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2003
Iacobellis, SF, McFarquhar GM, Mitchell DL, Somerville RCJ.  2003.  The sensitivity of radiative fluxes to parameterized cloud microphysics. Journal of Climate. 16:2979-2996.   10.1175/1520-0442(2003)016<2979:tsorft>2.0.co;2   AbstractWebsite

The sensitivity of modeled radiative fluxes to the specification of cloud microphysical parameterizations of effective radius and fallout are investigated using a single-column model and measurements from the Atmospheric Radiation Measurement (ARM) Program. The single-column model was run with data for the 3-month period of June - August 2000 at the ARM Southern Great Plains site forced with operational numerical weather prediction data. Several different packages of cloud microphysical parameterizations were used in the single-column model. The temporal evolution of modeled cloud amount as well as surface radiative fluxes from a control run compare well with ARM measurements. Mean ice particle fall speeds varied significantly with respect to the assumed ice particle habit. As particle fall speeds increased, the overall cloud fraction, cloud height, and grid-averaged ice water path decreased. The outgoing longwave radiation (OLR) differs by up to 4 W m(-2) over the range of fall speeds examined, while shortwave fluxes varied little as most of the changes in cloud properties occurred at times of minimal solar radiation. Model results indicate that surface and top-of-atmosphere radiative fluxes are sensitive to the scheme used to specify the ice particle effective radius. On the seasonal timescale this sensitivity is on the order of 4 W m(-2) and on the daily timescale can be as large as 32 W m(-2). A conclusive statement as to which microphysical scheme is performing best is not achievable until cloud microphysical measurements include an accurate representation of small ice particles. The modeled variance of the ice particle effective radius at any given height in the model is considerably smaller than that suggested by measurements. Model results indicate that this underestimation of the ice particle effective radius variance can alter the seasonal mean top-of-atmosphere radiative fluxes by up to 5 W m(-2) and the mean longwave cooling rate by up to 0.2degrees K day(-1) near the location of maximum cloud amount. These seemingly modest flux sensitivities may have important implications for numerical climate simulations. These numerical experiments and observational comparisons have provided valuable physical insight into ice cloud - radiation physics and also into the mechanisms through which contemporary cloud microphysical parameterizations interact with climate model radiation schemes. In particular, the results demonstrate the importance of the smaller ice particles and emphasize the critical role played by not only the average particle size and shape but also the width of the ice particle effective radius distribution about its mean. In fact, the results show that this variability in particle size can sometimes play a greater role in cloud - radiation interactions than the more obvious variations in cloud amount due to changes in ice particle fall speed.

2000
Ghan, S, Randall D, Xu KM, Cederwall R, Cripe D, Hack J, Iacobellis S, Klein S, Krueger S, Lohmann U, Pedretti J, Robock A, Rotstayn L, Somerville R, Stenchikov G, Sud Y, Walker G, Xie SC, Yio J, Zhang MH.  2000.  A comparison of single column model simulations of summertime midlatitude continental convection. Journal of Geophysical Research-Atmospheres. 105:2091-2124.   Doi 10.1029/1999jd900971   AbstractWebsite

Eleven different single-column models (SCMs) and one cloud ensemble model (CEM) are driven by boundary conditions observed at the Atmospheric Radiation Measurement (ARM) program southern Great Plains site for a 17 day period during the summer of 1995. Comparison of the model simulations reveals common signatures identifiable as products of errors in the boundary conditions. Intermodel differences in the simulated temperature, humidity, cloud, precipitation, and radiative fluxes reflect differences in model resolution or physical parameterizations, although sensitive dependence on initial conditions can also contribute to intermodel differences. All models perform well at times but poorly at others. Although none of the SCM simulations stands out as superior to the others, the simulation by the CEM is in several respects in better agreement with the observations than the simulations by the SCMs. Nudging of the simulated temperature and humidity toward observations generally improves the simulated cloud and radiation fields as well as the simulated temperature and humidity but degrades the precipitation simulation for models with large temperature and humidity biases without nudging. Although some of the intermodel differences have not been explained, others have been identified as model problems that can be or have been corrected as a result of the comparison.

1999
Somerville, RCJ, Iacobellis SF.  1999.  Single-column models, ARM observations, and GCM cloud-radiation schemes. Physics and Chemistry of the Earth Part B-Hydrology Oceans and Atmosphere. 24:733-740.   10.1016/s1464-1909(99)00074-x   AbstractWebsite

Among the most serious sources of uncertainty in current general circulation models (GCMs) is the treatment of clouds and cloud-radiation interactions. We have used a single-column model (SCM) diagnostically to evaluate parameterizations against observations from the Atmospheric Radiation Measurement (ARM) Program. We find that schemes with explicit cloud water budgets and interactive radiative properties are potentially capable of matching observational data closely. In our SCM, using an interactive cloud droplet radius decreases the cloud optical thickness and cloud infrared emittance of high clouds, which acts to increase the downwelling surface shortwave flux and the outgoing longwave radiation. However, it is difficult to evaluate the realism of the vertical distribution of model-produced cloud extinction, cloud emittance, cloud liquid water content and effective cloud droplet radius until high-quality observations of these quantities become more widely available. We also find that in the SCM, cloud parameterizations often underestimate the observed cloud amount, and that ARM observations indicate the presence of clouds while the corresponding maximum relative humidity is less than 80%. This implies that the underlying concept of a critical gridpoint relative humidity of about 80% for cloud formation, as used in many GCM cloud parameterizations, may need to be reexamined. (C) 1999 Elsevier Science Ltd. All rights reserved.