Adaptive time step algorithms for the simulation of marine ecosystem models using the transport matrix method implementation Metos3D (v0.5.0)

The reduction of the computational effort is desirable for the simulation of marine ecosystem models. Using a marine ecosystem model, the assessment and the validation of annual periodic solutions (i.e., steady annual cycles) against observational data are crucial to identify biogeochemical processes, which, for example, influence the global carbon cycle. For marine ecosystem models, the transport matrix method (TMM) already lowers the runtime of the simulation significantly and enables the application of larger time steps straightforwardly. However, the selection of an appropriate time step is a challenging compromise between accuracy and shortening the runtime. Using an automatic time step adjustment during the computation of a steady annual cycle with the TMM, we present in this paper different algorithms applying either an adaptive step size control or decreasing time steps in order to use the time step always as large as possible without any manual selection. For these methods and a variety of marine ecosystem models of different complexity, the accuracy of the computed steady annual cycle achieved the same accuracy as solutions obtained with a fixed time step. Depending on the complexity of the marine ecosystem model, the application of the methods shortened the runtime significantly. Due to the certain overhead of the adaptive method, the computational effort may be higher in special cases using the adaptive step size control. The presented methods represent computational efficient methods for the simulation of marine ecosystem models using the TMM but without any manual selection of the time step.

Pemodelan Sistem Karbonat di Laut Jawa

<p class="Papertext"><strong>Modeling Carbonate System in the Java Sea</strong>. Besides the global fossil fuel burning activities, forest fires in Kalimantan could potentially increase atmospheric CO₂ concentrations, impacting air-sea CO₂ gas exchange in the Java Sea and changing the balance of the marine carbonate system. This study uses a marine carbonate model to examine the processes that control CO₂ flux in the Java Sea and their relationship to CO₂ increase in the atmosphere. OCMIP-2 (<em>Ocean Carbon-Cycle Model Intercomparison Model Project, Phase-2</em>) is performed in this marine carbonate model coupled with the marine ecosystem model. The model results show that the quantity of carbon air flux differs during February and October 2000. More considerable flux is produced during February 2000, where the wind speeds are higher than in October 2000. However, the wind speeds have less impact when the CO₂ level in the atmosphere rises significantly. Due to the influence of a relatively high surface temperature in the tropical Java sea, the Java Sea functions as a carbon source to the atmosphere in general. In this case, the role of the <em>solubility pump</em> is more significant than that of biological processes in carbon absorption. Moreover, increased CO₂ in the atmosphere could alter the partial pressure equilibrium. In the case of 2002 forest fires (atmospheric CO₂ = 460 ppm), the carbon source of the Java Sea was less than before forest fires and even became carbon sink when atmospheric CO₂ rose to 1135.2 ppm based on the highest SSP scenario in 2100. This modeling also reveals marine acidification issues and could rapidly assess the future changes in marine ecosystems due to CO₂ levels rising in the atmosphere.</p>

Climate-driven zooplankton shifts could cause global declines in food quality for fish

Although zooplankton are the primary energy pathway from phytoplankton to fish, we understand little about how climate change will modify zooplankton communities and their role in marine ecosystems. Using a trait-based marine ecosystem model resolving key zooplankton groups, we assess climate change impacts on zooplankton community composition and implications for marine food webs globally. We find that future oceans favour food webs increasingly dominated by carnivorous (chaetognaths, jellyfish and carnivorous copepods) and gelatinous filter-feeding zooplankton (larvaceans and salps). By providing a direct energetic pathway from small phytoplankton to fish, the rise of gelatinous filter-feeders largely offsets the increase in trophic steps between primary producers and fish from declining phytoplankton production and increasing carnivorous zooplankton. However, our results indicate that future fish communities face not only reduced carrying capacity from falling primary production, but also lower quality diets as environmental conditions increasingly favour gelatinous zooplankton.

Next-generation ensemble projections reveal higher climate risks for marine ecosystems

Projections of climate change impacts on marine ecosystems have revealed long-term declines in global marine animal biomass and unevenly distributed impacts on fisheries. Here we apply an enhanced suite of global marine ecosystem models from the Fisheries and Marine Ecosystem Model Intercomparison Project (Fish-MIP), forced by new-generation Earth system model outputs from Phase 6 of the Coupled Model Intercomparison Project (CMIP6), to provide insights into how projected climate change will affect future ocean ecosystems. Compared with the previous generation CMIP5-forced Fish-MIP ensemble, the new ensemble ecosystem simulations show a greater decline in mean global ocean animal biomass under both strong-mitigation and high-emissions scenarios due to elevated warming, despite greater uncertainty in net primary production in the high-emissions scenario. Regional shifts in the direction of biomass changes highlight the continued and urgent need to reduce uncertainty in the projected responses of marine ecosystems to climate change to help support adaptation planning.

Skillful prediction of tropical Pacific fisheries provided by Atlantic Niños

&lt;p&gt;Tropical Pacific upwelling-dependent ecosystems are the most productive and variable worldwide, mainly due to the influence of El Ni&amp;#241;o Southern Oscillation (ENSO). ENSO can be forecasted seasons ahead thanks to assorted climate precursors (local-Pacific processes, pantropical interactions). However, owing to observational data scarcity and bias-related issues in earth system models, little is known about the importance of these precursors for marine ecosystem prediction. With recently released reanalysis-nudged global marine ecosystem simulations, these constraints can be sidestepped, allowing full examination of tropical Pacific ecosystem predictability. By complementing historical fishing records with marine ecosystem model data, we show herein that equatorial Atlantic Sea Surface Temperatures (SSTs) constitute a superlative predictability source for tropical Pacific marine yields, which can be forecasted over large-scale areas up to 2 years in advance. A detailed physical-biological mechanism is proposed whereby Atlantic SSTs modulate upwelling of nutrient-rich waters in the tropical Pacific, leading to a bottom-up propagation of the climate-related signal across the marine food web. Our results represent historical and near-future climate conditions and provide a useful springboard for implementing a marine ecosystem prediction system in the tropical Pacific.&lt;/p&gt;

Skillful prediction of tropical Pacific fisheries provided by Atlantic Niños

Tropical Pacific upwelling-dependent ecosystems are the most productive and variable worldwide, mainly due to the influence of El Niño Southern Oscillation (ENSO). ENSO can be forecasted seasons ahead thanks to assorted climate precursors (local-Pacific processes, pantropical interactions). However, owing to observational data scarcity and bias-related issues in earth system models, little is known about the importance of these precursors for marine ecosystem prediction. With recently released reanalysis-nudged global marine ecosystem simulations, these constraints can be sidestepped, allowing full examination of tropical Pacific ecosystem predictability. By complementing historical fishing records with marine ecosystem model data, we show herein that equatorial Atlantic Sea Surface Temperatures (SSTs) constitute a superlative predictability source for tropical Pacific marine yields, which can be forecasted over large-scale areas up to 2 years in advance. A detailed physical-biological mechanism is proposed whereby Atlantic SSTs modulate upwelling of nutrient-rich waters in the tropical Pacific, leading to a bottom-up propagation of the climate-related signal across the marine food web. Our results represent historical and near-future climate conditions and provide a useful springboard for implementing a marine ecosystem prediction system in the tropical Pacific.

Stability and resilience in a nutrient-phytoplankton marine ecosystem model

We seek to understand, in mathematical terms, the causes of stability in marine phytoplankton biomass. The stability of a simple, mixed-layer-phytoplankton-nutrient model is analysed. Primary production is modelled as a non-linear function of nutrient concentration and light. The steady state of the model system is demonstrated to be stable with a linear relation between steady state biomass and nutrients. The causes of stability are shown to be shading and nutrient limitation. When only light limitation and shading are taken into account, the steady state is a sink node. However, when nutrient limitation is taken into account, without shading, the steady state can be either a sink node or a spiral sink. The transition from a sink node to a spiral sink occurs when normalized mixed layer production becomes larger than the equivalent influx rate of nutrients into the mixed layer, demonstrating that nutrient limitation of production is a necessary, but not a sufficient condition for oscillatory solutions. In both cases, the characteristic return times are derived explicitly. The effect of shading is found to cause the depression of the steady state towards lower biomass than would otherwise be attainable. The influence of mixed-layer depth variation on stability is also analysed.

Modeling mercury cycling in the marine environment

&lt;p&gt;Five decades of Hg science have shown the &lt;strong&gt;tremendous complexity of the global Hg cycle&lt;/strong&gt;. Yet, the pathways that lead from anthropogenic Hg emissions to MeHg exposure through sea food are not fully comprehended. Moreover, the observed amount of MeHg in fish exhibits a large temporal and spatial variability that we cannot predict yet. A key issue is that fully speciated Hg measurements in the ocean are difficult to perform and thus we will never be able to achieve a comprehensive spatial and temporal coverage.&lt;/p&gt;&lt;p&gt;Therefore, we need complex modeling tools that allow us to fill the gaps in the observations and to predict future changes in the system under changing external drivers (emissions, climate change, ecosystem changes). Numerical models have a long history in Hg research, but so far have virtually only addressed inorganic Hg cycling in atmosphere and oceans.&lt;/p&gt;&lt;p&gt;Here we present a novel 3d-hydrodynamic mercury modeling framework based on fully coupled compartmental models including atmosphere, ocean, and ecosystem. The generalized high resolution model has been set up for European shelf seas and was used to model the transition zone from estuaries to the open ocean. Based on this model we present our findings on intra- and inter-annual dynamics and variability of mercury speciation and distribution in a coastal ocean. Moreover, we present the first results on the dynamics of mercury bio-accumulation from a fully coupled marine ecosystem model. Most importantly, the model is able to reproduce the large variability in methylmercury accumulation in higher trophic levels.&lt;/p&gt;

Description and evaluation of the Diat-HadOCC model v1.0: the ocean biogeochemical component of HadGEM2-ES

The Diat-HadOCC model (version 1.0) is presented. A simple marine ecosystem model with coupled equations representing the marine carbon cycle, it formed the ocean biogeochemistry sub-model in the Met Office's HadGEM2-ES Earth system model. The equations are presented and described in full, along with the underlying assumptions, and particular attention is given to how they were implemented for the CMIP5 simulations. Results from the CMIP5 historical simulation (particularly those for the simulated 1990s) are shown and compared to data: dissolved nutrients and dissolved inorganic carbon, as well as biological components, productivity and fluxes. Where possible, the amplitude and phase of the predicted seasonal cycle are evaluated. Since the model was developed to explore and predict the effects of climate change on the marine ecosystem and marine carbon cycle, the response of the model to the RCP8.5 future scenario is also shown. While the model simulates the historical and current global annual mean air–sea CO2 flux well and is consistent with other modelling studies about how that flux will change under future scenarios, several of the ecosystem metrics are less well simulated. The total chlorophyll is higher than observations, while the primary productivity is just below the estimated range. In the CMIP5 simulations certain parameter choices meant that the diatoms and the misc-phytoplankton state variables behave more similarly than they should, and the surface dissolved silicate concentration drifts to excessively high levels. The main structural problem with the model is shown to be the iron sub-model.