Surface Carbon EOV Report

Surface carbon syntheses and impact of AtlantOS observation

Direct measurements of CO2 flux in the Greenland Sea

During summer 2006 eddy correlation CO2 fluxes were measured in the Greenland Sea using a novel system set-up with two shrouded LICOR-7500 detectors. One detector was used exclusively to determine, and allow the removal of, the bias on CO2 fluxes due to sensor motion. A recently published correction method for the CO2-H2O cross-correlation was applied to the data set. We show that even with shrouded sensors the data require significant correction due to this cross-correlation. This correction adjusts the average CO2 flux by an order of magnitude from -6.7 x 10⁻² mol m⁻² day⁻¹ to -0.61 x 10⁻² mol m⁻² day⁻¹, making the corrected fluxes comparable to those calculated using established parameterizations for transfer velocity

The Nordic Seas carbon budget: Sources, sinks, and uncertainties

A carbon budget for the Nordic Seas is derived by combining recent inorganic carbon data from the CARINA database with relevant volume transports. Values of organic carbon in the Nordic Seas' water masses, the amount of carbon input from river runoff, and the removal through sediment burial are taken from the literature. The largest source of carbon to the Nordic Seas is the Atlantic Water that enters the area across the Greenland-Scotland Ridge; this is in particular true for the anthropogenic CO2. The dense overflows into the deep North Atlantic are the main sinks of carbon from the Nordic Seas. The budget show that presently 12.3 ± 1.4 Gt C yr−1 is transported into the Nordic Seas and that 12.5 ± 0.9 Gt C yr−1 is transported out, resulting in a net advective carbon transport out of the Nordic Seas of 0.17 ± 0.06 Gt C yr−1. Taking storage into account, this implies a net air-to-sea CO2 transfer of 0.19 ± 0.06 Gt C yr−1 into the Nordic Seas. The horizontal transport of carbon through the Nordic Seas is thus approximately two orders of magnitude larger than the CO2 uptake from the atmosphere. No difference in CO2 uptake was found between 2002 and the preindustrial period, but the net advective export of carbon from the Nordic Seas is smaller at present due to the accumulation of anthropogenic CO2

Respiration Patterns in the Dark Ocean

In the dark ocean, respiring organisms are the main sink for dissolved oxygen. The respiration rate in a given seawater volume can be quantified through dissolved oxygen drawdown or organic matter consumption as a function of time. Estimates of dissolved oxygen utilization rates (OUR) abound in the literature, but are typically obtained using proxies of questionable accuracy, often with low vertical resolution, and neglecting key regions such as the Southern and Indian oceans. Respiration rates based on particulate (POC) or dissolved (DOC) organic carbon are also sparsely observed and for DOC are unavailable in many regions. Consequently, the relative contributions of POC or DOC as a respiration substrate in the dark ocean are unknown. Here, we use recent datasets of true oxygen utilization, seawater age, and DOC to derive OUR and DOC consumption-rate profiles in 10 oceanic regions. We demonstrate that although DOC and POC consumption rates are globally consistent with OUR, they underestimate OUR in the deep, suggesting strong oxygen utilization at the seafloor. In the abyss, we find a negative correlation of the DOC consumption rate with seawater age, suggesting that DOC reactivity decreases along the deep branch of the conveyor circulation. Our results highlight that benthic organisms are sensitive to perturbations in the surface production of organic matter and to large-scale circulation changes that affect its supply to the abyss

Context matters when using climate model projections for aquaculture

At present, specific guidance on how to choose, assess and interpret climate model projections for the aquaculture sector is scarce. Since many aspects of aquaculture production are influenced by the local farm-level environment, there is a need to consider how climate model projections can be used to predict potential future farming conditions locally. This study compared in-situ measurements of temperature and salinity from Norwegian salmon farms and fixed monitoring stations to simulations from a regional ocean climate model for multiple locations and depths in southern Norway. For locations considered in this study, a similar seasonal cycle in terms of phasing was visible for modelled and measured temperatures. For some depths and times of the year the modelled and measured temperatures were similar, but for others there were differences. The model tended to underestimate temperature. On occasion there were differences between average modelled and measured temperatures of several degrees and aquaculture users would need to consider the implications of using the modelled temperatures. As for salinity, the model does not include localized freshwater inputs, so the model overestimated salinity for locations close to shore and was not able to represent more brackish water conditions in shallower depths. It was not possible to draw a general conclusion as to whether the model was suitable for aquaculture purposes, as the similarities and differences between the modelled and measured values varied by variable, area, depth, and time. These findings made it clear that aquaculture users would have to implement a process to determine whether they could use climate model outputs for their specific purpose. A model vetting framework is presented that can be used to support decisions on the use of climate model projections for aquaculture purposes. The vetting framework describes four stages that can be used to establish the necessary context regarding the aquaculture requirements and model capabilities, and then check how the model is simulating the conditions of interest at farm sites. Although the focus was aquaculture, the findings are relevant for other sectors and the framework can guide use of climate models for more local-scale assessment and management in coastal locations

How is the ocean anthropogenic carbon reservoir filled?

About a quarter of the total anthropogenic CO2 emissions during the industrial era has been absorbed by the ocean. The rate limiting step for this uptake is the transport of the anthropogenic carbon (Cant) from the ocean mixed layer where it is absorbed to the interior ocean where it is stored. While it is generally known that deep water formation sites are important for vertical carbon transport, the exact magnitude of the fluxes across the base of the mixed layer in different regions is uncertain. Here, we determine where, when, and how much Cant has been injected across the mixed-layer base and into the interior ocean since the start of the industrialized era. We do this by combining a transport matrix derived from observations with a time-evolving boundary condition obtained from already published estimates of ocean Cant. Our results show that most of the Cant stored below the mixed layer are injected in the subtropics (40.1%) and the Southern Ocean (36.0%), while the Subpolar North Atlantic has the largest fluxes. The Subpolar North Atlantic is also the most important region for injecting Cant into the deep ocean with 81.6% of the Cant reaching depths greater than 1,000 m. The subtropics, on the other hand, have been the most efficient in transporting Cant across the mixed-layer base per volume of water ventilated. This study shows how the oceanic Cant uptake relies on vertical transports in a few oceanic regions and sheds light on the pathways that fill the ocean Cant reservoir

Dissolved Inorganic Nutrients in the Western Mediterranean Sea (2004-2017)

Abstract. Long-term time-series are a fundamental prerequisite to understand and detect climate shifts and trends. Understanding the complex interplay of changing ocean variables and the biological implication for marine ecosystems requires extensive data collection for monitoring and hypothesis testing and validation of modelling products. In marginal seas, such as Mediterranean Sea, there are still monitoring gaps, both in time and in space. To contribute filling these gaps, an extensive dataset of dissolved inorganic nutrients profiles (nitrate, NO3; phosphate, PO4 ; and silicate, SiO2) have been collected between 2004 and 2017 in the Western Mediterranean Sea and subjected to quality control techniques to provide to the scientific community a publicly available, long-term, quality controlled, internally consistent biogeochemical data product. The database includes 27 870 stations of dissolved inorganic nutrients sampled during 24 cruises, including temperature and salinity. Details of the quality control (primary and secondary quality control) applied are reported. The data are available in PANGAEA (https://doi.pangaea.de/10.1594/PANGAEA.904172, Belgacem et al. 2019) Keywords: Mediterranean Sea, Dissolved Inorganic Nutrient, biogeochemistr

Context matters when using climate model projections for aquaculture

At present, specific guidance on how to choose, assess and interpret climate model projections for the aquaculture sector is scarce. Since many aspects of aquaculture production are influenced by the local farm-level environment, there is a need to consider how climate model projections can be used to predict potential future farming conditions locally. This study compared in-situ measurements of temperature and salinity from Norwegian salmon farms and fixed monitoring stations to simulations from a regional ocean climate model for multiple locations and depths in southern Norway. For locations considered in this study, a similar seasonal cycle in terms of phasing was visible for modelled and measured temperatures. For some depths and times of the year the modelled and measured temperatures were similar, but for others there were differences. The model tended to underestimate temperature. On occasion there were differences between average modelled and measured temperatures of several degrees and aquaculture users would need to consider the implications of using the modelled temperatures. As for salinity, the model does not include localized freshwater inputs, so the model overestimated salinity for locations close to shore and was not able to represent more brackish water conditions in shallower depths. It was not possible to draw a general conclusion as to whether the model was suitable for aquaculture purposes, as the similarities and differences between the modelled and measured values varied by variable, area, depth, and time. These findings made it clear that aquaculture users would have to implement a process to determine whether they could use climate model outputs for their specific purpose. A model vetting framework is presented that can be used to support decisions on the use of climate model projections for aquaculture purposes. The vetting framework describes four stages that can be used to establish the necessary context regarding the aquaculture requirements and model capabilities, and then check how the model is simulating the conditions of interest at farm sites. Although the focus was aquaculture, the findings are relevant for other sectors and the framework can guide use of climate models for more local-scale assessment and management in coastal locations

Nordic Seas Heat Loss, Atlantic Inflow, and Arctic Sea Ice cover over the last century

Poleward ocean heat transport is a key process in the earth system. We detail and review the northward Atlantic Water (AW) flow, Arctic Ocean heat transport, and heat loss to the atmosphere since 1900 in relation to sea ice cover. Our synthesis is largely based on a sea ice-ocean model forced by a reanalysis atmosphere (1900-2018) corroborated by a comprehensive hydrographic database (1950-), AW inflow observations (1996-), and other long-term time series of sea ice extent (1900-), glacier retreat (1984-) and Barents Sea hydrography (1900-). The Arctic Ocean, including the Nordic and Barents Seas, has warmed since the 1970s. This warming is congruent with increased ocean heat transport and sea ice loss and has contributed to the retreat of marine-terminating glaciers on Greenland. Heat loss to the atmosphere is largest in the Nordic Seas (60% of total) with large variability linked to the frequency of Cold Air Outbreaks and cyclones in the region, but there is no long-term statistically significant trend. Heat loss from the Barents Sea (∼30%) and Arctic seas farther north (∼10%) is overall smaller, but exhibit large positive trends. The AW inflow, total heat loss to the atmosphere, and dense outflow have all increased since 1900. These are consistently related through theoretical scaling, but the AW inflow increase is also wind-driven. The Arctic Ocean CO2 uptake has increased by ∼30% over the last century - consistent with Arctic sea ice loss allowing stronger air-sea interaction and is ∼8% of the global uptake

A new global interior ocean mapped climatology: the 1° × 1° GLODAP version 2

We present a mapped climatology (GLODAPv2.2016b) of ocean biogeochemical variables based on the new GLODAP version 2 data product (Olsen et al., 2016; Key et al., 2015), which covers all ocean basins over the years 1972 to 2013. The quality-controlled and internally consistent GLODAPv2 was used to create global 1°  ×  1° mapped climatologies of salinity, temperature, oxygen, nitrate, phosphate, silicate, total dissolved inorganic carbon (TCO2), total alkalinity (TAlk), pH, and CaCO3 saturation states using the Data-Interpolating Variational Analysis (DIVA) mapping method. Improving on maps based on an earlier but similar dataset, GLODAPv1.1, this climatology also covers the Arctic Ocean. Climatologies were created for 33 standard depth surfaces. The conceivably confounding temporal trends in TCO2 and pH due to anthropogenic influence were removed prior to mapping by normalizing these data to the year 2002 using first-order calculations of anthropogenic carbon accumulation rates. We additionally provide maps of accumulated anthropogenic carbon in the year 2002 and of preindustrial TCO2. For all parameters, all data from the full 1972–2013 period were used, including data that did not receive full secondary quality control. The GLODAPv2.2016b global 1°  ×  1° mapped climatologies, including error fields and ancillary information, are available at the GLODAPv2 web page at the Carbon Dioxide Information Analysis Center (CDIAC; doi:10.3334/CDIAC/OTG.NDP093_GLODAPv2)