Evaluating and improving cloud phase in the Community Atmosphere Model version 5 using spaceborne lidar observations

CAM3 (Community Atmosphere Model version 3) simulation bias is diagnosed using the vorticity equation. The study compares CAM3 output with ECMWF (European Centre for Medium-Range Weather Forecasts) 40 year reanalysis (ERA-40) data. A time mean vorticity bias equation is also formulated and the terms are grouped into categories: linear terms, nonlinear terms, transient contributions, and friction (calculated as a residual). Frontal cyclone storms have much weaker band passed kinetic energy and enstrophy in CAM3. The downstream end of the North Atlantic storm track (NAST) has large location error. While the vorticity equation terms have similar amplitude ranking in CAM3 and ERA-40 at upper levels, the ranking differs notably in the lower troposphere. The linear and friction terms dominate the vorticity bias equation. The transient terms contribute along the storm track, but the nonlinear terms are generally much smaller, with the primary exception being over the Iberian peninsula. Friction is much stronger in CAM3. As evidence, nearly all wavelengths (including the longest planetary waves) have smaller amplitude in CAM3 than in ERA-40 vorticity data. Negative near surface vorticity tendency bias on the European side of the Arctic is linked to the NAST track error (evident in the divergence term). CAM3 misses the Beaufort high in sea level pressure (SLP) due to low level warm temperature bias, too little vortex compression, and to too little horizontal advection of negative vorticity compared with ERA-40. Generally lower SLP values in CAM3 over the entire Arctic follow from lower level warm bias in CAM3.

Characteristics of, and fundamental differences between, the radiative‐convective equilibrium (RCE) climate states following the Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) protocols in the Community Atmosphere Model version 5 (CAM5) and version 6 (CAM6) are presented. This paper explores the characteristics of clouds, moisture, precipitation and circulation in the RCE state, as well as the tropical response to surface warming, in CAM5 and CAM6 with different parameterizations. Overall, CAM5 simulates higher precipitation rates that result in larger global average precipitation, despite lower outgoing longwave radiation compared to CAM6. Differences in the structure of clouds, particularly the amount and vertical location of cloud liquid, exist between the CAM versions and can, in part, be related to distinct representations of shallow convection and boundary layer processes. Both CAM5 and CAM6 simulate similar peaks in cloud fraction, relative humidity, and cloud ice, linked to the usage of a similar deep convection parameterization. These anvil clouds rise and decrease in extent in response to surface warming. More generally, extreme precipitation, aggregation of convection, and climate sensitivity increase with warming in both CAM5 and CAM6. This analysis provides a benchmark for future studies that explore clouds, convection, and climate in CAM with the RCEMIP protocols now available in the Community Earth System Model. These results are discussed within the context of realistic climate simulations using CAM5 and CAM6, highlighting the usefulness of a hierarchical modeling approach to understanding model and parameterization sensitivities to inform model development efforts.

The parameterizations of clouds and precipitation processes have been revised considerably in the Community Atmosphere Model version 3 (CAM3) compared to its predecessors, CAM2 and the Community Climate Model version 3 (CCM3). The parameterizations in CAM3 are more realistic in their representation of processes affecting cloud liquid and ice particles and represent the linkages between processes more completely. This paper describes the changes to the representation of clouds in CAM3, including the partitioning of cloud water between liquid and ice phases, the determination of particle sizes and sedimentation rates, the phase and evaporation rate of precipitation, and the calculation of the cloud fraction. Parameterization changes between CCM3 and CAM2 introduced a significant cold bias at the tropical tropopause, resulting in a dry bias for stratospheric water vapor. Tests of the sensitivity of the tropical temperature profile and the tropical tropopause temperature to individual process changes suggested that the radiative balance at the tropopause was altered by improvements in both clouds and relative humidity below. Radiative equilibrium calculations suggested that the cold bias could be removed by improving the representation of subvisible cirrus clouds. These results motivated the complete separation of the representation of liquid and ice cloud particles and an examination of the processes that determine their sources and sinks. As a result of these changes, the tropopause cold bias has been almost eliminated in CAM3. The total cloud condensate variable, used in CAM2, has been separated into cloud liquid and cloud ice variables in CAM3. Both sedimentation and large-scale transport of the condensate variables are now included. Snowfall is computed explicitly and the latent heat of fusion has been included for all freezing and melting processes. Both deep and shallow convection parameterizations now detrain cloud condensate directly into the stratiform clouds instead of evaporating the detrained condensate into the environment. The convective parameterizations are not easily modified to include the latent heat of fusion. Therefore, the determination of the phase of convective precipitation, and of detrained condensate, is added as a separate step. Evaporation is included for sedimenting cloud particles and for all sources of precipitation.

The parameterization of subgrid‐scale processes such as boundary layer (PBL) turbulence introduces uncertainty in Earth System Model (ESM) results. This uncertainty can contribute to or exacerbate existing biases in representing key physical processes. This study analyzes the influence of tunable parameters in an experimental version of the Cloud Layers Unified by Binormals (CLUBBX) scheme. CLUBB is the operational PBL parameterization in the Community Atmosphere Model version 6 (CAM6), the atmospheric component of the Community ESM version 2 (CESM2). We perform the Morris one‐at‐a‐time (MOAT) parameter sensitivity analysis using short‐term (3‐day), initialized hindcasts of CAM6‐CLUBBX with 24 unique initial conditions. Several input parameters modulating vertical momentum flux appear most influential for various regionally‐averaged quantities, namely surface stress and shortwave cloud forcing (SWCF). These parameter sensitivities have a spatial dependence, with parameters governing momentum flux most influential in regions of high vertical wind shear (e.g., the mid‐latitude storm tracks). We next evaluate several experimental 20‐year simulations of CAM6‐CLUBBX with targeted parameter perturbations. We find that parameter perturbations produce similar physical mechanisms in both short‐term and long‐term simulations, but these physical responses can be muted due to nonlinear feedbacks manifesting over time scales longer than 3 days, thus causing differences in how output metrics respond in the long‐term simulations. Analysis of turbulent fluxes in CLUBBX indicates that the influential parameters affect vertical fluxes of heat, moisture, and momentum, providing physical pathways for the sensitivities identified in this study.

Abstract. Marine stratocumuli are the most dominant cloud type by area coverage in the Southern Ocean (SO). They can be divided into different self-organized cellular morphological regimes known as open and closed mesoscale-cellular convective (MCC) clouds. Open and closed cells are the two most frequent types of organizational regimes in the SO. Using the liDAR-raDAR (DARDAR) version 2 retrievals, we quantify 59 % of all MCC clouds in this region as mixed-phase clouds (MPCs) during a 4-year time period from 2007 to 2010. The net radiative effect of SO MCC clouds is governed by changes in cloud albedo. Both cloud morphology and phase have previously been shown to impact cloud albedo individually, but their interactions and their combined impact on cloud albedo remain unclear. Here, we investigate the relationships between cloud phase, organizational patterns, and their differences regarding their cloud radiative properties in the SO. The mixed-phase fraction, which is defined as the number of MPCs divided by the sum of MPC and supercooled liquid cloud (SLC) pixels, of all MCC clouds at a given cloud-top temperature (CTT) varies considerably between austral summer and winter. We further find that seasonal changes in cloud phase at a given CTT across all latitudes are largely independent of cloud morphology and are thus seemingly constrained by other external factors. Overall, our results show a stronger dependence of cloud phase on cloud-top height (CTH) than CTT for clouds below 2.5 km in altitude. Preconditioning through ice-phase processes in MPCs has been observed to accelerate individual closed-to-open cell transitions in extratropical stratocumuli. The hypothesis of preconditioning has been further substantiated in large-eddy simulations of open and closed MPCs. In this study, we do not find preconditioning to primarily impact climatological cloud morphology statistics in the SO. Meanwhile, in-cloud albedo analysis reveals stronger changes in open and closed cell albedo in SLCs than in MPCs. In particular, few optically thick (cloud optical thickness >10) open cell stratocumuli are characterized as ice-free SLCs. These differences in in-cloud albedo are found to alter the cloud radiative effect in the SO by 21 to 39 W m−2 depending on season and cloud phase.

The accurate representation of clouds and their phase is crucial to enable a correct representation of the Earth’s radiation balance. This has been demonstrated by large radiative errors in global models over the Southern Ocean mainly caused by an incorrect representation of supercooled liquid lowlevel clouds. In contrast to lowlevel clouds, midlevel clouds are rarely investigated. To fill this gap, this study investigates active satellite observations of midlevel clouds over the Southern Ocean and the Arctic Ocean from 2007 and 2008 with a comprehensive comparison to observations of lowlevel clouds. Midlevel and lowlevel clouds are distinguished by cloud base height. The DARDAR dataset provides a detailed phase categorization based on CloudSat and CALIPSO measurements. We have analyzed the cloud phase partitioning as a function of cloud top temperature, vertical cloud thickness, and the horizontal cloud extent. A local minimum in the mean liquid fraction within a cloud column can be observed for a cloud top temperature of -15 °C. An exception to this observation occurs for lowlevel clouds over the Arctic Ocean, which feature a plateau instead of a minimum. This hints at processes producing ice at these temperatures, which could be habit dependent vapor growth, secondary ice production, or a combination of both processes, as already discussed in other studies. Furthermore, daily sea ice concentrations from a passive microwave instrument are collocated to investigate their correlation with the cloud phase. At equal cloud top temperature, lowlevel clouds over the Southern Ocean and the Arctic Ocean have a higher liquid fraction, if they occur over sea ice. Midlevel clouds over the Southern Ocean show the same behaviour, while midlevel clouds over the Arctic Ocean show no significant phase dependence on the sea ice concentration. In addition, collocated CAMS reanalysis data are used to investigate the influence of different concentrations of various aerosol types such as sea salt, dust, black carbon, or organic matter on the cloud phase. Preliminary results show a stronger influence of the mixing ratio of sea salt on the phase of lowlevel clouds, but also the phase of midlevel clouds over the Southern Ocean seems to be influenced. Future work will further investigate the influence of different parameters, such as sea ice concentration, aerosol concentration, and cloud top temperature on the cloud phase by applying a machine learning model and exploring the relative importance of these parameters for the cloud phase, as well as their interactions and synergies.

<strong class="journal-contentHeaderColor">Abstract.</strong> The Community Earth System Model (CESM) community has been providing versatile modeling options, with simple to complex chemistry and aerosol schemes in a single model, in order to support the broad scientific community with various research interests. While different model configurations are available in CESM and these can be used for different fields of Earth system science, simulation results that are consistent across configurations are still desirable. Here we develop a new simple secondary organic aerosol (SOA) scheme in the Community Atmosphere Model version 6.3 (CAM6.3), the atmospheric component of the CESM. The main purpose of this simplified SOA scheme is to reduce the differences in aerosol concentrations and radiative fluxes between CAM and CAM with detailed chemistry (CAM-chem) while maintaining the computational efficiency of CAM. CAM simulation results with the current and the new SOA schemes are compared to the CAM-chem results as a reference. More consistent SOA concentrations are obtained globally when using the new SOA scheme, for both temporal and spatial variabilities. Furthermore, the overestimation of other carbonaceous aerosols (black carbon and primary organic aerosol) in CAM is greatly reduced, which results in improved global atmospheric burden and concentrations at the high latitudes of the Northern Hemisphere compared to the full chemistry version (CAM-chem). As a result, the high bias of radiative flux in the Arctic region is significantly reduced for both nudged and free-running simulations. We find that the current SOA scheme in CAM can still be used for radiative forcing calculation as the high biases exist both in pre-industrial and present conditions, but studies focusing on the instantaneous radiative effects would benefit from using the new SOA scheme. The new SOA scheme also has technical advantages including the use of identical SOA precursor emissions as CAM-chem from the online biogenic emissions, instead of pre-calculated emissions that may introduce differences. Future parameter updates on the CAM-chem SOA scheme can be easily translated to the new CAM SOA scheme as it is derived from the CAM-chem SOA scheme.

Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) is one of the longest-serving observation platforms which provides the cloud fraction data with higher spatial and vertical resolutions. Their simulators are also incorporated in the General Circulation Models (GCMs) under the Coupled Model Intercomparison Project Phase 5 (CMIP5). Here, we have examined the spatial and vertical cloud fraction (CF) distributions and corresponding biases (CFmodel−CFobservations; CF bias) from CALIPSO observations and their simulators for the period 2006–2015 over Indian land and oceanic regions for Indian summer monsoon season of June to September. It is reported that the CF biases over the whole Indian land and oceanic regions are largely negative (> 55%) except the northeastern land regions and southern Bay of Bengal (BOB) which show positive biases (~ 10–60%). Such CF biases are prominent and consistent in all CMIP5 models. The CF biases are further analyzed in the vertical dimension using contoured frequency by altitude diagrams (CFADs). The large CF biases exist at each vertical level especially at higher altitudes (> 12 km). CF biases over BOB based on spatial distributions give the false impression of better performance of simulators which are exhibited by the co-existence of both positive and negative biases at the same level, especially at higher altitude levels. As a result, both positive and negative CF biases cancel each other which lead to the minimum values of CF biases at respective altitude levels. This mutual ambiguity between spatial and vertical CF biases is found to be a permanent feature of the CALIPSO simulator.

The Greenland Ice Sheet (GrIS) is losing mass in an accelerated fashion, which is for ~60% dominated by an increase in surface melting. Clouds exhibit an important control on the GrIS surface energy balance and surface melt. Therefore, to better simulate present and future GrIS climate, it is essential to represent clouds correctly in climate models. Here we use ground (at Summit Station) and satellite remote sensing (from CloudSat‐CALIPSO) observations to evaluate GrIS cloud characteristics in several versions of the Community Atmosphere Model (CAM) over the period 2007–2012. Cloud cover, phase, water path, and radiative effects over the GrIS vary widely across the atmosphere models. Thanks to the inclusion of new cloud physical parameterizations, that is, ice nucleation and prognostic precipitation, in the most recent CAM version (CAM6), this model, amongst the various CAM versions, is best able to represent GrIS clouds, summer temperatures, and surface melting. However, CAM6 shows excessive rainfall over the ice sheet, which is an important outstanding model bias. Our study demonstrates the importance of simulating realistic cloud properties to improve climate model simulations of GrIS climate and climate change.

The impact of Asian dust on the determination of cloud phase is analyzed over dust sources and downwind using cloud phase products from cloud-aerosol lidar and infrared pathfinder satellite observations (CALIPSO), atmospheric infrared sounder (AIRS), moderate resolution imaging spectroradiometer (MODIS), and polarization and anisotropy of reflectances for atmospheric sciences coupled with observations from a lidar (PARASOL). The results show that the presence of dust greatly affects determination of cloud phase in both source and downwind regions. CALIPSO products demonstrate better ice cloud discrimination of about 70% and 60% over source and downwind regions, respectively, compared to passive sensors. These results suggest that semi-direct effects of dust, which act to warm clouds and evaporate large cloud particles, may play a role in cloud phase determination. This study suggests that the presence of dust tends to increase misclassification of ice clouds as water or uncertain phase by AIRS, MODIS, and PARASOL.

The Community Earth System Model version 2 (CESM2) includes three main atmospheric configurations: the Community Atmosphere Model version 6 (CAM6) with simplified chemistry and a simplified organic aerosol (OA) scheme, CAM6 with comprehensive tropospheric and stratospheric chemistry representation (CAM6‐chem), and the Whole Atmosphere Community Climate Model version 6 (WACCM6). Both, CAM6‐chem and WACCM6 include a more comprehensive secondary organic aerosols (SOA) approach using the Volatility Basis Set (VBS) scheme and prognostic stratospheric aerosols. This paper describes the different OA schemes available in the different atmospheric configurations of CESM2 and discusses differences in aerosol burden and resulting climate forcings. Derived OA burden and trends differ due to differences in OA formation using the different approaches. Regional differences in Aerosol Optical Depth with larger values using the comprehensive approach occur over SOA source regions. Stronger increasing SOA trends between 1960 and 2015 in WACCM6 compared to CAM6 are due to increasing biogenic emissions aligned with increasing surface temperatures. Using the comprehensive SOA approach further leads to improved comparisons to aircraft observations and SOA formation of ≈143 Tg/yr. We further use WACCM6 to identify source contributions of OA from biogenic, fossil fuel, and biomass burning emissions, to quantify SOA amounts and trends from these sources. Increasing SOA trends between 1960 and 2015 are the result of increasing biogenic emissions aligned with increasing surface temperatures. Biogenic emissions are at least two thirds of the total SOA burden. In addition, SOA source contributions from fossil fuel emissions become more important, with largest values over Southeast Asia. The estimated total anthropogenic forcing of OA in WACCM6 for 1995–2010 conditions is −0.43 W/m2, mostly from the aerosol direct effect.

Abstract. Aerosols affect cirrus formation and evolution, yet quantification of these effects remain difficult based on in situ observations due to the complexity of nucleation mechanisms and large variabilities in ice microphysical properties. This work employed a method to distinguish five evolution phases of cirrus clouds based on in situ aircraft-based observations from seven U.S. National Science Foundation (NSF) and five NASA flight campaigns. Both homogeneous and heterogeneous nucleation were captured in the 1 Hz aircraft observations, inferred from the distributions of relative humidity in the nucleation phase. Using linear regressions to quantify the correlations between cirrus microphysical properties and aerosol number concentrations, we found that ice water content (IWC) and ice crystal number concentration (Ni) show strong positive correlations with larger aerosols (&gt;500 nm) in the nucleation phase, indicating strong contributions of heterogeneous nucleation when ice crystals first start to nucleate. For the later growth phase, IWC and Ni show similar positive correlations with larger and smaller (i.e., &gt;100 nm) aerosols, possibly due to fewer remaining ice-nucleating particles in the later growth phase that allows more homogeneous nucleation to occur. Both 200 m and 100 km observations were compared with the nudged simulations from the National Center for Atmospheric Research (NCAR) Community Atmosphere Model version 6 (CAM6). Simulated aerosol indirect effects are weaker than the observations for both larger and smaller aerosols for in situ cirrus, while the simulated aerosol indirect effects are closer to observations in convective cirrus. The results also indicate that simulations overestimate homogeneous freezing, underestimate heterogeneous nucleation and underestimate the continuous formation and growth of ice crystals as cirrus clouds evolve. Observations show positive correlations of IWC, Ni and ice crystal mean diameter (Di) with respect to Na in both the Northern and Southern Hemisphere (NH and SH), while the simulations show negative correlations in the SH. The observations also show higher increases of IWC and Ni in the SH under the same increase of Na than those shown in the NH, indicating higher sensitivity of cirrus microphysical properties to increases of Na in the SH than the NH. The simulations underestimate IWC by a factor of 3–30 in the early/later growth phase, indicating that the low bias of simulated IWC was due to insufficient continuous ice particle formation and growth. Such a hypothesis is consistent with the model biases of lower frequencies of ice supersaturation and lower vertical velocity standard deviation in the early/later growth phases. Overall, these findings show that aircraft observations can capture both heterogeneous and homogeneous nucleation, and their contributions vary as cirrus clouds evolve. Future model development is also recommended to evaluate and improve the representation of water vapor and vertical velocity on the sub-grid scale to resolve the insufficient ice particle formation and growth after the initial nucleation event.

Abstract. Carbonaceous aerosols significantly affect global radiative forcing and climate through absorption and the scattering of sunlight. Black carbon (BC) and brown carbon (BrC) are light-absorbing carbonaceous aerosols. The direct radiative effect (DRE) of BrC is uncertain. A recent study suggests that BrC absorption is comparable to BC in the upper troposphere over biomass burning regions and that the resulting radiative heating tends to stabilize the atmosphere. Yet current climate models do not include proper physical and chemical treatments of BrC. In this study, we derived a BrC global biomass burning emission inventory on the basis of the Global Fire Emissions Database version 4 (GFED4), developed a module to simulate the light absorption of BrC in the Community Atmosphere Model version 5 (CAM5) of the Community Earth System Model (CESM), and investigated the photobleaching effect and convective transport of BrC on the basis of Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and Deep Convective Clouds and Chemistry Project (DC3) measurements. The model simulations of BC were also evaluated using HIAPER (High-Performance Instrumented Airborne Platform for Environmental Research) Pole-to-Pole Observations (HIPPO) measurements. We found that globally BrC is a significant absorber, the DRE of which is 0.10 W m−2, more than 25 % of BC DRE (+0.39 W m−2). Most significantly, model results indicated that BrC atmospheric heating in the tropical mid and upper troposphere is larger than that of BC. The source of tropical BrC is mainly from wildfires, which are more prevalent in the tropical regions than higher latitudes and release much more BrC relative to BC than industrial sources. While BC atmospheric heating is skewed towards the northern mid-latitude lower atmosphere, BrC heating is more centered in the tropical free troposphere. A possible mechanism for the enhanced convective transport of BrC is that hydrophobic high molecular weight BrC becomes a larger fraction of the BrC and less easily activated in a cloud as the aerosol ages. The contribution of BrC heating to the Hadley circulation and latitudinal expansion of the tropics is likely comparable to BC heating.

The Southern Ocean radiative bias continues to impact climate and weather models, including the Australian Community Climate and Earth System Simulator (ACCESS). The radiative bias, characterised by too much shortwave radiation reaching the surface, is attributed to the incorrect simulation of cloud frequency and phase. In this work, we use k-means cloud clustering, combined with nudged simulations of the latest generation ACCESS atmosphere model, to evaluate cloud and radiation biases when cloud types are correctly and incorrectly simulated. We find that even if the ACCESS model correctly simulates the cloud type, biases of equivalent, or in some cases greater, magnitude then when they are incorrectly simulated remain in the cloud and radiation fields examined. Furthermore, we find that even when radiative biases appear small on average, cloud property biases, such as liquid or ice water paths or cloud fractions remain large. Our results suggest that simply getting the right cloud type (or the cloud macrophysics) is not enough to reduce the Southern Ocean radiative bias. Furthermore, in instances where the radiative bias is small, it may be so for the wrong reasons. Considerable effort is still required to improve cloud microphysics, with a particular focus on cloud phase.

The Southern Ocean radiative bias continues to impact climate and weather models, including the Australian Community Climate and Earth System Simulator (ACCESS). The radiative bias, characterised by too much shortwave radiation reaching the surface, is attributed to the incorrect simulation of cloud frequency and phase. In this work, we use k-means cloud clustering, combined with nudged simulations of the latest generation ACCESS atmosphere model, to evaluate cloud and radiation biases when cloud types are correctly and incorrectly simulated. We find that even if the ACCESS model correctly simulates the cloud type, biases of equivalent, or in some cases greater, magnitude then when they are incorrectly simulated remain in the cloud and radiation fields examined. Furthermore, we find that even when radiative biases appear small on average, cloud property biases, such as liquid or ice water paths or cloud fractions remain large. Our results suggest that simply getting the right cloud type (or the cloud macrophysics) is not enough to reduce the Southern Ocean radiative bias. Furthermore, in instances where the radiative bias is small, it may be so for the wrong reasons. Considerable effort is still required to improve cloud microphysics, with a particular focus on cloud phase.