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We assess the detectability of COVID-like emissions reductions in global atmospheric CO2 concentrations using a suite of large ensembles conducted with an Earth system model. We find a unique fingerprint of COVID in the simulated growth rate of CO2 sampled at the locations of surface measurement sites. Negative anomalies in growth rates persist from January 2020 through December 2021, reaching a maximum in February 2021. However, this fingerprint is not formally detectable unless we force the model with unrealistically large emissions reductions (2 or 4 times the observed reductions). Internal variability and carbon-concentration feedbacks obscure the detectability of short-term emission reductions in atmospheric CO2. COVID-driven changes in the simulated, column-averaged dry air mole fractions of CO2 are eclipsed by large internal variability. Carbon-concentration feedbacks begin to operate almost immediately after the emissions reduction; these feedbacks reduce the emissions-driven signal in the atmosphere carbon reservoir and further confound signal detection.

The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NO x emissions. Second, the response of O3 to decreased NO x emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors including carbon-cycle feedbacks to CH4 and CO2, background pollutant levels, the timing and location of emissions changes, and climate feedbacks on air quality, such as wildfires and the ozone climate penalty.

For several decades, a suite of satellite sensors has enabled us to study the global spatiotemporal distribution of phytoplankton through remote sensing of chlorophyll. However, the satellite record has extensive missing data, partially due to cloud cover; regions characterized by the highest phytoplankton abundance are also some of the cloudiest. To quantify potential sampling biases due to missing data, we developed a satellite simulator for ocean chlorophyll in the Community Earth System Model (CESM) that mimics what a satellite would detect if it were present in the model-generated world. Our Chlorophyll Observation Simulator Package (ChlOSP) generates synthetic chlorophyll observations at model runtime. ChlOSP accounts for missing data – due to low light, sea ice, and cloud cover – and it can implement swath sampling. Here, we introduce this new tool and present a preliminary study focusing on long timescales. Results from a 50-year pre-industrial control simulation of CESM–ChlOSP suggest that missing data impact the apparent mean state and variability of chlorophyll. The simulated observations exhibit a nearly -20 % difference in global mean chlorophyll compared with the standard model output, which is the same order of magnitude as the projected change in chlorophyll by the end of the century. Additionally, missing data impact the apparent seasonal cycle of chlorophyll in subpolar regions. We highlight four potential future applications of ChlOSP: (1) refined model tuning; (2) evaluating chlorophyll-based net primary productivity (NPP) algorithms; (3) revised time to emergence of anthropogenic chlorophyll trends; and (4) a test bed for the assessment of gap-filling approaches for missing satellite chlorophyll data. [ABSTRACT FROM AUTHOR]

Biogeochemical (BGC) models are widely used in ocean simulations for a range of applications but typically include parameters that are determined based on a combination of empiricism and convention. Here, we describe and demonstrate an optimization-based parameter estimation method for high-dimensional (in parameter space) BGC ocean models. Our computationally efficient method combines the respective benefits of global and local optimization techniques and enables simultaneous parameter estimation at multiple ocean locations using multiple state variables. We demonstrate the method for a 17-state-variable BGC model with 51 uncertain parameters, where a one-dimensional (in space) physical model is used to represent vertical mixing. We perform a twin-simulation experiment to test the accuracy of the method in recovering known parameters. We then use the method to simultaneously match multi-variable observational data collected at sites in the subtropical North Atlantic and Pacific. We examine the effects of different objective functions, sometimes referred to as cost functions, which quantify the disagreement between model and observational data. We further examine increasing levels of data sparsity and the choice of state variables used during the optimization. We end with a discussion of how the method can be applied to other BGC models, ocean locations, and mixing representations. [ABSTRACT FROM AUTHOR]

The document is a compilation of scientific articles and reports related to oceanography and climate research. The articles cover a wide range of topics including phytoplankton bloom phenology, ocean currents, carbon cycle simulations, sea-ice dynamics, and subsurface chlorophyll concentrations. These articles provide valuable information for researchers studying these specific topics and highlight the importance of ongoing research and monitoring efforts in understanding and predicting changes in the marine environment. [Extracted from the article]

Orbital precession has been linked to glacial cycles and the atmospheric carbon dioxide (CO2) concentration, yet the direct impact of precession on the carbon cycle is not well understood. We analyze output from an Earth system model configured under different orbital parameters to isolate the impact of precession on air‐sea CO2 flux in the Southern Ocean—a component of the global carbon cycle that is thought to play a key role on past atmospheric CO2 variations. Here, we demonstrate that periods of high precession are coincident with anomalous CO2 outgassing from the Southern Ocean. Under high precession, we find a poleward shift in the southern westerly winds, enhanced Southern Ocean meridional overturning, and an increase in the surface ocean partial pressure of CO2 along the core of the Antarctic Circumpolar Current. These results suggest that orbital precession may have played an important role in driving changes in atmospheric CO2. Plain Language Summary: Over the past one million years, Earth has experienced several glacial and interglacial periods. As a glacial period is ending, carbon in the atmosphere can rise by up to 50%. The cause for this change is currently unknown, but most theories suggest that this carbon is released from the deep ocean into the atmosphere. The Southern Ocean surrounding Antarctica is the location of a lot of carbon outgassing from the deep ocean into the atmosphere, so it could be responsible for some of this change in atmospheric carbon. One of Earth's orbital cycles, precession, has been shown to change circulation in the Southern Ocean, that can affect how much carbon is carried from the deep ocean to the surface and released into the atmosphere. This paper uses simulations of a climate model to show that high precession corresponds to a 20% increase in the release of carbon from the Southern Ocean into the atmosphere. These findings suggest that precession could have affected changes in past atmospheric carbon concentrations. Key Points: Increased insolation during austral summer due to orbital precession shifts the southern westerlies polewardPoleward shifted westerlies enhance CO2 outgassing due to increased turbulent exchange and vertical transport of carbon‐rich watersEnhanced transport of carbon‐rich waters is driven by a deepening of the overturning circulation in response to poleward shifted winds [ABSTRACT FROM AUTHOR]

Anthropogenic carbon emissions and associated climate change are driving rapid warming, acidification, and deoxygenation in the ocean, which increasingly stress marine ecosystems. On top of long‐term trends, short term variability of marine stressors can have major implications for marine ecosystems and their management. As such, there is a growing need for predictions of marine ecosystem stressors on monthly, seasonal, and multi‐month timescales. Previous studies have demonstrated the ability to make reliable predictions of the surface ocean physical and biogeochemical state months to years in advance, but few studies have investigated forecast skill of multiple stressors simultaneously or assessed the forecast skill below the surface. Here, we use the Community Earth System Model (CESM) Seasonal to Multiyear Large Ensemble (SMYLE) along with novel observation‐based biogeochemical and physical products to quantify the predictive skill of dissolved inorganic carbon (DIC), dissolved oxygen, and temperature in the surface and subsurface ocean. CESM SMYLE demonstrates high physical and biogeochemical predictive skill multiple months in advance in key oceanic regions and frequently outperforms persistence forecasts. We find up to 10 months of skillful forecasts, with particularly high skill in the Northeast Pacific (Gulf of Alaska and California Current Large Marine Ecosystems) for temperature, surface DIC, and subsurface oxygen. Our findings suggest that dynamical marine ecosystem prediction could support actionable advice for decision making. Plain Language Summary: Human‐driven climate change is rapidly altering the global ocean, with strong warming, increasing acidity, and declining oxygen trends. On top of long‐term trends, short term variations can lead to rapid changes that can have major effects on marine ecosystems. There is a growing need to predict these short‐term changes in order to better inform marine fisheries managers. In this study, we use a climate model designed to predict changes in the real world months‐to‐years in advance to better determine our ability to forecast changes. Previous studies with similar goals have been limited by sparse observations of acidity and oxygen. We utilize brand new observational products that estimate acidity and oxygen levels in the subsurface ocean for the first time to analyze subsurface forecasts. Our results demonstrate a high potential to predict warming, acidity, and oxygen levels in key marine ecosystems with this climate model. These results suggest that there is potential for eventual operational forecasts of marine ecosystems to better inform marine managers. Key Points: Community Earth System Model Seasonal to Multiyear Large Ensemble (SMYLE) forecasts variations in multiple marine stressors up to a year in advance and outperforms statistical persistenceNovel observation‐based products allow for the first skill analysis of subsurface carbon and oxygenAnalysis of predictability from the SMYLE reconstruction reveals high potential to gain additional temperature and oxygen forecast skill [ABSTRACT FROM AUTHOR]

Earth system models suggest that anthropogenic climate change will influence marine phytoplankton over the coming century with light-limited regions becoming more productive and nutrient-limited regions less productive. Anthropogenic climate change can influence not only the mean state but also the internal variability around the mean state, yet little is known about how internal variability in marine phytoplankton will change with time. Here, we quantify the influence of anthropogenic climate change on internal variability in marine phytoplankton biomass from 1920 to 2100 using the Community Earth System Model 1 Large Ensemble (CESM1-LE). We find a significant decrease in the internal variability of global phytoplankton carbon biomass under a high emission (RCP8.5) scenario and heterogeneous regional trends. Decreasing internal variability in biomass is most apparent in the subpolar North Atlantic and North Pacific. In these high-latitude regions, bottom-up controls (e.g., nutrient supply, temperature) influence changes in biomass internal variability. In the biogeochemically critical regions of the Southern Ocean and the equatorial Pacific, bottom-up controls (e.g., light, nutrients) and top-down controls (e.g., grazer biomass) affect changes in phytoplankton carbon internal variability, respectively. Our results suggest that climate mitigation and adaptation efforts that account for marine phytoplankton changes (e.g., fisheries, marine carbon cycling) should also consider changes in phytoplankton internal variability driven by anthropogenic warming, particularly on regional scales. [ABSTRACT FROM AUTHOR]

Air‐sea exchange of carbon dioxide (CO2) in the Southern Ocean plays an important role in the global carbon budget. Previous studies have suggested that flow around topographic features of the Southern Ocean enhances the upward supply of carbon from the deep to the surface, influencing air‐sea CO2 exchange. Here, we investigate the role of seafloor topography on the transport of carbon and associated air‐sea CO2 flux in an idealized channel model. We find elevated CO2 outgassing upstream of a seafloor ridge, driven by anomalous advection of dissolved inorganic carbon. Argo‐like Lagrangian particles in our channel model sample heterogeneously in the vicinity of the seafloor ridge, which could impact float‐based estimates of CO2 flux. Plain Language Summary: The Southern Ocean, the ocean surrounding Antarctica, contributes significantly to carbon exchange between the global ocean and the atmosphere, which in turn matters for climate change. Here, we use a simplified model of the Southern Ocean to see how mountain ranges on the sea floor influence the carbon exchange at the ocean‐atmosphere interface. We find that the seafloor mountain ranges lead to more carbon exchange. Floating carbon sensors in our model ocean may under or over sample the water near the mountains and this can affect the carbon exchange that they report. Key Points: We examine the localized patterns of air‐sea carbon dioxide (CO2) fluxes in an idealized Southern Ocean‐like model with simple biogeochemistryWe find intense sea‐air CO2 fluxes upstream of seafloor topography driven by anomalous advection of inorganic carbonDue to the topography, uncertainty in the flux is highly sensitive to sampling network design [ABSTRACT FROM AUTHOR]

For several decades, a suite of satellite sensors has enabled us to study the global spatiotemporal distribution of phytoplankton through remote sensing of chlorophyll. However, the satellite record has extensive missing data, partially due to cloud cover; regions characterized by the highest phytoplankton abundance are also some of the cloudiest. To quantify potential sampling biases due to missing data, we developed a satellite simulator for ocean chlorophyll in the Community Earth System Model (CESM) that mimics what a satellite would detect if it were present in the model-generated world. Our Chlorophyll Observation Simulator Package (ChlOSP) generates synthetic chlorophyll observations at model runtime. ChlOSP accounts for missing data - due to low light, sea ice, and cloud cover - and it can implement swath sampling. Results from a 50-year pre-industrial control simulation of CESM-ChlOSP suggest that missing data impacts the apparent mean state and variability of chlorophyll. The simulated observations exhibit a nearly -20 % difference in global mean chlorophyll compared with the standard model output, which is the same order of magnitude as the projected change in chlorophyll by the end of the century. Additionally, missing data impacts the apparent seasonal cycle of chlorophyll in subpolar regions. We highlight four potential future applications of ChlOSP: (1) refined model tuning, (2) evaluating chlorophyll-based NPP algorithms, (3) revised time to emergence of anthropogenic chlorophyll trends, and (4) a testbed for the assessment of gap-filling approaches for missing satellite chlorophyll data. [ABSTRACT FROM AUTHOR]

The ocean has absorbed 41 per cent of all anthropogenic carbon emitted as a result of fossil fuel burning and cement manufacture (1,2). The magnitude and the large-scale distribution of the ocean carbon sink is well quantified for recent decades (3,4). In contrast, temporal changes in the oceanic carbon sink remain poorly understood (5-7). It has proved difficult to distinguish between air-to-sea carbon flux trends that are due to anthropogenic climate change and those due to internal climate variability (5,6,8-13). Here we use a modelling approach that allows for this separation (14), revealing how the ocean carbon sink may be expected to change throughout this century in different oceanic regions. Our findings suggest that, owing to large internal climate variability, it is unlikely that changes in the rate of anthropogenic carbon uptake can be directly observed in most oceanic regions at present, but that this may become possible between 2020 and 2050 in some regions., Recent observationally based syntheses have quantified mean ocean carbon uptake and its spatial distribution (1,3,4,15) (Extended Data Fig. 1). In addition, interior ocean observations analysed under the assumption of constant [...]

This article describes how an India-Pakistan nuclear war might come to pass, and what the local and global effects of such a war might be. The direct effects of this nuclear exchange would be horrible; the authors estimate that 50 to 125 million people would die, depending on whether the weapons used had yields of 15, 50, or 100 kilotons. The ramifications for Indian and Pakistani society would be major and long lasting, with many major cities largely destroyed and uninhabitable, millions of injured people needing care, and power, transportation, and financial infrastructure in ruins. But the climatic effects of the smoke produced by an India-Pakistan nuclear war would not be confined to the subcontinent, or even to Asia. Those effects would be enormous and global in scope. [ABSTRACT FROM AUTHOR]