The Community Atmosphere Model (CAM) version 5 includes a spectral element dynamical core option from NCAR's High-Order Method Modeling Environment. It is a continuous Galerkin spectral finite element method designed for fully unstructured quadrilateral meshes. The current configurations in CAM are based on the cubedsphere grid. The main motivation for including a spectral element dynamical core is to improve the scalability of CAM by allowing quasi-uniform grids for the sphere that do not require polar filters. In addition, the approach provides other state-of-the-art capabilities such as improved conservation properties. Spectral elements are used for the horizontal discretization, while most other aspects of the dynamical core are a hybrid of well tested techniques from CAM's finite volume and global spectral dynamical core options. Here we first give a overview of the spectral element dynamical core as used in CAM. We then give scalability and performance results from CAM running with three different dynamical core options within the Community Earth System Model, using a pre-industrial time-slice configuration. We focus on high resolution simulations, using 1/4 degree, 1/8 degree, and T341 spectral truncation horizontal grids.

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.

Abstract. While climate change mitigation targets necessarily concern maximum mean state changes, understanding impacts and developing adaptation strategies will be largely contingent on how climate variability responds to increasing anthropogenic perturbations. Thus far Earth system modeling efforts have primarily focused on projected mean state changes and the sensitivity of specific modes of climate variability, such as the El Niño–Southern Oscillation. However, our knowledge of forced changes in the overall spectrum of climate variability and higher-order statistics is relatively limited. Here we present a new 100-member large ensemble of climate change projections conducted with the Community Earth System Model version 2 over 1850–2100 to examine the sensitivity of internal climate fluctuations to greenhouse warming. Our unprecedented simulations reveal that changes in variability, considered broadly in terms of probability distribution, amplitude, frequency, phasing, and patterns, are ubiquitous and span a wide range of physical and ecosystem variables across many spatial and temporal scales. Greenhouse warming in the model alters variance spectra of Earth system variables that are characterized by non-Gaussian probability distributions, such as rainfall, primary production, or fire occurrence. Our modeling results have important implications for climate adaptation efforts, resource management, seasonal predictions, and assessing potential stressors for terrestrial and marine ecosystems.

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.

Abstract. While climate change mitigation targets necessarily concern maximum mean state change, understanding impacts and developing adaptation strategies will be largely contingent on how climate variability responds to increasing anthropogenic perturbations. Thus far Earth system modeling efforts have primarily focused on projected mean state changes and the sensitivity of specific modes of climate variability, such as the El Niño-Southern Oscillation. However, our knowledge of forced changes in the overall spectrum of climate variability and higher order statistics is relatively limited. Here we present a new 100-member large ensemble of climate change projections conducted with the Community Earth System Model version 2 to examine the sensitivity of internal climate fluctuations to greenhouse warming. Our unprecedented simulations reveal that changes in variability, considered broadly in terms of probability, distribution, amplitude, frequency, phasing, and patterns, are ubiquitous and span a wide range of physical and ecosystem variables across many spatial and temporal scales. Greenhouse warming will in particular alter variance spectra of Earth system variables that are characterized by non-Gaussian probability distributions, such as rainfall, primary production, or fire occurrence. Our modeling results have important implications for climate adaptation efforts, resource management, seasonal predictions, and for assessing potential stressors for terrestrial and marine ecosystems.

This paper presents a description of the CESM/DART ensemble coupled data assimilation (DA) system based on the Community Earth System Model (CESM) and the Data Assimilation Research Testbed (DART) assimilation software. The CESM/DART should be viewed as a flexible system to support the DA needs of the CESM research community and not as a static reanalysis product. In this implementation of the CESM/DART, conventional insitu observations of the ocean and atmosphere are assimilated into the respective component models of the CESM using a 30‐member ensemble adjustment Kalman filter (EAKF). CESM/DART is run in a “weakly coupled” configuration wherein observations native to each climate system component only directly impact the state vector for that component. Information is passed between components indirectly through the short‐term coupled model forecasts that provide the EAKF background ensemble. This system leverages previous ensemble DA development for the Community Atmosphere Model and Parallel Ocean Program models using the DART EAKF. The CESM/DART project is a step towards providing increasingly useful DA capabilities for the CESM research community. Results are presented for our prototype 12‐year reanalysis, run from 1970 to mid 1982. Multiple lines of evidence demonstrate that the system is capable of constraining the CESM coupled model to simulate the historical variability of the climate system in the well‐observed Northern Hemisphere. A collection of monthly average variables, climate mode indices, observation diagnostics and snapshots of synoptic weather in the ocean and atmosphere are compared to established datasets, showing especially good agreement in the Northern Hemisphere. A discussion of the CESM/DART as a modular, community facility and the benefits and challenges associated with this vision is also included.

Abstract. We present results from a conservative formulation of the spectral element method applied to global atmospheric circulation modeling. Exact local conservation of both mass and energy is obtained via a new compatible formulation of the spectral element method. Compatibility insures that the key integral property of the divergence and gradient operators required to show conservation also hold in discrete form. The spectral element method is used on a cubed-sphere grid to discretize the horizontal directions on the sphere. It can be coupled to any conservative vertical/radial discretization. The accuracy and conservation properties of the method are illustrated using a baroclinic instability test case. IntroductionThe spectral element method is a finite element method which relies on polynomial basis functions and quadrilateral elements. The equations of interest are solved in integral formulation and the integrals are evaluated with Gauss-Lobatto quadrature within each element. The GaussLobatto quadrature leads to a diagonal mass matrix, which allows the method to obtain spectral accuracy while retaining both parallel efficiency and the geometric flexibility of unstructured finite elements grids. The method has proven accurate and efficient for a wide variety of geophysical problems, including global atmospheric circulation modeling [1,2,3,4] ocean modeling [5,6,7] and planetary scale seismology [8]. The method has unsurpassed parallel performance; it was used for earthquake modeling by the 2003 Gordon Bell Best Performance winner [8] and for climate modeling by a 2002 Gordon Bell Award honorable mention [9].In this work, we use a modified version of the spectral element component of HOMME, the High Order Multiscale Modeling Environment [10], which we refer to as HOMME-SE. HOMME-SE models the global circulation of the Earth's atmosphere using the three-dimensional hydrostatic primitive equations. The formulation of the equations is taken from [11]. Spectral elements on a cubed-sphere grid are used to discretize the horizontal directions (the surface of the Earth). In the radial direction, HOMME-SE uses the hybrid η pressure vertical coordinate system [12,11]. We made several modifications to HOMME-SE in order to make the method locally conservative: we implemented the compatible spectral element formulation from [13], which involved slightly different forms of the metric terms in the discrete integrals, divergence, gradient and vorticity operators, and we switched from advection of log(p s ) to surface pressure p s .