Examining the Influence of Recording System on the Pure Temperature Error in XBT Data

Author:

Tan Zhetao12,Reseghetti Franco3,Abraham John4,Cowley Rebecca5,Chen Keyi6,Zhu Jiang1,Zhang Bin78,Cheng Lijing127

Affiliation:

1. a International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

2. b University of Chinese Academy of Sciences, Beijing, China

3. c ENEA, Research Centre Santa Teresa, Lerici, Italy

4. d School of Engineering, University of St. Thomas, Saint Paul, Minneapolis

5. e Oceans and Atmosphere, CSIRO, Hobart, Tasmania, Australia

6. f School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China

7. g Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, China

8. h Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China

Abstract

AbstractExpendable bathythermographs (XBTs) have been widely deployed for ocean monitoring since the late 1960s. Improving the quality of XBT data is a vital task in climatology. Many factors (e.g., temperature, probe type, and manufacturing time) have been identified as major influences of XBT systematic bias. In addition, the recording system (RS) has long been suspected as another factor. However, this factor has not been taken into account in any global XBT correction schemes, partly because its impact is poorly understood. Here, based on analysis of an XBT–CTD side-by-side dataset and a global collocated reference dataset, the influence of RSs on the pure temperature error (PTE) is examined. Results show a clear time dependency of PTE on the RS, with maximum values occurring in the 1970s. In addition, the method used to convert thermistor resistance into temperature in the RS (using a resistance–temperature equation) has changed over time. These changes, together with the decadal changes in RSs, might contribute a small error (10% on average) to the RS dependency. Here, an improvement of global XBT bias correction that accounts for the RS dependency is proposed. However, more than 70% of historical global XBT data are missing RS-type information. We investigate several assumptions about the temporal distribution of RS types, and all scenarios lead to at least a ~50% reduction in the time variation of PTE compared with the uncorrected data. Therefore, the RS dependency should be taken into account in updated XBT correction schemes, which would have further implications for climatology studies.

Funder

Key Deployment Project of Centre for Ocean Mega-Research of Science, CAS

Strategic Priority Research Program of the Chinese Academy of Sciences

National Key R&D Program of China

The Earth Systems and Climate Change Hub of the Australian Government's National Environmental Science Program

Publisher

American Meteorological Society

Subject

Atmospheric Science,Ocean Engineering

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