On the porosity of barrier layers

Barrier layers are defined as the layer between the pycnocline and the thermocline when the latter are different as a result of salinity stratification. We present a revisited 2-degree resolution global climatology of monthly mean oceanic Barrier Layer (BL) thickness first proposed by de Boyer Montégut et al. (2007). In addition to using an extended data set, we present a modified computation method that addresses the observed porosity of BLs. We name porosity the fact that barrier layers distribution can, in some areas, be very uneven regarding the space and time scales that are considered. This implies an intermittent alteration of air-sea exchanges by the BL. Therefore, it may have important consequences for the climatic impact of BLs. Differences between the two computation methods are small for robust BLs that are formed by large-scale processes. However, the former approach can significantly underestimate the thickness of short and/or localized barrier layers. This is especially the case for barrier layers formed by mesoscale mechanisms (under the intertropical convergence zone for example and along western boundary currents) and equatorward of the sea surface salinity subtropical maxima. Complete characterisation of regional BL dynamics therefore requires a description of the robustness of BL distribution to assess the overall impact of BLs on the process of heat exchange between the ocean interior and the atmosphere

Southern Ocean bottom water characteristics in CMIP5 models

Southern Ocean deep water properties and formation processes in climate models are indicative of their capability to simulate future climate, heat and carbon uptake, and sea level rise. Southern Ocean temperature and density averaged over 1986–2005 from 15 CMIP5 (Coupled Model Intercomparison Project Phase 5) climate models are compared with an observed climatology, focusing on bottom water. Bottom properties are reasonably accurate for half the models. Ten models create dense water on the Antarctic shelf, but it mixes with lighter water and is not exported as bottom water as in reality. Instead, most models create deep water by open ocean deep convection, a process occurring rarely in reality. Models with extensive deep convection are those with strong seasonality in sea ice. Optimum bottom properties occur in models with deep convection in the Weddell and Ross Gyres. Bottom Water formation processes are poorly represented in ocean models and are a key challenge for improving climate predictions

Changes in global ocean bottom properties and volume transports in CMIP5 models under climate change scenarios

Changes in bottom temperature, salinity and density in the global ocean by 2100 for CMIP5 climate models are investigated for the climate change scenarios RCP4.5 and RCP8.5. The mean of 24 models shows a decrease in density in all deep basins except the North Atlantic which becomes denser. The individual model responses to climate change forcing are more complex: regarding temperature, the 24 models predict a warming of the bottom layer of the global ocean; in salinity, there is less agreement regarding the sign of the change, especially in the Southern Ocean. The magnitude and equatorward extent of these changes also vary strongly among models. The changes in properties can be linked with changes in the mean transport of key water masses. The Atlantic Meridional Overturning Circulation weakens in most models and is directly linked to changes in bottom density in the North Atlantic. These changes are due to the intrusion of modified Antarctic Bottom Water, made possible by the decrease in North Atlantic Deep Water formation. In the Indian, Pacific and South Atlantic, changes in bottom density are congruent with the weakening in Antarctic Bottom Water transport through these basins. We argue that the greater the 1986-2005 meridional transports, the more changes have propagated equatorwards by 2100. However, strong decreases in density over 100 years of climate change cause a weakening of the transports. The speed at which these property changes reach the deep basins is critical for a correct assessment of the heat storage capacity of the oceans as well as for predictions of future sea level rise

The Met Office Global Coupled model 3.0 and 3.1 (GC3.0 & GC3.1) configurations

The Global Coupled 3 (GC3) configuration of the Met Office Unified Model is presented. Amongst other applications, GC3 is the basis of the United Kingdom's submission to the Coupled Model Intercomparison Project 6 (CMIP6). This paper documents the model components that make up the configuration (although the scientific description of these components are in companion papers), and details the coupling between them. The performance of GC3 is assessed in terms of mean biases and variability in long climate simulations using present-day forcing. The suitability of the configuration for predictability on shorter timescales (weather and seasonal forecasting) is also briefly discussed. The performance of GC3 is compared against GC2, the previous Met Office coupled model configuration, and against an older configuration (HadGEM2-AO) which was the submission to CMIP5. In many respects, the performance of GC3 is comparable with GC2, however there is a notable improvement in the Southern Ocean warm sea surface temperature bias which has been reduced by 75%, and there are improvements in cloud amount and some aspects of tropical variability. Relative to HadGEM2-AO, many aspects of the present-day climate are improved in GC3 including tropospheric and stratospheric temperature structure, most aspects of tropical and extra-tropical variability and top-of-atmosphere & surface fluxes. A number of outstanding errors are identified including a residual asymmetric sea surface temperature bias (cool northern hemisphere, warm Southern Ocean), an overly strong global hydrological cycle and insufficient European blocking

Global assessment of ocean carbon export by combining satellite observations and food-web models

The export of organic carbon from the surface ocean by sinking particles is an important, yet highly uncertain, component of the global carbon cycle. Here we introduce a mechanistic assessment of the global ocean carbon export using satellite observations, including determinations of net primary production and the slope of the particle size spectrum, to drive a food-web model that estimates the production of sinking zooplankton feces and algal aggregates comprising the sinking particle flux at the base of the euphotic zone. The synthesis of observations and models reveals fundamentally different and ecologically consistent regional-scale patterns in export and export efficiency not found in previous global carbon export assessments. The model reproduces regional-scale particle export field observations and predicts a climatological mean global carbon export from the euphotic zone of ~6 Pg C yr−1. Global export estimates show small variation (typically < 10%) to factor of 2 changes in model parameter values. The model is also robust to the choices of the satellite data products used and enables interannual changes to be quantified. The present synthesis of observations and models provides a path for quantifying the ocean's biological pump

Mining a Sea of Data: Deducing the Environmental Controls of Ocean Chlorophyll

Chlorophyll biomass in the surface ocean is regulated by a complex interaction of physiological, oceanographic, and ecological factors and in turn regulates the rates of primary production and export of organic carbon to the deep ocean. Mechanistic models of phytoplankton responses to climate change require the parameterization of many processes of which we have limited knowledge. We develop a statistical approach to estimate the response of remote-sensed ocean chlorophyll to a variety of physical and chemical variables. Irradiance over the mixed layer depth, surface nitrate, sea-surface temperature, and latitude and longitude together can predict 83% of the variation in log chlorophyll in the North Atlantic. Light and nitrate regulate biomass through an empirically determined minimum function explaining nearly 50% of the variation in log chlorophyll by themselves and confirming that either light or macronutrients are often limiting and that much of the variation in chlorophyll concentration is determined by bottom-up mechanisms. Assuming the dynamics of the future ocean are governed by the same processes at work today, we should be able to apply these response functions to future climate change scenarios, with changes in temperature, nutrient distributions, irradiance, and ocean physics

Potential controls of isoprene in the surface ocean

Isoprene surface ocean concentrations and vertical distribution, atmospheric mixing ratios, and calculated sea-to-air fluxes spanning approximately 125° of latitude (80°N–45°S) over the Arctic and Atlantic Oceans are reported. Oceanic isoprene concentrations were associated with a number of concurrently monitored biological variables including chlorophyll a (Chl a), photoprotective pigments, integrated primary production (intPP), and cyanobacterial cell counts, with higher isoprene concentrations relative to all respective variables found at sea surface temperatures greater than 20°C. The correlation between isoprene and the sum of photoprotective carotenoids, which is reported here for the first time, was the most consistent across all cruises. Parameterizations based on linear regression analyses of these relationships perform well for Arctic and Atlantic data, producing a better fit to observations than an existing Chl a-based parameterization. Global extrapolation of isoprene surface water concentrations using satellite-derived Chl a and intPP reproduced general trends in the in situ data and absolute values within a factor of 2 between 60% and 85%, depending on the data set and algorithm used

Testing the climate intervention potential of ocean afforestation using the Great Atlantic Sargassum Belt

Ensuring that global warming remains 2 emissions reduction. Additionally, 100–900 gigatons CO2 must be removed from the atmosphere by 2100 using a portfolio of CO2 removal (CDR) methods. Ocean afforestation, CDR through basin-scale seaweed farming in the open ocean, is seen as a key component of the marine portfolio. Here, we analyse the CDR potential of recent re-occurring trans-basin belts of the floating seaweed Sargassum in the (sub)tropical North Atlantic as a natural analogue for ocean afforestation. We show that two biogeochemical feedbacks, nutrient reallocation and calcification by encrusting marine life, reduce the CDR efficacy of Sargassum by 20–100%. Atmospheric CO2 influx into the surface seawater, after CO2-fixation by Sargassum, takes 2.5–18 times longer than the CO2-deficient seawater remains in contact with the atmosphere, potentially hindering CDR verification. Furthermore, we estimate that increased ocean albedo, due to floating Sargassum, could influence climate radiative forcing more than Sargassum-CDR. Our analysis shows that multifaceted Earth-system feedbacks determine the efficacy of ocean afforestation

Skill metrics for confronting global upper ocean ecosystem-biogeochemistry models against field and remote sensing data

Author Posting. © Elsevier B.V., 2009. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Journal of Marine Systems 76 (2009): 95-112, doi:10.1016/j.jmarsys.2008.05.015.We present a generalized framework for assessing the skill of global upper ocean ecosystem-biogeochemical models against in-situ field data and satellite observations. We illustrate the approach utilizing a multi-decade (1979-2004) hindcast experiment conducted with the Community Climate System Model (CCSM-3) ocean carbon model. The CCSM-3 ocean carbon model incorporates a multi-nutrient, multi-phytoplankton functional group ecosystem module coupled with a carbon, oxygen, nitrogen, phosphorus, silicon, and iron biogeochemistry module embedded in a global, threedimensional ocean general circulation model. The model is forced with physical climate forcing from atmospheric reanalysis and satellite data products and time-varying atmospheric dust deposition. Data-based skill metrics are used to evaluate the simulated time-mean spatial patterns, seasonal cycle amplitude and phase, and subannual to interannual variability. Evaluation data include: sea surface temperature and mixed layer depth; satellite derived surface ocean chlorophyll, primary productivity, phytoplankton growth rate and carbon biomass; large-scale climatologies of surface nutrients, pCO2, and air-sea CO2 and O2 flux; and time-series data from the Joint Global Ocean Flux Study (JGOFS). Where the data is sufficient, we construct quantitative skill metrics using: model-data residuals, time-space correlation, root mean square error, and Taylor diagrams.This work was supported in part by grants from the NSF/ONR National Ocean Partnership Program (N000140210370), the NASA Ocean Biology and Biogeochemistry Program (NNX07AL80G), and the NSF Center for Microbial Oceanography Research and Education (C-MORE)

Mechanisms of decadal variability in the Labrador Sea and the wider North Atlantic in a high-resolution climate model

A necessary step before assessing the performance of decadal predictions is the evaluation of the processes that bring memory to the climate system, both in climate models and observations. These mechanisms are particularly relevant in the North Atlantic, where the ocean circulation, related to both the Subpolar Gyre and the Meridional Overturning Circulation (AMOC), is thought to be important for driving significant heat content anomalies. Recently, a rapid decline in observed densities in the deep Labrador Sea has pointed to an ongoing slowdown of the AMOC strength taking place since the mid 90s, a decline also hinted by in-situ observations from the RAPID array. This study explores the use of Labrador Sea densities as a precursor of the ocean circulation changes, by analysing a 300-year long simulation with the state-of-the-art coupled model HadGEM3-GC2. The major drivers of Labrador Sea density variability are investigated, and are characterised by three major contributions. First, the integrated effect of local surface heat fluxes, mainly driven by year-to-year changes in the North Atlantic Oscillation, which accounts for 62% of the total variance. Additionally, two multidecadal-to-centennial contributions from the Greenland-Scotland Ridge outflows are quantified; the first associated with freshwater exports via the East Greenland Current, and the second with density changes in the Denmark Strait Overflow. Finally, evidence is shown that decadal trends in Labrador Sea densities are followed by important atmospheric impacts. In particular, a negative winter NAO response appears to follow the positive Labrador Sea density trends, and provides a phase reversal mechanism