, WA 98195

June 2001

Contribution 2339 from NOAA/Pacific Marine Environmental Laboratory

Contribution 839 from the Joint Institute for the Study of the Atmosphere

and Ocean (JISAO)
NOTICE

Mention of a commercial company or product does not constitute an endorsement by

NOAA/OAR. Use of information from this publication concerning proprietary products

or the tests of such products for publicity or advertising purposes is not authorized.

Contribution No. 2339 from NOAA/Pacific Marine Environmental Laboratory

Contribution No. 839 from the Joint Institute for the Study of the Atmosphere and Ocean

(JISAO)

For sale by the National Technical Information Service, 5285 Port Royal Road

Springfield, VA 22161

ii
Contents iii

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

2. Sensor Operation and Calibration . . . . . . . . . . . . . . . 2

2.1 Wind speed . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2.2 Wind vane . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2.3 Compass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

3. Data Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . 8

4. Estimation of Sensor Accuracy . . . . . . . . . . . . . . . . . 8

4.1 Wind speed . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

4.2 Wind vane . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

4.3 Compass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

4.4 Wind direction . . . . . . . . . . . . . . . . . . . . . . . . . . 13

5. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

6. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . 15

7. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Appendix A: Sample wind speed calibration . . . . . . . . . . . . 16

Appendix B: Sample wind vane calibration check . . . . . . . . . 17

Appendix C: Sample compass calibration . . . . . . . . . . . . . . 18
iv Contents
Calibration procedures and instrumental accuracies for ATLAS

wind measurements

H.P. Freitag1, M. O’Haleck1,2, G.C. Thomas1,2, and M.J. McPhaden1

Abstract. We describe calibration procedures and instrumental accuracies for wind speed and

direction on Autonomous Temperature Line Acquisition System (ATLAS) buoys deployed in the

tropical Pacific and Atlantic Oceans. Accuracy of wind speed measurements over a range of 1 m s−1

to 20 m s−1 is estimated as 0.3 m s−1 or 3% of the speed, whichever is greater. A conservative

estimate for root-mean-square (RMS) wind direction error for sensors deployed before November

2000 is 7.8◦, of which 6.8◦ is a mean error in a counterclockwise direction. Beginning in November

2000, wind sensors on ATLAS moorings were modified to correct for this direction bias. Wind

direction errors from modified sensors are expected to be reduced to about 5◦ RMS with minimal

bias.

1. Introduction

The Tropical Atmosphere Ocean (TAO) Array was initiated as an in situ

observing system contribution to the Tropical Ocean-Global Atmosphere

(TOGA) Program, a 10-year (1985–1994) study of climate variability on

seasonal to interannual timescales, the most pronounced mode of which is

the El Ni ̃no/ Southern Oscillation (ENSO) phenomenon (McPhaden et al.,

1998). The array consists of approximately 70 deep-ocean moorings spanning the equatorial Pacific Ocean between 8◦S and 8◦N from 95◦W to 137◦E

and typically separated by 2–3◦ latitude and 10–15◦ longitude (Fig. 1a).

The majority of moorings are ATLAS moorings (Hayes et al., 1991). The

array has continued after TOGA as a major component of the ENSO Observing System under the auspices of the international Climate Variability

and Predictability (CLIVAR), Global Ocean Observing System (GOOS),

and Global Climate Observing System (GCOS) programs. As of January

2000, the westernmost portion of the array is maintained by Japan Marine Science and Technology Center (JAMSTEC), which deploys Triangle

Trans-Ocean buoy network (TRITON) moorings between 138◦E and 156◦E.

The TAO/TRITON array, as it is now known, is supported primarily by

the United States (NOAA) and Japan (JAMSTEC) with contributions from

France via the L’Institut de Recherche pour le D ́eveloppement (IRD). TAO

collaboration with France (through IRD) and Brazil (through the Instituto

Na ̧cional de Pesquisas Espa ̧ciais or INPE) led to the development of the

Pilot Research Moored Array in the Tropical Atlantic (PIRATA), a similar

array of ATLAS moorings in the tropical Atlantic (Fig. 1b) (Servain et al.,

1998).

ATLAS moorings were developed by NOAA’s Pacific Marine Environmental Laboratory (PMEL). Standard ATLAS measurements include surface wind, air temperature, relative humidity, sea surface temperature, and

subsurface temperature to a depth of 500 m. Recent development of Next

1NOAA/Pacific Marine Environmental Laboratory, 7600 Sand Point Way NE, Seattle,

WA 98115 2Joint Institute for the Study of the Atmosphere and Ocean (JISAO), University of

Washington, Box 351640, Seattle, WA 98195
2 Freitag et al.

Table 1: Manufacturer’s specifications for TAO wind speed and

direction sensors.

Measurement Sensor type Manufacturer/Model Specifications

Wind speed Propeller R.M. Young/05103 Maximum Speed: 60 m s−1

Threshold: 1.0 m s−1

Accuracy: ±0.3 m s−1

Wind direction Vane R.M. Young/05103 Range: 0–355◦

Threshold: 1.1 m s−1

Accuracy: ±3◦

Fluxgate compass EG&G/63764 or Range: 0–360◦

KVH/LP101-5 Accuracy: 5◦

Generation ATLAS moorings added the option to measure rainfall, shortand long-wave radiation, barometric pressure, salinity, and ocean currents.

Data are transmitted daily to shore via NOAA polar-orbiting satellite by

Service Argos and made available on the World Wide Web at http://

www.pmel.noaa.gov/tao/. Data are also submitted to the Global Telecommunications System (GTS) by Service Argos. Moorings are generally designed for a nominal 1-year deployment.

Calibration techniques and estimated accuracy for TAO temperature,

relative humidity, and short-wave radiation measurements are described by

Freitag et al. (1994). This report covers the calibration techniques and estimated accuracies of wind speed and direction measurements from TAO

moorings as performed at PMEL by TAO technicians. Calibrations of sensors are performed both prior to deployment and after recovery, unless lost

or damaged.

Wind speed and direction relative to the buoy are measured with an R.M.

Young Co. model 05103 propeller/vane wind monitor on both Standard and

Next Generation ATLAS moorings. Buoy orientation relative to magnetic

north is measured by a fluxgate compass, either EG&G model 63764 or KVH

model LP101-5. Manufacturer’s specifications are listed in Table 1. The electronics hardware and firmware components that digitize and record sensor

outputs and transmit averaged data were designed by PMEL’s Engineering

Development Division (EDD) and constructed by TAO Project technicians.

2. Sensor Operation and Calibration

2.1 Wind speed

Wind speed is measured with a four blade, 18 cm diameter × 30 cm pitch

helicoid propeller anemometer (Fig. 2), manufactured by R.M. Young of Traverse City, Michigan. Rotation of a magnet on the propeller shaft produces

an AC sine wave with output frequency proportional to the wind speed.

The output signal is induced in a centrally mounted coil by a six-pole permanent magnet attached to the propeller shaft; thus for every rotation of

the propeller, there are three complete cycles of output.
ATLAS Wind Calibration Procedures and Instrumental Accuracies 3

Figure 1a: Map of the TAO/TRITON Array. In addition to the ATLAS and TRITON moorings there are

5 subsurface ADCP (Acoustic Doppler Current Profiler) moorings deployed along the equator.

Figure 1b: Map of the PIRATA Array.
4 Freitag et al.

Figure 2: Repairing sensors on an ATLAS Mooring.

Speed calibrations are performed in an on-site wind tunnel. The PMEL

standard anemometer is an R.M. Young model 27106T propeller anemometer, which is calibrated by R.M. Young on an annual basis by comparison to

an identical model calibrated by the National Institute of Standards. The

wind tunnel has a 1.08 square meter rectangle closed test section 8 m long

with straight walls and an open return. The test instrument and a standard

are attached on side-by-side stands in the wind tunnel test section. The

two are monitored for 90 s at each of 8 settings from approximately 1 to

20 m s−1. A software program reads the voltage output from the standard

and the frequency output (expressed in counts) from the test instrument.

The frequency output of the test instrument is digitized by circuitry identical to that used on the moorings. Voltage from the standard is converted

to speed using a calibration transfer function as determined by R.M. Young.

Calibration coefficients for the test instrument are computed from a linear

least-squares fit between the wind speed from the standard and the counts

from the test instrument. Residual differences between the speed of the

standard and that predicted by the linear least-squares fit to the test sensor

output are used to evaluate the test sensor performance. Generally a sensor

fails the calibration and is not used on a mooring if the residual at any test

point is greater than 0.2 m s−1. A sample calibration is shown in Figs. 3a

and 3b and included in Appendix A.
ATLAS Wind Calibration Procedures and Instrumental Accuracies 5

Figure 3: Sample pre-deployment calibrations. (a) Wind speed versus sensor counts (solid circles) and

computed calibration equation (line). (b) Residual difference between calibration fit and measured wind

speed. (c) Residual between wind vane set point and sensor output. (d) Residual between compass set point

and sensor output. Open circles are uncorrected. Solid circles are corrected.
6 Freitag et al.

2.2 Wind vane

The vane measurement is made with a potentiometer within the anemometer

assembly. The vane assembly rotates freely on a vertical shaft and is coupled

to the middle arm of a 10 kΩ precision potentiometer. A regulated constant

voltage is applied to the ends of the potentiometer and the resulting output

voltage from the middle arm is directly proportional to the angle of the vane.

The potentiometer has an open section resulting in a dead zone of nominally

5◦ which is near the 0◦ orientation.

Prior to deployment, calibration checks are performed by TAO technicians, during which a voltage of 3.55 V is applied across the potentiometer.

The orientation of the potentiometer is then adjusted such that an output

reading of 1.8 V from the middle arm corresponds to a vane orientation of

180◦. The output voltage is then read at 15◦ intervals through its entire

range. In general, if the error at any test point is greater than 5◦ the sensor

fails the calibration and is not used until it is repaired. For sensors that pass

pre-deployment tests and are subsequently deployed, the calibration check

is repeated after the sensor is recovered. If a wind sensor has been deployed

for more than 6 months the potentiometer is replaced when returned to

the lab and its calibration rechecked before re-deployment. A sample vane

calibration check is shown in Fig. 3c and included in Appendix B.

Vane calibrations as described above check the accuracy of the vane potentiometer alone. In this regard, vane calibrations differ from those of the

compass which combine sensor and digitization electronics. Analog to digital

(A/D) converters and their related electronic components were designed to

be linear to within 1 bit (∼1.4◦). For Standard ATLAS systems, individual

A/Ds were not routinely checked for accuracy. On Next Generation systems,

however, each A/D circuit is checked for accuracy and RMS errors have been

confirmed to be within the 1 bit design criteria.

While documenting the vane calibration procedures for this report, it

was found that the potentiometer polarity was reversed during calibrations

relative to that during field measurements. The effect of this error was such

that the dead zone, which was thought to be near the range 355◦ to 0◦,

was in fact near 0◦ to 5◦. This rotation introduced a counterclockwise bias

when deployed, i.e., the vane output would be about 5◦ lower than the true

orientation. We refer to this as the alignment error.

An error in the digitization of the vane output was also found during

the preparation of this document. When computing vector components of

wind velocity (see section 3) the instrument software assumed that each vane

count represented approximately 1.4◦, so that the full range of values (360◦)

was represented by counts from 0 to 255. In actuality, the digitization did

not account properly for the 5◦ dead zone, so that the full range of counts

(255) was output over a range of 355◦. This firmware error, which was only

present in Next Generation ATLAS systems, caused vane values to be high

by about 1%.

It was also found that modification of a component in the vane digitization circuitry would improve its accuracy. The circuitry employs a pulldown

resistor to force the vane output to zero when in the 5◦ dead zone. The
ATLAS Wind Calibration Procedures and Instrumental Accuracies 7

value of the resistor caused vane values to be low by about 1% when outside

the dead zone. By changing the value of the pulldown resistor, this circuitry

error was decreased to about 0.2%. This circuitry error was in both Standard and Next Generation ATLAS systems. Both firmware and circuitry

errors are gain errors and theoretically range from negligible values for vane

orientations near 0◦ to a maximum of 3.6◦ at an orientation of 355◦. Note

also that firmware and circuitry errors are of opposite sign, and in theory

would compensate each other on Next Generation systems.

In late 2000, modifications were made to the vane alignment, firmware

and circuitry to correct for these errors. The calibration procedure was also

modified so that the vane output is now digitized with circuitry identical

to that used on the moorings, as opposed to the previous method of only

recording the analog output of the sensor.

2.3 Compass

The compass bearing of the buoy is measured with a magnetic flux gate

compass. Standard ATLAS buoys were typically equipped with model 63764

compasses manufactured by EG&G of Herndon, Virginia. EG&G stopped

the manufacture of this compass around 1996, just as the Next Generation

ATLAS was being developed. New Next Generation buoys were typically

equipped with model LP101-5 compasses manufactured by KVH of Middletown, Rhode Island. However, the different compasses can be used interchangeably in either type of ATLAS buoy, and EG&G compasses are used

in Next Generation buoys as Standard ATLAS systems are retired.

Primary coils in the compass are driven with a 400 Hz square wave

excitation signal. Secondary coils produce an 800 Hz square wave output

with a phase shift proportional to the direction of the ambient magnetic

field. The phase shift is measured by a counter which measures the time

between the leading edges of the 400 Hz excitation signal and the 800 Hz

sensing signal. More details on the general operation of fluxgate compasses

can be found in Watson (1992).

The fluxgate compass is housed in an aluminum tube with sensor I/O

boards, memory, and batteries. To account for the field created by other

electronics within this tube, the compass is calibrated after assembly of the

tube is complete. Calibrations are performed prior to deployment and are

checked again after recovery.

To calibrate the compass, the tube is attached to a compass calibration

stand and aligned to magnetic north. The area near the calibration stand

was surveyed for magnetic anomalies before installation and the stand was

carefully orientated relative to local magnetic north. An independent check

of the stand in April 2001 indicated that its orientation was correct to within

0.25◦ (Capt. Keith Sternberg, Sternberg Compass Adjusting and Nautical

Instrument Repair, personal communication).

During the compass calibration, the tube is rotated in 45◦ increments

through 360◦ clockwise then repeated counterclockwise. An average of the

clockwise and counterclockwise readings are made for each increment. From

differences between the raw compass output and its known orientation,
8 Freitag et al.

firmware internal to the tube (based upon a method outlined in Defense

Mapping Agency Publication No. 226) then creates a table of corrections

to reduce the size of the raw compass errors. Using the table, the compass

is retested at 15◦ increments. Residual errors (differences between the set

orientation and that reported by the corrected compass) are recorded to the

nearest degree. Prior to deployment, the maximum residual error allowed at

any test point is 5◦. Instruments with residuals larger than 5◦ are generally

not deployed. In a few rare cases, compasses with pre-deployment errors of

up to 8◦ at one or two calibration points, but with mean errors less than

1◦ and RMS errors less than 4◦ were deployed when no other compass was

available. A sample calibration is shown in Fig. 3d included in Appendix C.

3. Data Acquisition

Anemometer and compass outputs are measured simultaneously at a 2-Hz

rate and converted to vector-averaged orthogonal wind components. Mean

wind components are recorded over averaging periods of 6 min once per hour

on standard ATLAS moorings and 2 min every 10 min on Next Generation

ATLAS moorings.

The onboard processing of the wind velocity components is a multi-stage

process. First, the sensors sample the environment and generate an analog

signal. Next, input/output (I/O) boards, designed at PMEL, convert the

analog signals to digital counts. The analog signal from the wind speed

sensor is digitized by a frequency counter, reporting the number of cycles

counted in a 0.5 s interval. Resolution is approximately 0.2 m s−1 per count.

At the same 2-Hz rate, voltage from the anemometer vane is passed through

an A/D converter, and stored in memory, with a resolution of approximately

1.4◦ per count. The phase shift of the compass is likewise digitized to a

value with resolution of approximately 1.4◦ per count. Compass and vane

are summed to give wind direction relative to magnetic north. Orthogonal

components of the wind direction are obtained from a set of trigonometric

lookup tables which are then applied to the wind speed to give zonal (east–

west) and meridional (north–south) wind components. These components

are accumulated at the 2-Hz rate, averaged, and stored.

Wind direction as reported by the mooring is relative to magnetic north.

Rotation to true north is performed after the data are telemetered to shore,

by applying the magnetic variation for the specific location of the buoy.

4. Estimation of Sensor Accuracy

Accuracies are estimated from an ensemble of pre-deployment and postrecovery calibrations performed on each of the three types of sensors; wind

speed, wind vane, and compass. Calibration residuals of pre-deployment calibrations are used to estimate expected instrumental errors when moorings

are first deployed. Differences between pre-deployment and post-recovery

calibrations are used to estimate calibration stability while deployed.
ATLAS Wind Calibration Procedures and Instrumental Accuracies 9

Table 2: Wind sensor calibration statistics. Coefficients A0 and

A1 are the y-intercept and slope of the linear calibration equation.

The maximum residual for a given calibration is the largest absolute

difference between the wind tunnel speed and that predicted by the

calibration equation. N is the number of instruments calibrated

over which the statistics are computed. Units of A0 and maximum

residual are m s−1, and m s−1 per count for A1.

Standard

N Minimum Maximum Mean deviation RMS

Pre-deployment A0 856 –0.11 0.57 0.21 0.11 0.23

Pre-deployment A1 0.179 0.206 0.195 0.004 0.195

Pre-deployment –0.26 0.33 0.05 0.13 0.14

maximum residual

Post-recovery A0 240 –0.13 0.75 0.08 0.10 0.13

Post-recovery A1 0.183 0.206 0.197 0.004 0.197

Post-recovery –0.32 0.69 0.02 0.14 0.14

maximum residual

All A0 1096 –0.13 0.75 0.18 0.12 0.21

All A1 0.179 0.206 0.195 0.004 0.195

All maximum –0.32 0.69 0.04 0.14 0.14

residual

4.1 Wind speed

A total of 1096 wind speed calibrations performed between 1991 and 1999

were analyzed, of which 856 were pre-deployment calibrations and 240 were

post-recovery calibrations (Table 2). Wind sensor calibration coefficients

consist of a y-intercept (A0) and slope (A1) of the linear calibration equation.

Most of the calibration statistics were not significantly different between the

pre-deployment and post-recovery calibrations. The RMS of maximum calibration residuals (0.14 m s−1) did not vary between pre-deployment and

post-recovery calibrations. The mean slope coefficient, A1, increased by

only 1% between pre-deployment and post-recovery calibrations and the

standard deviation of A1 did not differ between the two. The mean yintercept coefficient, A0, for post-recovery calibrations was less than half

the pre-deployment value (0.08 m s−1 vs. 0.21 m s−1). However, the difference (0.13 m s−1) is small in absolute terms. Mean differences in A0 and A1

compensate each other, so that computed wind speeds, if based on either

pre-deployment or post-recovery mean values, would be nearly the same. At

wind speeds of 1 m s−1, values computed from mean pre-deployment coefficients are about 0.1 m s−1 larger than values computed from mean postrecovery coefficients; at 10 m s−1 differences are near zero, and at 20 m s−1

speeds computed from pre-deployment values are about 0.1 m s−1 smaller.

From the 1096 calibrations above, 168 pre-deployment/post-recovery calibration pairs were analyzed for individual sensor calibration drift. For

each calibration pair, differences in wind speed from application of pre-
10 Freitag et al.

Table 3: Wind speed difference between pre-deployment and postrecovery calibrations, normalized to one-year. Percent differences

are RMS differences divided by the nominal wind speed.

Standard

Nominal Mean deviation RMS Percent

wind speed difference difference difference difference

(m s−1) (m s−1) (m s−1) (m s−1)

1 −0.20 0.19 0.27 27.4

2 −0.18 0.17 0.25 11.7

3 −0.17 0.15 0.23 7.4

4 −0.15 0.15 0.22 5.3

5 −0.14 0.15 0.21 4.1

6 −0.13 0.17 0.21 3.5

7 −0.11 0.18 0.21 3.1

8 −0.10 0.21 0.23 2.8

10 −0.07 0.26 0.27 2.7

12 −0.04 0.32 0.32 2.7

14 −0.01 0.39 0.39 2.8

16 0.02 0.45 0.45 2.8

18 0.04 0.52 0.52 2.9

20 0.07 0.59 0.59 3.0

deployment vs. post-recovery calibration coefficients were computed at nominal speed values between 1 m s−1 and 20 m s−1, at 1 m s−1 to 2 m s−1

increments. Typically, moorings are deployed for about 1 year, so differences have been normalized to annual values, based on the actual number of

days deployed at sea (Table 3). It is presumed that sensor drifts result from

mechanical wear and/or corrosion occurring over the time that a sensor was

in the field.

Annual drift rates (based on RMS differences) ranged in absolute terms

from 0.2 m s−1 to 0.6 m s−1, with larger values at higher wind speeds. Alternately, we can characterize the drift as being less than or equal to 0.3 m s−1

or 3% of the measured value, whichever is larger. The sense of the mean

differences implies that, on average, recovered sensors are slightly overestimating low wind speeds and slightly underestimating high wind speeds.

4.2 Wind vane

The vane error was first evaluated by considering a large number of calibrations made over several years, but before the alignment, firmware and

circuitry problems described in section 2.2 were discovered. These early calibrations are reported here since they provide important information related

to error variance and stability over time. A second, smaller set of calibrations were performed recently to measure the total error including combined

firmware, circuitry, and alignment biases.

A total of 303 anemometer vane calibration checks performed in 1997

through 2000 were examined, of which 188 were pre-deployment calibration

checks and 115 were post-recovery calibration checks (Table 4). The mean
ATLAS Wind Calibration Procedures and Instrumental Accuracies 11

Table 4: Vane calibration error statistics for calibration checks

made before firmware, circuitry, and alignment errors were discovered. N is the number of instruments calibrated. Negative values

imply that measured orientation is clockwise, or to the right, of the

true orientation.

Standard

Type N Minimum Maximum mean Deviation RMS

(deg.) (deg.) (deg.) (deg.) (deg.)

Pre-deployment 188 –5.7 5.8 −0.28 1.13 1.16

Post-recovery 115 −22.5 14.0 −1.01 3.19 3.23

All 303 −22.5 14.0 −0.56 2.14 2.19

error was small (−0.28◦) for pre-deployment calibration checks, and only

slightly larger (−1.01◦) for post-recovery calibration checks. Thus the mean

error did not change appreciably during deployment. Since mean errors were

small, standard deviation and RMS error were nearly the same. The error

standard deviation was 1.13◦ for pre-deployment calibration checks with a

range of maximum errors of about ±6◦. As would be expected, errors were

larger for recovered sensors, with an error standard deviation of 3.19◦ and

range from −22◦ to +14◦. The error standard deviation was 2.14◦ for the

combined set of pre-deployment and post-recovery instruments.

The location of the wind vane dead zone was also checked before deployment and after recovery of the sensors. The values presented here (Table 5)

have been adjusted to reflect the alignment bias described in section 2.2.

On average, the width of the dead zone was 3.9◦ for both pre-deployment

and post-recovery checks, compared to a nominal value of 5◦ as specified by

the manufacturer. The location of the dead zone typically rotated counterclockwise about 1◦ during deployment, which is consistent with the change

in mean error in Table 4.

When in the dead zone, the vane orientation is reported as 0◦. Therefore,

on average, errors when in the dead zone would range from about −1◦ to

+3◦ at deployment and about ±2◦ at recovery. These values are comparable

in magnitude to ensemble errors outside the dead zone (given in Table 4).

Once the errors due to firmware, circuitry, and alignment errors were

discovered, we checked 23 vanes by recording their digitized output with the

alignment correctly measured. Of these, 21 had not been used in the field,

and two had been used for a 2-month long test on land at the Woods Hole

Table 5: Average location of the vane dead zone. N is the number

of instruments tested.

Type N Start End Width

(deg.) (deg.) (deg.)

Pre-deployment 188 359.1 3.0 3.9

Post-recovery 115 358.2 2.1 3.9

All 303 358.8 2.7 3.9
12 Freitag et al.

Table 6: Vane calibration error statistics for calibration checks

made after measurement errors were discovered. N is the number

of instruments calibrated. Negative values imply that measured

orientation is counterclockwise, or to the left, of the true orientation.

Standard

Type N Minimum Maximum Mean deviation RMS

(deg.) (deg.) (deg.) (deg.) (deg.)

Uncorrected 23 0.0 10.8 −6.8 2.0 7.1

Corrected for alignment 10 −0.9 9.8 −4.1 2.2 4.6

Corrected for alignment, firmware,

and circuitry

20 −2.3 5.6 −1.0 1.3 1.6

Oceanographic Institution, near the seashore. The mean error for these vanes

is clearly larger than that presented in Table 4 and is a better indication

of true mean error characteristics. The mean error was −6.8◦ (Table 6),

the sign of which implies that vane readings were biased in the counter

clockwise direction. For example, if the reported direction was 90◦, the true

direction would have been 96.8◦. The error standard deviation was 2.0◦, only

1◦ larger than the error standard deviation for pre-deployment calibration

checks made previously (Table 4). This suggests that the combined firmware,

circuitry, and misalignment errors can be characterized mainly as a mean

bias.

Beginning in fall 2000 the vane alignment method, firmware, and circuitry were modified to improve the accuracy of the vane measurement.

First, ten vanes were realigned and checked with the original firmware and

circuitry. Compared to the uncorrected vanes, the mean and RMS error of

this group decreased by 2.7◦ and 2.5◦, respectively. Four anemometers from

this group were deployed on moorings in October–November 2000. Soon after, a group of 20 vanes were evaluated using corrected alignment, firmware

and circuitry. These modifications reduced the mean error for the ensemble to 1.0◦ and the RMS error to 1.6◦, values that are comparable to the

resolution (1.4◦) of the digitization circuitry. Most moorings deployed in

November 2000 and all moorings deployed thereafter had or will have vanes

corrected for alignment, firmware, and circuitry.

4.3 Compass

A total of 355 compass calibrations performed in 1997 through 1999 were

examined. Of these 244 were pre-deployment calibrations and 111 were postrecovery calibration tests. Pre-deployment calibrations for the two types of

compass were similar with an overall RMS error of 1.44◦ for 244 calibrations

(Table 7).

The RMS error for 111 EG&G post-recovery calibration tests was 2.38◦.

Note that while the mean error is small (0.61◦), its sign is opposite to the

mean vane error in Table 6. At the time of this analysis the number of

recovered KVH compasses was much smaller and did not allow the compu-
ATLAS Wind Calibration Procedures and Instrumental Accuracies 13

Table 7: Compass calibration error statistics. N is the number

of instruments calibrated. Positive values imply that measured

orientation is clockwise, or to the right, of the true orientation.

Note that the manufacturer of three compasses included in the

“All Pre-deployment” group could not be identified and thus were

not included in the EG&G or KVH groups.

Standard

Type N Minimum Maximum Mean deviation RMS

(deg.) (deg.) (deg.) (deg.) (deg.)

EG&G re-deployment 135 −7 7 0.04 1.42 1.42

KVH Pre-deployment 106 −6 8 0.33 1.41 1.45

All pre-deployment 244 −7 8 0.18 1.43 1.44

EG&G post-recovery 111 −10 10 0.61 2.31 2.38

tation of stable error statistics. However, preliminary indications are that

the KVH post-recovery errors are somewhat larger than those of the EG&G.

As more KVH calibrations become available their performance will be evaluated quantitatively.

4.4 Wind direction

The wind direction error, dir, is the combined error of the compass, v, and

vane, c. The mean direction error is given by

< dir >=< v > + < c >

where < > designates ensemble means. In general, post-recovery sensors

have larger errors, so use of post-recovery calibration statistics gives a more

conservative (larger) error estimate. For the wind vane, most pre-deployment

calibrations and all post-deployment calibrations available at this time are

known to underestimate mean error due to the recently discovered errors in

alignment, firmware, and circuitry. Therefore, we use the ensemble mean of

−6.8◦ from Table 6 as an estimate of < v >. As indicated in Table 4, the

mean vane error differed by less than 1◦ between pre-deployment and postrecovery, thus use of the pre-deployment value from Table 6 is a reasonable

choice. Mean compass errors (Table 7) are of opposite sign compared to mean

vane errors and thus tend to compensate for vane errors. However, mean

compass errors are small and only marginally different from zero. Therefore as a conservative estimate for mean direction error we assume a mean

compass error of zero, so that the mean direction error, < dir >, is estimated to be −6.8◦. The negative sign implies that the measured direction

is counterclockwise, or to the left, of the true direction.

Assuming that the fluctuating components of the compass and vane errors are uncorrelated, an estimate for the standard deviation of wind direction errors may be computed as

σ = < 2

dir >

1

2 =



< 2

v > + < 2c >

1

2
14 Freitag et al.

where < 2

v > is the standard deviation of the vane errors about its mean,

and < 2

c > is the standard deviation of the compass errors about its mean.

A conservative estimate is obtained by using post-recovery values since,

at the beginning of a deployment and for some time thereafter, errors would

be smaller. Thus, we use 3.2◦ as the standard deviation for vane errors

(Table 4) and 2.3◦ as the standard deviation of compass errors. This leads

to an overall standard deviation of direction errors of 3.9◦. Combining the

mean and fluctuating components of the wind direction error then gives a

conservative estimate of total direction error of

RMS Wind Direction Error = ((6.8)2 + (3.9)2)

1

2 = 7.8◦

As noted in section 3.2, most sensors deployed in November 2000 and all

thereafter have improved vane alignment, firmware, and circuitry. Initial

calibrations of these modified systems indicate that post-recovery RMS vane

errors should be reduced to around 3◦ with little or no mean bias. In the

future, therefore, we expect that wind direction errors will be around 5◦ or

less.

5. Summary

The RMS error estimate for wind speed measured on Standard and Next

Generation ATLAS moorings was found to be less than or equal to 0.3 m

s−1 or 3% of the speed, whichever is greater. This is a conservative estimate

of overall instrumental error, as it was based upon the sensors’ recovered

state. When first deployed, the RMS error is estimated to be 0.14 m s−1

over wind speeds from 1 m s−1 to 20 m s−1.

The RMS error estimate for ATLAS mooring wind direction was found

to be 7.8◦, most of which was due to a mean wind direction error of –6.8◦

(counterclockwise, or to the left, of the true direction). This bias was primarily due to a misalignment of the vane and a bias in the vane digitization

firmware and circuitry. Calibration procedures and firmware versions have

changed with time since the first ATLAS mooring was deployed in 1984.

However, we believe that some mean direction bias has been present in the

majority of historical ATLAS data, even though the time history of the error

is not exactly known. Given the uncertainty in mean bias for older data, no

correction will be made to archived data from Standard ATLAS systems.

On the other hand, calibration procedures and firmware versions for

Next Generation ATLAS systems have been consistent with regard to vane

processing. For this reason we plan to apply a mean direction correction

to all data from Next Generation moorings. These moorings began entering the TAO Array in 1996 and will comprise 100% of the array after fall

2001. All moorings in PIRATA have been Next Generation systems. The

6.8◦ correction to be applied (Table 6) will be a significant improvement to

data obtained from systems deployed before new alignment procedures and

firmware were developed. It is estimated that the new alignment procedures

and firmware will essentially eliminate the directional bias and lower RMS

wind direction errors to about 5◦ or less in future deployments.
ATLAS Wind Calibration Procedures and Instrumental Accuracies 15

Direction bias between buoy winds and NSCAT satellite observations

have been reported to be of order 8◦ (Dickinson et al., 2001; Wentz and

Smith, 1999). This bias is of similar magnitude and sign as that found in

this study, indicating that a significant amount of the satellite-buoy bias

reported previously may be due to the vane errors reported here. To our

knowledge, however, no scientific study has been compromised as a result of

biases in ATLAS wind directions.

6. Acknowledgments

We would like to thank Pat McLain of PMEL, who designed the ATLAS

electronics and firmware and provided the authors with valuable details and

insights into their operation. This work was supported by NOAA’s Office

of Oceanic and Atmospheric Research, and by the Joint Institute for the

Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative

Agreement #NA67RJO155.

7. References

Anonymous (1980): Handbook of magnetic compass adjustment. Defense Mapping

Agency Pub. No. 226, 96 pp.

Dickinson, S., K.A. Kelly, M.J. Caruso, and M.J. McPhaden (2001): A note on comparisons between TAO buoy and NASA scatterometer wind vectors. J. Atmos.

Oceanic Tech., 18, 799–806.

Freitag, H.P., Y. Feng, L.J. Mangum, M.P. McPhaden, J. Neander, and L.D. Stratton (1994): Calibration procedures and instrumental accuracy estimates of

TAO temperature, relative humidity and radiation measurements. NOAA Tech.

Memo. ERL PMEL-104, 32 pp.

Hayes, S.P., L.J. Mangum, J. Picaut, A. Sumi, and K. Takeuchi (1991): TOGATAO: A moored array for real-time measurements in the tropical Pacific Ocean.

Bull. Am. Meteorol. Soc., 72, 339–347.

McPhaden, M.J., A.J. Busalacchi, R. Cheney, J.R. Donguy, K.S. Gage, D. Halpern,

M. Ji, P. Julian, G. Meyers, G.T. Mitchum, P.P. Niiler, J. Picaut, R.W.

Reynolds, N. Smith, and K. Takeuchi (1998): The Tropical Ocean-Global Atmosphere (TOGA) observing system: A decade of progress. J. Geophys. Res.,

103, 14,169–14,240.

Servain, J., A.J. Busalacchi, M.J. McPhaden, A.D. Moura, G. Reverdin, M. Vianna,

and S.E. Zebiak (1998): A Pilot Research Moored Array in the Tropical Atlantic

(PIRATA). Bull. Am. Meteorol. Soc., 79, 2019–2031.

Watson, J.D. (1992): Fluxgate compass limitations at high magnetic latitudes.

APL-US Tech. Memo. TM 8-92, 34 pp.

Wentz, F.J., and D.K. Smith (1999): A model function for the ocean-normalized

radar cross section at 14 GHz derived from NSCAT observations. J. Geophys.

Res., 104, 11,499–11,514.
16 Freitag et al.

Appendix A: Sample wind speed calibration

The results of a wind speed calibration of a TAO anemometer. A0 and A1

are the calibration coefficients computed from a linear least-squares fit of

the sensor output (counts) to the wind tunnel speed reported by a standard

anemometer. Units (other than the sensor counts) are m s−1.

Sensor serial number: 28510

A0 = 2.3924703e-01

A1 = 1.8729044e-01

Tunnel Sensor

Counts Speed Speed Residual

5.734 1.439 1.313 0.126

11.941 2.402 2.476 -0.073

21.311 4.188 4.231 -0.042

32.983 6.415 6.417 -0.002

41.095 7.951 7.936 0.015

54.896 10.477 10.521 -0.044

75.747 14.401 14.426 -0.025

104.812 19.916 19.870 0.046

MAXIMUM RESIDUAL = 0.1257
ATLAS Wind Calibration Procedures and Instrumental Accuracies 17

Appendix B: Sample wind vane calibration check

In the upper half of the form the sensor output (volts) is checked at 15◦

increments as recovered after use. In the lower half the sensor is rechecked

after replacement and reorientation of the potentiometer. The location of

the potentiometer dead zone is also measured.
18 Freitag et al.

Appendix C: Sample compass calibration

Firmware in the ATLAS electronics leads the technician through the calibration procedure. The compass is first rotated 360◦ clockwise and its output

recorded at 45◦ increments. The procedure is then repeated in the counterclockwise direction.

CAL.COMP

08/31/1999 20:36:04

Compass calibration

enter any comments desired.

end with <cr><cr>

PRECRUISE CAL OF TUBE 424T 31 AUG 99

Align the instrument to the angle

requested. Type <CR> when ready,

<CONTROL-Z> to quit.

align the instrument to 0 degrees

Compass reading was 8 degrees is this ok? Y

align the instrument to 45 degrees

Compass reading was 51 degrees is this ok? Y

align the instrument to 90 degrees

Compass reading was 94 degrees is this ok? Y

align the instrument to 135 degrees

Compass reading was 138 degrees is this ok? Y

align the instrument to 180 degrees

Compass reading was 181 degrees is this ok? Y

align the instrument to 225 degrees

Compass reading was 228 degrees is this ok? Y

align the instrument to 270 degrees

Compass reading was 276 degrees is this ok? Y

align the instrument to 315 degrees

Compass reading was 325 degrees is this ok? Y

align the instrument to 360 degrees

Compass reading was 8 degrees is this ok? Y

align the instrument to 315 degrees

Compass reading was 325 degrees is this ok? Y

align the instrument to 270 degrees

Compass reading was 276 degrees is this ok? Y

align the instrument to 225 degrees

Compass reading was 228 degrees is this ok? Y

align the instrument to 180 degrees

Compass reading was 181 degrees is this ok? Y

align the instrument to 135 degrees

Compass reading was 136 degrees is this ok? Y

align the instrument to 90 degrees

Compass reading was 94 degrees is this ok? Y

align the instrument to 45 degrees

Compass reading was 51 degrees is this ok? Y
ATLAS Wind Calibration Procedures and Instrumental Accuracies 19

Next the firmware calculates a table of corrected compass values for each

of the 256 possible raw compass output values. This table is stored onboard

the instrument and corrects the compass in real time. The coefficients, P0

through P4 may be used to rebuild the table, should it be corrupted in the

firmware.

Calculating table...

P0= -312

P1= 50

P2= -100

P3= 50

P4= 75

0123456789ABCDEF

F10000 FD FD FF 00 01 02 03 04 05 06 07 08 09 0A 0B 0C

F10010 0D 0E 0F 10 11 12 13 14 15 16 17 18 19 1A 1B 1C

F10020 1D 1E 1F 20 21 22 23 24 25 26 27 28 29 2A 2B 2C

F10030 2D 2E 2F 30 31 32 33 34 35 36 37 38 39 3A 3B 3C

F10040 3D 3E 3F 40 41 42 43 44 45 46 47 48 49 4A 4B 4C

F10050 4D 4E 4F 50 51 52 53 54 55 56 57 58 59 5A 5B 5C

F10060 5D 5E 60 61 62 63 64 65 66 67 68 69 6A 6B 6C 6D

F10070 6E 6F 70 71 72 73 74 75 76 77 78 7A 7B 7C 7D 7E

F10080 7F 80 81 82 83 84 85 86 87 88 89 8A 8B 8C 8D 8E

F10090 8E 8F 90 91 92 93 94 95 96 97 98 99 9A 9B 9C 9D

F100A0 9E 9F A0 A1 A1 A2 A3 A4 A5 A6 A7 A8 A9 AA AB AC

F100B0 AD AE AE AF B0 B1 B2 B3 B4 B5 B6 B7 B8 B9 BA BB

F100C0 BC BD BE BE BF C0 C1 C2 C3 C4 C5 C6 C7 C8 C9 CA

F100D0 CB CC CD CE CF D0 D1 D2 D3 D4 D5 D6 D7 D8 D9 DA

F100E0 DB DC DD DE DF E0 E2 E3 E4 E5 E6 E7 E8 E9 EA EB

F100F0 EC ED EE EF F0 F1 F2 F3 F4 F5 F6 F7 F8 FA FB FC

F10100 08 31 19 99 00 00 7F 69 FF FF FF FF FF FF FF FF
20 Freitag et al.

The compass is rotated again. This time the corrected compass output is

recorded at 15◦ increments. Angles are computed from the compass output

(counts) by application of the factor 360/256.

do you want a cal test? Y

08/31/1999 20:39: 27

Compass calibration

enter any comments desired.

end with <cr><cr>

TEST 424 31 AUG 99

Enter the test angle value, then <enter>.

The system will respond with the calibrated

value for that angle.

TO QUIT enter an angle value of 999.

TEST ANGLE CORRECTED ANGLE RAW ANGLE CORRECTED CNTS RAW CNTS

0 4 83 6

15 18 23 13 16

30 32 37 23 26

45 46 51 33 36

60 60 65 43 46

75 76 80 54 57

90 89 93 63 66

105 104 108 74 77

120 120 124 85 88

135 135 138 96 98

150 149 152 106 108

165 163 166 116 118

180 180 181 128 129

195 195 197 139 140

210 210 212 149 151

225 225 228 160 162

240 239 243 170 173

255 255 260 181 185

270 270 277 192 197

285 285 293 203 208

300 301 308 214 219

315 319 325 227 231

330 335 340 238 242

345 349 354 248 252

360 4 8 3 6

999

done testing