Ocean warming is a key factor impacting future changes in climate. Here we investigate vertical structure changes in globally averaged ocean heat content (OHC) in high- (HR) and low-resolution (LR) future climate simulations with the Community Earth System Model (CESM). Compared with observation-based estimates, the simulated OHC anomalies in the upper 700 m and 2000 m during 1960-2020 are more realistic in CESM-HR than -LR. Under RCP8.5 scenario, the net surface heat into the ocean is very similar in CESM-HR and -LR However, CESM-HR has a larger increase in OHC in the upper 250 m compared to CESM-LR, but a smaller increase below 250 m. This difference can be traced to differences in eddy-induced vertical heat transport between CESM-HR and -LR in the historical period. Moreover, our results suggest that with the same heat input, upper-ocean warming is likely to be underestimated by most non-eddy-resolving climate models.

Emerging high-resolution global ocean climate models are expected to improve both hindcasts and forecasts of coastal sea level variability by better resolving ocean turbulence and other small-scale phenomena. To examine this hypothesis, we compare annual to multidecadal coastal sea level variability over the 1993-2018 period, as observed by tide gauges and as simulated by two identically-forced ocean models, at $\sim$1$^{\circ}$ (LR) and $\sim$0.1$^{\circ}$ (HR) horizontal resolution. Differences between HR and LR, and misfits with tide gauges, are spatially coherent at regional alongcoast scales. Resolution-related improvements are largest in, and near, marginal seas. Near attached western boundary currents, sea level variance is several times greater in HR than LR, but correlations with observations may be reduced, due to intrinsic ocean variability. Globally, in HR simulations, intrinsic variability comprises from zero to over 80\% of coastal sea level variance. Outside of eddy-rich regions, simulated coastal sea level variability is generally damped relative to observations. We hypothesize that weak coastal variability is related to large-scale, remotely-forced, variability; in both HR and LR, tropical sea level variance is underestimated by $\sim$50\% relative to satellite altimetric observations. Similar coastal dynamical regimes (e.g., attached western boundary currents) exhibit a consistent sensitivity to horizontal resolution, suggesting that these findings are generalizable to regions with limited coastal observations.

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 ecosystems 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 forecasts 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, 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.

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.

Rapid Arctic warming and sea ice decline in recent decades might have profound impacts on midlatitude weather and climate. This study uses a high-top atmospheric general circulation model - Whole Atmosphere Community Climate Model version 6 (WACCM6) - to investigate the atmospheric responses to the Arctic sea ice reduction, including impacts on mid-latitude blocking and cyclones. The high-top configuration (top layer at about 100 km or 0.001 hPa) together with the finer vertical resolution (70 layers) in WACCM6 allow more realistic representation of stratosphere-troposphere interactions. The sea ice impact during 1979-2015 is obtained by comparing ensemble simulations forced by daily observational sea ice concentration (SIC) and sea surface temperature (SST) to simulations where the time-varying SIC is replaced by a daily SIC climatology. A series of SIC-SST adjustments are performed to minimize unrealistic SIC and SST forcings used in the simulations. Each ensemble consists of 30 members with slightly different atmospheric initial conditions in order to separate forced atmospheric responses from internal model spread.

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.

A framework to enable Earth system predictability research on the subseasonal timescale is developed with the Community Earth System Model, version 2 (CESM2) using two model configurations that differ in their atmospheric components. One configuration uses the Community Atmosphere Model, version 6 (CAM6) with its top near 40 km, referred to as CESM2(CAM6). The other employs the Whole Atmosphere Community Climate Model, version 6 (WACCM6) whose top extends to ~ 140 km in the vertical and it includes fully interactive tropospheric and stratospheric chemistry (CESM2(WACCM6)). Both configurations were used to carry out subseasonal reforecasts for the time period 1999 to 2020 following the Subseasonal Experiment’s (SubX) protocol. CESM2(CAM6) and CESM2(WACCM6) show very similar subseasonal prediction skill of 2-meter temperature, precipitation, the Madden-Julian Oscillation (MJO), and North Atlantic Oscillation (NAO) to the Community Earth System Model, version 1 with the Community Atmosphere Model, version 5 (CESM1(CAM5)) and to operational models. CESM2(CAM6) and CESM2(WACCM6) reforecast sets provide a comprehensive dataset for predictability research of multiple Earth system components, including three-dimensional output for many variables, and output specific to the mesosphere and lower-thermosphere (MLT) region. We show that MLT variability can be predicted ~ 10 days in advance of sudden stratospheric warming events. Weekly real-time forecasts with CESM2(WACCM6) contribute to the multi-model mean ensemble forecast used to issue the NOAA weeks 3-4 outlooks. As a freely available community model, both CESM2 configurations can be used to carry out additional experiments to elucidate sources of subseasonal predictability.

Impacts of model horizontal resolution on sea-surface temperature (SST) biases are studied using high-resolution (HR) and low-resolution (LR) simulations with the Community Earth System Model (CESM) where the nominal resolutions are 0.1° for ocean and sea-ice and 0.25° for atmosphere and land in HR, and 1° for all component models in LR, respectively. Results show that, except within eastern boundary upwelling systems, SST is warmer in HR than LR. Globally averaged surface ocean heat budget analysis indicates that 1°C warmer global-mean SST in HR is mainly attributable to stronger nonlocal vertical mixing and shortwave heat flux, with the former prevailing over the latter in eddy-active regions. In the tropics, nonlocal vertical mixing is slightly more important than shortwave heat flux for the warmer SST in HR. Further analysis shows that the stronger nonlocal mixing in HR can be attributed to differences in both the surface heat flux and shape function strength used in the parameterization. In addition, the shape function shows a nonlinear relationship with surface heat flux in HR and LR, modulated by the eddy-induced vertical heat transport. The stronger shortwave heat flux in HR, on the other hand, is mainly caused by fewer clouds in the tropics. Finally, investigation of ocean advection reveals that the improved western boundary currents in HR also contribute to the reduction of SST biases in eddy-active regions.