Abstract

Abstract. Autonomous measurements aboard ships of opportunity (SOOP) provide in situ data sets with high spatial and temporal coverage. In this study, we use 8 years of carbon dioxide (CO2) and methane (CH4) observations from SOOP Finnmaid to study the influence of upwelling on trace gas dynamics in the Baltic Sea. Between spring and autumn, coastal upwelling transports water masses enriched with CO2 and CH4 to the surface of the Baltic Sea. We study the seasonality, regional distribution, relaxation, and interannual variability in this process. We use reanalysed wind and modelled sea surface temperature (SST) data in a newly established statistical upwelling detection method to identify major upwelling areas and time periods. Large upwelling-induced SST decrease and trace gas concentration increase are most frequently detected around August after a long period of thermal stratification, i.e. limited exchange between surface and underlying waters. We found that these upwelling events with large SST excursions shape local trace gas dynamics and often lead to near-linear relationships between increasing trace gas levels and decreasing temperature. Upwelling relaxation is mainly driven by mixing, modulated by air–sea gas exchange, and possibly primary production. Subsequent warming through air–sea heat exchange has the potential to enhance trace gas saturation. In 2015, quasi-continuous upwelling over several months led to weak summer stratification, which directly impacted the observed trace gas and SST dynamics in several upwelling-prone areas. Trend analysis is still prevented by the observed high variability, uncertainties from data coverage, and long water residence times of 10–30 years. We introduce an extrapolation method based on trace gas–SST relationships that allows us to estimate upwelling-induced trace gas fluxes in upwelling-affected regions. In general, the surface water reverses from CO2 sink to source, and CH4 outgassing is intensified as a consequence of upwelling. We conclude that SOOP data, especially when combined with other data sets, enable flux quantification and process studies addressing the process of upwelling on large spatial and temporal scales.

Highlights

  • Coastal upwelling areas are known to be hotspots of greenhouse gas emissions from marine systems to the atmosphere (Capelle and Tortell, 2016; Morgan et al, 2019)

  • We found that these upwelling events with large sea surface temperature (SST) excursions shape local trace gas dynamics and often lead to near-linear relationships between increasing trace gas levels and decreasing temperature

  • To assess the prevalence of upwelling in the data set of ships of opportunity (SOOP) Finnmaid, we identified the main upwelling periods and areas along the transect using the method of combining a SST and a wind criterion (Sect. 2.3)

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Summary

Introduction

Coastal upwelling areas are known to be hotspots of greenhouse gas emissions from marine systems to the atmosphere (Capelle and Tortell, 2016; Morgan et al, 2019). The large extent to which the Baltic Sea is influenced by climatic and anthropogenic forces and the availability of the presented 8-year data set of SOOP Finnmaid and of highresolution models (Placke et al, 2018; Gräwe et al, 2019) make the Baltic Sea a unique study site to detect feedbacks early and to develop methods and process understanding that can be used to analyse long-term data sets with respect to, for example, upwelling-induced trace gas dynamics. The SOOP strategy allows us to investigate the influence of coastal upwelling on surface pCO2 and cCH4 in the Baltic Sea on a large spatial and temporal scale without issues of bad coverage of seasonality due to (biased) individual research-vesselbased studies. – – Only east of Öland Only south-east of Gotland Only north-west of Gotland – Only south-east of Hanko Peninsula –

Measurements aboard SOOP Finnmaid
Wind and modelled SST data
Identification of upwelling events
Upwelling statistics based on wind and modelled SST data
Regional comparison of upwelling events
Typical relaxation of upwelling-induced trace gas signals
Interannual variability in upwelling-induced trace gas signals
Potential to estimate upwelling-induced air–sea trace gas fluxes
Conclusions
Data processing and visualisation
Air–water equilibrator response times
Calculation of theoretical relaxation and flux estimates
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