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Ensembles of climate model simulations are commonly used to separate externally forced climate change from internal climate variability. However, much of the information gained from running large ensembles is lost in traditional methods of data reduction such as linear trend analysis or large scale spatial averaging. This paper demonstrates a pattern recognition method (forced pattern filtering) that extracts patterns of externally forced climate change from large ensembles and identifies the forced climate response with up to 10 times fewer ensemble members than simple ensemble averaging. It is particularly effective at filtering out spatially coherent modes of internal variability (e.g., El Ni˜no, North Atlantic Oscillation), which would otherwise alias into estimates of regional responses to forcing. This method is used to identify forced climate responses within the 40-member Community Earth System Model (CESM) large ensemble, including an El-Ni˜no-like response to volcanic eruptions and forced trends in the North Atlantic Oscillation. The ensemble-based estimate of the forced response is used to test statistical methods for isolating the forced response from a single realization (i.e., individual ensemble members). Low-frequency pattern filtering is found to effectively identify the forced response within individual ensemble members and is applied to the HadCRUT4 reconstruction of observed temperatures, whereby it identifies slow components of observed temperature changes that are consistent with the expected effects of anthropogenic greenhouse gas and aerosol forcing. 

This study presents a description of the El Niño–Southern Oscillation (ENSO) and Pacific Decadal Variability (PDV) in a multicentury preindustrial simulation of the Community Earth System Model Version 2 (CESM2). The model simulates several aspects of ENSO relatively well, including dominant timescale, tropical and extratropical precursors, composite evolution of El Niño and La Niña events, and ENSO teleconnections. The good model representation of ENSO spectral characteristics is consistent with the spatial pattern of the anomalous equatorial zonal wind stress in the model, which results in the correct adjustment timescale of the equatorial thermocline according to the delayed/recharge oscillator paradigms, as also reflected in the realistic time evolution of the equatorial Warm Water Volume. PDV in the model exhibits a pattern that is very similar to the observed, with realistic tropical and South Pacific signatures which were much weaker in some of the CESM2 predecessor models. The tropical component of PDV also shows an association with ENSO decadal modulation which is similar to that found in observations. However, the ENSO amplitude is about 30% larger than observed in the preindustrial CESM2 simulation, and even larger in the historical ensemble, perhaps as a result of anthropogenic influences. In contrast to observations, the largest variability is found in the central Pacific rather than in the eastern Pacific, a discrepancy that somewhat hinders the model's ability to represent a full diversity in El Niño spatial patterns and appears to be associated with an unrealistic confinement of the precipitation anomalies to the western Pacific.

 

One of the most robust responses of the climate system to future greenhouse gas emissions is the melting of Arctic sea ice. It is thus essential to elucidate its impacts on other components of the climate system. Here we focus on the response of the annual mean Hadley cell (HC) to Arctic sea ice loss using a hierarchy of model configurations: atmosphere only, atmosphere coupled to a slab ocean, and atmosphere coupled to a full‐physics ocean. In response to Arctic sea ice loss, as projected by the end of the 21st century, the HC shows negligible changes in the absence of ocean‐atmosphere coupling. In contrast, by warming the Northern Hemisphere thermodynamic coupling weakens the HC and expands it northward. However, dynamic coupling acts to cool the Northern Hemisphere which cancels most of this weakening and narrows the HC, thus opposing its projected expansion in response to increasing greenhouse gases.

 

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 and 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.