XBT Science: Assessment of Instrumental Biases and Errors

Abstract

Expendable bathythermograph (XBT) data were the major component of the ocean temperature profile observations from the late 1960s through the early 2000s, and XBTs still continue to provide critical data to monitor surface and subsurface currents, meridional heat transport, and ocean heat content. Systematic errors have been identified in the XBT data, some of which originate from computing the depth in the profile using a theoretically and experimentally derived fall-rate equation (FRE). After in-depth studies of these biases and discussions held in several workshops dedicated to discussing XBT biases, the XBT science community met at the Fourth XBT Science Workshop and concluded that XBT biases consist of 1) errors in depth values due to the inadequacy of the probe motion description done by standard FRE and 2) independent pure temperature biases. The depth error and temperature bias are temperature dependent and may depend on the data acquisition and recording system. In addition, the depth bias also includes an offset term. Some biases affecting the XBT-derived temperature profiles vary with manufacturer/probe type and have been shown to be time dependent. Best practices for historical XBT data corrections, recommendations for future collection of metadata to accompany XBT data, impact of XBT biases on scientific applications, and challenges encountered are presented in this manuscript. Analysis of XBT data shows that, despite the existence of these biases, historical XBT data without bias corrections are still suitable for many scientific applications, and that bias-corrected data can be used for climate research

Observed and simulated full-depth ocean heat-content changes for 1970–2005

“…It shows a 0-700 m OHC decrease of ∼ −2.67 [−3.28, −2.06] × 10 22 J after El Chichón and ∼ −2.72 [−3.97, −1.47] × 10 22 J after Pinatubo, indicating the strong ocean cooling. The negative radiative forcing to the ocean (and climate system) due to the volcano eruption is probably the major reason for this decrease (Church et al, 2005Balmaseda et al 2013), but our observational analyses can not exclude the possibility that the unforced ocean variability (such as ENSO, Trenberth and Fasullo, 2012) and the insufficiency of data coverage (which could induce spurious interannual OHC change) are fully or partly responsible for the values calculated above, which requires more careful model-based studies in the future. Moreover, it is also suggested that volcanic eruptions can trigger an El Niño-like response in the ocean, which is another possible explanation (Mann et al, 2005).…”

“…Numerous correction schemes have been proposed to remove the time-varying XBT biases (Cheng et al, 2015b), but these schemes vary in their formulation and performance. Hence, the XBT community met in 2014 and made a series of recommendations on the factors that should be accounted for when designing and implementing an XBT bias-correction scheme (Cheng et al, 2015b).…”

“…Numerous correction schemes have been proposed to remove the time-varying XBT biases (Cheng et al, 2015b), but these schemes vary in their formulation and performance. Hence, the XBT community met in 2014 and made a series of recommendations on the factors that should be accounted for when designing and implementing an XBT bias-correction scheme (Cheng et al, 2015b). Only one bias-correction scheme ) meets all of these recommendations, and has been shown to correct the overall bias to less than 0.02 • C (for the 0-700 m layer, less than 10 % of the total 0-700 m temperature change since 1970) and also reduce the spatio-temporal variation of bias.…”

Indication of recent warming process at the intermediate level in the Tyrrhenian Sea from SOOP XBT measurements

“…We do not apply any correction to XBT depths or temperature and we refer to literature for discussions on uncertainties in XBT measurements (e.g. see Cowley et al, 2013;Cheng et al, 2014Cheng et al, , 2015.We note that the robustness and consistency of XBT data has been a well-know problem for dozens of years. Several studies have been published on this subject (e.g.…”

XBT Effects on the Global Ocean State Estimates Using a Coupled Data Assimilation System

“…FRE has an error of about ±5 m or 2% depth that yields a significant uncertainty in temperature measurements (Goes et al 2015a). Hanawa et al (1995) first suggested a correction for XBT FRE biases, and many subsequent studies have continuously proven the negative impact of XBT biases on ocean climate studies (Kizu et al 2005;Gouretski and Koltermann 2007;Domingues et al 2008;Wijffels et al 2008;Levitus et al 2009;DiNezio and Goni 2011;Cowley et al 2013;Goes et al 2013;Cheng et al 2014Cheng et al , 2015. So far, no agreement has been reached on how the XBT data should be corrected before it is used in climate studies.…”