Correction for Systematic Errors in the Global Dataset of Temperature Profiles from Mechanical Bathythermographs

Abstract

A homogeneous, consistent, high-quality in situ temperature dataset covering some decades in time is crucial for the detection of climate changes in the ocean. For the period from 1940 to the present, this study investigates the data quality of temperature profiles from mechanical bathythermographs (MBT) by comparing these data with reference data obtained from Nansen bottle casts and conductivity-temperature-depth (CTD) profilers. This comparison reveals significant systematic errors in MBT measurements. The MBT bias is as large as 0.28C before 1980 on the global average and reduces to less than 0.18C after 1980. A new empirical correction scheme for MBT data is derived, where the MBT correction is country, depth, and time dependent. Comparison of the new MBT correction scheme with three schemes proposed earlier in the literature suggests a better performance of the new schemes. The reduction of the biases increases the homogeneity of the global ocean database being mostly important for climate change-related studies, such as the improved estimation of the ocean heat content changes.

An Overview of Ocean Climate Change Indicators: Sea Surface Temperature, Ocean Heat Content, Ocean pH, Dissolved Oxygen Concentration, Arctic Sea Ice Extent, Thickness and Volume, Sea Level and Strength of the AMOC (Atlantic Meridional Overturning Circulation)

“…After correcting the systematic errors, the XBT data quality has been improved and the OHC time series show a more homogeneous warming in the half century (Cheng et al, 2018a,b;Goni et al, 2019). In addition to the XBT error, several other sources of uncertainty in OHC estimates have been identified, including MBT biases (Gouretski and Cheng, 2020), mapping methods, and choice of climatology etc. Boyer et al (2016) found that the major source of error in OHC estimates is the mapping method, which defines how the global map of a variable is created from incomplete observations and how the reconstructed field is smoothed.…”

Heat stored in the Earth system: where does the energy go?

“…The Earth system responds to an imposed radiative forcing through a number of feedbacks, which operate on various different timescales. Conceptually, the relationships between EEI, radiative forcing and surface temperature change can be expressed as (Gregory and Andrews, 2016)…”

“…Thus, N TOA represents the difference between the applied radiative forcing and Earth's radiative response through climate feedbacks associated with surface temperature rise (e.g., Hansen et al, 2011). Observation-based estimates of N TOA are therefore crucial both to our understanding of past climate change and for refining projections of future climate change (Gregory and Andrews, 2016;Kuhlbrodt and Gregory, 2012). The long atmospheric lifetime of carbon dioxide means that N TOA , F ERF and T S will remain positive for centuries, even with substantial reductions in greenhouse gas emissions, and lead to substantial committed sea-level rise (Cheng et al, 2019a;Hansen et al, 2017;Nauels et al, 2017;Palmer et al, 2018).…”

Reply on RC2

“…Primarily for model verification, we use ocean observation datasets from EN4 (EN.4.2.2, bias corrections .g10, downloaded 2021-01-12) (Good et al, 2013;Gouretski and Reseghetti, 2010;Gouretski and Cheng, 2020) and OSNAP (Lozier et al, 2019;Li et al, 2021).…”