Microphysical Processes in Cloud-Resolving Models I
Presiding: W Tao, NASA Goddard Space Flight Center; C L Perez, International Research Institute, Columbia University
A51C-01 08:30h
Cirrus Cloud Microphysics - What is Important?
Cirrus clouds result from mesoscale and synoptic lifting and convective detrainment. In climate applications and extended range forecasting, it is important to simulate the evolving extent and properties of cirrus clouds associated directly with weather systems and with more benign environments. This talk will provide insights gained from very detailed microphysical modeling studies of cirrus (bin model). Specifically, approaches used to represent ice cloud properties in cloud system and global models will be discussed in light of the results from high-resolution bin model studies.
A51C-02 08:45h
Microphysics of Arctic Mixed Phase Clouds
Persistent mixed-phase stratiform clouds are ubiquitous in the Arctic. Cloud-scale and large-scale models have had difficulty in simulating the microphysics of these clouds in terms of their duration, phase, and precipitation. Data from SHEBA and from the ARM MPACE experiment have been used in the evaluation of and further development of a bin resolving stochastic kinetic microphysics model and a dual moment bulk microphysics scheme, both of which depend explicitly on aerosol characteristics. Essential features of these schemes that result in improved simulation of mixed phase clouds include prognostic supersaturation fluctuations, a new heterogeneous ice nucleation scheme that includes deliquescence freezing, and a new fall speed parameterization. These microphysics schemes have been incorporated into and evaluated in a single column model, cloud resolving model, and mesoscale model, and evaluated against SHEBA and MPACE observations.
A51C-03 09:00h
Simulations of the July 16 and 21 CRYSTAL-FACE Cirrus Cases Using a Cloud-Resolving Model With an Improved Sedimentation Parameterization
To understand what could influence the evolution and maintenance of subtropical anvil cirrus, we present results from a paired mesoscale-cloud scale numerical modeling system. The mesoscale model is used to simulate the development of convection over southern FL during the CRYSTAL-FACE study days and to provide a guide as to how the atmosphere responds to the convection. Data from the mesoscale model is used to provide initial conditions and mesoscale forcing terms for a LES simulation of detached anvil. The LES simulations use a sedimentation parameterization with improved particle fallspeed relationships and an algorithm that mimics bin microphysics. Results suggest that the amount of initial condensate present in the anvil simulation has a role in the maintenance and evolution of the cirrus layer comparable to the role played by the mesoscale forcing.
A51C-04 09:15h
Measurements and application of cloud condensation nuclei spectra
Simultaneous detailed airborne measurements of cloud condensation nuclei (CCN) spectra from the two Desert Research Institute (DRI) CCN spectrometers (Hudson 1989) are presented. In order to accurately measure the entire cloud supersaturation (S) range (i.e., 1.2-0.02%) these instruments were operated at different S ranges. Agreement between these instruments in the overlapping S range centered about 0.1% provided confidence in these difficult measurements. Extensive spatial and temporal measurements are presented from two projects: one continental, AIRS2 over the Great Lakes area, and one maritime, RICO over the Caribbean. Comparisons of nearby cloud droplet concentrations with these CCN spectra yield estimates of cloud S. Plots of droplet concentrations versus liquid water contents compared with estimates of adiabatic liquid water contents can yield estimates of measured adiabatic droplet concentrations (Hudson and Yum 2001, 2002). Alternatively these CCN spectra can also be used as input to an adiabatic model, which along with measured updraft velocity yields predictions of adiabatic cloud droplet concentrations (e.g., Yum et al. 1998). Comparisons of these predictions with measurements of cloud droplet concentrations can yield estimates of the degree of cloud adiabaticity-i.e., degree of out of cloud mixing. Comparisons with the adiabatic cloud droplet concentrations noted in the last paragraph can yield estimates of the condensation coefficient, which is also a fundamental input to the adiabatic model. This could be altered by anomalous aerosol. The effect of anthropogenic CCN on cloud radiative and precipitation properties is the largest climate uncertainty--the indirect aerosol effect. Hudson, J.G., 1989: An instantaneous CCN spectrometer. J. Atmos. & Ocean. Techn., 6, 1055-1065. Hudson, J.G., and S.S. Yum, 2001: Maritime-continental drizzle contrasts in small cumuli. J. Atmos. Sci., 58, 915-926. Hudson, J.G., and S.S. Yum, 2002: Cloud condensation nuclei spectra and polluted and clean clouds over the Indian Ocean. J. Geophys. Res., 107(D19), 8022, doi:10.1029/2001JD000829. Yum, S.S., J.G. Hudson, and Y. Xie, 1998: Comparisons of cloud microphysics with cloud condensation nuclei spectra over the summertime Southern Ocean. J. Geophys. Res., 103, 16,625-16,636.
A51C-05 09:30h
Interactions of Cloud Microphysics and Dynamics Simulated in a PRE-STORM Squall Line Case
The Goddard Cumulus Ensemble (GCE) Model is used to simulate the June 10-11, 1985 PRE-STORM squall line. The 2-D version of the GCE model initialized with a cool pool is integrated for 12 hours until the storm develops into a semi-steady state. It is found that, with all environmental conditions identical, the strength of the rain evaporation affects the steady state storm dynamics significantly. When the rain evaporation is weak, the negative vorticity generated by the surface cool pool nearly balances the positive vorticity of the ambient wind shear. The leading convective cell in this type of squall system is upright and tall. The air detrained from the leading convective cell loses most of its buoyancy. It brings the ice particles back to the stratiform region without developing any weak convective cells, producing uniform weak ascending and more homogeneous stratiform rain with a prominent bright band in the simulated radar reflectivity pattern. On the other hand, when the rain evaporation rate is strong, the cool pool is strong, too. The negative vorticity generated by the cool pool overpowers the ambient near surface positive vorticity. The resulted leading cell tilts downshear. The updraft in the leading cell is cut by the downdraft produced by rain evaporation. The remained buoyant air parcel continues to rise while moving into the stratiform region, forming weak convective cells in the stratiform region. The differences in evaporation strengths simulated in the GCE Model are produced by two self-consistent microphysical schemes, one is a bulk type, and the other is an explicit bin model. The assumption in the bulk scheme that the intercept of the raindrop size distribution is a fixed value results in stronger rain evaporations, especially in the downdraft cores. In a dry and unstable summer time mid-latitude environment, this produces significant differences in storm structure, rainfall pattern, and rain efficiencies. This study suggests that under certain circumstances, small differences in cloud microphysical processes may have comparable sensitivities as changing some of the environmental conditions. In addition to the rain evaporation, the terminal fall velocity of precipitable ice particles also plays an important role in shaping the stratiform rain in this squall line case. When the fall velocities of ice particles are reduced, significantly more stratiform rain is produced by the squall line. The wind and pressure patterns of the squall line changes accordingly, too.
A51C-06 09:45h
A Modeling study of the Ultragiant CCN Effect on Precipitation
In a recent study, Cheng et al. (2005) used the two-moment warm cloud parameterization of Chen and Liu (2004) to study the impacts of aerosol concentration on cloud radiative properties and precipitation. It is found that more aerosols increase the cloud condensate nucleus (CCNs), leading to an increase in cloud albedo and a decrease in precipitation. However, the study does not consider adequately the effects of giant (radius >5 mm) and ultragiant CCNs (radius >10 mm), which has been suggested to enhance precipitation because these giant CCNs can form larger condensate drops, producing rains more efficiently, especially in an environment with high aerosol concentration (Feingold et al., 1999). Here we conduct model simulations to study the effects of ultragiant CCNs by altering aerosol size spectrum to increase the amount of larger size CCNs which are directly activated as raindrops to collect and remove cloud drops when their radiuses are larger than 10 mm. Similar to Cheng et al. (2005), the model simulations were conducted for the case when a front passed through the northern Taiwan during May 16-17, 2003, triggering deep convection and precipitation. Reference Chen, J.-P., and S.-T. Liu, 2004: Physically based two-moment bulk water parameterization for Warm Cloud Microphysics. Quart. J. Roy. Meteor. Soc., 130, 51V78. Cheng, C.-T., W.-C. Wang, and J.-P. Chen, 2005: A Modeling Study of Aerosol Impacts on Cloud Radiative Properties and Precipitation. (submitted to Geophys. Res. Lett. February 2005) Feingold, G., W. R. Cotton, S. M. Kreidenweis, and J. T. Davis, 1999: The impact of giant cloud condensation nuclei on drizzle formation in stratocumulus: Implication for cloud radiative properties. J. Atmos. Sci., 56, 4100-4117.