Deep-Sea Research I - ICDC Datenzentrum · PDF fileTrial versions were produced by several...

ARTICLE IN PRESS

Deep-Sea Research I 57 (2010) 812–833

Contents lists available at ScienceDirect

Deep-Sea Research I

0967-06

doi:10.1

� Corr1 Be2 Af

journal homepage: www.elsevier.com/locate/dsri

Instruments and Methods

On depth and temperature biases in bathythermograph data: Developmentof a new correction scheme based on analysis of a global ocean database

Viktor Gouretski a,b,�, Franco Reseghetti c

a Alfred Wegener Institute for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany1

b KlimaCampus, University of Hamburg, Grindelberg 5, 20144 Hamburg, Germany2

c ENEA, ACS-CLIMMED, Forte S. Teresa, 19032 Pozzuolo di Lerici, Italy

a r t i c l e i n f o

Article history:

Received 15 April 2009

Received in revised form

10 March 2010

Accepted 25 March 2010Available online 3 April 2010

Keywords:

Expendable bathythermograph

Mechanical bathythermograph

Hydrographic data

Temperature bias

Global temperature anomaly

37/$ - see front matter & 2010 Elsevier Ltd. A

016/j.dsr.2010.03.011

esponding author.

fore 15 December 2008.

ter 15 December 2008.

a b s t r a c t

The World Ocean Database 2005 as of May 2009 is used to estimate temperature and sample depth

biases of expendable (XBT) and mechanical (MBT) bathythermographs by comparing bathythermo-

graph temperature profiles with more accurate bottle and conductivity/temperature/depth (CTD) data.

It is shown that the application of depth corrections estimated earlier from side-by-side XBT/CTD inter-

comparisons, without accounting for a pure thermal bias, leads to even larger disagreement with the

CTD and bottle reference temperatures. Our calculations give evidence for a depth-variable XBT fall-rate

correction with the manufacturer-derived depth being underestimated in the upper 200 m and

overestimated below this depth. These results are in agreement with side-by-side inter-comparisons

and direct fall-rate estimates. Correcting XBT sample depths by a multiplicative factor which is constant

with depth does not allow an effective elimination of the total temperature bias throughout the whole

water column. The analysis further suggests a dependence of the fall rate on the water temperature

which was reported earlier in the literature. Comparison among different correction schemes implies a

significant impact of systematic biases on the estimates of the global ocean heat content anomaly.

& 2010 Elsevier Ltd. All rights reserved.

1. Introduction

Estimation of the long-term temperature changes in the globalocean, the main heat reservoir of the Earth climate system, hasreceived growing attention during recent years as a part of theclimate change issue. Accumulation of temperature observationsin the oceanographic data record has stimulated attempts toquantify temperature changes in the global ocean. An averageglobal ocean warming of 0.31 1C has been reported between 1955and 1993 (Levitus et al., 2000), corresponding to a heat contentincrease of around 20�1022 J heat for the 0–3000 m layer. Usingadditional temperature profiles, Levitus et al. (2005) obtainednew estimates for a progressive warming of the global ocean,yielding an increase of the heat content of 14.5�1022 J between1957 and 1997 for the upper 3000 m layer, and determined byfitting a linear trend. In both studies, a pronounced heat contentmaximum between 1973 and 1982 was found. Gouretski andKoltermann (2007) (hereinafter GK07) argued that the ‘‘warmdecade’’ in the Levitus et al. (2005) calculations was an artefactdue to biases in the XBT data. Lyman et al. (2006) presentedestimates of a global upper-ocean heat content anomaly from1993 through 2005 using a subsurface temperature data set from

ll rights reserved.

profiling floats and found a cooling event between 2003 and 2005,with a net heat loss of 3.2 (71.1) 1022 J. However, the reported

cooling was later found to be a data artefact (Schiermeier, 2007).

As explained by Willis et al. (2009), the cooling was a combination

of two errors, some Argo floats’ pressure sensor errors, and biases

in XBT data.The above-mentioned examples of instrumentation flaws

made it clear that systematic errors in oceanographic data needto be examined more closely. Correcting XBT data in a mannersimilar to the method by GK07, Levitus et al. (2009) (hereafterL09) provided new estimates of the global heat content changeand confirmed the overall global warming, with the inter-decadalvariability of the heat content being reduced due to the correctionprocedure. Ishii and Kimoto (2009) re-evaluated the global oceanheat content time series using a different method to correct XBTand MBT data and also found that corrections eliminate theartificial warm pattern during 1970s. Wijffels et al. (2008)(hereafter W08) hypothesized that the temperature bias in XBTdata was solely due to the depth errors and suggested respectivetime-varying depth corrections. The latter were used in the heatcontent calculations by Domingues et al. (2008) which, similar toIshii and Kimoto (2009) and L09, also result in time series withoutthe artificial warming pattern during the 1970s.

Instruments for measuring temperature and other seawaterparameters have undergone significant changes since the begin-ning of routine observations of the world ocean, with mechanical

www.elsevier.com/dsri

dx.doi.org/10.1016/j.dsr.2010.03.011

ARTICLE IN PRESS

V. Gouretski, F. Reseghetti / Deep-Sea Research I 57 (2010) 812–833 813

instruments being supplanted by more precise electronic devices.However, this change in ocean instrumentation was gradual, sothat since the 1960s a mixture of both mechanical and electronicinstruments makes up the global oceanographic database. Timeseries of the global heat content anomaly during the last 50 yearsobtained by different research groups (Palmer et al., in press)demonstrate a mean spread of about 5�1022 J (in the layer0–700 m) which is partly linked to the residual biases in thebathythermograph data. As these data contributed the majority ofthe subsurface temperature data before the introduction ofprofiling floats and may continue to provide some fraction offuture subsurface temperature measurements, understandingsystematic errors in the XBT and MBT data is important for thecorrect estimation of global ocean heat content changes. In thisstudy, we further investigate the causes for depth and tempera-ture biases in the XBT and MBT data and suggest respectivecorrections. An assessment of the systematic error impact onglobal temperature anomaly estimates is also presented.

Fig. 1. Vertical temperature gradient at 150 m depth based on the WOCE Global

Hydrographic Climatology (Gouretski and Koltermann, 2004). Positive direction of

the depth axis is downward.

2. Data

2.1. General description and precision

The NODC hydrographic data collection – World OceanDatabase 2005 (WOD2005) (Boyer et al., 2006) (hereinafterreferred to as B06) – was the main temperature data set for thisstudy (download of additions to WOD2005 as of May 2009). Aftera crude range check was applied to the observed temperatureprofiles, they were interpolated on a regular 5 m grid in thevertical using the interpolation scheme of Reiniger and Ross(1968). Profiles with less than three retained observed-level datawere not used. For the time period 1967–2008, a total of 596,663CTD; 1,980,277 bottle and low-resolution CTD (ocean station datatype in WOD2005); 2,012,461 XBT and 2,309,891 MBT profileswere retained for the analysis. Measurement accuracy, as listed inTable 1, renders the CTD data by far the most precise among theinstrument types considered, both in temperature and in depth.The assessment of sample depth errors is crucial for the detectionof long-term temperature variability in the ocean, since sampledepth errors are translated into temperature errors in case of a(typically) non-zero vertical temperature gradient. To assess themagnitude of possible equivalent temperature errors and in orderto bring the calculated temperature differences between thebathythermograph and CTD/bottle data into a geographicalcontext, the global vertical temperature gradients werecalculated, using gridded data from the WOCE (World OceanCirculation Experiment) Climatology (Gouretski and Koltermann,2004), which does not use any XBT or MBT data. For a givensystematic depth error of 1 m, typical equivalent temperature

Table 1Temperature and depth accuracies for different instrument types.

Instrument Temperature accuracy (1C)

Reverse thermometers on Nansen

bottles

�0.01 a

CTD (STD) 0.001 for modern CTD models older CTD types

accurate a, c

XBT 0.2 d

MBT �0.1 d

a Estimate according to Emery and Thompson (1997).b Estimate according to Wust et al. (1932).c World Ocean circulation experiment specified 0.002 1C as a target CTD accuracy.d Manufacturer values.

error may well exceed 0.1 1C above 150 m in regions with a strongthermocline (Fig. 1).

2.2. Reference data

In this study, bottle and CTD temperature data are used as areference against which the bathythermograph data are validated.Temperature data from all types of profiling CTD floats wereexcluded from this analysis because of reported pressure errors(Willis et al., 2009). Historically, Nansen bottles with reversingthermometers were the first devices specifically designed fortaking deep water samples and measuring temperature at depth.A detailed description of the method and its accuracy was givenby Wust et al. (1932), based on the results of the Germanoceanographic expedition in the South Atlantic in 1925–1927.Pairs of pressure-protected and unprotected thermometers wereused for the determination of sampling depths by means of thedifference between the temperatures of the two thermometers.Since such paired thermometers enabled sufficient accuracy onlyat depths greater than about 200 m, sampling depths of shallowcasts were usually calculated from the amount of wire paid outand the angle of the wire from the vertical, at the height of thehydrographic winch. Such depth estimates were often subject toconsiderable errors, as the real shape of the wire with attachedbottles, under specific local conditions (wind, currents), remainedunknown. It was not until the mid-1930s that the thermometricsample depth determination became general practice (Iselin,1936).

Sample depth accuracy Year of

introduction

o6% full scale (0–200 m) bo1.5% full scale

(4200 m) b

Before 1897

less 0.015% full scale 1966

5 m (0–250 m) 2% below 250 m 1966

41% of sample depth c 1940

ARTICLE IN PRESS

Fig. 2. Normalized histogram of the deepest data from XBT profiles from the

World Ocean Database 2005 (Boyer et al., 2006).

V. Gouretski, F. Reseghetti / Deep-Sea Research I 57 (2010) 812–833814

Observations by means of Nansen bottles have been graduallyreplaced by the CTD—an electronic sampler and profiler forcontinuous measurements of temperature and salinity (conduc-tivity) from oceanographic ships or other platforms. Introduced inthe mid-1960s, CTDs had almost entirely replaced Nansen bottlesby the 1980s. For instance, at the Woods Hole OceanographicInstitution Nansen bottles were entirely supplanted by the CTD in1981 (Warren, 2008). Personal communications with colleaguesfrom the United Kingdom, France, Australia and the USA suggestthe transition period from Nansen casts to CTDs as 1980–1985.However, in some countries which contributed substantially tothe oceanographic databases (for instance, the former SovietUnion), this replacement did not apparently take place until the1990s. From the author’s personal experience, a large oceano-graphic fleet of the Hydrometeorological Service of the formerSoviet Union still used Nansen bottles at the end of 1980s. Animportant difference to the older Nansen cast procedure is thatthe bottles of the Rosette sampler can be closed at arbitrary depth,which is measured by a precise pressure sensor.

2.3. XBT data

XBT probes were developed in the early 1960s when the USNavy required a cost-effective, robust, and easy-to-use instru-ment to estimate the sound speed profile for military application.Trial versions were produced by several companies, but thewinning model was developed by Francis Associates (thenSippican Corporation, now Lockheed Martin Sippican Inc., here-inafter SC), which started a mass production in the late 1960s(Francis and Campbell, 1965; Arthur D. Little Inc., 1965). By theearly 1990s, XBTs had almost completely replaced mechanicalbathythermographs. XBT probes were also manufactured by othercompanies, such as Plessey Company (UK) under SC license,Sparton of Canada Ltd. (Canada), and Tsurumi Seiki Corp. (TSK),the other official manufacturer, for Japanese buyers. Recently,Electronic Corporation of India Ltd. (ECIL) and Kerala StateElectronics Development Corporation Ltd. (Keltron) also manu-factured a small amount of probes.

The XBT probe is a slim body falling through the water columnat a speed of about 6.5 m/s. It measures the seawater temperaturewith a negative temperature coefficient (NTC) thermistor em-bedded in the zinc nose and connected to the on-boardacquisition device by means of a coated, twin-copper wireunreeling from spools within the probe and in the on-boardlauncher. XBTs have no pressure sensors, so that the depth of theprobe is calculated from the time elapsed since the probe hitsthe seawater. There are several types of XBT probes designedfor different ship velocities and depth ranges, but in thisstudy only the most widely used XBT types, T-4, T-6, T-7 andDeep Blue (hereinafter DB), have been analyzed. When the probetype information was not available in the database, a histogramof the deepest sampled level (Fig. 2) was used to define themaximum depth level to distinguish between different XBT types.Two maxima on the histogram mark the nominal maximumsample depth of the shallower (460 m, T-4 and T-6) and deeper(760 m, T-7 and DB) XBT versions: we selected 550 m as themaximum sample depth for the T-4/T-6 probes and 900 m for T-7/DB probes. As the T-7 and DB probes may also be used for bottomdepths of less than 550 m, the above criteria cannot distinguishbetween the probe types in this case unless the information onthe probe type is available. The percentage of deep-reachingprobes used in shallow water is unknown, but is expected to besmall. B06 note that numerous XBT profiles obtained after thepublications of Hanawa et al. (1994, 1995) (hereinafter referred toas H9495) report sample depth according to the H9495 fall-rate

equation (hereinafter FRE). In all cases, when the metadataindicated the use of H9495 coefficients, sample depths wererecalculated to original manufacturer values using a correctionfactor of 0.9675.

2.4. Errors in the XBT data

A number of factors can lead to errors in XBT data:(1) differences in physical characteristics of the probes;(2) instability and differences in acquisition systems; (3) transienteffects in the near-surface layer; (4) launching conditions;(5) varying ambient conditions; and (6) inaccuracy of the FRE. Itshould be noted that the majority of the XBT bias studies havebeen focused on the last issue.

According to SC (M. Gifford, personal communication) thephysical characteristics of the XBT probes, which determine theirdynamics in seawater (shape, weight, and wire), remainedessentially unchanged since the start of production in the late1960s. The two known modifications of the manufacturingprocess included: (1) change in the coating process, resulting ina slight reduction of the weight of wire per unit length in air after1995 (the respective weight in the water remained unchanged);(2) introduction in 1999 of a net around the spool to protectthe wire during transportation and in order to improve thedeployment reliability. SC regularly conducts tests to ensurethe manufacturing stability, including thermistor, wire and thecomponents of the XBT recording system. The uncertainties setby SC are 0.2 1C on the MK21 recording system, 0.1 1C on thethermistor, and 2% or 5 m on the estimated depth, whichever isgreater.

Since the early 1970s, several inter-comparison experimentswere conducted in order to establish the accuracy of XBTmeasurements during field operations. One of the most extensiveand complex inter-comparison study was conducted by Anderson(1980), who compared about two thousand XBT temperatureprofiles (T-4 type) with concurrent hydro- and STD casts, thermistorchains, and surface towed thermistors. The overall XBT systematictemperature errors were found to be in the range (�0.19, +0.24 1C),close to the manufacturer’s 70.2 1C envelope. Below we reviewseveral possible factors leading to errors in XBT data.

2.4.1. Inaccuracy of the fall-rate equation

The XBT manufacturer provides the FRE in the formZ(t)¼At�Bt2, where Z is the probe depth, t is the elapsed time,A denotes the terminate fall velocity and the quadratic term takesaccount of the probe’s weight loss due to wire de-reeling, whichleads to the decrease of speed with time. To determine thenumerical values of the coefficients, SC conducted tests in waters

ARTICLE IN PRESS


with different characteristics; however, the results of those testsare not presently available to the oceanographic community. Thevalidity of the manufacturer’s FRE was checked during numerousinter-comparison experiments, where XBT temperature profileswere compared with collocated and simultaneous CTD profiles.The XBT/CTD inter-comparisons were carried out in variousgeographical areas by different institutions implementing theirown procedures and methods. Almost all inter-comparisons gaveevidence of the XBT fall rate being faster than given by theoriginal FRE.

To establish new FRE coefficients, further inter-comparisontests under controlled experimental conditions were initiated atthe beginning of the 1990s. Using a method independent oftemperature errors to compare side-by-side XBT and CTD profiles,new coefficients for the depth-time equations were calculatedseparately for T-7/DB and T-4/T-6 probes, and a unique pair ofcoefficients was obtained for four XBT data types (T-4/T-6 andT-7/DB) manufactured by SC and TSK (H9495). Only TSK T-6probes evidenced a less satisfactory agreement with the newequation. It was recommended to correct XBT depths using thenew FRE or simply to multiply the original depths by a factor of1.0336. Similar analysis (Rual et al., 1996) was also conducted forSparton T-7 probes with the results being in agreement withthose for the SC and TSK probes.

Since the late 1970s, a multitude of studies report various FREcoefficients in peer-reviewed literature, reports, or personalcommunication (Table A1). These coefficients were obtainedusing a slightly different definition of collocation with differentcalculation methods and are based on a different number of XBT/CTD pairs. Respective linear depth correction factors calculatedfor the depths below 100 m display significant scattering (Fig. 3),with a mean value of 1.0275+0.0034 (which is lower than thecorrection factor of 1.0336 recommended by H9495).

Though the new FRE coefficients are based on inter-compar-ison experiments in 11 regions of the World Oceans most of themare within the tropical and subtropical belts with their higherwater temperatures. Studies have shown that the new FRE maynot be overall valid due to dependence of water viscosity ontemperature. Fall-rate estimates on cruises occupied in colderregions (Wisotzki and Fahrbach, 1991; Turner, 1992; Owens,1993; Thadathil et al., 2002) indicate rather the validity of theoriginal SC FRE. According to Green (1984), the kinematicviscosity of the seawater increases typically by about 50%between the near-surface layer and 750 m depth. In case of afully turbulent flow around the probe, the hydrodynamic dragcoefficient would exhibit an increase by less than 0.1% for a 5 1Ctemperature change (and the corresponding fall speed decrease ofabout 0.05%). On the other hand, the Reynolds number for the XBTprobe (�3.5�105) estimated by Seaver and Kuleshov (1982)

Fig. 3. Estimates of the linear depth correction factor from 64 side-by-side XBT

versus CTD inter-comparisons listed in Table A1. In case when only FRE

coefficients were reported, the XBT sample depths were calculated and the

average linear correction factor was obtained for the water column below 100 m.

suggests the flow regime around the probe to be transitionalbetween the laminar and partly turbulent state. In this case, astronger dependence of the drag force on water viscosity isexpected.

2.4.2. Characteristics of the probes and acquisition systems

The weight of the probe is an important parameter influencingthe fall rate, with the effect of weight loss being included in theFRE. SC stated that the characteristics of the zinc nose for T-4/T-6/T-7/DB XBT types were designed to have the same ‘‘wet weight’’to guarantee the same fall velocity in the water. In fact, both thewet weight and the probe external dimensions together define thehydrodynamic behaviour of the probe. Seaver and Kuleshov(1982) estimated that weight variations of 2% would result in8.8 m depth error at 750 m depth. According to SC, the nominalprobe weight in the air is 730.975 g, with the uncertainty for thewet weight being 72 g. Our laboratory measurements for probesmanufactured since 1992 confirm the stability for the nose weightin air within less than 1.5 g for both probe types (T-4/T-6 and T-7/DB), but indicate a slight decrease of the total XBT weight in theair, probably explained by a decrease in wire density after 1996(wire density changed from about 0.125 to about 0.120 g/m). Theweights in the air were found to be within the range 732.6–736.5 g for T-4 probes manufactured in 1992–1995, in the range726.4–731.0 g for T-4 probes manufactured in 1998–2004, andin the range 727.2–734.9 g for DB probes manufactured in2007–2008. Though the amount of wire usually allows a greaterthan nominal depth to be reached by the probes (down to about520 and 880 m for T-4/T-6 and T-7/DB, respectively), themeasurement accuracy can be significantly deteriorated becauseof possible wire tension, different probe spin rate and alteredprobe stability (M. Gifford, personal communication).

Since the introduction of the XBT probes, several differentrecording systems were used. During the 1960–1970s the datawere recorded by analogue strip-chart devices. Later, since themiddle of the 1980s the transition toward electronic digitizerstook place (Emery et al., 1986). In strip-chart recorders, the chartpaper moved for 88.0 s nominally (for T-4 probes), with atolerance of 2% (Plessey-Sippican, 1975; IntergovernmentalOceanographic Commission (IOC), 1975). The chart drive hasbeen frequently indicated as a possible source of uncertainty(Fenner and Cronin, 1978; H9495), and a regular calibration checkof the strip-chart system was always strongly recommended bySC. It was a common practice to read XBT analogue recordsvisually, with an accuracy of 0.2 1C in temperature and 2 m indepth, but some digitizer systems reduced temperature and depthreading errors to 0.05 1C and 0.9 m, respectively (Anderson, 1980).

Few comparisons between different recording systems areavailable in the literature, but only for digital devices. Wright andSzabados (1989) compared four different acquisition systemsused during the same survey and found an agreement within�0.06 to 0.10 1C for the temperature range 0–30 1C. Szabados(1991) (IOC, 1991) found no statistically significant differencesbetween the XBT measurements when using analogue or digitalrecorders. The XBT recorder BathySystem SA810 used in the endof 1980s was found to be responsible for the so called ‘‘bowing’’effect, as insufficient current in the recorder produced an artificialtemperature increase with depth up to +0.7 1C (IOC, 1992).Zanasca (1996) reported a small difference of 0.02 1C when twoMK12 systems were connected to the same set of probes inlaboratory tests. Kizu and Hanawa (2002a) found temperaturedifferences up to 0.1 1C among recorders manufactured in Japan,and identified another acquisition system responsible for the‘‘bowing’’ effect. D. Snowden et al. (personal communication,March 2008) compared MK21 and Devil recorders, manufactured,

ARTICLE IN PRESS


respectively, by SC and Turo Technology Pty Ltd. (Australia), andmeasured differences at a level of 0.05 1C. We conductedlaboratory tests on some MK12 and MK21 recorders used oncruises in Mediterranean Sea, using a simulated XBT setup withhigh precision resistances (accuracy 0.014%), an XBT test-probe,and with some XBT probes placed in a calibration bath. Theabsolute difference between the recorders varied within 0.05 1C at�2 1C and 0.08 1C at 30 1C, well within the nominal instrumentalaccuracy. According to our laboratory and on-board tests, somerecorders exhibited a temporal variability of about 0.05 1C in theirperformance on a daily scale, when calibrations with the sametest-probe, cables and devices were repeated. Several studiesinvestigated thermistor temperature errors, though the laboratorytests usually do not reproduce in situ conditions, with a properwater flow around the probe. In 1988–1989, bath calibrationswere conducted by Sy (IOC, 1989) on SC DB and T-7 Spartonprobes at six temperatures in the range 1–20 1C. It was found thattemperature differences were a linear function of temperature,with the slope of 0.0029 1C/1C for T-7 probes, and from 0.0056 to0.0092 1C/1C for DB probes. Comparisons conducted at the NURCLaboratories in La Spezia (Italy) in the 1990s for a few hundred T-4/T-7 probes at T¼12 and 22 1C, found XBT temperatures beinghigher than the reference bath by approximately 0.02 1C, with astandard deviation from 0.02 to 0.04 1C (Zanasca, 1996). Calibra-tion tests in 2004 and 2008 with DB probes conducted in the sameLaboratories (Fig. 4) confirmed the dependence of the thermistorerror on bath temperature at a level compatible with the resultsby Sy (IOC, 1989).

2.4.3. Start-up transients and motion in near-surface layers.

Thermal temperature biases significantly deteriorate thereliability of XBT measurements near the surface (Kizu andHanawa, 2002b) because XBT probes need a finite time to adjustto the temperature of the surrounding water. The thermistor timeconstant of 0.1 s (the time required to detect 63% of a step-likethermal signal) matches well with the 10 Hz sampling ratenormally implemented in recording devices. However, larger

Fig. 4. Mean difference between the XBT (TXBT) and reference (TBath) temperature a

Laboratories conducted in 2004 (Reseghetti et al., 2007) and 2008 Same probes were t

values of the time constant (up to 0.63 s) are quoted in theliterature (Magruder, 1970; Shenoi, 1976; Perez-Martell andCianca, 1997; Australian Oceanographic Data Centre, 1999).Roemmich and Cornuelle (1987) noted that a significant differencein temperature between the probe storage room and seawaterinduces a sort of thermal shock affecting measurements near thesurface. They also estimated an electronic transient of about 0.1 sdue to the recording system, whereas a longer transient mightoccur due to the thermal inertia of the XBT zinc nose. In 2008 theseeffects were qualitatively confirmed in the calibration bath atNURC Laboratories. It was found that an agreement of XBTtemperatures with the bath temperature within the nominalaccuracy (70.11C) was achieved only after a certain delay timeinterval depending on the temperature difference between thebath and the XBT storage room. The observed delay was changingat a rate of about 1 s per each degree of temperature difference.We note, however, that the flow of water in the calibration bathwas slower compared to the real fall conditions for XBT probes.

As a solution to the transient problem, it was recommended toreject temperature values within the uppermost layer. Accordingto the recommendation of the IOC (1975), temperature valuesrecorded by XBT between the surface and 3.7 m should beconsidered unreliable and not used. Stegen et al. (1975) andAustralian Oceanographic Data Center (AODC) (1999) eliminatedmeasurements between the surface and 4 m depth, Manzella et al.(2003) suggested a cut off at 5 m depth, and Kizu and Hanawa(2002b) proposed a cut varying from 2 to 10 m depending on therecording system. Reseghetti et al. (2007) proposed a phenom-enological correction scheme calculating an Empirical TimeConstant (ETC), the average amount of time needed before therecorded temperature becomes constant within the nominalaccuracy during the first second. In this scheme, the valuesrecorded down to about 2 m depth are rejected and all otherrecorded values are shifted upward by 2 m. The procedureallowed a significant reduction of the observed XBT warm biasdown to the base of the thermocline.

Following the recommendation of one of the reviewers weestimated the size of temperature error depending on the total

nd the respective standard deviations from calibrations of DB probes at NURC

ested with different recording systems.

ARTICLE IN PRESS


response time lag of the XBT system. The estimates were obtainedby using the vertical profile of the global mean vertical tempera-ture gradient calculated from the global ocean climatology byGouretski and Koltermann (2004). Even for smoothed climatologictemperature gradient profile the XBT system time lag would causea positive temperature bias from 0.025 to 0.10 1C for the time lag of0.1 and 0.3 s, respectively, at the depth of the maximal seasonalthermocline at about 40 m depth. Correspondingly, in case ofstronger vertical gradients typical for observed profiles highervalues of the time lag induced temperature bias are expected.

Apart from the pure thermal transient effects, the dynamics ofthe XBT probe during the first few seconds may differ significantlyfrom the stable regime in lower layers and thus introduce biasesin the XBT data (M. Gifford, personal communication). Thebehaviour of the XBT probe at the beginning of its cast is difficultto model because of the ‘‘splash’’ effect, the deviation of the angleat which the XBT enters the water from the vertical, and theinfluence of waves, ship wake, etc. Direct observations in a specialfacility could clarify the issue but are currently unavailable for theoceanographic community. The unknown initial velocity of theprobe, which depends on the height of the launch platform,further complicates the issue. Green (1984) analyzed possiblevariations of the real depth of the probe as a function of the initialvelocity and estimated the depth overestimation to be about 2 mfor the initial velocity exceeding the nominal one by a factor ofthree. Field tests with pairs of SC T-4 and DB XBT probes launchedat 2.5 and 8.0 m heights did not indicate any dependence of deptherror on the launch height (Reseghetti et al., 2007), probably dueto a small number of probes tested. We repeated similar testswith 12 SC DB probes in 2008 but again could not establish arelation between the launch height and XBT fall rate.

Generally, only the data below approximately 100 m are usedfor the determination of the FRE, so that different probe dynamicsin the near-surface layer are essentially neglected by the FRE.Theoretical considerations (see, for instance, Landau and Lifschitz,1966, y11) suggest that the movement of a body in a fluid isaccompanied by the transfer of momentum to the ambient fluid,and the change of this momentum with time leads to anadditional force acting on the body, which should slow down itsvelocity. Though the XBT is a slim body, it usually enters the waterunder oblique angle, and it takes some time for the probe toachieve a stable rotation with its main axis aligned with gravity.

An overestimation of the true depth by the XBT probes withinthe upper layer was indicated in several earlier studies. Thus,Hallock and Teague (1992) determined the position of selected

Fig. 5. (a) XBT–CTD depth difference of the thermocline location based on 124 side-by-

Mediterranean Sea between 2003 and 2009 and (b) frequency histogram of the dept

respectively (for interpretation of the references to color in this figure legend, the read

temperature profile features on collocated pairs of XBT and CTDprofiles (118 profiles and 16 features) and found the XBT depthsto be on average of 4 m shallower than the CTD depths near thesurface. According to their Fig. 4, XBTs underestimate the realdepth within the upper 75 m. Rual et al. (1994, 1996) estimatedfall rate for 372 SC T-4, T-6, T-7 probes and for 63 Sparton T-7probes, respectively. Though the data from the upper 100 m layerwere not used for the determination of the FRE coefficients, bothstudies clearly evidence change in the XBT depth error sign in thedepth range 40–70 m (see Fig. 2 in Rual et al., 1994, and Fig. 1 inRual et al., 1996), implying depth overestimation within the topseveral tens of meters. Wright and Szabados (1989) investigateddepth error for several XBT types, using four different recordingsystems. Averaged for the upper 50 m layer, mean XBT–CTD depthdifferences were about 1 m, again indicating depth overestima-tion (this estimate is based on their Fig. 3 and represents theaverage over all four recorder types). Seaver and Kuleshov (1982)obtained a positive XBT–CTD depth difference for the upper130 m layer comparing XBT profiles (corrected for temperatureerror) with collocated and concurrent CTD profiles. Within theupper 100 m the T-7 XBTs systematically overestimated depth byabout 1 m (see their Fig. 4). Fedorov et al. (1978) reported onpositive XBT–CTD depth differences observed in the subtropicalWest Atlantic for water temperatures higher than 18 1C. Thoughthe authors tend to explain this positive difference by asystematic depth error in their CTD instrument, the alternativeexplanation through XBTs’ slower fall rate is also possible. Kezeleand Friesen (1993) calculated sample depth errors for 59 Spartonand 26 SC T-7 probes launched within 1 min of a CTD cast. Theirresults also indicate a overestimation of the sample depth withinthe layer 50-100 m.

We compared a total of 124 XBT/CTD side-by-side pairs (XBTtypes T-4/T-6/T-7/DB) obtained on cruises during the 2003–2004and 2007–2009 in the Mediterranean Sea. Using the manufac-turer’s FRE for each profile pair, XBT–CTD depth differences weredetermined at the depth of the thermocline or by temperaturepatterns in the upper part of the profile which allowed forreliable depth estimation (Fig. 5a). For the thermocline positionsoccurring between the surface and 130 m, 35 pairs showed zeroXBT–CTD depth difference, 28 pairs showed a negative difference,and 65 pairs showed a positive depth difference, with thehistogram peak corresponding to the XBT depths being 1 mdeeper than the reference CTD depths (Fig. 5b). It should be noted,that though the differences are within the manufacturer’s 75 muncertainty they seem to be systematic.

side profile pairs obtained during the XBT/CTD inter-comparisons on cruises in the

h differences. Red and blue correspond to T-4/T-6 and T-7/Deep Blue XBT types,

er is referred to the web version of this article).

ARTICLE IN PRESS


2.4.4. Direct measurements of XBT fall rate in the near-surface layer

The above indications of the depth overestimation within theupper layer were obtained by indirect methods comparing CTDand XBT temperature profiles. This depth overestimation may be(1) due to a slower fall rate; (2) due to transient effects of thethermistor and/or the whole acquisition system (e.g., time lag dueto a finite reaction time of the XBT system); or (3) due to botheffects. At least two technical reports give evidence of a slowerXBT fall rate within the uppermost layer. Bartz (1992) describesdirect measurements of the XBT fall rate in a 19-m deep watertank for Sparton T-5, T-4 and T-7 probes. The fall rate determinedfor 18 probes (T-4, T-7 and T-5 probe types with and without thewire on the inner spool) was on average about 20% slower whencompared to the velocity for the SC FRE. However the probes hadweights which were 15–20 g less compared to the typical meanvalues. The observed probe spin rate of 3.5–7.5 revolutionsper second was also lower compared to the nominal value of 12–15 rev/s. A significantly lower spin rate indicates that the probeshave not reached the nominal spin rate within the first 3 s.Magruder (1970) reported on the average terminal XBT velocity of6.066 m/s which was reached at about 5 m depth. Unfortunately,no details about the test facility were provided.

In order to further investigate the probe behaviour in theuppermost layer, we conducted XBT drops in shallow water at thetest site near La Spezia, Italy, with bottom depth of 7.55, 15.4, 27.3and 47.2 m. These direct measurements gave the average velocitya few percent lower compared to the nominal one (Fig. 6). All butone estimate suggest fall rate lower than the nominal valueobtained by H9495. Videos taken at 3 m depth showed a spiralmotion of the XBT probes accompanied by a wake of bubbles anda reduced spin rate of about 5–8 Hz. The helical trajectory of T-7probes was also reported by Seaver and Kuleshov (1982) for theupper 10 m. Air entrapment among coils of the wire couldpotentially influence the fall rate in the uppermost layers.However, according to Kezele and Friesen (1993) air entrapmentamounts to only 2% of the water displaced by the XBT probe andbecomes negligible below 20 m.

Fig. 6. Direct measurements of the XBT fall rate within the near-surface layer.

Thickness of the near-surface layer in different experiments is indicated by color.

Fall-rate values correspond to the velocity averaged within the near-surface layer.

Results obtained by Magruder (1970) (1), Bartz (1992) (3), and in this study (2) are

indicated in the centre of the circles, with vertical bars representing observation

errors. Horizontal lines correspond to the nominal fall rate (e.g. the value of the

first coefficient in the fall-rate equation) for the original manufacturer (grey) and

Hanawa et al. (1994) (magenta) fall-rate equations (for interpretation of the

references to color in this figure legend, the reader is referred to the web version of

this article).

2.4.5. Summary

A brief review of possible causes for errors in the XBT datademonstrates that several errors have a systematic (intrinsic)

nature and cannot be detected using conventional statisticalapproaches to flag outliers. Evaluation of XBT accuracy during sixinter-comparison experiments between 1971 and 1975 showedthat even with the omission of obviously erroneous profiles madewhen XBT systems malfunction, there remain enough erroneousprofiles to positively bias the average temperature (Anderson,1980). Commenting on XBT accuracy studies by Anderson (1980),SC stated that insufficient wire and thermistor insulation wouldcause higher temperature readings in a majority of cases.Similarly, the ‘‘bowing’’ effect also causes a positive temperatureerror. A systematically lower fall rate within the near surfacewould tend to increase XBT temperatures systematically as watertemperature typically decreases with depth. Similar effects wouldresult from an XBT system response lag. An increase of waterviscosity due to decreasing temperature would cause a system-atically lower fall rate for probes dropped in moderate and highlatitudes compared to subtropical and tropical belts.

3. XBT–CTD temperature difference

Below we statistically compare XBT (and MBT) temperaturedata to reference data in geographical and temporal bins to lookfor biases. We conclude that these biases can be modelled as asum of time-varying but depth-independent temperature offsetand time-independent but depth-varying FRE errors.

3.1. Binning of the XBT and CTD data

To investigate systematic components of the bias in the XBTdata, we first performed temporal and spatial binning of theoriginal temperature profiles retained after the quality controlprocedure, which consisted of a temperature range checkaccording to Conkright et al. (2002). To bin the data spatially,the ocean was subdivided into 169 one-degree belts between 791Sand 901N. Each belt was further subdivided into boxes, with thenumber of boxes being defined as the integer value of 360/cos(f),where f is the central latitude of the respective 1-degree belt. Thedifference in area between the individual boxes does not exceed afew percent. During the time-binning step, all valid measure-ments in each spatial bin falling within the respective calendarmonth between January 1967 and December 2008 are averaged toobtain a binned (monthly) temperature. Binning was performedat each 5-m level, and sets of binned temperature profiles wereobtained separately for two XBT types (T-4/T-6 and T-7/DB,respectively), for all XBT types blended together, and for the blendof CTD and bottle data, with the latter providing a reference forthe analysis. As only few observations are typically availablewithin a bin (Fig. 7a, d), the median, as opposed to the arithmeticaverage, was used to calculate binned temperatures, as it reducesthe influence of outliers and because the statistical outlier checkdoes not work properly for small samples.

In the present analysis, we define the binned temperatureprofiles from two different data types as overlapping if they referto the same spatial bin (grid-box) and fall within the sameyear and month. The choice of the time and spatial bins was thetrade-off between the data abundance and the necessity tohave enough bins for stable estimates of differences betweenthe bathythermograph and reference data. Typically about100–300 overlapping binned temperature profiles are availableeach month for the shallow XBT types between about 1970 and2000, with typically less than 50 binned profiles per month after2001. As opposed to the shallow type, T-7 and DB overlapping

ARTICLE IN PRESS

Fig. 7. Characteristics of the XBT monthly binned profiles overlapping with the respective CTD binned profiles and used for the bias estimations: (a, d) percentages of bins

with numbers of profiles per bin; (b, e) number of binned profiles vs. time and (c, f) total number of original profiles vs. maximal sample depth. Upper and lower rows

correspond to T-4/T-6 and T-7/Deep Blue XBT types, respectively. Size of the spatial bins is �111�111 km2.


binned profiles are the most numerous between 1990 and 2000,but even during this decade they amount to only 50–150 profilesper month (Fig. 7b, e). The number of overlapping profiles shows aclear annual cycle with more overlapping binned data availableduring the summer of the northern hemisphere. Distribution ofthe overlapping data with depth reflects the general decrease ofthe total number of both XBT and reference observations. Step-like changes of the box number with depth (Fig. 7c, f) correspondto the abrupt change of the last sampled depth of original profiles,which often terminate at some round ‘‘standard’’ value.

Temperature differences between the overlapping binned XBTand CTD/bottle profiles were calculated for each month and grid-box, and the median of the differences for all overlapping bins ateach 5-m level was finally computed. In agreement with L09 wefind that using the median leads to a smaller overall difference(offset) compared to the arithmetic mean, and the higher offsetvalues in the case of using the arithmetic mean are explainedthrough the presence of outliers and non-normality of thefrequency distribution of XBT–CTD/bottle differences.

Each individual temperature difference is affected by the noisein the data due to temporal and spatial variability within eachgeographical box. However, this variability most probably israndom in nature (the distribution of both XBT and reference datawithin a particular bin is random) and can be effectively averagedout for a sufficiently large sample size. For the 42-year timeperiod there is a total of 106980 overlapping profiles for theblended XBT data set (T-4, T-6, T-7, and DB probe types). Onaverage, about 10% of XBT and 14% of CTD/bottle binned profilesfrom the total number of profiles contributed to the presentanalysis. This 10% of binned profiles correspond to about 200,000original, not-averaged XBT profiles and may be compared with afew tens to a few hundreds of CTD/XBT profile pairs, availabletypically from the side-by-side inter-comparisons (for instance,the H9495 assessment of the new coefficients for the XBT fall-rateequation was based on a total of 372 XBT/CTD profile pairs). Werecognize that our method is a trade-off between a noisy

statistical analysis with many samples and a less noisy side-by-side analysis with much fewer samples.

There are a total of 11,190 distinct geographical boxes with atleast one overlapping profile during the time period 1967–2008.Maps of the time-mean XBT–CTD temperature offsets for the 300-m level indicate generally higher XBT temperatures compared tothe reference CTD/bottle data (Fig. 8). The overlapping bins aremuch more abundant in the moderate latitudes of the NorthernHemisphere, where the general warm bias is clearly evident.Further to the south, in the subtropical and tropical latitudes, anincrease in the percentage of boxes with negative bias is observed.According to the vertical temperature gradient map (Fig. 1), thisarea is characterized by the strongest (negative) temperaturegradient. (Here and throughout the paper the origin of coordinatesis at the sea surface with depth increasing downwards). In thepresence of a systematic depth underestimation in XBT data (withprobes falling faster than stated by the manufacturer, according toH9495), a negative vertical temperature gradient would translatethis depth error into a negative temperature bias.

3.2. Observed characteristics of the mean XBT–CTD temperature

difference for the blended, binned data

For the subsequent bias analysis it is useful to examine thedepth-dependent temperature offsets DT¼TXBT�TCTD plotted as afunction of three different dependent variables. To obtain theoffset distribution as a function of time and depth, the median ofthe individual offsets of all grid-boxes was computed for eachmonth (Fig. 9a). In agreement with GK07 and L09, the monthlyglobal offsets exhibit a maximum within the upper layer, withvalues gradually decreasing with depth. However, the depth ofthe maximum offset in our calculations is observed at the depth of20–30 m, compared to about 50–70 m in L09 calculations, whichwe explain by a coarser vertical resolution in their calculations.Also, a warm anomaly during the 1970s revealed in GK07

ARTICLE IN PRESS

Fig. 8. Time-mean (1967–2008) XBT–CTD/bottle temperature difference at 300 m level for 111�111 km2 spatial bins: (a, c) calculated over all 11,190 bins and

(b, d) calculated for spatial bins where absolute value of the vertical temperature gradient at 300 m does not exceed 0.005 1C/m (left panels for T-4/T-6 probes, right panels

for T-7/Deep Blue probes). Original manufacturer’s fall-rate equation was used.

Fig. 9. (a) Monthly global temperature bias (TXBT�Treference) plotted as a function of depth and time for the blended binned XBT data set including T-4, T-6, T-7 and Deep

Blue XBT types and (b) histogram for the number of XBT/CTD overlapping monthly bins. At each level monthly bias is represented by the median of all spatial bins.

Fig. 10. Monthly values of the global mean vertical temperature gradient in the

upper 450 m layer based on the monthly binned XBT temperature profiles and

plotted as a function of depth and time (estimation done for the binned data

including T-4, T-6, T-7 and Deep Blue XBT types). At each level monthly vertical

gradient is represented by the median of all spatial bins.


calculations is confirmed by the analysis. Except for the timeperiod before the mid-1980s, a transition from positive offsetswithin the upper 100 m layer to negative values at deeper levels isobserved. The offset pattern becomes noisier after about year2000 as the number of overlapping bins decreases considerably(Fig. 9b). Imposed on the long-term offset change, a significantseasonal component is observed. We argue that seasonalvariations in the strength of the vertical temperature gradientcould be responsible for this effect if a systematic error in sample

depth is present. Monthly mean vertical temperature gradients at5-m levels were calculated using the binned temperature profilesand show a clear annual cycle with a typical amplitude of 0.1 1C/min the upper 100 m layer (Fig. 10). To further investigate offsets inthe XBT data, binned profiles were grouped according to thetemperature value at 10 m depth (T10 m) by using 0.5 1C tempe-rature bins. At each level the median of the offsets, irrespective oftime, was computed for each T10 m bin (Fig. 11a). The procedureresults in a rather vertically uniform positive offset for the T10 m

range from 3 to 23 1C and above 460 m, with a maximum near 20–30 m, in agreement with Fig. 9a. For T10 m423 1C a transition frompositive offset values above 150–200 m to negative values isobserved, and we explain it again through a depth-error inducedbias. This effect is more pronounced in the warm water regions ofthe World Ocean with their typically stronger stratification. Asomewhat different offset pattern below the nominal maximumdepth of shallow XBT probes is attributed both to a much smallernumber of the T-7/DB XBT probes and to their differentcharacteristics. For the time being, we do not have an explanationfor the negative offsets in cold waters (T10 mo3 1C) within theupper 150–200 m diagnosed only for the T-4/T-6 data. According tothe frequency histogram, the majority of overlapping binnedprofiles comes from the ocean regions with T10 m between 14and 29 1C (Fig. 11b), with only a small percentage of boxescontaining extremely high (429 1C) or extremely low (o1 1C)10-m temperatures.

ARTICLE IN PRESS

Fig. 11. (a) Time-mean global temperature bias (TXBT�Treference) plotted as a function of sample depth and water temperature at 10 m level (T10 m) and (b) histogram for

the number of individual offsets falling into the respective 0.5-degree T10 m temperature class (estimation done for the binned data including T-4, T-6, T-7 and Deep Blue

XBT types). At each level the time-mean temperature bias is represented by the median of all individual monthly bins falling into the respective 0.5-degree T10 m

temperature class.

Fig. 12. (a) Time-mean zonally averaged parameter distributions plotted as a function of sample depth and latitude: (a) temperature bias (TXBT�Treference); (b) vertical

temperature gradient; (c) water temperature; (d) histogram for the number of individual offsets falling into 1-degree latitude belts (estimation done for the binned data

including T-4, T-6, T-7 and Deep Blue XBT types). At each level the respective time-mean parameter is represented by the median of all individual monthly bins falling into

a 1-degree latitude belt.


Plotting XBT offsets versus latitude provides another insightinto the bias pattern (Fig. 12a). Here, the median of all grid-boxoffsets within 1-degree latitude belts was computed. Similar toFigs. 10a, 11a, an offset maximum is observed within theuppermost layer. Though the geographical distribution of theoverlapping profiles is extremely inhomogeneous (the majority ofprofiles is situated between 25 and 451N, Fig. 12d), an offsetpattern remarkably symmetrical about the equator is observed. Inboth hemispheres, poleward of 35–40 degrees latitude, positivetemperature biases are observed at least down to the maximumT-4/T-6 sample depth. In lower latitudes a transition from positiveto negative values is observed at the depth of about 100 m. Twooffset minima are clearly seen in both hemispheres between 30–101S and 10–301N, respectively. The two minima are divided byan intermediate relative offset maximum within the equatorialzone. The geographical offset pattern described above can be

explained by comparison with the zonally averaged distributionsof the vertical temperature gradient (Fig. 12b) and watertemperature (Fig. 12c). A close correspondence between theoffset minima in the tropics and the stronger stratification inthese latitudes is evident and points to a systematicunderestimation of the XBT sample depth, which (in the case ofa strong negative vertical gradient) translates into a negativetemperature bias. The intermediate offset values within theequatorial belt correspond to a weaker vertical temperaturegradient here due to a general doming of isotherms (Fig. 12c).

3.3. Thermal bias in XBT data

A common feature of the offsets plotted as a function of thetemperature at 10 m and geographical latitude is a domination of

ARTICLE IN PRESS

Fig. 13. Yearly temperature bias (TXBT�Treference) plotted as a function of depth and time for the weakly stratified regions (9@T/@z9o0.005 1C/m) for T-4/T-6 (a) and T-7/

Deep Blue (b) XBT types. Depth-averaged monthly temperature bias (TXBT�Treference) for the weakly stratified regions (green curves) and for the whole World Ocean (blue

curves) for T-4/T-6 (c) and T-7/Deep Blue (d) XBT types. Standard errors are shown as vertical bars. At each level the number of degrees of freedom is equal to the number of

monthly collocated bins within the year. Black dots correspond to the independent estimates of the XBT thermal bias summarized in Table A3 with error estimates (grey

bars) (for interpretation of the references to color in this figure legend, the reader is referred to the web version of this article).


the positive offset values for ocean regions with weak stratifica-tion (Figs. 11a, 12a). In most regions of the World Ocean, anegative vertical temperature gradient is observed (Fig. 1), exceptfor some layers in polar regions where temperature increaseswith depth (for instance, between the layer of the AntarcticWinter water and the Circumpolar Deep water). The generallypositive temperature bias is thus in obvious disagreement withthe statement that XBT depths are systematically underestimatedby the FRE as documented by H9495 and many other researchgroups. Positive temperature bias is also observed within theupper mixed layer with its weak stratification, which is evident bycomparing Fig. 12a and b for the uppermost 20-m thick layer. Thisapparent disagreement with H9495 results (which suggest rathera negative temperature bias) may be explained by the assumptionof XBT data being positively biased in temperature. Unfortunately,reliable estimates of this thermal bias from side-by-side XBT/CTDinter-comparisons are not as numerous as the estimates ofsystematic depth errors, probably because most of the studieswere concentrated on the uncertainties in the FRE equation, andbecause the respective analysis methods were intentionally madeto be independent from possible errors in XBT temperature.

To estimate the thermal bias in XBTs, we selected boxes wherethe absolute vertical temperature gradient does not exceed0.005 1C/m (see map in Fig. 9b, d). This reduces the total amountof overlapping profiles by a factor of 3.5. As a consistent change inthe total bias is observed for the blended XBT data set between450 and 500 m (Figs. 9a, 11a, 12a), separate binned datasets wereused for T-4/T-6 and for T-7/DB XBT types. To estimate thermalbiases for each level, the median of all individual offsets wascomputed for each calendar year between 1967 and 2008(Fig. 13). Given the limit imposed on the value of the verticaltemperature gradient, the error from confusing thermal bias withthat due to the depth error is estimated to be smaller than 0.075and 0.12 1C for T-4/T-6 and for T-7/DB XBT types, assuming adepth error of 3% at 500 and 800 m, respectively.

Compared to the all-data mean offsets (Fig. 9a), an offsetdistribution more homogeneous over the whole depth range isobserved. The thermal bias both for shallow and deep XBT typesvaries with time and attains a maximum near 1975–1980, similarto the total temperature bias. The yearly thermal bias values forindividual levels were then averaged over depth (Fig. 13c, d). Wenoted above that limiting calculations to the boxes with weakstratification significantly reduces the amount of data, with

thermal bias estimates obviously becoming noisier. Using thesame procedure we also computed yearly depth-averaged biasesbased on all overlapping binned profiles, regardless of themagnitude of the vertical temperature gradient. The time seriesof depth-averaged offsets are very similar in both cases, withoffsets for the low-gradient regions being systematically higher.The average difference between the two time series was found tobe 0.0594 1C for T-4/T-6 probes and 0.026 1C for T-7/DB probes.We explain these differences as a result of the XBT depth-errorcomponent providing negative input to the depth-averaged bias.Considering an overall similarity of the both depth-averaged timeseries and taking into account the higher reliability of thetime series based on all grid-boxes, we shift the all-data meantime series of depth-averaged bias by 0.059 and 0.026 1C, and usethem as the best estimate of the thermal bias for shallow anddeep XBT modifications, respectively (Table A2). Among the XBTaccuracy studies available to us, we selected those with reliableestimates of the depth-independent temperature bias (Table A3)obtained usually by comparing XBT and CTD temperature profileswithin thermostads or within the surface mixed layer. In spite of arelatively large uncertainty in these estimates, a general agree-ment with calculated temperature bias is observed (Fig. 13c, d).We have also considered the possibility of using the surface biasas an estimate of the ‘‘pure’’ temperature bias, as the depth erroris zero when the probe enters the water. Using the surface bias asa proxy to the thermal bias gives qualitatively similar results.However, transient effects described above along with a highernoise level in the near-surface temperature measurementssignificantly reduce the reliability of using such estimates of thethermal bias.

3.4. Method of estimating XBT depth bias

3.4.1. Decomposition of the total temperature bias

After the overall warm temperature bias was documented byGK07, a method of correcting the XBT data was suggested by W08where the observed XBT–CTD temperature difference DT waspostulated to be only due to the error in the XBT depthestimation: z¼zx�z, where zx and z are the XBT and the truesample depth, respectively. The depth error is translated into atemperature bias:

B¼ Tx�T ¼ z@T=@z, ð1Þ

ARTICLE IN PRESS

Table 2Summary of methods used to correct thermal and/or depth biases in XBT data a.

Correction

method, figure

Thermal bias, BT Depth correction factor, s

1 (Figs. 14a, 15a) BT(t)¼0 s¼1 (original

manufacturer FRE)

2 (Figs. 14b, 15b) BT¼BT (t) estimated from the

binned data set

s¼s(zx, t)—best fit

3 (Figs. 14c, 15c) BT¼BT (t) estimated from the

binned data sets¼s(zx, t, DT)—best fit

4 (Figs. 14d, 15d) BT¼BT (t) estimated from the

binned data sets¼s(zx, DT)—best fit

5 (Figs. 14e, 15e) BT¼0 s¼1.0336 (Hanawa et al.,

1995)

6 (Figs. 14f, 15f) BT¼0 s¼s(t) from Wijffels et al.

(2008)

7 (Figs. 14g, 15g) BT¼BT (t, zx) estimated from the

binned data set

s¼1

a t—year, zx—sample depth, DT¼Yo(zx)�Y (zx), where Yo(zx) and Y (zx) are

temperatures averaged between the surface and level zx for the all-data mean

temperature profile and for the individual temperature profile, respectively.


where qT/qz represents the local temperature gradient, Tx and T

correspond to the XBT and reference temperature, respectively.W08 applied formula (1) to calculate z using the climatologicvalues of qT/qz. The application of the above formula has itslimitations. Though (1) holds for all values of the vertical gradientmethod, its application in the regions with weak stratification(qT/qz�0) could lead to unacceptably large errors in z.

As noted above, the observed bias distributions in weaklystratified waters (Fig. 13) suggests the presence of a thermal biasin the XBT data which is independent of error in depth. In thefollowing, we assume that the total temperature bias is given bythe sum of two biases: a depth-error-independent thermal bias (apure temperature bias) and the bias arising due to a systematicXBT depth error. For each pair of overlapping binned profiles withcoordinates (x, y) in each monthly time bin t, we represent thetotal temperature bias b at the XBT depth level zx as

bðx,y,zx,tÞ ¼ bT ðx,y,tÞþzðzx,tÞgðx,y,zx,tÞþeðx,y,zx,tÞ: ð2Þ

The first term on the right side represents the thermal bias(assumed to be depth-independent), the second term describesthe bias due to the error in depth z(zx, t) where g(x, y, zx, t)denotes the vertical temperature gradient, and the last term, S(x,y, zx, t), represents the noise in the data due to imperfectcollocation and simultaneity of original profiles. In order to reducerandom noise e the total bias (2) is averaged over all overlappingspatial bins (grid-boxes) within each calendar year t to obtain ayearly global mean temperature bias:

Bðzx,tÞ ¼ BT ðtÞþzðzx,tÞGðzx,tÞ, ð3Þ

where BT and G represent globally averaged yearly values of thethermal bias and of the vertical temperature gradient, respec-tively. It is assumed in this bias model that the systematic deptherror remains constant within the year t for all spatial bins.Introducing a depth correction factor s(zx, t)¼zx/z (z is the truedepth) we finally obtain

Bðzx,tÞ ¼ BT ðtÞþzUxð1�sðzx,tÞ�1ÞGðzx,tÞ: ð4Þ

In our calculations, we change incrementally the value of s(zx, t)for each binned profile to find an optimal depth correction factorsopt, which corresponds to the minimal root mean square residualbias B(zx, t)�BT(t). This method does not require estimation of thevertical gradient; the modified temperature profiles are simplyinterpolated back to the standard 5 m levels using the interpola-tion scheme by Reiniger and Ross (1968). A similar procedureto estimate XBT depth bias was implemented by Wright andSzabados (1989) for the data from side-by-side XBT/CTDinter-comparisons, with incremental depth shifting done withinthe 50 m segments. Following the suggestions of one reviewer, weestimated optimal depth correction factors separately for theshallow and deep XBT types as the fall rate was expected tobe different for these two groups. Using the same data set ofbinned temperature profiles we have also conducted a numberof experiments to evaluate other correction schemes. Thesummary of experiments is given in Table 2 and the residualbiases for each correction method at standard levels are displayedin Figs. 14 and 15 as functions of year, binned temperature at10-m levels and profile latitude.

Total temperature biases in the original data (SC fall-rateequation, Figs. 14a, 15a) are qualitatively similar to the biases forthe blended XBT data set (Figs. 9a, 11a, 12a). Applying the biasmodel (4), a significant reduction of the original bias is achievednot only in the time/depth bias representation, where the residualbias is minimized, but also for the residual bias pattern displayedversus the 10-m level temperature and latitude. In contrast to thecorrection schemes by H9495 and W08, where a depth-indepen-dent stretching factor was assumed, our optimal depth correction

factor exhibits considerable variations with depth (Fig. 16),indicating that the XBT sample depth is overestimated aboveabout 200 m and underestimated below this depth.

3.4.2. Dependence of the XBT fall rate on temperature

In spite of the overall significant reduction of the original biasby the bias model (2) (Figs. 14b, 15b, Table 2), a systematicpattern of negative biases in tropical belts (more clearly seen inthe original bias distribution with depth and latitude) indicatesthat the depth correction factor which is optimal for the wholeglobal ocean may not be optimal regionally. Using the same time-dependent thermal bias we calculated time-mean profiles of thedepth correction factor for latitude belts selected according to thezonally averaged bias pattern: equatorial belt (121S–121N),tropical belt (25–121S and 12–251N) and for the mid-latitude belt(80–351S and 35–801N) (Fig. 17a). We hypothesize thatsystematic differences in depth correction profiles observedbetween the latitude belts are related to the differenttemperature in these geographical regions. Considering theresults by Kezele and Friesen (1993), Owens (1993), Thadathilet al. (2002), Kizu et al. (2005, 2008), and one would expect aslower fall rate of XBT probes in colder waters, and our Fig. 17a isin agreement with this expectation. We further assume that ateach depth level the XBT depth error is connected to the meanvalue of the kinematic viscosity above this level which is directlyrelated to the mean water temperature. Shown in Fig. 17b areprofiles of the mean temperature between the surface and therespective level calculated using binned temperature data withinthe latitude belts selected above. In spite of the increased noisedue to a reduced number of overlapping profiles for selected belts,slightly lower values are evident for the equatorial belt comparedto the tropical belt, implying a lower fall rate within theequatorial belt. This result agrees with the near-equatorialwater column being colder due to the doming of isothermscompared to the tropical belts. We parameterize the effect of thechanging water temperature (viscosity) on the fall velocity (andeventually on the depth correction factor) as

sðx,y,zx,t,Yo,YÞ ¼ soðzx,tÞþk½YoðzxÞ�Yðx,y,zx,tÞ�, ð5Þ

where Yo(zx) and Y(x, y, zx, t)] are the mean temperature betweenthe surface and the level z for the all-data mean temperatureprofile, and for an arbitrary individual binned profile, respectively.Correspondingly, the bias model is represented by the formula

Bðzx,tÞ ¼ BTðtÞþ/zxðx,y,tÞð1�sðx,y,zx,tÞ�1Þgðx,y,zx,tÞS ð6Þ

ARTICLE IN PRESS

Fig. 14. Total XBT temperature bias diagnosed in the XBT data for different correction methods as listed in the Table 2. The three leftmost panels in each row show original

(a) and residual (b–g) biases at depths plotted as a function time, temperature at 10 m, and latitude, respectively. The three rightmost panels show the number of

collocated binned profiles (h) and the bias reduction after correcting the data (i–n). The bias reduction is defined as 9Boriginal9�9Bcorrected9, where Boriginal and Bcorrected

correspond to the total temperature bias in the original and corrected XBT data, respectively (results obtained for the T-4 and T-6 XBT types).


where /yS denotes averaging of monthly values within the yeart, and s is represented by (5). The optimal value of k¼0.0015 wasdetermined by comparing residual bias in experiments done withdifferent values of k. Comparison between the two bias models(Figs. 14b, 15b and 14c, 15c) shows that taking account fordifferences in water temperature allows further reduction ofresidual bias within the tropical belts.

3.4.3. Analytical form of the XBT depth correction factor

Our calculations show that the variations in the vertical profileof the depth correction factor from year to year (Fig. 16) arerelatively small, with the standard error below 200 m being of theorder of 0.01–0.02. A relatively low scattering of the yearly valuessuggests a high temporal stability of the XBT fall-rate character-istics. This result may be directly linked to the efforts which theXBT manufacturer puts into maintaining the stability of the XBTproduction process over the years (M. Gifford, personal commu-nication). As suggested by our direct fall-rate measurements therequired depth correction (a upward shift of XBT depths) can not

be explained by the slightly reduced fall rate near the surface(Fig. 16). A time lag in the XBT system seems to provide a moreplausible explanation. Following the suggestion of one reviewer,the time-mean profile of the stretching factor, So(z), was fitted toan analytical formula which can conveniently be applied tocorrect the XBT sample depths:

SoðzxÞ ¼ a�b=zx�cz2x for zx4b, ð7Þ

where coefficients have the following numerical values:a¼1.0164, b¼2.7 m, and c¼0 for shallow XBT types; a¼1.0261,b¼4.60 m and c¼1�10�8 m�2 for deep XBT types. Sample depthzx is given in meters.

Using the unique time-independent depth correction factorallows a significant reduction of the original temperature bias(Figs. 14d, 15d), so that we recommend to use formula (7) for thecorrection of the XBT sample depths. However, the application oftime-independent corrections still results in a small residualtime-variable bias. Further reduction of this residual bias mayrequire the use of time-varying depth corrections.

ARTICLE IN PRESS

Fig. 15. Same as Fig. 14 but for the T-7 and Deep Blue XBT types.


3.4.4. Comparison with other bias correction methods

The total temperature bias was also calculated for three othercorrection schemes using the same set of binned temperatureprofiles. The right side panels of Figs. 14 and 15 represent adifference between the absolute value of the original bias(Figs. 14a, 15a) and the absolute value of the residual biasafter the application of the respective correction method. AsFigs. 14b–d and 15b–d show, our model of bias decomposition ischaracterized by the smallest residual bias compared to thecorrection methods by H9495, W08 and L09. Applying the H9495depth correction factor of 1.0336 (Figs. 14e, 15e) results in theoverall increase of the total temperature bias, as the originaltemperature values (already positively biased due to the thermalbias) are placed to a deeper (and generally colder) level thusleading to an even higher total bias. Our zonally averaged biascomputed using H9495 corrected depths agrees with Fig. 3 inW08 paper, displaying an overall positive total temperature bias.Since practically all yearly values of the time-varying depthcorrection factor suggested by W08 are less than unity and sincethese corrections are applied to the depths already increased bythe H9495 factor, the W08 method essentially returns the XBTdepths to the original values based on SC FRE, so that the residualbias pattern (Figs. 14f, 15f) resembles the original one, but with a

reduced temporal bias variation. In the last experiment (Figs. 14g,15g), the corrections were calculated similar to GK07 and L09.Here the bias was eliminated by subtracting the global-averageddifferences (e.g. the original bias pattern as displayed versusdepth and time) from each XBT profile, respectively, at each levelfor each year in which the XBT profile was obtained. This methodseems to achieve a better bias elimination compared to the W08method.

3.5. Discussion

Our experiments with the global XBT data set have demon-strated that the effective removal of the total temperature bias ispossible only if (1) depth-error-independent temperature bias istaken into account and (2) the depth stretching factor is allowed tobe variable with depth. The existence of the ‘‘pure’’ temperaturebias (thermal bias) was repeatedly confirmed in the literature andwe attribute its origin to the whole acquisition system (thermistor,wire, recorder, cables). According to our calculations, the thermalbias remains generally within +0.05 1C limits after 1990, so thatthe profound bias maximum in the 1970s is most probablyexplained by the bias inherent to older analogue strip-chart

ARTICLE IN PRESS

Fig. 16. Profiles of the XBT optimal depth correction factor for the bias model presented in this paper. Time-mean values (black dots) of the depth correction factor are

shown for T-4/T-6 (a) and T-7/Deep Blue (b) XBT probes with standard error bars. Solid red curves represent the analytical approximation of the mean depth correction

factor (formula (7)). Grey area corresponds to the depth error envelope according to the manufacturer’s specifications. Blue circles correspond to the XBT depth corrections

obtained from the direct fall-rate measurements within the upper layer (see Fig. 6). Vertical line (magenta) corresponds to the depth correction factor suggested by Hanawa

et al. (1995). Horizontal bars (light red) indicate standard errors of the time-mean correction factor at levels. The number of degrees of freedom is equal to the number of

yearly estimates (42) of the depth correction factor (for interpretation of the references to color in this figure legend, the reader is referred to the web version of this article).

Fig. 17. (a) Vertical profiles of the XBT depth correction factor calculated separately for the whole World Ocean (801S–801N, grey curve) and for selected latitude belts using

method described in the paper; (b) vertical profiles of water temperature averaged between the surface and the respective sample depth level within the same latitude

belts as in (a); (c) depth correction factors for selected 1-degree latitude belts calculated using analytical form (7) with the account for temperature according to the

formula (5) (all calculations for the T-4 and T-6 XBT types). Horizontal bars indicate standard errors of the time-mean correction factor at levels for different latitude belts.

The number of degrees of freedom is equal to the number of yearly estimates (42) of the depth correction factor (a) and to the number of individual binned profiles within

the respective 1-degree latitude belts (c).


acquisition systems, which were phased out in favour of the digitalsystems during 1980s. However, in the absence of the metadata itremains unknown why the positive bias was lower before 1970–1972. Our calculations suggest a fall rate varying with depth, sothat a varying correction factor is required to bring the XBT depths

in agreement with the reference depths. We note that an additivenegative term was used in several XBT depth correction schemes(Heinmiller et al., 1983; Hallock and Teague, 1992; Zanasca, 1996;Snowden, personal communication, 2008). The effect of such acorrection term is maximal in the surface layer.

ARTICLE IN PRESS

Fig. 18. (a) Temperature difference between the CTD and bottle data plotted as a function of depth and year; (b) vertical profile of the time-averaged temperature

difference; and (c) number of overlapping CTD and bottle binned profiles per year. The number of degrees of freedom at each level is equal to the number of collocated

binned profiles within the respective year.


Direct measurements of the XBT fall rate within the upper47 m give values only slightly lower than the manufacturer’snominal fall rate, so that the required depth correction (a generalupward shift of 2–3 m) can not be mainly attributed to a transienthydrodynamic behaviour of the XBT probes near the surface. Weexplain the observed depth overestimation through an inherentresponse lag of the XBT system. However, it remains unknownwhether more typical launching conditions from a moving shipcan seriously change the hydrodynamic behaviour of the XBTprobes within the near-surface layer.

3.6. Consistency of the reference bottle and CTD data set

To check the internal consistency of the reference data, binnedprofiles were constructed separately for the bottle casts and CTDcasts, respectively, with yearly mean differences at levels (Bottle-CTD) shown in Fig. 18. According to our calculations, the absolutedifference is generally less than 0.05 1C, with the bottle data beingon average colder in the upper 100 m layer, and warmer belowthat level. In spite of detectable offsets between the CTDand Nansen cast data, these are typically an order of magnitudesmaller compared to the offsets for all kinds of bathythermographs,so that the use of Nansen and CTD profiles as a reference isobviously justified. We tend to explain the detected bottle-CTDtemperature difference rather as an average effect of the Nansencast depth errors, with bottle depths being systematicallyoverestimated above about 100 m and underestimated in thedeeper layers.

4. Biases in the MBT data

Before the introduction of XBTs, mechanical bathythermo-graphs (MBTs) were the most abundant data type in the upper200 m layer. They provide continuous temperature profiles versusdepth presented as a trace on a coated slide. Generally operatedwhile the ship was underway at speeds up to 18 knots, the MBTsmost satisfactorily worked at lower ship speeds (Stewart, 1963).The temperature and depth biases of the MBT profiles wereinvestigated by Stewart (1963), Casciano (1967), and Dinkel andStawnychy (1973). It was found that accuracies of +0.1 1F(0.056 1C) for temperature and +1% for depth, as specified bythe manufacturer, were practically never achieved because ofmishandling and abuse in field work, long intervals betweencalibrations, and instrument errors due to hysteresis, responsetime and shift relative to the calibration grids (Stewart, 1963). Inall three studies listed above, MBTs were tested in a special test

facility allowing for changes in pressure and temperature. Thesetests indicate, on average, higher temperatures and larger depthas measured by MBTs compared to the reference values.

The number of MBT profiles available in the WOA2005database reduces abruptly from 1991 to 1992, with a resultingreduction in the monthly number of binned profiles overlappingwith CTD/bottle data from about 300 to less than 30. Therefore,estimates of the total MBT temperature bias were not made forthe period after 1992.

Similar to the XBT data we decompose the total temperaturebias into a thermal component and a bias due to the depth error(formula (4)). The thermal bias (determined for the overlappingdata with the absolute vertical temperature gradient less than0.005 1C/m) is characterized by positive values and decreasesfrom 0.10 to 0.15 1C in the 1950s to values indistinguishable fromzero after about 1982 (Fig. 19a). The optimal depth correctionfactor indicates that MBT depths are being systematicallyoverestimated (Fig. 19b). This result is in a qualitativeagreement with the majority of the independent estimates.(Fig. 20). It should be noted; however, that depth errorsdetermined by Dinkel and Stawnychy (1973) are based on testsof only four bathythermographs, with one returned from fieldservice, which could lead to a large scattering of the errorestimates. Casciano (1967) results might be more reliable as theyare supported by the calibration checks on 144 new and rebuiltMBTs. Unfortunately, depth and temperature errors from thesecalibrations are presented in the form of overall histograms, sothat no vertical profile of the depth or temperature error isavailable for comparison with our results. It is also not clear whichdepth range is most appropriate for the comparison with ourestimates. However, the agreement of our depth corrections withCasciano (1967) error estimates is better than 1.5 m.

Application of the time-varying temperature and depthcorrections allows a significant reduction of the original tem-perature bias (Fig. 21a, b) within the upper 200 m. Using the time-mean instead of a time-varying depth correction factor results invirtually indistinguishable results (Fig. 22c, f) We provide thefollowing analytical formula for the mean MBT depth correctionfactor s:

s¼ 1:0091-z�0:8581 for z435m, ð8Þ

s¼ 0:967 for zr35m:

According to Fig. 21, bias reduction is less satisfactory for thedepths exceeding 200 m. It may indicate different bias character-istics for the MBT models designed for measurements below200 m. However, such MBT profiles contribute only about 1% of all

ARTICLE IN PRESS

Fig. 20. Optimal depth correction according to the formula (8) (black curve) and

estimates of MBT depth errors from the laboratory tests by Dinkel and Stawnychy

(1973) (blue), Casciano (1967) (green) and Stewart (1963) (red) (for interpretation

of the references to color in this figure legend, the reader is referred to the web

version of this article).

Fig. 19. (a) Thermal bias in the MBT data as a function of time. Standard errors are shown as vertical bars. For each year the number of degrees of freedom is equal to the

total number of overlapping bins. (b) Time-mean MBT depth correction factor (red dots) with standard error bars and the analytical fit (black) according to the formula (8).

The number of degrees of freedom is equal to the number of yearly estimates (42) of the depth correction factor (for interpretation of the references to color in this figure

legend, the reader is referred to the web version of this article).


MBT data. Finally, we note that the mechanical bathythermo-graphs are characterized by smaller and less time-variable biasescompared to the expendable bathythermographs. This rendersthem a useful source of historical temperature data for the upper250 m layer.

5. Possible impact of XBT biases on global temperatureanomaly estimates

In order to assess the effects of systematic biases in the XBTdata on the estimates of the long-term variability, we used thesame temporal and spatial binning and produced monthly binnedprofiles of blended XBT and CTD/bottle data. For each calendarmonth, all-data mean temperatures were calculated for eachspatial bin for the time period 1967 to 2005 to obtain a referenceclimatology. Here we used the XBT profiles corrected for thermaland depth biases according to the method described in this paper.

Subsequently, monthly deviations from the respective climatolo-gic value were calculated for each spatial bin. Finally, thearithmetic average of monthly anomalies over all spatial binsproduces anomaly time series at depth levels (Fig. 22). Werecognize that in our calculations no infilling was performed andour anomalies do not take into account a considerable geogra-phical sampling bias (GK07), so that the computed anomalies arenot global. However, for the uppermost levels, a robust averagingof monthly binned anomalies produces time series, which are inqualitative agreement with the independent global sea surfacetemperature time series based on the International Comprehen-sive Ocean Atmosphere Data Set (ICOADS) (Woodruff et al., 2008).The latter data set comprises a number of sea surface temperatureobservations two orders of magnitude larger compared to ouroriginal profile data set.

Comparison of three correction schemes was done: (1)corrections after W08 (time-dependent, depth-independentstretching factor); (2) corrections similar to GK07 and L09(depth- and time-dependent temperature correction); and(3) depth and temperature corrections from this study(Table 2, model (4)). All time series were adjusted to thesame reference period by subtracting a mean anomaly value forthe time period 1967–2005. All three correction methods lead tothe reduction of the artificial warm anomaly with a maximumaround 1975, and all three methods indicate a general warmingtrend during the last 40 years, with our depth and temperaturecorrections resulting in a larger warming, comparedwith correction methods by L09 and W08. However, disagree-ment between the correction schemes is observed on shortertime scales. For instance, W09 fall-rate corrections result in thelowest warming trend at 30 and 100 m depth among the threecorrection schemes, mostly because W09 corrections lead to aconsiderably smaller temperature increase since 1995 (thetime series for 400 m depth indicates a temperature decrease).The best agreement with the CTD anomaly time series is generallyachieved when applying our depth and temperature corrections.However, caution is required when comparing the CTD andXBT time series, as the former are based on a considerablysmaller amount of profiles. The range of the three temperatureanomaly estimates remains rather stable over the upper 700 m(Fig. 22e), varying on average within 0.04–0.05 1C. These valuestranslate into an average uncertainty of about 4.5�1022 J for theglobal heat content anomaly in the layer 0–700 m. This un-certainty may be compared with a total increase of global ocean

ARTICLE IN PRESS

Fig. 21. (a) Total MBT temperature bias diagnosed in the original data; (b) residual bias after applying corrections for the thermal bias (Fig. 19a) and for the optimal time-

mean depth bias (Fig. 19b); (c) the number of MBT monthly binned profiles collocated with the binned reference data; and (d) bias reduction after correcting the data

defined as 9Boriginal9�9Bcorrected9, where Boriginal and Bcorrected correspond to the total temperature bias in the original and corrected MBT data, respectively.

Fig. 22. (a–d) Global monthly temperature anomaly at selected levels based on the blended CTD/Bottle and XBT binned temperature profiles. Anomalies are calculated

relative to the common monthly climatology and are adjusted to the time period 1967–2005. Time series differ only in the application of the XBT correction schemes:

original SC FRE (blue), time/depth-varying temperature corrections similar to GK07 and L09 (cyan), time-varying depth correction factors from W09 (magenta), and time-

varying temperature and depth-varying depth corrections from this study (red). Anomaly time series based only on CTD and bottle data are shown in green. All time series

correspond to the mean values obtained by the averaging the original monthly anomalies within the 13-month wide window. The error bars correspond to the respective

formal standard error of the mean with 13 degrees of freedom. The ICOADS global mean sea surface temperature time series is plotted in grey (a) for comparison. (e) Time

mean (1967–2005) range of anomaly estimates obtained using three XBT correction schemes (GK07 and L09, W09 and this paper) as a function of depth (for interpretation

of the references to color in this figure legend, the reader is referred to the web version of this article).


heat content of about 12�1022 J since the late 1960s (Palmeret al., in press).

6. Conclusions

In this study, we analyzed systematic errors in subsurfacebathythermograph temperature data. These errors wereidentified through the comparison of the instrument-specific datawith the collocated bottle and CTD data, which were used as areference. In agreement with the earlier results by Gouretski andKoltermann (2007), the mechanical and expendable bathyther-mograph data were found to be, on average, warm-biased. Thistotal temperature bias appears through a combination of twofactors: a depth-independent time-variable thermal bias (gener-ally positive) and a depth-dependent depth bias. Accordingly, asimple bias model, unifying the thermal bias and the bias due tosample depth error is suggested. In agreement with independentXBT–CTD inter-comparisons, our results suggest that the XBT

depth is overestimated above about 200 m and underestimated inthe deeper part of the water column. Though our directmeasurements do confirm a slightly slower initial fall rate ofthe XBTs the required optimal depth correction can not beattributed to a reduced fall velocity near the surface. We suggestthat a time lag in the whole XBT system provides a majorcontribution to the depth overestimation within the surface layer.In agreement with earlier studies our results confirm ageneral underestimation of the XBT depth by the manufacturer’sfall-rate equation. Since the optimal depth correction variesconsiderably over depth an effective elimination of the totaltemperature bias cannot be achieved through a constant depthcorrection factor such as suggested in earlier studies. Additionally,application of the recommended H9495 depth corrections with-out a proper account for a pure temperature bias leads to aneven larger disagreement (in temperature) between the collo-cated CTD and XBT profiles. Accounting both for a depth-independent, time-variable temperature bias and for a depth-variable, time-independent depth correction allows effective

ARTICLE IN PRESS


elimination of the total temperature bias throughout the wholewater column. Our results suggest that the XBT fall rate varieswith water temperature due to changes in water viscosity.Parameterization of this effect allows for a better bias eliminationin different geographical regions. Using the same XBT data set, weassess the effect of different correction schemes on estimates ofthe global temperature anomaly. Comparison between the heatcontent time series based on the same original data but withdifferent methods to correct the XBT data suggest the averageuncertainty in the global heat content for the layer 0–700 m to beabout 4.5�1022 J. Current analysis demonstrates that an effectiveelimination of biases in both XBT and MBT data is possible andopens the possibility to use the bathythermograph data inclimate-relevant applications. Further improvement of correctionschemes is critically dependent both on the availability of thehigh-quality reference data and the metadata, with the latterallowing for more precise identification of possible error sources.

Acknowledgements

We thank Sergey Danilov, Jens Schroter and Alexander Sy fortheir helpful comments during the preparation of the manuscript.

Table A1Estimates of the linear correction factor and of the first coefficient a in the XBT fall-ra

No Year of XBT vs. CTD

inter-comparison

Correction factor Coefficient a in FRE XBT ty

01 1976 1.0356 – T-4

02 1976 1.0206 6.601 T-7

03 1977 1.0121 – T-7

04 1979 0.9933 6.440 T-7

05 1978 1.0031 6.450 T-7

06 1985 1.0367 6.715 T-7

07 1985 1.0320 – T-7

08 1986 1.0280 – T-7

09 1985 1.0399 6.741 T-7

10 1987 1.0298 6.652 T-7

11 1987 1.0305 6.666 T-7

12 1987 1.0507 6.796 T-4

13 1987 1.0344 6.720 T-7

14 1987 1.0303 6.645 T-7

15 1987 1.0272 6.665 T-7

16 1987 1.0505 6.941 T-7

17 1988 1.0499 6.796 T-4/T-6

18 1988 1.0531 6.854 T-7

19 1988 1.0491 6.810 T-4/T-6

20 1988 1.0245 6.674 TSK T-

21 1989 1.0195 6.562 T-7

22 1988 1.0374 6.723 T-7

23 1988 1.0569 6.867 T-7

24 1988 1.0514 6.751 T-6

25 1988 1.0568 6.812 T-4

26 1988 1.0277 – T-7

27 1989 1.0206 6.601 DB

28 1989 1.0308 6.666 T-7

29 1989 1.0410 6.731 T-7

30 1989 1.0308 6.666 T-4/T-6

31 1989 1.0450 – ?

32 1989 1.0465 6.824 T-7

33 1989 1.0326 6.680 T-7

34 1989 1.0314 6.672 T-7

35 1989 1.0449 6.747 T-7

36 1989–1992 1.0190 6.566 T-4/T-6

37 1990 1.0334 6.798 T-7

38 1991 1.0315 6.655 T-7

39 1991 1.0490 – T-7

40 1989–1992 1.0310 6.656 T-4/T-6

41 1991 1.0172 6.561 T-7

42 1991 1.0326 –

We are grateful to B. King, A. Mantyla, Y.H. Park, L. Talleyand T. Byrne for their personal communications with respect tothe changes in hydrographic instrumentation. We also wish tothank S. Levitus for sending us the archive papers related to theassessment of the MBT performance. We are grateful to S. Kizufor his comments and suggestions, M. Gifford (SC) for usefuldetails on Sippican products, the captain and the crews of RVUrania, the personnel of NURC Laboratory in La Spezia, Italy,and S. Latorre (INFN, Milan) for their collaboration duringinter-comparisons and laboratory tests. The contribution ofresearchers and technicians of S. Teresa Centre during the testsnear La Spezia is also acknowledged. We are grateful to SusanBeddig for helping us to straighten out the original text. Ourspecial thanks go to Marc Carson both for his valuable commentsand his language help. The research was carried out at all threeaffiliation addresses.

Appendix A

See Tables A1–A4

te equation.

pe Number XBT/CTD pairs Reference

12 Heinmiller et al. (1983) (personal

communication by A. Mantyla)

47 Seaver and Kuleshov (1982)

103 Seaver and Kuleshov (1982)

139 Heinmiller et al. (1983)

139 Green (1984)

15 Hanawa and Yoritaka (1987)

14 Singer (1990)

11 Singer (1990)

12 Hanawa and Yoshikawa (1991)


19 H9495

35 IOC (1992) (results by Henin)

8 IOC (1992) (results by Bailey)




/T-7 126 Wright and Szabados (1989)

25 H9495

40 H9495

7 Yoshida et al. (1989)


34 H9495

7 IOC (1992) (results by Szabados)



15 Biggs (1992)

12 IOC (1992) (results by Sy)

22 IOC (1992) (results by Rual)



36 Watts et al. (1990)


16 H9495

24 H9495

11 H9495

17 H9495

Ca.100 Hallock and Teague (1992)

4 Hanawa and Yasuda (1992)

19 Gould (1991)

66 H9495

10 H9495

Franklin National Facility (1991)

ARTICLE IN PRESS

Table A1 (continued )

No Year of XBT vs. CTD

inter-comparison

Correction factor Coefficient a in FRE XBT type Number XBT/CTD pairs Reference

43 1991 1.0460 – Franklin National Facility (1991)

44 1991–1992 1.0212 6.609 T-7 26 Kezele and Friesen (1993)

45 1991–1992 1.0158 6.573 Sparton T-7 59 Kezele and Friesen (1993)

46 1992 1.0342 6.708 T-4/T-6 41 H9495

47 1992 1.0180 6.514 T-4/T-6 21 H9495

48 1992 1.0336 – ? ? Owens (1993)

49 1993 1.0270 6.624 Old Sparton T-7 27 Rual et al. (1995)

50 1992–1995 1.0364 6.705 Sparton T-7 63 Rual et al. (1996)

51 1993 1.0381 – T-7 ? Fargion and Davis (1994)

52 1994–1997 1.0350 6.694 T-7 ? Thadathil et al. (1998)

53 1998 1.0047 6.487 DB 18 Snowden (2008 pers. communication)


55 2003–2004 1.0156 6.570 T-4/T-6 30 Reseghetti et al. (2007)

56 2003–2004 1.0305 6.720 DB 25 Reseghetti et al. (2007)







Mean over all estimates 1.0275

Table A2Diagnosed year-mean thermal bias BT with standard errors for shallow (T-4 and T-6 and deep (T-7 and DB) XBT modifications.

T-4 and T-6 T-7 and DB

Year BT (1C) Error (1C) BT (1C) Error (1C)

1967 0.046 0.096 �0.009 0.115

1968 0.030 0.057 �0.024 0.085

1969 0.075 0.038 0.092 0.101

1970 0.090 0.037 0.092 0.054

1971 0.141 0.036 0.105 0.054

1972 0.151 0.026 0.019 0.056

1973 0.181 0.023 0.067 0.058

1974 0.144 0.030 0.093 0.066

1975 0.151 0.028 0.123 0.077

1976 0.192 0.031 0.131 0.069

1977 0.160 0.031 0.070 0.052

1978 0.145 0.032 0.067 0.034

1979 0.119 0.030 0.089 0.054

1980 0.092 0.034 0.091 0.054

1981 0.096 0.030 0.086 0.091

1982 0.081 0.033 0.033 0.116

1983 0.072 0.033 �0.020 0.066

1984 0.054 0.027 0.040 0.059

1985 0.059 0.030 �0.041 0.050

1986 0.042 0.029 �0.009 0.086

1987 0.017 0.024 �0.034 0.070

1988 0.010 0.030 �0.047 0.047

1989 0.028 0.033 0.001 0.044

1990 0.013 0.028 �0.010 0.041

1991 0.028 0.031 0.016 0.032

1992 0.022 0.049 0.011 0.041

1993 0.022 0.041 0.029 0.034

1994 0.016 0.050 0.028 0.041

1995 0.027 0.042 0.002 0.042

1996 �0.025 0.070 0.047 0.052

1997 0.007 0.082 �0.001 0.070

1998 �0.021 0.092 0.000 0.050

1999 �0.032 0.080 0.031 0.050

2000 �0.028 0.091 0.009 0.060

2001 0.010 0.129 0.011 0.049

2002 �0.030 0.171 0.040 0.100

2003 0.036 0.168 0.013 0.116

2004 0.050 0.150 0.055 0.101

2005 �0.031 0.104 0.021 0.069

2006 0.016 0.149 0.037 0.090

2007 �0.021 0.213 0.028 0.126

2008 0.065 0.279 0.059 0.139


ARTICLE IN PRESS

Table A3Estimates of the depth-independent thermal bias in XBT data.

Year of observation Thermal bias Standard deviation XBT type Reference

1972 0.073 0.20 T-4 Anderson (1980)

1975 0.27 0.14 ? Tabata (1978)

1976 0.17 0.08 T-7 Heinmiller et al. (1983)










1988 0.029 0.046 T-4 T-6 T-7 Wright and Szabados (1989)


1988 �0.074 0.083 T-4 T-6 T-7 Wright and Szabados (1989)


1990 0.07 0.06 DB Budeus and Krause (1993)

1990 0.15 ? T-7 Wisotzki and Fahrbach (1991)

1990 0.026 0.043 T-4 T-6 T-7 Szabados (1991)

1996 �0.020 ? T-7 Pelegri et al. (2005)

2001 0.05 0.15 T-7 Boedecker (2001)

2002 0.05 0.15 T-7 Fang (2002)

2004 0.056 0.0769 T-6 This study

Table A4Diagnosed thermal bias BT in MBT data with standard error.

Year BT (1C) Error (1C)

1950 0.031 0.043

1951 0.025 0.035

1952 0.089 0.019

1953 0.073 0.023

1954 0.080 0.024

1955 0.128 0.020

1956 0.104 0.025

1957 0.062 0.020

1958 0.053 0.013

1959 �0.004 0.017

1960 0.029 0.018

1961 0.021 0.017

1962 0.077 0.015

1963 0.041 0.015

1964 0.076 0.014

1965 0.049 0.016

1966 0.025 0.016

1967 0.021 0.016

1968 0.049 0.018

1969 0.036 0.017

1970 0.053 0.021

1971 0.013 0.021

1972 0.010 0.018

1973 �0.008 0.021

1974 0.031 0.021

1975 0.026 0.019

1976 0.024 0.018

1977 0.006 0.021

1978 0.0137 0.020

1979 0.0154 0.019

1980 0.0125 0.020

1981 0.0061 0.022

1982 �0.0139 0.021

1983 �0.0089 0.020

1984 �0.002 0.016

1985 �0.006 0.016

1986 �0.002 0.016

1987 �0.004 0.018

1988 �0.007 0.021

1989 �0.011 0.018

1990 �0.010 0.018

1991 �0.005 0.062


References

Anderson, E.R., 1980. Expendable Bathythermograph (XBT) accuracy studies.Technical Report 550, Naval Ocean Systems Center, San Diego, California, 201pp.

Arthur D. Little, Inc., 1965. Experimental evaluation of Expendable Bathythermo-graphs. ASW Sonar Technology Report AD632008, Department of NAVY,Bureau of Ships, NObsr-93055, pp. 1–51.

Australian Oceanographic Data Center, 1999. Guide to MK12-XBT System(Including Launching, Returns and Faults), pp. 1–63.

Bartz, R., 1992. Development of an Expendable Particle Sensor. Progress Report toOffice of Naval Research, Sea Tech Inc., Contract No. N00014-90-C-0123, ItemNo. 0001AG, Corvallis, Oregon, pp. 1–5.

Biggs, D.C., 1992. Nutrients, plankton, and productivity in a warm-core ring in theWestern Gulf of Mexico. Journal of Geophysical Research 97, 2143–2154.

Boedecker, S., 2001. Comparison of CTD and XBT Temperature Profiles. NavalPostgraduate School, Monterey, California (available at /http://www.weather.nps.navy.mil/sguest/OC3570/CDROM/summer2001/BoedeckerS).

Boyer, T.P., Antonov, J.I., Garcia, H.E., Johnson, D.R., Locarnini, R.A., Mishonov, A.V.,Pitcher, M.T., Baranova, O.K., Smolyar, I.V., 2006. World Ocean Database 2005.In: Levitus, S. (Ed.), NODC Atlas NESDIS 60. US Government Print Office,Washington, DC, pp. 190, DVDs.

Budeus, G., Krause, G., 1993. On-cruise calibration of XBT probes. Deep-SeaResearch 40, 1359–1363.

Casciano, D.L., 1967. Mechanical Bathythermograph. Geo-Marine Technology(December/January 1966/67), 19–21.

Conkright, M.E., Antonov, J.I., Baranova, O., Boyer, Garcia, H.E., Gelfeld, R., Johnson,D., Locarnini, R.A., Murphy, P.P., O’Brian, T.D., Smolyar, I., Stefens, C., 2002.Ocean Database 2001, vol. 1: Introduction. In: Levitus, S. (Ed.), NOAA AtlasNESDIS 42. U.S. Government Printing Office, Washington, DC 167 pp., CD-ROMs.

Dinkel, C.R., Stawnychy, M., 1973. Reliability study of mechanical bathythermo-graph. Marine Technology Society Journal 7, 41–47.

Domingues, C.M., Church, J.A., White, N.J., Glecker, P.J., Wijffels, S.E., Barker, P.M.,Dunn, J.R., 2008. Improved estimates of upper-ocean warming and multi-decadal sea-level rise. Nature 453, 1090–1093.

Emery, W.J., Thompson, R.E., 2004. Data Analysis Methods in Physical Oceano-graphy. Elsevier B.V., Amsterdam, 637 p.

Emery, W.J., Lee, W., Zenk, W., Meincke, J., 1986. A low-cost digital XBT system andits application to the real-time computation of dynamic height. Journal ofAtmospheric and Oceanic Technology 3, 75–83.

Fang, C.L., 2002. XBT/CTD comparisons. Project Report for OC3570, NavalPostgraduate School, Monterey, California (available at /http://www.weather.nps.navy.mil/sguest/OC3570/CDROM/summer2002/FangS).

Fargion, G.S., Davis, R., 1994. GulfCet cruise 07 hydrographic data. Technical Report94-03-T of the Department of Marine Biology Texas A&M University,Galveston, pp. 1–128.

Fedorov, K.N., Ginzburg, A.I., Zatsepin, A.G., 1978. Systematic differences inisotherm depths derived from XBT and CTD data. POLYMODE News 50, 1–6.

http://www.weather.nps.navy.mil/sguest/OC3570/CDROM/summer2001/Boedecker

http://www.weather.nps.navy.mil/sguest/OC3570/CDROM/summer2001/Boedecker

http://www.weather.nps.navy.mil/sguest/OC3570/CDROM/summer2002/Fang

http://www.weather.nps.navy.mil/sguest/OC3570/CDROM/summer2002/Fang

ARTICLE IN PRESS


Fenner, D.F., Cronin, W.J., 1978. Bearing stake exercise: sound speed and otherenvironmental variability. Naval Ocean Research and Development Activity,NORDA Report 18, pp. 1–60.

Francis, S.A., Campbell, G.C., 1965. A low cost expendable bathythermograph. In:Proceedings of the Third National Marine Sciences Symposium held April21–23, 1965, Miami, FL, pp. 85–89.

Franklin National Facility, 1991. Cruise Summary, Cruise FR 10/91. MiscellaneousPublications, CSIRO Division of Oceanography for Franklin National Facility.

Gould, W.J., 1991. RRS Charles Darwin Cruise 50, 29 June–22 July 1990.Oceanography of the Iceland Basin. The fate of Iceland and Scotland overflowwater. IOS Deacon Laboratory, Cruise Report 221, pp. 1–51.

Gouretski, V.V., Koltermann, K.P., 2004. WOCE Global Hydrographic Climatology,Berichte des Bundesamt fur Seeschiffahrt und Hydrographie, Nr. 35/2004,CDROMs.

Gouretski, V.V., Koltermann, K.P., 2007. How much is the Ocean really warming?Geophysical Research Letters 34 L01610, doi:10.1029/2006GL027834.

Green, A.W., 1984. Bulk dynamics of the expendable bathythermograph XBT.Deep-Sea Research 31, 415–426.

Hallock, Z.R., Teague, W.J., 1992. The fall rate of the T-7 XBT. Journal ofAtmospheric and Oceanic Technology 9, 470–483.

Hanawa, K., Rual, P., Bailey, R., Sy, A., Szabados, M., 1994. Calculation of new depthequations for expendable bathythermographs using a temperature-error-freemethod (Application to Sippican/TSK T-7, T-6 and T-4 XBTs). UNESCOTechnical Papers in Marine Sciences, vol. 67, pp. 1–51.

Hanawa, K., Rual, P., Bailey, R., Sy, A., Szabados, M., 1995. A new depth-timeequation for Sippican or TSK T-7, T-6 and T-4 Expendable bathythermographs(XBT). Deep-Sea Research 42, 1423–1451.

Hanawa, K., Yasuda, T., 1992. New Detection method for XBT depth error andrelationship between the depth error and coefficients in the depth-timeequation. Journal of Oceanography 48, 221–230.

Hanawa, K., Yoritaka, H., 1987. Detection of systematic errors in XBT dataand their correction. Journal of the Oceanographical Society of Japan 43,68–76.

Hanawa, K., Yoshikawa, Y., 1991. Re-examination of depth error in XBT data.Journal of Atmospheric and Oceanic Technology 8, 422–429.

Heinmiller, R.H., Ebbesmeyer, C.C., Taft, B.A., Olson, D.B., Nikitin, O.P., 1983.Systematic errors in expendable bathythermograph. Journal of PhysicalOceanography 12, 592–600.

Intergovernmental Oceanographic Commission, 1975. Guide to Oceanographic andMarine Meteorological Instruments and Observing Practices. UNESCO, ISBN:92-3-101325-4, pp. 1–78.

Intergovernmental Oceanographic Commission, 1989. Integrated Global OceanServices System IGOSS. Summary of Ship-Of-Opportunity Programmes andTechnical Reports, Hamburg Germany, 16–20 October 1989, IOC/INF-804,pp. 1–183.

Intergovernmental Oceanographic Commission, 1992. Ad Hoc meeting of theIGOSS Task Team on quality control for automated systems, Marion,Massachusetts, USA, 3–6 June 1991, IOC/INF-888, pp. 1–179.

Iselin, C.O.D., 1936. A study of the circulation of the western North Atlantic. Papersin Physical Oceanography and Meteorology 4.

Ishii, M., Kimoto, M., 2009. Reevaluation of historical ocean heat content variationswith time-varying XBT and MBT depth bias corrections. Journal of Oceano-graphy 65 (3), 287–299, doi:10.1007/s10872-009-0027-7.

Kezele, D., Friesen, G., 1993. XBT test data comparison and analysis. SeaTechnology 34 (2), 15–22.

Kizu, S., Hanawa, K., 2002a. Recorder-dependant temperature error of expendablebathythermograph. Journal of Oceanography 58, 469–476.

Kizu, S., Hanawa, K., 2002b. Start-up transient of XBT measurement. Deep-SeaResearch 49, 935–940.

Kizu, S., Itoh, S., Watanabe, T., 2005. Inter-manufacturer difference andtemperature dependency of the fall rate of T-5 expendable bathythermograph.Journal of Oceanography 61 (5), 905–912.

Kizu, S., Onishi, H., Suga, T., Hanawa, K., Watanabe, T., Iwamiya, H., 2008.Evaluation of the fall rates of the present and developmental XCTDs. Deep-SeaResearch, Part I 55, 571–586.

Landau, L.D., Lifschitz, E.M., 1966. Hydrodynamik. Akademie-Verlag, Berlin.Levitus, S., Antonov, J., Boyer, T., Stephens, C., 2000. Warming of the World Ocean.

Science 287, 2225–2229, doi:10.1126/science.287.5461.2225.Levitus, S., Antonov, J., Boyer, T., 2005. Warming of the World Ocean, 1955–2003.

Geophysical Research Letters 32, L12602, doi:10.1029/2005GL023112.Levitus, S., Antonov, J.I., Boyer, T.P., Locarnini, R.A., Garcia, H.E., Mishonov, A.V.,

2009. Global ocean heat content 1955–2008 in light of recently revealedinstrumentation problems. Geophysical Research Letters 36, L07608,doi:10.1029/2008GL037155.

Lyman, J.M., Willis, J.K., Johnson, G.C., 2006. Recent cooling of the upper ocean.Geophysical Research Letters 33, L18604, doi:10.1019/2006GL027033.

Magruder, P.M., 1970. Some characteristics of temperature microstructure in theOcean. Thesis, US Naval Postgraduate School, pp. 1–156.

Manzella, G.M.R., Scoccimarro, E., Pinardi, N., Tonani, M., 2003. Improved near realtime data management procedure for the Mediterranean ocean forecastingsystem—voluntary observing ship program. Annals of Geophysics 21, 49–62.

Owens, N.J.P., 1993. BOFS ’Sterna 92’ Cruise Report: RRS James Clark Ross 02 26/11/92–18/12/92, Plymouth Marine Laboratory, pp. 1–81.

Palmer, M.D., Antonov, J.I., Barker, P., Bindoff, N., Boyer, T., Carson, M., Domingues,C.M., Gille, S., Glecker, P., Good, S., Gouretski, V., Guinehut, S., Haines,K.,

Harrison, D.E., Ishii, M., Johnson, G.C., Levitus, S., Lozier, M.S., Lymann, J.M.,Meijers, A., von Schuckmann, K., Smith, D., Wijffels, S., Willis, J., Futureobservations for monitoring global ocean heat content, in press.

Pelegri, J.L., Marrero-Diaz, A., Ratssimandresy, A., Antoranz, A., Cisneros-Aguirre, J.,Gordo, C., Grisolia, D., Hernandez-Guerra, A., Laiz, I., Martinez, A., Parilla, G.,Perez-Rodriguez, P., Rodrigues-Santana, A., Sangria, P., 2005. Hydrographiccruises off northwest Africa: the Canary current and the Cape Ghir region.Journal of Marine Systems 54, 39–63.

Perez-Martell, E., Cianca, A., 1997. XBT Lines. In: Informes tecnicos del InstitutoCanario de Ciencias Marinas 7, pp. 7–8.

Plessey-Sippican Corp., 1975. Plessey-Sippican expendable bathythermographsystem Plessey-Sippican MP0400, Issue 1.

Reseghetti, F., Borghini, M., Manzella, G.M.R., 2007. Factors affecting the quality ofCTD data, XBT data—results of analysis on profiles from the WesternMediterranean Sea. Ocean Science 3, 59–75.

Reiniger, R.F., Ross, C.F., 1968. A method of interpolation with application tooceanographic data. Deep-Sea Research 9, 185–193.

Roemmich, D., Cornuelle, B., 1987. Digitization and calibration of the expendablebathythermograph. Deep-Sea Research 32, 299–307.

Rual, P.A., Hanawa, K., Bailey, R., Sy, A., Szabados, M., 1994. New depth equation forcommonly used expendable bathythermographs: Sippican and TSK T-4, T-6and T-7 probes. International WOCE Newsletter 17, 13–16.

Rual, P., Dessier, A., Rebert, J.P., Sy, A., 1995. New depth equation for old SpartonXBT-7 expendable bathythermographs. International WOCE Newsletter 19,33–34.

Rual, P., Dessier, A., Rebert, J.P., Sy, A., Hanawa, K., 1996. New depth equation forSparton XBT-7 expendable bathythermographs, preliminary results. Interna-tional WOCE Newsletter 24, 39–40.

Schiermeier, Q., 2007. Artefacts in ocean data hide rising temperatures. Nature 447(3), 8.

Seeaver, G.A., Kuleshov, S., 1982. Experimental and analytical error of theexpendable bathythermograph. Journal of Physical Oceanography 12,592–600.

Shenoi, V.M., 1976. New techniques in Bathythermograph systems. DefenceScience Journal 26, 97–104.

Singer, J.J., 1990. On the error observed in electronically digitized T-7 XBT data.Journal of Atmospheric and Oceanic Technology 7, 603–611.

Stegen, G., Delisi, D.P., Voncolln, R.C., 1975. A portable, digital recording,Expendable Bathythermograph (XBT) system. Deep-Sea Research 22, 447–453.

Stewart, R.L., 1963. Test and Evaluation of the Mechanical Bathythermograph.Unpublished manuscript. Marine Science Department, US Navy OceanographicOffice, Washington, DC.

Szabados, M.W., 1991. Evaluation of the Expendable Bathythermographic (XBT)Fall Rate Equation. Ocean Observations Division/Office of Ocean Services,National Ocean Service, NOAA, pp. 19–27.

Tabata, S., 1978. On the accuracy of sea-surface temperatures and salinitiesobserved in the Northeast Pacific Ocean. Atmosphere–Ocean 16, 237–247.

Thadathil, P., Ghosh, A., Muraleedharan, P.M., 1998. An evaluation of XBT depthequations for the Indian Ocean. Deep-Sea Research 45, 819–827.

Thadathil, P., Saran, A.K., Gopalakrishna, V.V., Vethamony, P., Araligidad, N., Bailey,R., 2002. XBT fall rate in waters of extreme temperature: a case study in theAntarctic Ocean. Journal of Atmospheric and Oceanic Technology 19, 391–396.

Turner, D., 1992. R/V Discovery Cruise Report SR01. November 11, 1992–December17, 1992, pp. 1–93.

Warren, B., 2008. Nansen-bottle stations At the Woods Hole OceanographicInstitution. Deep-Sea Research 55 (4), 379–395.

Watts, R., Mohammad, K., Fields, E., 1990. XBT systematic depth error correction.The Synoptician 1, 6–7.

Wijffels, S.E., Willis, J., Domingues, C.M., Barker, P., White, N.J., Gronell, A.,Ridgway, K., Church, J.A., 2008. Changing Expendable Bathythermograph fallrates and their impact on estimates of thermosteric sea level rise. Journal ofClimate 21, 5657–5672.

Willis, J., Lyman, J., Johnson, G., Gilson, J., 2009. Situ data biases and recent oceanheat content variability. Journal of Atmospheric and Oceanic Technology 26(4), 846–852.

Wisotzki, A., Fahrbach, E., 1991. XBT-Data measured from 1984 to 1991 in theAtlantic sector of the Southern Ocean by R.V. ‘‘Meteor’’ and R.V. ‘‘Polarstern’’.Technical Report 18, Alfred Wegener Institut, Bremerhaven, pp. 1–86.

Woodruff, S.D., Diaz, H.F., Kent, E.C., Reynolds, R.W., Worley, S.J., 2008. Theevolving SST record from ICOADS. In: Bronnimann, S., Luterbacher, J., Ewen, T.,Diaz, H.F., Stolarski, R.S., Neu, U. (Eds.), Climate Variability and ExtremesDuring the Past 100 Years. Advances in Global Change Research, vol. 33.Springer, pp. 65–83.

Wright, D., Szabados, M., 1989. Field evaluation of real-time XBT systems. OCEANS’89 Proceedings, vol. 5; pp. 1621–1626.

Wust, G.G., Bennecke, G., Meyer, H.H.F., 1932. Ozeanographische Methoden undInstrumente. Wissenschaftliche Ergebnisse der Deutschen Atlantischen Ex-pedition auf dem Forschungs- und Vermessungsschiff Meteor‘‘ 1925–1927,Band IV, Erster Teil.

Yoshida, J., Suzuki, T., Sudo, H., 1989. Correction of XBT depth error. Journal of theTokyo University of Fisheries 76, 55–63.

Zanasca, P., 1996. On Board XBTs Calibration. NURC, Internal Notes, La Spezia, pp.1–17.

dx.doi.org/10.1029/2006GL027834.3d

dx.doi.org/10.1007/s10872-009-0027-7.3d

dx.doi.org/10.1126/science.287.5461.2225

dx.doi.org/10.1029/2005GL023112.3d

dx.doi.org/10.1029/2008GL037155.3d

dx.doi.org/10.1019/2006GL027033.3d

Deep-Sea Research I - ICDC Datenzentrum · PDF fileTrial versions were produced by several...

Documents

Transcript of Deep-Sea Research I - ICDC Datenzentrum · PDF fileTrial versions were produced by several...