Posts Tagged 'globalmodeling'

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.

Continue reading ‘Drivers and implications of change in global ocean health over the past five years’

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.

Continue reading ‘The role of biological rates in the simulated warming effect on oceanic CO2 uptakel’

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.

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

Response of export production and dissolved oxygen concentrations in oxygen minimum zones to pCO2 and temperature stabilization scenarios in the biogeochemical model HAMOCC 2.0 (update)

Dissolved oxygen (DO) concentration in the ocean is an important component of marine biogeochemical cycles and will be greatly altered as climate change persists. In this study a global oceanic carbon cycle model (HAMOCC 2.0) is used to address how mechanisms of oxygen minimum zone (OMZ) expansion respond to changes in CO2 radiative forcing. Atmospheric pCO2 is increased at a rate of 1 % annually and the model is stabilized at 2 ×, 4 ×, 6  ×, and 8 × preindustrial pCO2 levels. With an increase in CO2 radiative forcing, the OMZ in the Pacific Ocean is controlled largely by changes in particulate organic carbon (POC) export, resulting in increased remineralization and thus expanding the OMZs within the tropical Pacific Ocean. A potential decline in primary producers in the future as a result of environmental stress due to ocean warming and acidification could lead to a substantial reduction in POC export production, vertical POC flux, and thus increased DO concentration particularly in the Pacific Ocean at a depth of 600–800 m. In contrast, the vertical expansion of the OMZs within the Atlantic is linked to increases POC flux as well as changes in oxygen solubility with increasing seawater temperature. Changes in total organic carbon and increase sea surface temperature (SST) also lead to the formation of a new OMZ in the western subtropical Pacific Ocean. The development of the new OMZ results in dissolved oxygen concentration of  ≤  50 µmol kg−1 throughout the equatorial Pacific Ocean at 4 times preindustrial pCO2. Total ocean volume with dissolved oxygen concentrations of  ≤  50 µmol kg−1 increases by 2.4, 5.0, and 10.5 % for the 2 ×, 4 ×, and 8 × CO2 simulations, respectively.

Continue reading ‘Response of export production and dissolved oxygen concentrations in oxygen minimum zones to pCO2 and temperature stabilization scenarios in the biogeochemical model HAMOCC 2.0 (update)’

Timing of global regression and microbial bloom linked with the Permian-Triassic boundary mass extinction: implications for driving mechanisms

New high-resolution U-Pb dates indicate a duration of 89 ± 38 kyr for the Permian hiatus and of 14 ± 57 kyr for the overlying Triassic microbial limestone in shallow water settings of the Nanpanjiang Basin, South China. The age and duration of the hiatus coincides with the Permian-Triassic boundary (PTB) and the extinction interval in the Meishan Global Stratotype Section and Point, and strongly supports a glacio-eustatic regression, which best explains the genesis of the worldwide hiatus straddling the PTB in shallow water records. In adjacent deep marine troughs, rates of sediment accumulation display a six-fold decrease across the PTB compatible with a dryer and cooler climate as indicated by terrestrial plants. Our model of the Permian-Triassic boundary mass extinction (PTBME) hinges on the synchronicity of the hiatus with the onset of the Siberian Traps volcanism. This early eruptive phase released sulfur-rich volatiles into the stratosphere, thus simultaneously eliciting a short-lived ice age responsible for the global regression and a brief but intense acidification. Abrupt cooling, shrunk habitats on shelves and acidification may all have synergistically triggered the PTBME. Subsequently, the build-up of volcanic CO2 induced a transient cool climate whose early phase saw the deposition of the microbial limestone.

Continue reading ‘Timing of global regression and microbial bloom linked with the Permian-Triassic boundary mass extinction: implications for driving mechanisms’

The geologic history of seawater pH

Although pH is a fundamental property of Earth’s oceans, critical to our understanding of seawater biogeochemistry, its long-timescale geologic history is poorly constrained. We constrain seawater pH through time by accounting for the cycles of the major components of seawater. We infer an increase from early Archean pH values between ~6.5 and 7.0 and Phanerozoic values between ~7.5 and 9.0, which was caused by a gradual decrease in atmospheric pCO2 in response to solar brightening, alongside a decrease in hydrothermal exchange between seawater and the ocean crust. A lower pH in Earth’s early oceans likely affected the kinetics of chemical reactions associated with the origin of life, the energetics of early metabolisms, and climate through the partitioning of CO2 between the oceans and atmosphere.

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Ocean acidification in the IPCC AR5 WG II

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