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Abstract We assess to what extent seven state-of-the-art dynamical prediction systems can retrospectively predict winter sea surface temperature (SST) in the subpolar North Atlantic and the Nordic seas in the period 1970–2005. We focus on the region where warm water flows poleward (i.e., the Atlantic water pathway to the Arctic) and on interannual-to-decadal time scales. Observational studies demonstrate predictability several years in advance in this region, but we find that SST skill is low with significant skill only at a lead time of 1–2 years. To better understand why the prediction systems have predictive skill or lack thereof, we assess the skill of the systems to reproduce a spatiotemporal SST pattern based on observations. The physical mechanism underlying this pattern is a propagation of oceanic anomalies from low to high latitudes along the major currents, the North Atlantic Current and the Norwegian Atlantic Current. We find that the prediction systems have difficulties in reproducing this pattern. To identify whether the misrepresentation is due to incorrect model physics, we assess the respective uninitialized historical simulations. These simulations also tend to misrepresent the spatiotemporal SST pattern, indicating that the physical mechanism is not properly simulated. However, the representation of the pattern ismore »slightly degraded in the predictions compared to historical runs, which could be a result of initialization shocks and forecast drift effects. Ways to enhance predictions could include improved initialization and better simulation of poleward circulation of anomalies. This might require model resolutions in which flow over complex bathymetry and the physics of mesoscale ocean eddies and their interactions with the atmosphere are resolved. Significance Statement In this study, we find that dynamical prediction systems and their respective climate models struggle to realistically represent ocean surface temperature variability in the eastern subpolar North Atlantic and Nordic seas on interannual-to-decadal time scales. In previous studies, ocean advection is proposed as a key mechanism in propagating temperature anomalies along the Atlantic water pathway toward the Arctic Ocean. Our analysis suggests that the predicted temperature anomalies are not properly circulated to the north; this is a result of model errors that seems to be exacerbated by the effect of initialization shocks and forecast drift. Better climate predictions in the study region will thus require improving the initialization step, as well as enhancing process representation in the climate models.« less

Multiple 50‐member ensemble simulations with the Community Earth System Model version 2 are performed to estimate the coupled climate responses to the 2019–2020 Australian wildfires and COVID‐19 pandemic policies. The climate response to the pandemic is found to be weak generally, with global‐mean net top‐of‐atmosphere radiative anomalies of +0.23 ± 0.14 W m⁻²driving a gradual global warming of 0.05 ± 0.04 K by the end of 2022. While regional anomalies are detectable in aerosol burdens and clear‐sky radiation, few significant anomalies exist in other fields due to internal variability. In contrast, the simulated response to Australian wildfires is a strong and rapid cooling, peaking globally at−0.95 ± 0.15 W m⁻²in late 2019 with a global cooling of 0.06 ± 0.04 K by mid‐2020. Transport of fire aerosols throughout the Southern Hemisphere increases albedo and drives a strong interhemispheric radiative contrast, with simulated responses that are consistent generally with those to a Southern Hemisphere volcanic eruption.

The Community Earth System Model Version 2 (CESM2) has an equilibrium climate sensitivity (ECS) of 5.3 K. ECS is an emergent property of both climate feedbacks and aerosol forcing. The increase in ECS over the previous version (CESM1) is the result of cloud feedbacks. Interim versions of CESM2 had a land model that damped ECS. Part of the ECS change results from evolving the model configuration to reproduce the long‐term trend of global and regional surface temperature over the twentieth century in response to climate forcings. Changes made to reduce sensitivity to aerosols also impacted cloud feedbacks, which significantly influence ECS. CESM2 simulations compare very well to observations of present climate. It is critical to understand whether the high ECS, outside the best estimate range of 1.5–4.5 K, is plausible.

An overview of the Community Earth System Model Version 2 (CESM2) is provided, including a discussion of the challenges encountered during its development and how they were addressed. In addition, an evaluation of a pair of CESM2 long preindustrial control and historical ensemble simulations is presented. These simulations were performed using the nominal 1° horizontal resolution configuration of the coupled model with both the “low‐top” (40 km, with limited chemistry) and “high‐top” (130 km, with comprehensive chemistry) versions of the atmospheric component. CESM2 contains many substantial science and infrastructure improvements and new capabilities since its previous major release, CESM1, resulting in improved historical simulations in comparison to CESM1 and available observations. These include major reductions in low‐latitude precipitation and shortwave cloud forcing biases; better representation of the Madden‐Julian Oscillation; better El Niño‐Southern Oscillation‐related teleconnections; and a global land carbon accumulation trend that agrees well with observationally based estimates. Most tropospheric and surface features of the low‐ and high‐top simulations are very similar to each other, so these improvements are present in both configurations. CESM2 has an equilibrium climate sensitivity of 5.1–5.3 °C, larger than in CESM1, primarily due to a combination of relatively small changes to cloud microphysics andmore »boundary layer parameters. In contrast, CESM2's transient climate response of 1.9–2.0 °C is comparable to that of CESM1. The model outputs from these and many other simulations are available to the research community, and they represent CESM2's contributions to the Coupled Model Intercomparison Project Phase 6.

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