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.

An overview is presented of the GLENS project, a community-wide effort enabling analyses of global and regional changes from stratospheric aerosol geoengineering in the presence of internal climate variability. CESM1(WACCM) STRATOSPHERIC AEROSOL GEOENGINEERING LARGE ENSEMBLE PROJECTSimone TilmeS, Jadwiga H. RicHTeR, Ben KRaviTz, douglaS g. macmaRTin, micHael J. millS, iSla R. SimpSon, anne S. glanville, JoHn T. FaSullo, adam S. pHillipS, Jean-FRancoiS lamaRque, JoSepH TRiBBia, Jim edwaRdS, SHeRi micKelSon, and SiddHaRTHa gHoSH S olar geoengineering using stratospheric sulfate aerosols has been discussed as a potential means of deliberately offsetting some of the effects of climate change (Crutzen 2006). Various model studies have demonstrated that reducing incoming solar radiation globally can offset the increase in global average surface temperature associated with increasing greenhouse gases (e.g., Kravitz et al. 2013). Despite the stabilization of global surface temperature, these simulations show significant changes in atmospheric conditions with global solar reductions or stratospheric sulfur or aerosol injections. Side effects in these simulations include "overcooling" of the tropics and "undercooling" of the poles, leading to continued Arctic summer sea ice loss (e.g., Moore et al. 2014;Tilmes et al. 2016). Additionally, the slowing of the hydrological cycle (e.g., Schmidt et al. 2012) and the potentially uneven cooling between the two hemispheres resulting from solar geoengineering can lead to shifts in precipitation patterns (Haywood et al. 2013; Jones et al. 2017) and reductions in monsoon precipitation (Tilmes et al. 2013). Many available model results to date are based on an artificial design intended to explore the impact of large forcing effects through global solar dimming. For other experiments, only a few ensemble members are performed, making it difficult to identify the robustness of regional climate effects.Simulations of stratospheric sulfate aerosol geoengineering inject sulfur dioxide (SO 2 ) into the stratosphere that oxidizes to form sulfate aerosols or they use direct injections of sulfate aerosols. These experiments require model capabilities beyond those in solar reduction simulations. The stratospheric aerosol distribution resulting from such injections depends on the model's aerosol microphysical scheme, as well as interactions with chemical, dynamical, and radiative processes (Pitari et al. 2014;Mills et al. 2017). Aerosol size and sedimentation are increased with the injection amount and the efficiency of the sulfates to affect the top of the atmosphere radiative imbalance is reduced (Niemeier and Timmreck 2015;Kleinschmitt et al. 2017). The warming of the tropical stratosphere in response to the enhanced aerosol burden results in circulation changes in the stratosphere with potential effects 2361NOVEMBER 2018 AMERICAN METEOROLOGICAL SOCIETY | on the quasi-biennial oscillation (QBO; Aquila et al. 2014), as well as impacts on the tropospheric circulation (Richter et al. 2018). Chan...

Abstract. Climate simulation codes, such as the Community Earth System Model (CESM), are especially complex and continually evolving. Their ongoing state of development requires frequent software verification in the form of quality assurance to both preserve the quality of the code and instill model confidence. To formalize and simplify this previously subjective and computationally expensive aspect of the verification process, we have developed a new tool for evaluating climate consistency. Because an ensemble of simulations allows us to gauge the natural variability of the model's climate, our new tool uses an ensemble approach for consistency testing. In particular, an ensemble of CESM climate runs is created, from which we obtain a statistical distribution that can be used to determine whether a new climate run is statistically distinguishable from the original ensemble. The CESM ensemble consistency test, referred to as CESM-ECT, is objective in nature and accessible to CESM developers and users. The tool has proven its utility in detecting errors in software and hardware environments and providing rapid feedback to model developers.

High-resolution climate simulations require tremendous computing resources and can generate massive datasets. At present, preserving the data from these simulations consumes vast storage resources at institutions such as the National Center for Atmospheric Research (NCAR). The historical data generation trends are economically unsustainable, and storage resources are already beginning to limit science objectives. To mitigate this problem, we investigate the use of data compression techniques on climate simulation data from the Community Earth System Model. Ultimately, to convince climate scientists to compress their simulation data, we must be able to demonstrate that the reconstructed data reveals the same mean climate as the original data, and this paper is a first step toward that goal. To that end, we develop an approach for verifying the climate data and use it to evaluate several compression algorithms. We find that the diversity of the climate data requires the individual treatment of variables, and, in doing so, the reconstructed data can fall within the natural variability of the system, while achieving compression rates of up to 5:1.

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