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. Internal variability and carbon-concentration feedbacks obscure the detectability of short-term emission reductions in atmospheric CO2. COVID-driven changes in the simulated interhemispheric CO2 gradient and column-averaged dry air mole fractions of CO2 (total column or XCO2) 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 decline in global emissions of carbon dioxide due to the COVID-19 pandemic provides a unique opportunity to investigate the sensitivity of the global carbon cycle and climate system to emissions reductions. Recent efforts to study the response to these emissions declines has not addressed their impact on the ocean, yet ocean carbon absorption is particularly susceptible to changing atmospheric carbon concentrations. Here, we use ensembles of simulations conducted with an Earth system model to explore the potential detection of COVID-related emissions reductions in the partial pressure difference in carbon dioxide between the surface ocean and overlying atmosphere (ΔpCO2), a quantity that is regularly measured. We find a unique fingerprint in global-scale ΔpCO2 that is attributable to COVID and potentially detectable in observations, but only with much larger emissions reductions than those that have been observed to date.

Inter-annual to decadal variability in the strength of the land and ocean carbon sinks impede accurate predictions of year-to-year atmospheric carbon dioxide (CO2) growth rate. Such information is crucial to verify the effectiveness of fossil fuel emissions reduction measures. Using a multi-model framework comprising prediction systems based on Earth system models, we find a predictive skill for the global ocean carbon sink of up to 6 years. Longer regional predictability horizons and robust spatial patterns are found across single models. On land, a predictive skill of up to 2 years is primarily maintained in the tropics and extra-tropics enabled by the initialization of the physical climate variables towards observations. We further show that anomalies of atmospheric CO2 growth rate inferred from natural variations of the land and ocean carbon sinks are predictable at lead time of 2 years and the skill is limited by the land carbon sink predictability horizon.

Internal climate variability plays an important role in the abundance and distribution of phytoplankton in the global ocean. Previous studies using large ensembles of Earth system models (ESMs) have demonstrated their utility in the study of marine phytoplankton variability. These ESM large ensembles simulate the evolution of multiple alternate realities, each with a different phasing of internal climate variability. However, ESMs may not accurately represent real world variability as recorded via satellite and in situ observations of ocean chlorophyll over the past few decades. Observational records of surface ocean chlorophyll equate to a single ensemble member in the large ensemble framework, and this can cloud the interpretation of long-term trends: are they externally forced, caused by the phasing of internal variability, or both? Here, we use a novel statistical emulation technique to place the observational record of surface ocean chlorophyll into the large ensemble framework. Much like a large initial condition ensemble generated with an ESM, the resulting synthetic ensemble represents multiple possible evolutions of ocean chlorophyll concentration, each with a different phasing of internal climate variability. We further demonstrate the validity of our statistical approach by recreating a ESM ensemble of chlorophyll using only a single ESM ensemble member. We use the synthetic ensemble to explore the interpretation of long-term trends in the presence of internal variability. Our results suggest the potential to explore this approach for other ocean biogeochemical variables.

Ocean primary production constitutes approximately half of global biospheric production, affecting both fisheries productivity and biogeochemical cycling. Although climate change is predicted to affect the ocean's biological productivity, the extent of the global impact is poorly quantified. Assessing changes in the ocean biosphere using remote sensing data is challenged by the relatively short length of the observational record, restricting our ability to disentangle fluctuations in internal variability from forced anthropogenic trends. Additionally, the majority of ocean circulation models with embedded biogeochemistry do not skillfully predict observational records of ocean chlorophyll at ocean time series locations. To overcome these limitations, we have constructed a synthetic ensemble of global ocean chlorophyll concentration. By employing statistical resampling methods to the SeaWiFS and MODIS ocean color datasets and creating surrogate climate modes of ENSO and PDO, we quantify the range of internal climate variability in the 20 year observational record and create multiple alternate realities for the possible evolution of the ocean biosphere over time. Our synthetic ensemble can be used for a variety of purposes, including diagnosing patterns of internal variability and emergence of anthropogenic trends in observed chlorophyll, and validating Earth system model representation of such variability.

The Blob was a marine heat wave in the Northeast Pacific from 2013 to 2016. While the upper ocean temperature in the Blob has been well described, the impacts on marine biogeochemistry have not been fully studied. Here, we characterize and develop understanding of Eastern North Pacific upper ocean biogeochemical properties during the Winter of 2013-14 using in situ observations, an observation-based product, and reconstructions from a collection of ocean models. We find that the Blob is associated with significant upper ocean biogeochemical anomalies: a 5% increase in aragonite saturation state (temporary reprieve of ocean acidification) and a 3% decrease in oxygen concentration (enhanced deoxygenation). Anomalous advection and mixing drives the aragonite saturation anomaly, while anomalous heating and air-sea gas exchange drive the oxygen anomaly. Marine heatwaves do not necessarily serve as an analogue for future change as they may enhance or mitigate long-term trends.

Large volcanic eruptions drive significant climate perturbations through major anomalies in radiative fluxes and the resulting widespread cooling of the surface and upper ocean. Recent studies suggest that these eruptions also drive important variability in air-sea carbon and oxygen fluxes. By simulating the Earth system using two initial-condition large ensembles, with and without the aerosol forcing associated with the Mt. Pinatubo eruption in June 1991, we isolate the impact of this event on ocean physical and biogeochemical properties. The Mt. Pinatubo eruption generated significant anomalies in surface fluxes and the ocean interior inventories of heat, oxygen, and carbon. Pinatubo-driven changes persist for multiple years in the upper ocean and permanently modify the ocean’s heat, oxygen, and carbon inventories. Positive anomalies in oxygen concentrations emerge immediately post-eruption and penetrate into the deep ocean. In contrast, carbon anomalies intensify in the upper ocean over several years post-eruption, and are largely confined to the upper 150 m. In the tropics and northern high latitudes, the change in oxygen is dominated by surface cooling and subsequent ventilation to mid-depths, while the carbon anomaly is associated with solubility changes and eruption-generated ENSO variability. Our results indicate that Pinatubo does not substantially impact oxygen or carbon in the Southern Ocean; forced signals do not emerge from the large internal variability in this region.