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

Langmuir turbulence and surface heating in the ocean surface boundary layer

This study uses large-eddy simulation to investigate the structure of the ocean surface boundary layer (OSBL) in the presence of Langmuir turbulence and stabilizing surface heat fluxes. The OSBL consists of a weakly stratified layer, despite a surface heat flux, above a stratified thermocline. The weakly stratified (mixed) layer is maintained by a combination of a turbulent heat flux produced by the wave-driven Stokes drift and downgradient turbulent diffusion. The scaling of turbulence statistics, such as dissipation and vertical velocity variance, is only affected by the surface heat flux through changes in the mixed layer depth. Diagnostic models are proposed for the equilibrium boundary layer and mixed layer depths in the presence of surface heating. The models are a function of the initial mixed layer depth before heating is imposed and the Langmuir stability length. In the presence of radiative heating, the models are extended to account for the depth profile of the heating

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

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)

Steric sea level variability (1993-2010) in an ensemble of ocean reanalyses and objective analyses

Quantifying the effect of the seawater density changes on sea level variability is of crucial importance for climate change studies, as the sea level cumulative rise can be regarded as both an important climate change indicator and a possible danger for human activities in coastal areas. In this work, as part of the Ocean Reanalysis Intercomparison Project, the global and regional steric sea level changes are estimated and compared from an ensemble of 16 ocean reanalyses and 4 objective analyses. These estimates are initially compared with a satellite-derived (altimetry minus gravimetry) dataset for a short period (2003–2010). The ensemble mean exhibits a significant high correlation at both global and regional scale, and the ensemble of ocean reanalyses outperforms that of objective analyses, in particular in the Southern Ocean. The reanalysis ensemble mean thus represents a valuable tool for further analyses, although large uncertainties remain for the inter-annual trends. Within the extended intercomparison period that spans the altimetry era (1993–2010), we find that the ensemble of reanalyses and objective analyses are in good agreement, and both detect a trend of the global steric sea level of 1.0 and 1.1 ± 0.05 mm/year, respectively. However, the spread among the products of the halosteric component trend exceeds the mean trend itself, questioning the reliability of its estimate. This is related to the scarcity of salinity observations before the Argo era. Furthermore, the impact of deep ocean layers is non-negligible on the steric sea level variability (22 and 12 % for the layers below 700 and 1500 m of depth, respectively), although the small deep ocean trends are not significant with respect to the products spread

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