The northern European shelf as an increasing net sink for CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;

Meike Becker,Gregor Rehder,Are Olsen,Peter Landschützer,Ingunn Skjelvan,Christian Rödenbeck,Abdirhaman Omar

doi:10.5194/bg-18-1127-2021

Abstract

Abstract. We developed a simple method to refine existing open-ocean maps and extend them towards different coastal seas. Using a multi-linear regression we produced monthly maps of surface ocean fCO2 in the northern European coastal seas (the North Sea, the Baltic Sea, the Norwegian Coast and the Barents Sea) covering a time period from 1998 to 2016. A comparison with gridded Surface Ocean CO2 Atlas (SOCAT) v5 data revealed mean biases and standard deviations of 0 ± 26 µatm in the North Sea, 0 ± 16 µatm along the Norwegian Coast, 0 ± 19 µatm in the Barents Sea and 2 ± 42 µatm in the Baltic Sea. We used these maps to investigate trends in fCO2, pH and air–sea CO2 flux. The surface ocean fCO2 trends are smaller than the atmospheric trend in most of the studied regions. The only exception to this is the western part of the North Sea, where sea surface fCO2 increases by 2 µatm yr−1, which is similar to the atmospheric trend. The Baltic Sea does not show a significant trend. Here, the variability was much larger than the expected trends. Consistently, the pH trends were smaller than expected for an increase in fCO2 in pace with the rise of atmospheric CO2 levels. The calculated air–sea CO2 fluxes revealed that most regions were net sinks for CO2. Only the southern North Sea and the Baltic Sea emitted CO2 to the atmosphere. Especially in the northern regions the sink strength increased during the studied period.

Highlights

For facing global challenges, such as predicting and tracking climate change, it is important to improve our understanding of the ocean carbon sink and its variability
The multi-linear regression (MLR) substantially improve the predictions of the open-ocean maps in all studied regions, showing a better average offset and standard deviation (SD) to Surface Ocean CO2 Atlas (SOCAT) v5 and method efficiency (ME) than the coarser-resolution open-ocean maps
The performance of the MLR and the maps is evaluated in different ways: (1) using the R2 and the root mean square error (RMSE) of the fit; (2) using the average deviation and its SD, as well as the ME between the produced f CO2 maps and the gridded observations as a regional average; (3) showing the median deviation between the MLR and the gridded observations on a monthly level; and (4) by comparing the data from the f CO2 maps to observations from two time series stations. (2)–(4) will be shown for the time period covered by the driver data (1998– 2016) and for the prediction of the f CO2 values for 2017 and 2018

Summary

Introduction

For facing global challenges, such as predicting and tracking climate change, it is important to improve our understanding of the ocean carbon sink and its variability. Reliable autonomous systems for measuring carbon dioxide partial pressure from commercial vessels were developed in the early 2000s (Pierrot et al, 2009) and have since been deployed on a large number of vessels (e.g., Bakker et al, 2016). This has resulted in sufficient data to develop methods to interpolate the data and to describe largescale air–sea CO2 exchange and its variability (Landschützer et al, 2014, 2013; Rödenbeck et al, 2013; Jones et al, 2015). By comparing the different results, it is possible to achieve a good estimate of the uncertainty associated with the respective methods (Rödenbeck et al, 2015)

Methods

Results

Discussion

Conclusion