The University of Washington Shallow Convection and Moist Turbulence Schemes and Their Impact on Climate Simulations with the Community Atmosphere Model

Park, Sungsu; Bretherton, Christopher S.

doi:10.1175/2008jcli2557.1

Cited by 530 publications

(485 citation statements)

References 32 publications

(23 reference statements)

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“…The CAM5 physics suite consists of shallow convection (Park and Bretherton, 2009), deep convection (Zhang and McFarlane, 1995;Richter and Rasch, 2008), cloud microphysics (Morrison and Gettelman, 2008) and macrophysics (Park et al, 2014), radiation (Iacono et al, 2008), and aerosols . For aerosols, a modal aerosol module (MAM) is adopted to represent the internal and external mixing of aerosol components such as BC, OC, sulfate, ammonium, sea salt, and mineral dust .…”

Section: Model and Experimental Designmentioning

confidence: 99%

Impacts of absorbing aerosol deposition on snowpack and hydrologic cycle in the Rocky Mountain region based on variable-resolution CESM (VR-CESM) simulations

Liu

Lin

et al. 2018

Atmos. Chem. Phys.

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Abstract. The deposition of light-absorbing aerosols (LAAs), such as black carbon (BC) and dust, onto snow cover has been suggested to reduce the snow albedo and modulate the snowpack and consequent hydrologic cycle. In this study we use the variable-resolution Community Earth System Model (VR-CESM) with a regionally refined highresolution (0.125 • ) grid to quantify the impacts of LAAs in snow in the Rocky Mountain region during the period 1981-2005. We first evaluate the model simulation of LAA concentrations both near the surface and in snow and then investigate the snowpack and runoff changes induced by LAAs in snow. The model simulates similar magnitudes of near-surface atmospheric dust concentrations as observations in the Rocky Mountain region. Although the model underestimates near-surface atmospheric BC concentrations, the model overestimates BC-in-snow concentrations by 35 % on average. The regional mean surface radiative effect (SRE) due to LAAs in snow reaches up to 0.6-1.7 W m −2 in spring, and dust contributes to about 21-42 % of total SRE. Due to positive snow albedo feedbacks induced by the LAA SRE, snow water equivalent is reduced by 2-50 mm and snow cover fraction by 5-20 % in the two regions around the mountains (eastern Snake River Plain and southwestern Wyoming), corresponding to an increase in surface air temperature by 0.9-1.1 • C. During the snow melting period, LAAs accelerate the hydrologic cycle with monthly runoff increases of 0.15-1.00 mm day −1 in April-May and reductions of 0.04-0.18 mm day −1 in June-July in the mountainous regions. Of all the mountainous regions, the Southern Rockies experience the largest reduction of total runoff by 15 % during the later stage of snowmelt (i.e., June and July). Compared to previous studies based on field observations, our estimation of dust-induced SRE is generally 1 order of magnitude smaller in the Southern Rockies, which is ascribed to the omission of larger dust particles (with the diameter > 10 µm) in the model. This calls for the inclusion of larger dust particles in the model to reduce the discrepancies. Overall these results highlight the potentially important role of LAA interactions with snowpack and the subsequent impacts on the hydrologic cycles across the Rocky Mountains.

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Section: Model and Experimental Designmentioning

confidence: 99%

Impacts of absorbing aerosol deposition on snowpack and hydrologic cycle in the Rocky Mountain region based on variable-resolution CESM (VR-CESM) simulations

Liu

Lin

et al. 2018

Atmos. Chem. Phys.

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“…[46] With regard to parameterizations, the improved boundary layer turbulence and shallow convection parameterizations in the Hadley Centre and Community Atmosphere models [Lock et al, 2000;Bretherton and Park, 2009;Park and Bretherton, 2009] are critical for the improved simulations in marine stratocumulus clouds. However, an improved simulation would not have been realized without also increasing the vertical resolution and, in the case of the Hadley Centre, incorporating a new semi-Lagrangian dynamical core [Martin et al, 2006].…”

Section: Why Are Simulations Of Clouds Improving and What Impacts MImentioning

confidence: 99%

Are climate model simulations of clouds improving? An evaluation using the ISCCP simulator

et al. 2013

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[1] The annual cycle climatology of cloud amount, cloud-top pressure, and optical thickness in two generations of climate models is compared to satellite observations to identify changes over time in the fidelity of simulated clouds. In more recent models, there is widespread reduction of a bias associated with too many highly reflective clouds, with the best models having eliminated this bias. With increased amounts of clouds with lesser reflectivity, the compensating errors that permit models to simulate the time-mean radiation balance have been reduced. Errors in cloud amount as a function of height or climate regime on average show little or no improvement, although greater improvement can be found in individual models. Measuring Changes in the Simulations of Global Cloudiness Over Time[2] The simulation of clouds by climate models is a key ongoing challenge in the numerical representation of Earth's climate. Due to their large impact on Earth's radiation budget, clouds are important for determining aspects of current climate, such as surface air temperatures in many regions [Ma et al., 1996;Curry et al., 1996], the strength and variability of atmospheric circulations [Slingo and Slingo, 1988], and the magnitude of climate changes that result from perturbations in the chemical composition of the atmosphere [IPCC, 2007]. While important, the modeling of clouds is very difficult because most cloud processes happen at scales far smaller than can be resolved by climate models, and thus, their bulk effects must be represented with imperfect parameterizations.[3] Given the efforts of many scientists over several decades to understand cloud processes and improve their representation in models, it is important to ask are climate model simulations of clouds improving and, if so, by how much? Here, we analyze the ability of two generations of climate models to simulate the climatological distribution of clouds and judge fidelity by comparison to several decades of satellite observations. Because of the significant differences between the ways clouds are observed and the ways they are represented in models, we use a "satellite simulator" to increase the chances that differences between the models and observations represent actual model deficiencies. We find that significant progress in the ability of models to simulate clouds has occurred over the last decade, particularly in reducing the over-prediction of highly reflective clouds [Zhang et al., 2005].

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“…The first, "singular (or deterministic) hypothesis", proposed by Langham and Mason (1958), assumes that the radius of the ice germ forming on the aerosol surface at a given supercooling is controlled by surface features and that thermal fluctuations have a negligible influence on the ice germ radius. Thus, the freezing of a droplet is only determined by whether the temperature is below the characteristic temperature of the immersed IN in the droplet (Phillips et al, 2008(Phillips et al, , 2012DeMott et al, 2010;Niemand et al, 2012). The second hypothesis, the "stochastic hypothesis" proposed by Bigg (1953), holds that heterogeneous ice nucleation is a function of time.…”

Section: Y Wang Et Al: Different Contact Angle Distributionsmentioning

confidence: 99%

Different contact angle distributions for heterogeneous ice nucleation in the Community Atmospheric Model version 5

et al. 2014

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Abstract. In order to investigate the impact of different treatments for the contact angle (α) in heterogeneous ice nucleating properties of natural dust and black carbon (BC) particles, we implement the classical-nucleation-theory-based parameterization of heterogeneous ice nucleation (Hoose et al., 2010) in the Community Atmospheric Model version 5 (CAM5) and then improve it by replacing the original singlecontact-angle model with the probability-density-functionof-α (α-PDF) model to better represent the ice nucleation behavior of natural dust found in observations. We refit the classical nucleation theory (CNT) to constrain the uncertain parameters (i.e., onset α and activation energy in the single-α model; mean contact angle and standard deviation in the α-PDF model) using recent observation data sets for Saharan natural dust and BC (soot). We investigate the impact of the time dependence of droplet freezing on mixed-phase clouds and climate in CAM5 as well as the roles of natural dust and soot in different nucleation mechanisms. Our results show that, when compared with observations, the potential ice nuclei (IN) calculated by the α-PDF model show better agreement than those calculated by the single-α model at warm temperatures (T ; T > −20 • C). More ice crystals can form at low altitudes (with warm temperatures) simulated by the α-PDF model than compared to the single-α model in CAM5. All of these can be attributed to different ice nucleation efficiencies among aerosol particles, with some particles having smaller contact angles (higher efficiencies) in the α-PDF model. In the sensitivity tests with the α-PDF model, we find that the change in mean contact angle has a larger impact on the active fraction at a given temperature than a change in standard deviation, even though the change in standard deviation can lead to a change in freezing behavior. Both the single-α and the α-PDF model indicate that the immersion freezing of natural dust plays a more important role in the heterogeneous nucleation than that of soot in mixed-phase clouds. The new parameterizations implemented in CAM5 induce more significant aerosol indirect effects than the default parameterization.

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The University of Washington Shallow Convection and Moist Turbulence Schemes and Their Impact on Climate Simulations with the Community Atmosphere Model

Cited by 530 publications

References 32 publications

Impacts of absorbing aerosol deposition on snowpack and hydrologic cycle in the Rocky Mountain region based on variable-resolution CESM (VR-CESM) simulations

Impacts of absorbing aerosol deposition on snowpack and hydrologic cycle in the Rocky Mountain region based on variable-resolution CESM (VR-CESM) simulations

Are climate model simulations of clouds improving? An evaluation using the ISCCP simulator

Different contact angle distributions for heterogeneous ice nucleation in the Community Atmospheric Model version 5

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