Explore the vast range of titles available.

The paper provides a basin-scale assessment of the spatiotemporal distribution of alkalinity in the Mediterranean Sea. The assessment is made by integrating the available observations into a 3-D transport–biogeochemical model. The results indicate the presence of complex spatial patterns: a marked west-to-east surface gradient of alkalinity is coupled to secondary negative gradients: (1) from marginal seas (Adriatic and Aegean Sea) to the eastern Mediterranean Sea and (2) from north to south in the western region. The west–east gradient is related to the mixing of Atlantic water entering from the Strait of Gibraltar with the high-alkaline water of the eastern sub-basins, which is correlated to the positive surface flux of evaporation minus precipitation. The north-to-south gradients are related to the terrestrial input and to the input of the Black Sea water through the Dardanelles. In the surface layers, alkalinity has a relevant seasonal cycle (up to 40 μmol kg−1) that is driven by physical processes (seasonal cycle of evaporation and vertical mixing) and, to a minor extent, by biological processes. A comparison of alkalinity vs. salinity indicates that different regions present different relationships: in regions of freshwater influence, the two quantities are negatively correlated due to riverine alkalinity input, whereas they are positively correlated in open sea areas of the Mediterranean Sea.

We investigated the effects of variations in the 4 primary mid-latitude large-scale atmospheric circulation patterns on nutrients potentially limiting phytoplankton growth in the Mediterranean Sea (nitrate and phosphate), with a focus on the key deep convective areas of the basin (Gulf of Lions, Southern Adriatic Sea, Southern Aegean Sea and Rhodes Gyre). Monthly indices of these 4 modes of variability, together with a high-resolution hindcast of the Mediterranean Sea physics and biogeochemistry covering the period 1961–1999, were used to determine the physical mechanisms explaining the influence of these patterns on nutrient distribution and variability. We found a decrease in the concentration of phosphate and nitrate for each unit of increase in the index values of the East Atlantic and East Atlantic/West Russian variability modes in the area of the Gulf of Lions, while a signal of the opposite sign was associated with the North Atlantic Oscillation in the Aegean Sea and Rhodes Gyre. In both cases, the variability observed was related to a significant variation in the mixed layer depth driven by heat losses and wind stress over the areas. The East Atlantic pattern played a major role in driving the long-term dynamics of both phosphate and nitrate availability in the Gulf of Lions, with a particularly pronounced effect in December and January. For both the Aegean Sea and Rhodes Gyre, the most prominent correlations were found between the North Atlantic Oscillation and phosphate, with a highly consistent behavior in the 2 areas associated with common physical forcing and exchange of properties among them.

We describe a new, state‐of‐the‐art, Earth System Regional Climate Model (RegCM‐ES), which includes the coupling between the atmosphere, ocean, and land surface, as well as a hydrological and ocean biogeochemistry model, with the capability of using a variety of physical parameterizations. The regional coupled model has been implemented and tested over some of the COordinated Regional climate Downscaling Experiment (CORDEX) domains and more regional settings featuring climatically important coupled phenomena. Regional coupled ocean‐atmosphere models can be especially useful tools to provide information on the mechanisms of air‐sea interactions and feedbacks occurring at fine spatial and temporal scales. RegCM‐ES shows a good representation of precipitation and SST fields over the domains tested, as well as realistic simulations of coupled air‐sea processes and interactions. The RegCM‐ES model, which can be easily implemented over any regional domain of interest, is open source, making it suitable for usage by the broad scientific community. Plain Language Summary The increasing availability of observational data sets of high temporal and spatial resolution is providing a more complete view of the ocean and atmosphere, revealing strong air‐sea coupling processes. In order to obtain an accurate representation and better understanding of the climate system, its variability, and possible future change, the inclusion of all mechanisms of interaction among the different climate components becomes ever more desirable. Regional coupled ocean‐atmosphere models can be especially useful tools to provide information on the mechanisms of air‐sea interactions and feedback occurring at regional fine spatial and temporal scales. Here we present a new, state‐of‐the‐art, Earth System Regional Climate Model (RegCM‐ES). Key Points A new Regional Earth System Model (RegCM‐ES) successfully simulates climate features in regions where coupled air‐sea processes are important RegCM‐ES shows reduction of precipitation biases and good performance simulating the effects of air‐sea interactions over frontal regions RegCM‐ES is an open source community model, making it suitable for use by a large scientific community on any regional domain of interest

An ensemble data assimilation scheme, Error Subspace Statistical Estimation (ESSE), is utilized to investigate the seasonal ecosystem dynamics of the Lagoon of Venice and provide guidance on the monitoring and management of the Lagoon, combining a rich data set with a physical‐biogeochemical numerical estuary‐coastal model. Novel stochastic ecosystem modeling components are developed to represent prior uncertainties in the Lagoon dynamics model, measurement model, and boundary forcing by rivers, open‐sea inlets, and industrial discharges. The formulation and parameters of these additive and multiplicative stochastic error models are optimized based on data‐model forecast misfits. The sensitivity to initial and boundary conditions is quantified and analyzed. Half‐decay characteristic times are estimated for key ecosystem variables, and their spatial and temporal variability are studied. General results of our uncertainty analyses are that boundary forcing and internal mixing have a significant control on the Lagoon dynamics and that data assimilation is needed to reduce prior uncertainties. The error models are used in the ESSE scheme for ensemble uncertainty predictions and data assimilation, and an optimal ensemble dimension is estimated. Overall, higher prior uncertainties are predicted in the central and northern regions of the Lagoon. On the basis of the dominant singular vectors of the ESSE ensemble, the two major northern rivers are the biggest sources of dissolved inorganic nitrogen (DIN) uncertainty in the Lagoon. Other boundary sources such as the southern rivers and industrial discharges can dominate uncertainty modes on certain months. For dissolved inorganic phosphorus (DIP) and phytoplankton, dominant modes are also linked to external boundaries, but internal dynamics effects are more significant than those for DIN. Our posterior estimates of the seasonal biogeochemical fields and of their uncertainties in 2001 cover the whole Lagoon. They provide the means to describe the ecosystem and guide local environmental policies. Specifically, our findings and results based on these fields include the temporal and spatial variability of nutrient and plankton gradients in the Lagoon; dynamical connections among ecosystem fields and their variability; strengths, gradients and mechanisms of the plankton blooms in late spring, summer, and fall; reductions of uncertainties by data assimilation and thus a quantification of data impacts and data needs; and, finally, an assessment of the water quality in the Lagoon in light of the local environmental legislation.

The projected warming, nutrient decline, changes in net primary production, deoxygenation and acidification of the global ocean will affect marine ecosystems during the 21st century. Here, the climate change-related impacts on the marine ecosystems of the Mediterranean Sea in the middle and at the end of the 21st century are assessed using high-resolution projections of the physical and biogeochemical state of the basin under Representative Concentration Pathways (RCPs) 4.5 and 8.5. In both scenarios, the analysis shows changes in the dissolved nutrient contents of the euphotic and intermediate layers of the basin, net primary production, phytoplankton respiration and carbon stock (including phytoplankton, zooplankton, bacterial biomass and particulate organic matter). The projections also show uniform surface and subsurface reductions in the oxygen concentration driven by the warming of the water column and by the increase in ecosystem respiration as well as an acidification signal in the upper water column linked to the increase in the dissolved inorganic carbon content of the water column due to CO2 absorption from the atmosphere and the increase in respiration. The projected changes are stronger in the RCP8.5 (worst-case) scenario and, in particular, in the eastern Mediterranean due to the limited influence of the exchanges in the Strait of Gibraltar in that part of the basin. On the other hand, analysis of the projections under the RCP4.5 emission scenario shows a tendency to recover the values observed at the beginning of the 21st century for several biogeochemical variables in the second half of the period. This result supports the idea – possibly based on the existence in a system such as the Mediterranean Sea of a certain buffer capacity and renewal rate – that the implementation of policies for reducing CO2 emission could indeed be effective and could contribute to the foundation of ocean sustainability science and policies.

Data assimilation has led to advancements in biogeochemical modelling and scientific understanding of the ocean. The recent operational availability of data from BGC-Argo (biogeochemical Argo) floats, which provide valuable insights into key vertical biogeochemical processes, stands to further improve biogeochemical modelling through assimilation schemes that include float observations in addition to traditionally assimilated satellite data. In the present work, we demonstrate the feasibility of joint multi-platform assimilation in realistic biogeochemical applications by presenting the results of 1-year simulations of Mediterranean Sea biogeochemistry. Different combinations of satellite chlorophyll data and BGC-Argo nitrate and chlorophyll data have been tested, and validation with respect to available independent non-assimilated and assimilated (before the assimilation) observations showed that assimilation of both satellite and float observations outperformed the assimilation of platforms considered individually. Moreover, the assimilation of BGC-Argo data impacted the vertical structure of nutrients and phytoplankton in terms of deep chlorophyll maximum depth, intensity, and nutricline depth. The outcomes of the model simulation assimilating both satellite data and BGC-Argo data provide a consistent picture of the basin-wide differences in vertical features associated with summer stratified conditions, describing a relatively high variability between the western and eastern Mediterranean, with thinner and shallower but intense deep chlorophyll maxima associated with steeper and narrower nutriclines in the western Mediterranean.

Effective observation of the ocean is vital for studying and assessing the state and evolution of the marine ecosystem and for evaluating the impact of human activities. However, obtaining comprehensive oceanic measurements across temporal and spatial scales and for different biogeochemical variables remains challenging. Autonomous oceanographic instruments, such as Biogeochemical (BGC)-Argo profiling floats, have helped expand our ability to obtain subsurface and deep-ocean measurements, but measuring biogeochemical variables, such as nutrient concentration, still remains more demanding and expensive than measuring physical variables. Therefore, developing methods to estimate marine biogeochemical variables from high-frequency measurements is very much needed. Current neural network (NN) models developed for this task are based on a multilayer perceptron (MLP) architecture, trained over point-wise pairs of input–output features. Although MLPs can produce smooth outputs if the inputs change smoothly, convolutional neural networks (CNNs) are inherently designed to handle profile data effectively. In this study, we present a novel one-dimensional (1D) CNN model to predict profiles leveraging the typical shape of vertical profiles of a variable as a prior constraint during training. In particular, the Predict Profiles Convolutional (PPCon) model predicts nitrate, chlorophyll, and backscattering (bbp700) starting from the date and geolocation and from temperature, salinity, and oxygen profiles. Its effectiveness is demonstrated using a robust BGC-Argo dataset collected in the Mediterranean Sea for training and validation. Results, which include quantitative metrics and visual representations, prove the capability of PPCon to produce smooth and accurate profile predictions improving upon previous MLP applications.

A downscaling approach is used to assess potential effects of variations in nutrient loads induced by possible future climate changes on biogeochemical properties of the Venice lagoon. The analysis is based on a hierarchy of dynamic and statistical models linking climatic change to effects on biogeochemical processes. The outputs of regional climate model simulations for present day and future (A2 and B2 IPCC emission scenarios) conditions are used to force 2 statistical models that provide forcing and boundary conditions for a 3D coupled transport-biogeochemical model of the lagoon. Results in terms of spatio-temporal dynamics of biogeochemical properties provide evidence of significant impacts of climate change. Under both the A2 and B2 scenarios, we observe an amplification of the seasonal precipitation patterns, with drier summers and wetter winters, which affect the timing of nutrient inputs to the lagoon. Nutrient loads are generally higher in the wintertime and lower in the summertime than in present-day conditions. In winter, nutrients are not used by phytoplankton whose productivity is low, and are mainly exported from the system. Conversely, reduced nutrient inputs to the lagoon in summer cause a reduction in planktonic productivity of the ecosystem. Between the 2 emission scenarios, the A2, which has higher levels of atmospheric greenhouse gas concentrations, shows more intense impact. Analysis of the effects of additional scenarios indicates that policy-driven changes in nutrient loads can overbalance changes due to climate driven modification of precipitation patterns.

The subsurface oxygen maximum (SOM) is observed in oligotrophic oceans and is associated with different physical and biological processes. This study characterizes the SOM in the Mediterranean Sea at the basin scale and investigates its driving mechanisms by analysing the output of the 1/24∘ resolution biogeochemical reanalysis provided by the Copernicus Marine Service for the 1999–2019 time period. We validated the model-derived oxygen concentration in the epipelagic layer at different spatial and temporal scales, including novel process comparisons with estimates from in situ observations. Moreover, using Biogeochemical Argo (BGC-Argo) float observations, we estimated the model uncertainty in reproducing the SOM concentration and depth in summer (13 mmol O2 m−3 and 13 m, respectively). The western and eastern Mediterranean Sea depicts different SOM signatures in summer, with higher oxygen values and shallower depths in the western Mediterranean. The concentrations and depths (in the ranges of 230–250 mmol O2 m−3 and 30–100 m, respectively) are in agreement with the estimations from the literature and show mesoscale variability patterns. The western Mediterranean also shows a stronger biological activity, specifically oxygen production and consumption, along the whole epipelagic layer and higher oxygen concentrations at the surface throughout the year, but heavy undersaturated waters are associated with winter deep convection in the northwestern Mediterranean Sea. A 1-year analysis conducted on selected areas that are representative of the heterogeneity of summer SOM highlighted that the SOM can actually be sustained by biological production (as in northwestern Mediterranean areas), or it can be a residual of the confinement of spring production (as in the central Ionian area) and vertical motions influence its depth (as in the Levantine subduction area).

We propose a new method to identify and characterise the occurrence of prolonged extreme events in marine ecosystems at the basin scale. There is growing interest in events that can affect ecosystem functions and services in a changing climate. Our method identifies extreme events as the peak occurrences over a predefined threshold (i.e. the 99th percentile) computed from a local time series, and it defines a series of extreme events that are connected over space and time as an extreme event wave (EEW). The main features of EEWs are then characterised by a set of novel indexes, related to initiation, extent, duration and strength. The indexes associated with the areas covered by each EEW were then statistically analysed to highlight the main features of the EEWs in the considered domain. We applied the method to a multidecadal series of winter–spring daily chlorophyll fields that was produced by a validated coupled hydrodynamic–biogeochemical model of the Mediterranean open-sea ecosystem. This application allowed us to identify and characterise surface chlorophyll EEWs in the period from 1994 to 2012. Finally, a fuzzy classification of EEW indexes provided bio-regionalisation of the Mediterranean Sea based on the occurrence of chlorophyll EEWs with different regimes.