Abstract
Marginal seas are a dynamic and still to large extent uncertain component of the global carbon cycle. The large temporal and spatial variations of sea-surface partial pressure of carbon dioxide (pCO2) in these areas are driven by multiple complex mechanisms. In this study, we analyzed the variable importance for the sea surface pCO2 estimation in the Baltic Sea and derived monthly pCO2 maps for the marginal sea during the period of July 2002–October 2011. We used variables obtained from remote sensing images and numerical models. The random forest algorithm was employed to construct regression models for pCO2 estimation and produce the importance of different input variables. The study found that photosynthetically available radiation (PAR) was the most important variable for the pCO2 estimation across the entire Baltic Sea, followed by sea surface temperature (SST), absorption of colored dissolved organic matter (aCDOM), and mixed layer depth (MLD). Interestingly, Chlorophyll-a concentration (Chl-a) and the diffuse attenuation coefficient for downwelling irradiance at 490 nm (Kd_490nm) showed relatively low importance for the pCO2 estimation. This was mainly attributed to the high correlation of Chl-a and Kd_490nm to other pCO2-relevant variables (e.g., aCDOM), particularly in the summer months. In addition, the variables’ importance for pCO2 estimation varied between seasons and sub-basins. For example, the importance of aCDOM were large in the Gulf of Finland but marginal in other sub-basins. The model for pCO2 estimate in the entire Baltic Sea explained 63% of the variation and had a root of mean squared error (RMSE) of 47.8 µatm. The pCO2 maps derived with this model displayed realistic seasonal variations and spatial features of sea surface pCO2 in the Baltic Sea. The spatially and seasonally varying variables’ importance for the pCO2 estimation shed light on the heterogeneities in the biogeochemical and physical processes driving the carbon cycling in the Baltic Sea and can serve as an important basis for future pCO2 estimation in marginal seas using remote sensing techniques. The pCO2 maps derived in this study provided a robust benchmark for understanding the spatiotemporal patterns of CO2 air-sea exchange in the Baltic Sea.
Highlights
IntroductionThe changing air-sea exchange of CO2 in marginal seas, those at high-latitude, is found to be the major source of uncertainties in the estimate of ocean CO2 uptake [3,4]
On the entire Baltic Sea scale, photosynthetically available radiation (PAR) was the most important variable for the sea surface pCO2 estimate during 2002–2011. It meant that the errors of the random forest model constructed without PAR would be by 66% higher than that constructed with PAR
We found that the contributions of the variables to pCO2 retrieval for the Baltic Sea vary both spatially and temporally and likely replicated the spatiotemporal characteristics of the driving forces
Summary
The changing air-sea exchange of CO2 in marginal seas, those at high-latitude, is found to be the major source of uncertainties in the estimate of ocean CO2 uptake [3,4]. As the atmospheric CO2 is as rather globally homogenous, sea surface partial pressure of carbon dioxide (pCO2 ) in the marginal sea is the key component for precisely determining the direction of the air-sea exchange of CO2 . Deriving maps of the changing pCO2 for marginal seas over time is critical for precise estimate of global air-sea exchange and ocean uptake of CO2 [2,3,5]. Sea surface pCO2 is jointly determined by biogeochemical processes, vertical and horizontal mixing of sea water, and the air-sea exchange of CO2 [6,7]. Many sea surface variables related to these processes are can be retrieved from remote sensing images
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