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Full text: A methodology to uncertainty quantification of essential ocean variables

% frontiers | Frontiers in Marine Science 
TYPE Original Research 
PUBLISHED 15 November 2022 
DO! 10.3389/fmars.2022.1002153 
N Check for updates 
A methodology to uncertainty 
quantification of essential 
ocean variables 
OPEN ACCESS 
ZDITED BY 
Juliet Hermes, 
South African Environmental 
Ibservation Network (SAEON), South 
Africa 
REVIEWED BY 
Mark Bushnell, 
National Ocean Service (NOAA), 
Jnited States 
diroshi Uchida, 
Japan Agency for Marine-Earth 
Science and Technology (JAMSTEC), 
Japan 
"CORRESPONDENCE 
Christoph Waldmann 
waldmann@uni-bremen.de 
Christoph Waldmann *, Philipp Fischer*, Steffen Seitz*, 
Manuela Köllner*, Jens-Georg Fischer“, Markus Bergenthal‘, 
Holger Brix>°, Stefan Weinreben® and Robert Huber‘? 
Center for Marine Environmental Sciences (MARUM), University of Bremen, Bremen, Germany, 
Biological Station, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWN 
delgoland, Germany, *Electrochemistry Department, Physikalisch-Technische Bundesanstalt, 
3raunschweig, Germany, *Oceanographic Assessment M22, Bundesamt fuer Seeschifffahrt und 
Aydrographie, Hamburg, Germany, °Institute of Carbon Cycles, Helmholtz- Zentrum Hereon, 
Geesthacht, Germany, °Physical Oceanography and Instrumentation, Leibniz-Institute for Baltic Sea 
Zesearch, Rostock, Germany 
SPECIALTY SECTION 
This article was submitted to 
Icean Observation, 
3 section of the journal 
Frontiers in Marine Science 
The goal of this study is to provide a universally applicable procedure for a 
systematic evaluation of in situ measured data from single sensors regarding 
quantifying the uncertainty of the measurement results. As determining 
Juncertainty for an environmental parameter also depends on the parameter 
itself, the focus here will be set on the variable water temperature in the first 
place. A separate analysis for salinity and other data will follow in later 
publications. With this first of a series of planned manuscripts on different 
parameters, we aim at providing a common understanding of how 
measurement uncertainty on single sensor measurements can be derived. 
Jsing an experimental /n situ set-up with 6 different standard CTD sensors of 
wo different brands, we created a four month-long, high-quality data set to be 
Jsed to develop a reliable method for quantifying measurement uncertainties. 
Although the CTDs were deployed in a mooring in a coastal environment the 
described method can be extended to other deployment configurations as 
well. The described procedures have evolved as a stepwise process that takes 
he different perspectives of the involved authors into account, as well as the 
special conditions for environmental measurements, which are collected while 
he observed volume/area is undergoing a constant change. By sharing the 
ideas with other stakeholders, the basic concept can be extended to other 
observing programs and to other essential ocean variables. 
ZECEIVED 24 July 2022 
ACCEPTED 31 October 2022 
JUBLISHED 15 November 202? 
ZITATION 
Waldmann C, Fischer P, Seitz S, 
<öllner M, Fischer J-G, Bergenthal M, 
Brix H, Weinreben S and Huber R 
2022) A methodology to uncertainty 
Juantification of essential 
ocean variables. 
-"ront. Mar. Sci. 9:1002153. 
doi: 10.3389/fmars.2022.1002153 
ZOPYRIGHT 
© 2022 Waldmann, Fischer, Seitz, 
Köllner, Fischer, Bergenthal, Brix, 
Weinreben and Huber. This is an open- 
access article distributed under the 
terms of the Creative Commons 
Attribution License (CC BY). The use, 
distribution or reproduction in other 
forums is permitted, provided the 
original author(s) and the copyright 
awner(s) are credited and that the 
ariginal publication in this journal is 
zited, in accordance with accepted 
academic practice. No use, 
distribution or reproduction is 
Jermitted which does not comply with 
chese terms. 
X<EYWORDS 
uncertainty quantification, essential ocean variables, CTD, coastal observatory 
calibration, metrology, quality control, flagging 
-rontiers in Marine Science 
IM 
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