Abstract.A modal aerosol module (MAM) has been developed for the Community Atmosphere Model version 5 (CAM5), the atmospheric component of the Community Earth System Model version 1 (CESM1). MAM is capable of simulating the aerosol size distribution and both internal and external mixing between aerosol components, treating numerous complicated aerosol processes and aerosol physical, chemical and optical properties in a physically-based manner. Two MAM versions were developed: a more complete version with seven lognormal modes (MAM7), and a version with three lognormal modes (MAM3) for the purpose of long-term (decades to centuries) simulations. In this paper a description and evaluation of the aerosol module and its two representations are provided. Sensitivity of the aerosol lifecycle to simplifications in the representation of aerosol is discussed.Simulated sulfate and secondary organic aerosol (SOA) mass concentrations are remarkably similar between MAM3 and MAM7. Differences in primary organic matter (POM) and black carbon (BC) concentrations between MAM3 and MAM7 are also small (mostly within 10 %). The mineral dust global burden differs by 10 % and sea salt burden by 30-40 % between MAM3 and MAM7, mainly due to the different size ranges for dust and sea salt modes and different standard deviations of the log-normal size distribution for sea salt modes between MAM3 and MAM7. The model is able to qualitatively capture the observed geographical and temporal variations of aerosol mass and number concentrations, size distributions, and aerosol optical properties. However, there are noticeable biases; e.g., simulated BC concentrations are significantly lower than measurements in the Arctic. There is a low bias in modeled aerosol optical depth on the global scale, especially in the developing countries. These biases in aerosol simulations clearly indicate the need for improvements of aerosol processes (e.g., emission fluxes of anthropogenic aerosols and precursor gases in developing countries, boundary layer nucleation) and properties (e.g., primary aerosol emission size, POM hygroscopicity). In addition, the critical role of cloud properties (e.g., liquid water content, cloud fraction) responsible for the wet scavenging of aerosol is highlighted.

A new two-moment stratiform cloud microphysics scheme in a general circulation model is described. Prognostic variables include cloud droplet and cloud ice mass mixing ratios and number concentrations. The scheme treats several microphysical processes, including hydrometeor collection, condensation/evaporation, freezing, melting, and sedimentation. The activation of droplets on aerosol is physically based and coupled to a subgrid vertical velocity. Unique aspects of the scheme, relative to existing two-moment schemes developed for general circulation models, are the diagnostic treatment of rain and snow number concentration and mixing ratio and the explicit treatment of subgrid cloud water variability for calculation of the microphysical process rates. Numerical aspects of the scheme are described in detail using idealized one-dimensional offline tests of the microphysics. Sensitivity of the scheme to time step, vertical resolution, and numerical method for diagnostic precipitation is investigated over a range of conditions. It is found that, in general, two substeps are required for numerical stability and reasonably small time truncation errors using a time step of 20 min; however, substepping is only required for the precipitation microphysical processes rather than the entire scheme. A new numerical approach for the diagnostic rain and snow produces reasonable results compared to a benchmark simulation, especially at low vertical resolution. Part II of this study details results of the scheme in single-column and global simulations, including comparison with observations.

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.

[1] Simulations of the stratosphere from thirteen coupled chemistry-climate models (CCMs) are evaluated to provide guidance for the interpretation of ozone predictions made by the same CCMs. The focus of the evaluation is on how well the fields and processes that are important for determining the ozone distribution are represented in the simulations of the recent past. The core period of the evaluation is from 1980 to 1999 but long-term trends are compared for an extended period . Comparisons of polar high-latitude temperatures show that most CCMs have only small biases in the Northern Hemisphere in winter and spring, but still have cold biases in the Southern Hemisphere spring below 10 hPa. Most CCMs display the correct stratospheric response of polar temperatures to wave forcing in the Northern, but not in the Southern Hemisphere. Global long-term stratospheric temperature trends are in reasonable agreement with satellite and radiosonde observations. Comparisons of simulations of methane, mean age of air, and propagation of the annual cycle in water vapor show a wide spread in the results, indicating differences in transport. However, for around half the models there is reasonable agreement with observations. In these models the mean age of air and the water vapor tape recorder signal are generally better than reported in previous model intercomparisons. Comparisons of the water vapor and inorganic chlorine (Cl y ) fields also show a large intermodel spread. Differences in tropical water vapor mixing ratios in the lower stratosphere are primarily related to biases in the simulated tropical tropopause temperatures and not transport. The spread in Cl y , which is largest in the polar lower stratosphere, appears to be primarily related to transport differences. In general the amplitude and phase of the annual cycle in total ozone is well simulated apart from the southern high latitudes. Most CCMs show reasonable agreement with observed total D223081 of 29 ozone trends and variability on a global scale, but a greater spread in the ozone trends in polar regions in spring, especially in the Arctic. In conclusion, despite the wide range of skills in representing different processes assessed here, there is sufficient agreement between the majority of the CCMs and the observations that some confidence can be placed in their predictions. Citation: Eyring, V., et al. (2006), Assessment of temperature, trace species, and ozone in chemistry-climate model simulations of the recent past,

[1] A new ensemble of climate models is becoming available and provides the basis for climate change projections. Here, we show a first analysis indicating that the models in the new ensemble agree better with observations than those in older ones and that the poorest models have been eliminated. Most models are strongly tied to their predecessors, and some also exchange ideas and code with other models, thus supporting an earlier hypothesis that the models in the new ensemble are neither independent of each other nor independent of the earlier generation. On the basis of one atmosphere model, we show how statistical methods can identify similarities between model versions and complement process understanding in characterizing how and why a model has changed. We argue that the interdependence of models complicates the interpretation of multimodel ensembles but largely goes unnoticed.Citation: Knutti, R., D. Masson, and A. Gettelman (2013), Climate model genealogy: Generation CMIP5 and how we got there,

[1] This paper reports on the early mission performance of the radar and other major aspects of the CloudSat mission. The Cloudsat cloud profiling radar (CPR) has been operating since 2 June 2006 and has proven to be remarkably stable since turn-on. A number of products have been developed using these space-borne radar data as principal inputs. Combined with other A-Train sensor data, these new observations offer unique, global views of the vertical structure of clouds and precipitation jointly. Approximately 11% of clouds detected over the global oceans produce precipitation that, in all likelihood, reaches the surface. Warm precipitating clouds are both wetter and composed of larger particles than nonprecipitating clouds. The frequency of precipitation increases significantly with increasing cloud depth, and the increased depth and water path of precipitating clouds leads to increased optical depths and substantially more sunlight reflected from precipitating clouds compared to than nonprecipitating warm clouds. The CloudSat observations also provide an authoritative estimate of global ice water paths. The observed ice water paths are larger than those predicted from most climate models. CloudSat observations also indicate that clouds radiatively heat the global mean atmospheric column (relative to clear skies) by about 10 Wm À2 . Although this heating appears to be contributed almost equally by solar and infrared absorption, the latter contribution is shown to vary significantly with latitude being influenced by the predominant cloud structures of the different region in questions. Citation: Stephens, G. L., et al. (2008), CloudSat mission: Performance and early science after the first year of operation,

[1] A process-based treatment of ice supersaturation and ice nucleation is implemented in the National Center for Atmospheric Research Community Atmosphere Model (CAM). The new scheme is designed to allow (1) supersaturation with respect to ice, (2) ice nucleation by aerosol particles, and (3) ice cloud cover consistent with ice microphysics. The scheme is implemented with a two-moment microphysics code and is used to evaluate ice cloud nucleation mechanisms and supersaturation in CAM. The new model is able to reproduce field observations of ice mass and mixed phase cloud occurrence better than previous versions. The model is able to reproduce observed patterns and frequency of ice supersaturation. Simulations indicate homogeneous freezing of sulfate and heterogeneous freezing on dust are both important ice nucleation mechanisms, in different regions. Simulated cloud forcing and climate is sensitive to different formulations of the ice microphysics. Arctic surface radiative fluxes are sensitive to the parameterization of ice clouds. These results indicate that ice clouds are potentially an important part of understanding cloud forcing and potential cloud feedbacks, particularly in the Arctic.

[1] Recent declines in Arctic sea ice extent provide new opportunities to assess cloud influence on and response to seasonal sea ice loss. This study combines unique satellite observations with complementary data sets to document Arctic cloud and atmospheric structure during summer and early fall. The analysis focuses on 2006-2008, a period over which ice extent plummeted to record levels, substantial variability in atmospheric circulation patterns occurred, and spaceborne radar and lidar observations of vertical cloud structure became available. The observations show that large-scale atmospheric circulation patterns, near-surface static stability, and surface conditions control Arctic cloud cover during the melt season. While no summer cloud response to sea ice loss was found, low clouds did form over newly open water during early fall. This seasonal variation in the cloud response to sea ice loss can be explained by near-surface static stability and air-sea temperature gradients. During summer, temperature inversions and weak air-sea temperature gradients limit atmosphere-ocean coupling. In contrast, relatively low static stability and strong air-sea gradients during early fall permit upward turbulent fluxes of moisture and heat and increased low cloud formation over newly open water. Because of their seasonal timing, cloud changes resulting from sea ice loss play a minor role in regulating ice-albedo feedbacks during summer, but may contribute to a cloud-ice feedback during early fall.