Posts Tagged 'globalmodeling'

The potential of 230Th for detection of ocean acidification impacts on pelagic carbonate production

Concentrations of dissolved 230Th in the ocean water column increase with depth due to scavenging and downward particle flux. Due to the 230Th scavenging process, any change in the calcium carbonate (CaCO3) fraction of the marine particle flux due to changes in biological CaCO3 hard shell production as a consequence of progressing ocean acidification would be reflected in the dissolved 230Th activity. Our prognostic simulations with a biogeochemical ocean general circulation model using different scenarios for the reduction of CaCO3production under ocean acidification and different greenhouse gas emission scenarios (RCPs 8.5 to 2.6) reveal the potential for deep 230Th measurements to detect reduced CaCO3 production at the sea surface. The time of emergence of an acidification induced signal on dissolved 230Th is of the same order of magnitude as for alkalinity measurements. Yet, deep ocean 230Th concentrations are less affected by seasonal and multiyear variability than surface alkalinity. Thus, deep ocean 230Th observations could be advantageous to guide monitoring and detection campaigns. Furthermore, given that the precision of 230Th measurements may potentially improve in the near future, earlier detection of ocean acidification impact signals would be possible. Our results indicate that the deep Pacific Ocean and the deep Southern Ocean are the most suitable regions for selected regular reoccupations of deep reaching 230Th stations.

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Climate, anchovy, and sardine

Anchovy and sardine populated productive ocean regions over hundreds of thousands of years under a naturally varying climate, and are now subject to climate change of equal or greater magnitude occurring over decades to centuries. We hypothesize that anchovy and sardine populations are limited in size by the supply of nitrogen from outside their habitats originating from upwelling, mixing, and rivers. Projections of the responses of anchovy and sardine to climate change rely on a range of model types and consideration of the effects of climate on lower trophic levels, the effects of fishing on higher trophic levels, and the traits of these two types of fish. Distribution, phenology, nutrient supply, plankton composition and production, habitat compression, fishing, and acclimation and adaptation may be affected by ocean warming, acidification, deoxygenation, and altered hydrology. Observations of populations and evaluation of model skill are essential to resolve the effects of climate change on these fish.

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Evaluation of the ocean ecosystem: Climate change modelling with backstop technologies

This paper discusses the economic impacts of climate change, including those on ecosystems, and whether a new backstop technology should be used under conditions of strict temperature targets. Using the dynamic integrated climate-economy (DICE) model, we developed a new model to calculate the optimal path by considering new backstop technologies, such as CO2 capture and storage (CCS). We identify the effects of parameter changes based on the resulting differences in CO2 leakage and sites, and we analyse the feasibility of CCS. In addition, we focus on ocean acidification and consider the impact on economic activity. As a result, when CCS is assumed to carry a risk of CO2 leakage and acidification is considered to result in a decrease in utility, we find that CCS can only delay the effects of climate change, but its use is necessary to achieve strict targets, such as a 1.5 °C limit. This observation suggests that if the target temperature is too tight, we might end up employing a technology that sacrifices the ecosystem too greatly.

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Drivers and implications of change in global ocean health over the past five years

Growing international and national focus on quantitatively measuring and improving ocean health has increased the need for comprehensive, scientific, and repeated indicators to track progress towards achieving policy and societal goals. The Ocean Health Index (OHI) is one of the few indicators available for this purpose. Here we present results from five years of annual global assessment for 220 countries and territories, evaluating potential drivers and consequences of changes and presenting lessons learned about the challenges of using composite indicators to measure sustainability goals. Globally scores have shown little change, as would be expected. However, individual countries have seen notable increases or declines due in particular to improvements in the harvest and management of wild-caught fisheries, the creation of marine protected areas (MPAs), and decreases in natural product harvest. Rapid loss of sea ice and the consequent reduction of coastal protection from that sea ice was also responsible for declines in overall ocean health in many Arctic and sub-Arctic countries. The OHI performed reasonably well at predicting near-term future scores for many of the ten goals measured, but data gaps and limitations hindered these predictions for many other goals. Ultimately, all indicators face the substantial challenge of informing policy for progress toward broad goals and objectives with insufficient monitoring and assessment data. If countries and the global community hope to achieve and maintain healthy oceans, we will need to dedicate significant resources to measuring what we are trying to manage.

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The role of biological rates in the simulated warming effect on oceanic CO2 uptakel

Marine biology plays an important role in the ocean carbon cycle. However, the effect of warming-induced changes in biological rates on oceanic CO2 uptake has been largely overlooked. We use an Earth system model of intermediate complexity to investigate the effect of temperature-induced changes in biological rates on oceanic uptake of atmospheric CO2 and compare it with the effects from warming-induced changes in CO2 solubility and ocean mixing and circulation. Under the representative CO2 concentration pathway RCP 8.5 and its extension, by year 2500, relative to the simulation without warming effect on the ocean carbon cycle, CO2-induced warming reduces cumulative oceanic CO2 uptake by 469 Pg C, of which about 20% is associated with the warming-induced change in marine biological rates. In our simulations, the bulk effect of biological-mediated changes on CO2 uptake is smaller than that mediated by changes in CO2 solubility and ocean mixing and circulation. However, warming-induced changes in individual biological rates, including phytoplankton growth, phytoplankton mortality, and detritus remineralization, are found to affect oceanic CO2 uptake by an amount greater than or comparable to that caused by changes in CO2 solubility and ocean physics. Our simulations, which include only a few temperature-dependent biological processes, demonstrate the important role of biological rates in the oceanic CO2 uptake. In reality, many more complicated biological processes are sensitive to temperature change, and their responses to warming could substantially affect oceanic uptake of atmospheric CO2.

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Sensitivity of future ocean acidification to carbon climate feedbacks

Carbon-climate feedbacks have the potential to significantly impact the future climate by altering atmospheric CO2 concentrations (Zaehle et al., 2010). By modifying the future atmospheric CO2 concentrations, the carbon-climate feedbacks will also influence the future trajectory for ocean acidification. Here, we use the CO2 emissions scenarios from 4 Representative Concentration Pathways (RCPs) with an Earth System Model to project the future trajectories of ocean acidification with the inclusion of carbon-climate feedbacks. We show that simulated carbon-climate feedbacks can significantly impact the onset of under-saturated aragonite conditions in the Southern and Arctic Oceans, the suitable habitat for tropical coral and the deepwater saturation states. Under higher emission scenarios (RCP8.5 and RCP6.0), the carbon-climate feedbacks advance the onset of under-saturation conditions and the reduction in suitable coral reef habitat by a decade or more. The impact of the carbon-climate feedback is most significant for the medium (RCP4.5) and low emission (RCP2.6) scenarios. For RCP4.5 scenario by 2100, the carbon-climate feedbacks nearly double the area of surface water under-saturated respect to aragonite and reduce by 50 % the surface water suitable for coral reefs. For RCP2.6 scenario by 2100, the carbon-climate feedbacks reduce the area suitable for coral reefs by 40 % and increase the area of under-saturated surface water by 20 %. The high sensitivity of the impact of ocean acidification to the carbon-climate feedbacks in the low to medium emissions scenarios is important because our recent commitments to reduce CO2 emissions are trying to move us on to such an emissions scenario. The study highlights the need to better characterise the carbon-climate feedbacks to ensure we do not excessively stress the oceans by under-estimating the future impact of ocean acidification.

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Estimates of water-column nutrient concentrations and carbonate system parameters in the global ocean: a novel approach based on neural networks


A neural network-based method (CANYON: CArbonate system and Nutrients concentration from hYdrological properties and Oxygen using a Neural-network) was developed to estimate water-column (i.e., from surface to 8,000 m depth) biogeochemically relevant variables in the Global Ocean. These are the concentrations of three nutrients [nitrate (NO3−), phosphate (PO43−), and silicate (Si(OH)4)] and four carbonate system parameters [total alkalinity (AT), dissolved inorganic carbon (CT), pH (pHT), and partial pressure of CO2 (pCO2)], which are estimated from concurrent in situ measurements of temperature, salinity, hydrostatic pressure, and oxygen (O2) together with sampling latitude, longitude, and date. Seven neural-networks were developed using the GLODAPv2 database, which is largely representative of the diversity of open-ocean conditions, hence making CANYON potentially applicable to most oceanic environments. For each variable, CANYON was trained using 80 % randomly chosen data from the whole database (after eight 10° × 10° zones removed providing an “independent data-set” for additional validation), the remaining 20 % data were used for the neural-network test of validation. Overall, CANYON retrieved the variables with high accuracies (RMSE): 1.04 μmol kg−1 (NO3−), 0.074 μmol kg−1 (PO43−), 3.2 μmol kg−1 (Si(OH)4), 0.020 (pHT), 9 μmol kg−1 (AT), 11 μmol kg−1 (CT) and 7.6 % (pCO2) (30 μatm at 400 μatm). This was confirmed for the eight independent zones not included in the training process. CANYON was also applied to the Hawaiian Time Series site to produce a 22 years long simulated time series for the above seven variables. Comparison of modeled and measured data was also very satisfactory (RMSE in the order of magnitude of RMSE from validation test). CANYON is thus a promising method to derive distributions of key biogeochemical variables. It could be used for a variety of global and regional applications ranging from data quality control to the production of datasets of variables required for initialization and validation of biogeochemical models that are difficult to obtain. In particular, combining the increased coverage of the global Biogeochemical-Argo program, where O2 is one of the core variables now very accurately measured, with the CANYON approach offers the fascinating perspective of obtaining large-scale estimates of key biogeochemical variables with unprecedented spatial and temporal resolutions. The Matlab and R codes of the proposed algorithms are provided as Supplementary Material.

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Ocean acidification in the IPCC AR5 WG II

OUP book