Microphysical Processes in Weather and Climate Models I
Presiding: B S Ferrier, NCEP Environmental Modeling Center and GSO/SAIC; W Tao, NASA Goddard Space Flight Center
A41F-01 08:30h
Understanding Cloud Processes in Midlatitude Storms
Clouds associated with extratropical baroclinic storms are often neglected in global climate models despite their importance for regional cloud feedback and climate changes in water availability. We discuss several issues associated with the simulation of these cloud systems in climate GCMs. In general, GCMs overestimate the occurrence of optically thick high clouds and underestimate midlevel cloud occurrence in such storms. For the GISS GCM we show that this bias is likely to be related to underestimates of the storm ageostrophic circulation and tilt of frontal surfaces, which also cause the model to underestimate the dynamical transport of water vapor and occurrence of midlatitude cirrus. GCMs make different assumptions about the conditions under which liquid vs. ice is created above the freezing level, usually making this a function of temperature alone. We use MODIS satellite data to argue that the temperature range of transition from liquid to ice varies systematically along the midlatitude storm tracks due to varying intensity and maturity of storms. There is also a hint in the satellite data of the transition from heterogeneous to homogeneous nucleation of ice at temperatures near 240 K. Both of these have implications for parameterizations of mixed phase processes in GCMs.
A41F-02 08:45h
Toward Quantitative Estimation of the Effect of Aerosol Particles in the Global Climate Model and Cloud Resolving Model
Identifying the effect of aerosols on the precipitation and optical properties of clouds is one of the keys to improving the climate model. Therefore it is desirable to install the cloud microphysical model which can estimate the effect of cloud condensation nuclei (CCN) on the cloud microstructure to the climate model or cloud model. To install the bin method cloud microphysical model to 3D non-hydrostatic model, we developed the parameterizations to predict the initial cloud droplet size distribution for bin method. These parameterizations were developed based on the numerous numerical experiments using the cloud microphysical model which can precisely estimate the effect of aerosol particles on the cloud microstructure of clouds. These parameterizations are useful not only for 3D non-hydrostatic cloud resolving model but also for the global model to estimate the effect of aerosol particles. As the first example of the application of these parameterizations, these parameterizations were installed to the global model CCSR/NIES/FRCGC-AGCM equipped with aerosol transportation model SPRINTARS (Takemura et al., 2000, 2002). Cooperating with Dr. Takemura, we calculated the annual mean value of the effective radius of cloud droplets at the top of clouds where the temperature is higher than 273 K in 2000. The calculation clearly demonstrates the land-ocean contrast of the effective radius, which is often shown in the global map of observational satellite data retrieved from AVHRR (Nakajima and Nakajima, 1995; Kawamoto, 2001). To estimate the effect of organic carbon aerosol particles on the effective radius of cloud droplets, another calculation was done in which organic carbon particles are neglected. The comparison of two results shows that the effect of organic carbon particles on the cloud microstructure is not negligible small at South Africa, Australia and South America continents. As the next step of the application of these parameterizations, these parameterizations and two-moment bin method are installed to 3D non-hydrostatic cloud model CReSS (Tsuboki and Sakakibara, 2002). Using this 3D non-hydrostatic cloud model equipped with two-moment bin method we will show the effect of CCN on the precipitation processes.
A41F-03 09:00h
A Microphysical Cloud Resolving LES Model That Integrates Robust Numerical, Experimental, and Observational Components to Predict Aerosol Effects on Climate
As part of an internal LANL project, three key components---numerics, experiments, and observations---needed to accurately model cloud-aerosol interactions at high spatial resolutions are currently being developed and integrated. Once validated, our cloud-aerosol model will be used to understand how aerosols modify mass, momentum, and energy budgets within the boundary-layer, thus providing critical information to develop parameterizations for both direct and indirect aerosol effects in coarser resolution global climate models. The numerical component involves solving the cloud-aerosol equation set via a nonlinear Newton-Krylov (NK) approach. This unique numerical approach is unlike most approaches used for cloud modeling in that it requires cloud parameterizations be smooth on the dynamical time scale of the problem. This ensures that the temporal error is small and bounded during a NK simulation. We stress that temporal errors in more traditional approaches can become so large that model interpretation becomes essentially meaningless. Another critical numerical component of our work is limiting evaporation at cloud boundaries, without which long-lived stratus clouds can spuriously disappear. Two new limiting approaches are being developed at LANL, a continuous probability distribution function-based approach commonly used in combustion modeling and a discrete approach based upon a stochastic particle model. Parameters in our aerosol microphysics model (e.g. what fraction of aerosol type (e. g. salt, sulfate, carbonaceous) are effective as a cloud condensation nuclei, and how effective are these at taking up water) are being tuned using laboratory experiments on water uptake on various aerosol types. Furthermore, we plan to utilize high resolution observations of temperature and water distributions in shallow cumulus clouds from DOE's Multispectral Thermal Imager (MTI) satellite over Oklahoma's ARM site to calibrate and validate our models, including 3D radiative transfer effects in the observations.
A41F-04 09:15h
Baiu frontal activity in the global warming climate simulated by a non-hydrostatic regional model with a horizontal grid of 5 km
The Baiu front in East Asia in the global warming climate as well as that in the present one, is studied using outputs of a global climate model with a horizontal grid size of 20km (GCM) and a non-hydrostatic regional model with a horizontal grid size of 5 km (NHM). The GCM was first run in both present and global warming climates for ten years. Then the NHM was run in June and July for ten years in a one-way nesting by using the GCM. To reduce the horizontal phase differences of propagating disturbances between two models, we adopted a spectral boundary coupling method, in which large- and small- scale modes are combined from the outputs of GCM and NHM, respectively. In the global warming climate, changes of the Baiu front are remarkable in July. The Baiu front is likely to stay over the southern Japan around the latitudes of 30 N - 32 N, and does not move northward. Thus, the activity of the Baiu front lasts longer, and the precipitation increases in the southern Japan. Meanwhile, the precipitation in the northern Japan and Korean Peninsula becomes weak. No end of the Baiu season is also often seen. The frequency of occurrence of heavy rainfall increases over the Japan Islands.
A41F-05 09:30h
Parameterization of the Autoconversion Process: Unification and Physics
A key process that must be parameterized in atmospheric models of various scales is the autoconversion process whereby large cloud droplets collect small ones and become embryonic raindrops. Accurate parameterization of this process is especially important for studies of the second indirect aerosol effect. In terms of the representation of the threshold behavior of the autoconversion process, existing parameterizations can be classified into either Kessler-type or Sundqvist-type. Kessler-type parameterizations have been developed to explicitly account for cloud droplet number concentration, relative dispersion, and liquid water content, whereas Sundqvist-type parameterizations consider only the liquid water content. In this work, we first put Sundqvist-type parameterizations on the same footing as Kessler-type parameterization by generalizing Sundqvist-type parameterizations to explicitly account for droplet number concentration, relative dispersion, as well as liquid water content. We then show that the more commonly used Kessler-type parameterizations are in fact a special case of the corresponding Sundqvist-type parameterizations, unifying the two types of parameterizations. A new parameterization is further derived theoretically, and is compared to Kessler-type and Sundqvist-type parameterizations.
A41F-06 09:45h
Simulating Tropical Precipitation Using the Weak Temperature Gradient Approximation
Tropical precipitation due to deep convection is typically forced in limited area models by specifying the large-scale vertical velocity or vertical advection terms. Since the dominant thermodynamic balance in the tropics is between adiabatic cooling and diabatic heating (or vice versa), and the latter is due mostly to precipitating convection, the standard approach determines the model precipitation rate almost independently of model physics. The model thus cannot be used to address the question: what causes deep convection to occur or not occur? We apply an alternate approach, based on the Weak Temperature Gradient (WTG) approximation, to a 2-D cloud resolving model, the Goddard Cumulus Ensemble Model (GCEM), to address this question. We first varied the sea surface temperature (SST) and examined the resulting statistically steady states simulated by the model, focusing on the total precipitation and rain rate. The precipitation and rain rate increase strongly and nonlinearly with SST in our simulations. Subsequent experiments with the GCEM in WTG mode were designed to study the effects of varying surface wind speed, vertical wind shear, horizontal moisture advection on precipitation. We will also present results of sensitivity tests of the model response to changes in the microphysics parameters.