XBTs do not measure depth directly (e.g. via pressure). Instead, fall-rate equations are used to derive the depth of the XBT as a function of time after the XBT is deployed into the ocean:
where z(t) is the depth of the XBT in meters, and a, b are constants determined using theoretical and empirical methods. top
The XBT has an accuracy of ±2% or 4.6m in depth (whichever is greater) and ±0.2°C in temperature. The XBT performs well within these levels of accuracy and is acceptable for most types of research. Researchers using XBT data for climate studies such as ocean heat content changes and thermosteric sea level change have found that inaccurate fall rate coefficients and a temperature bias have a significant impact on their calculations. The fall-rate and temperature bias vary over the years since the introduction of the XBT in 1967..
Several corrections for fall rate and/or temperature bias have been proposed and are presented below in the references. These corrections can be applied to XBT data downloaded via the WODselect tool. Currently, there is no consensus on how to correct XBT data for climate use. The XBT Science Team recommends careful review of all methods before choosing a correction.
Collection of XBT and CTD pairs is vital for the future correction of XBT biases. Cowley et al (2013) constructed a database of over 4,100 XBT and CTD co-located profile pairs (available at http://dx.doi.org/10.4225/08/52AE99A4663B1) and this database will be regularly updated as new pairs become available. Continued collection of co-located XBT and CTD pairs is imperative for monitoring XBT the fall-rate and temperature bias into the future. Collecting the XBT/CTD paired data requires international cooperation, since data from all ocean basins and latitudes are needed. Performing XBT testing at sea is generally not an onerous task, but does require some pre-planning and organization. The XBT Science Team encourages sea-going researchers to conduct these tests whenever possible, and submit collected data for inclusion in the XBT/CTD pairs database. Please contact Rebecca Cowley for support and information about collecting pairs data.top
The evolution of depth errors for low resolution Sippican T4/T6 (1969 to 1993, green dots) and high resolution (1987 to 2011, black dots) Sippican T7/DB probes. Dots are the depth errors for all the results. Heavy black lines are the median for all results and the shaded red area is two standard errors.
Depth error (α) for Sippican T4/T6 probes (a) and Sippican T7/DB probes (b) in non-overlapping time bins with a minimum of 30 pairs per bin. The manufacturer’s tolerance limits (±2%) are shown. The error bars are two standard errors. Shading of the error bars indicates how many pairs are included in the time bin and the width of the shaded areas indicates the time coverage. The original 1965 Sippican fall rate equivalent (0.0336m m-1) is included as the dotted line and marked as ‘S65’. ‘H95’ indicates the Hanawa et al (1995) fall rate equivalent.
Temperature bias after depth correction (DT) plotted by year for Sippican T4/T6 probes (a) and Sippican T7/DB probes (b). The error bars are two standard errors and shading of the error bars indicates how many pairs are included in the time bin. Manufacturer accuracy is ±0.2°C.
Cowley, R., Wijffels, S., Cheng, L., Boyer, T., & Kizu, S. (2013). Biases in historical Expendable BathyThermograph data: a new view based on side-by-side comparisons. J. Atmos. Oceanic Technol., 30, 1195–1225, (2013)
Goes, M., G.J. Goni, and K. Keller (2013), Reducing Biases in XBT Measurements by Including Discrete Information from Pressure Switches. J. Atmos. Ocean. Techn., 30(4), pp.810-824, 10.1175/JTECH-D-12-00126.1
Gouretski, V. (2012), Using GEBCO digital bathymetry to infer depth biases in the XBT data, Deep Sea Research-I, 62,40-52.
Hamon, M., Reverdin, G., and Le Traon, P. Y. (2012). Empirical correction of XBT data. Journal of Atmospheric and Oceanic Technology, 29(7), 960-973.
Di Nezio, P.N., and G. Goni (2011), Direct Evidence of Changes in the XBT Fall-rate Bias During 1986-2008. J. Atmos. Ocean. Techn., 28(11), 1569-1578,doi:10.1175/JTECH-D-11-00017.1.
Good, S.A (2011), Depth biases in XBT data diagnosed using Bathymetry data ,Journal of Atmospheric and Oceanic Technology, 28, 287-300, doi: 10.1175/2010JTECHO773.
Di Nezio, P.N., and G. Goni (2010), Identifying and Estimating Biases between XBT and Argo Observations Using Satellite Altimetry. J. Atmos. Ocean. Techn., 27(1):226-240.
Gouretski, V. and F. Reseghetti (2010), On depth and temperature biases in bathythermograph data: Development of a new correction scheme based on analysis of a global ocean database. Deep-Sea Research I, Vol. 57(6), pp. 812-834, doi:10.1016/j.dsr.2010.03.011.
Ishii, M. and M. Kimoto (2009), Reevaluation of Historical Ocean Heat Content Variations With An XBT depth bias Correction. J. Oceanogr. 65, 287299, doi:10.1007/s10872-009-0027-7.
Levitus, S., Antonov, J. I., Boyer, T. P., Locarnini, R. A., Garcia, H. E., and Mishonov, A. V. (2009). Global ocean heat content 1955–2008 in light of recently revealed instrumentation problems. Geophysical Research Letters, 36(7).
Wijffels, Susan E., Josh Willis, Catia M. Domingues, Paul Barker, Neil J. White, Ann Gronell, Ken Ridgway, John A. Church (2008), Changing Expendable Bathythermograph Fall Rates and Their Impact on Estimates of Thermosteric Sea Level Rise. J. Climate, 21, 56575672. doi: http://dx.doi.org/10.1175/2008JCLI2290.
Gouretski, V. V., and K. P. Koltermann (2007), How much is the ocean really warming? Geophysical Research Letters, L01610, doi:10.1029/2006GL027834.
A complete list of references to XBT biases can be found here.top