ALBERT

Description: As ocean acidification (OA) sensor technology develops and improves, in situ deployment of such sensors is becoming more widespread. However, the scientific value of these data depends on the development and application of best practices for calibration, validation, and quality assurance as well as on further development and optimization of the measurement technologies themselves. Here, we summarize the results of a 2-day workshop on OA sensor best practices held in February 2018, in Victoria, British Columbia, Canada, drawing on the collective experience and perspectives of the participants. The workshop on in situ Sensors for OA Research was organized around three basic questions: 1) What are the factors limiting the precision, accuracy and reliability of sensor data? 2) What can we do to facilitate the quality assurance/quality control (QA/QC) process and optimize the utility of these data? and 3) What sort of data or metadata are needed for these data to be most useful to future users? A synthesis of the discussion of these questions among workshop participants and conclusions drawn is presented in this paper.

Description: Ocean surface partial pressure of carbon dioxide (pCO2) is a key factor controlling air–sea CO2 fluxes. Most surface pCO2 data are collected with relatively large and complex air–water equilibrators coupled to stand‐alone infrared analyzers installed on Ships of OPportunity (SOOP‐CO2). This approach has proven itself through years of successful deployments, but expansion and sustainability of the future measurement network faces challenges in terms of certification, autonomy, and maintenance, which motivates development of new systems. Here, we compare performance of three underway pCO2 measurement systems (General Oceanics, SubCtech, and Pro‐Oceanus), including a recently developed compact flow‐through, sensor‐based system. The systems were intercompared over a period of 34 days during two crossings of the subpolar North Atlantic Ocean. With a mean difference from the General Oceanics system of −5.7 ± 4.0 μatm (Pro‐Oceanus) and −4.7 ± 2.9 μatm (SubCtech) during the 1st crossing, our results indicate potential for good agreement between the systems. The study highlighted the challenge of assuring accuracy over long periods of time, particularly seen in a worse agreement during the 2nd crossing, and revealed a number of sources of systematic errors. These can influence accuracy of the measurements, agreement between systems and include slow response of membrane‐based systems to pCO2 changes, “within‐ship” respiration due to biofouling, and bias in measurement of the temperature of equilibration. These error sources can be controlled or corrected for, however, if unidentified, their magnitude can be significant relative to accuracy criteria assigned to the highest‐quality data in global databases. The advantages of the compact flow‐through system are presented along with a discussion of future solutions for improving data quality.

Description: The uptake of dissolved oxygen from the atmosphere via air-sea gas exchange and its physical transport away from the region of uptake are crucial for supplying oxygen to the deep ocean. This process takes place in a few key regions that feature intense oxygen uptake, deep water formation, and physical oxygen export. In this study we analyze one such region, the Labrador Sea, utilizing the World Ocean Database (WOD) to construct a 65–year oxygen content time series in the Labrador Sea Water (LSW) layer (0–2200 m). The data reveal decadal variability associated with the strength of deep convection, with a maximum anomaly of 27 mol m–2 in 1992. There is no long-term trend in the time series, suggesting that the mean oxygen uptake is balanced by oxygen export out of the region. We compared the time series with output from nine models of the Ocean Model Intercomparison Project phase 1 in the Climate Model Intercomparison Project phase 6, (CMIP6-OMIP1), and constructed a “model score” to evaluate how well they match oxygen observations. Most CMIP6-OMIP1 models score around 50/100 points and the highest score is 57/100 for the ensemble mean, suggesting that improvements are needed. All of the models underestimate the maximum oxygen content anomaly in the 1990s. One possible cause for this is the representation of air-sea gas exchange for oxygen, with all models underestimating the mean uptake by a factor of two or more. Unrealistically deep convection and biased mean oxygen profiles may also contribute to the mismatch. Refining the representation of these processes in climate models could be vital for enhanced predictions of deoxygenation. In the CMIP6-OMIP1 multi-model mean, oxygen uptake has its maximum in 1980–1992, followed by a decrease in 1994–2006. There is a concurrent decrease in export, but oxygen storage also changes between the two periods, with oxygen accumulated in the first period and drained out in the second. Consequently, the change in oxygen export (5%) is much less than that in uptake (28%), suggesting that newly ventilated LSW which remains in the formation region acts to buffer the linkage between air-sea gas exchange and oxygen export.

Description: The field of oceanography is transitioning from data-poor to data-rich, thanks in part to increased deployment of in-situ platforms and sensors, such as those that instrument the US-funded Ocean Observatories Initiative (OOI). However, generating science-ready data products from these sensors, particularly those making biogeochemical measurements, often requires extensive end-user calibration and validation procedures, which can present a significant barrier. Openly available community-developed and -vetted Best Practices contribute to overcoming such barriers, but collaboratively developing user-friendly Best Practices can be challenging. Here we describe the process undertaken by the NSF-funded OOI Biogeochemical Sensor Data Working Group to develop Best Practices for creating science-ready biogeochemical data products from OOI data, culminating in the publication of the GOOS-endorsed OOI Biogeochemical Sensor Data Best Practices and User Guide. For Best Practices related to ocean observatories, engaging observatory staff is crucial, but having a “user-defined” process ensures the final product addresses user needs. Our process prioritized bringing together a diverse team and creating an inclusive environment where all participants could effectively contribute. Incorporating the perspectives of a wide range of experts and prospective end users through an iterative review process that included “Beta Testers’’ enabled us to produce a final product that combines technical information with a user-friendly structure that illustrates data analysis pipelines via flowcharts and worked examples accompanied by pseudo-code. Our process and its impact on improving the accessibility and utility of the end product provides a roadmap for other groups undertaking similar community-driven activities to develop and disseminate new Ocean Best Practices.