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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.

Global Earth system models are often enlisted to assess the impacts of climate variability and change on marine ecosystems. In this study, we compare high frequency (daily) outputs of potential ecosystem stressors, such as sea surface temperature and surface pH, and associated variables from an Earth system model (GFDL ESM4.1) with high frequency time series from a global network of moorings to directly assess the capacity of the model to resolve local biogeochemical variability on time scales from daily to interannual. Our analysis indicates variability in surface temperature is most consistent between ESM4.1 and observations, with a Pearson correlation coefficient of 0.93 and bias of 0.40°C, followed by variability in surface salinity. Physical variability is reproduced with greater accuracy than biogeochemical variability, and variability on seasonal and longer time scales is more consistent between the model and observations than higher frequency variability. At the same time, the well‐resolved seasonal and longer timescale variability is a reasonably good predictor, in many cases, of the likelihood of extreme events. Despite limited model representation of high frequency variability, model and observation‐based assessments of the fraction of days experiencing surface T‐pH and T‐Ωarag multistressor conditions show reasonable agreement, depending on the stressor combination and threshold definition. We also identify circumstances in which some errors could be reduced by accounting for model biases. Plain Language Summary: Ocean ecosystems are under stress from changing temperature and acidity due to the human‐driven increase in global atmospheric carbon dioxide. Global Earth system models (ESMs) are used to study the effects of climate variability and change on marine ecosystems. However, computing power and storage constraints limit the level of detail represented by these simulations. Some short timescale variability present in the real world is missing from ESM output. Despite this inconsistency, we show that at an array of sites where daily observation data from ocean moorings is available, models accurately capture observed spatial patterns in estimates of the amount of time the locations experience combined temperature and acidification stress. We also demonstrate circumstances in which some model errors can be reduced through bias correction. Key Points: Physical and biogeochemical variability from moorings and GFDL ESM4.1 output is most consistent on seasonal and longer time scalesMore high frequency (daily to monthly) variability is present in observations than in ESM outputDespite missing high frequency variability, ESM output can be applied to accurately quantify multiple stressor events [ABSTRACT FROM AUTHOR]

Coordinated experimental design and implementation has become a cornerstone of global climate modelling. Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models, by reducing the influence of ad hoc differences in model set-up or experimental boundary conditions. As it enters its 6th phase, the Coupled Model Intercomparison Project (CMIP6) has grown significantly in scope with the design and documentation of individual simulations delegated to individual climate science communities. The Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation, and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks are potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO2 and in the setting of emissions targets to stabilize climate or avoid dangerous climate change. For over a decade, C4MIP has coordinated coupled climate-carbon cycle simulations, and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate-carbon cycle community has created this experimental design, the simulations also fit within the wider CMIP activity, conform to some common standards including documentation and diagnostic requests, and are designed to complement the CMIP core experiments known as the Diagnostic, Evaluation and Characterization of Klima (DECK). C4MIP has three key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation, (2) idealized coupled and partially coupled simulations with 1% per year increases in CO2 to enable diagnosis of feedback strength and its components, (3) future scenario simulations to project how the Earth system will respond to anthropogenic activity over the 21st century and beyond. This paper documents in detail these simulations, explains their rationale and planned analysis, and describes how to set up and run the simulations. Particular attention is paid to boundary conditions, input data, and requested output diagnostics. It is important that modelling groups participating in C4MIP adhere as closely as possible to this experimental design.

The global ocean's coastal areas are rapidly experiencing the effects of climate change. These regions are highly dynamic, with relatively small-scale circulation features like shelf break currents playing an important role. Projections can produce widely diverging estimates of future regional circulation structures. Here, we use the northwestern North Atlantic, a hotspot of ocean warming, as a case study to illustrate how the uncertainty in future estimates of regional circulation manifests itself and affects projections of shelf-wide biogeochemistry. Two diverging climate model projections are considered and downscaled using a high-resolution regional model with intermediate biogeochemical complexity. The two resulting future scenarios exhibit qualitatively different circulation structures by 2075 where along-shelf volume transport is reduced by 70 % in one of them and while remaining largely unchanged in the other. The reduction in along-shelf transport creates localized areas with either amplified warming (+3 ∘ C) and salinification (+0.25 units) or increased acidification (-0.25 units) in shelf bottom waters. Our results suggest that a wide range of outcomes is possible for continental margins and suggest a need for accurate projections of small-scale circulation features like shelf break currents in order to improve the reliability of biogeochemical projections. [ABSTRACT FROM AUTHOR]

We present the development and evaluation of MOM6-COBALT-NWA12 version 1.0, a 1/12 ∘ model of ocean dynamics and biogeochemistry in the northwest Atlantic Ocean. This model is built using the new regional capabilities in the MOM6 ocean model and is coupled with the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALT) biogeochemical model and Sea Ice Simulator version-2 (SIS2) sea ice model. Our goal was to develop a model to provide information to support living-marine-resource applications across management time horizons from seasons to decades. To do this, we struck a balance between a broad, coastwide domain to simulate basin-scale variability and capture cross-boundary issues expected under climate change; a high enough spatial resolution to accurately simulate features like the Gulf Stream separation and advection of water masses through finer-scale coastal features; and the computational economy required to run the long simulations of multiple ensemble members that are needed to quantify prediction uncertainties and produce actionable information. We assess whether MOM6-COBALT-NWA12 is capable of supporting the intended applications by evaluating the model with three categories of metrics: basin-wide indicators of the model's performance, indicators of coastal ecosystem variability and the regional ocean features that drive it, and model run times and computational efficiency. Overall, both the basin-wide and the regional ecosystem-relevant indicators are simulated well by the model. Where notable model biases and errors are present in both types of indicator, they are mainly consistent with the challenges of accurately simulating the Gulf Stream separation, path, and variability: for example, the coastal ocean and shelf north of Cape Hatteras are too warm and salty and have minor biogeochemical biases. During model development, we identified a few model parameters that exerted a notable influence on the model solution, including the horizontal viscosity, mixed-layer restratification, and tidal self-attraction and loading, which we discuss briefly. The computational performance of the model is adequate to support running numerous long simulations, even with the inclusion of coupled biogeochemistry with 40 additional tracers. Overall, these results show that this first version of a regional MOM6 model for the northwest Atlantic Ocean is capable of efficiently and accurately simulating historical basin-wide and regional mean conditions and variability, laying the groundwork for future studies to analyze this variability in detail, develop and improve parameterizations and model components to better capture local ocean features, and develop predictions and projections of future conditions to support living-marine-resource applications across timescales. [ABSTRACT FROM AUTHOR]

The article discusses the Ocean Discovery Institute's model for empowering underrepresented students in STEM fields. The organization aims to address the poor performance of American students in science and the lack of diversity in the scientific workforce. They achieve this through a unique educational model that includes being embedded within the community, reaching all students in a single cluster of schools, and emphasizing science identity and mentorship. The organization operates in the San Diego community of City Heights, which is rich in diversity but lacks resources for science engagement. The implementation of this model has resulted in significant impacts, with high rates of high school graduation, college enrollment, and career success in science-related fields among program alumni. [Extracted from the article]