Evaluation of Cirrus Properties Simulated by a Single-Column Model Using Cloud Radar Observations and Results from a Cloud-Resolving Model Simulation
Luo, Y.(a), Krueger, S.K.(a), Moorthi, S.(b), and Pan, H.-L.(b), University of Utah (a), EMC/NCEP/NOAA (b)
Twelfth Atmospheric Radiation Measurement (ARM) Science Team Meeting
Using cloud radar observations of cirrus cloud properties obtained at the ARM (Atmospheric Radiation Measurement program) SGP (Southern Great Plains) site and results from a CRM (cloud-resolving model) simulation, we are evaluating the cirrus properties simulated by a SCM (single-column model). The SCM is based on the NCEP (National Centers for Environmental Prediction) MRF (Medium Range Forecast) model, which includes cloud water/ice as a prognostic variable, and rain and snow as diagnostic variables. We used SCM and CRM simulations based on intensive observations made at the ARM SGP site for 29 days from 19 June to 17 July 1997. During this period, cirrus clouds, many generated by deep convection, were observed about 30 percent of the time by the cloud radar. To produce cirrus statistics from the SCM results that are comparable to the cloud radar observations, we used a method described by Klein and Jakob (1999) that uses the SCM cloud fraction profile and the SCM's overlap assumption (random or maximum/random) to create a synthetic cloud field. The SCM's cloud water/ice is assumed to be uniformly distributed in the cloud layer at each level. Synthetic snow and rain fields were similarly created. We then sampled the synthetic cloud and precipitation fields like a cloud radar would to determine the statistical properties of "cirrus" and "thin cirrus", as defined by Mace et al. (2001). We compared the SCM's cirrus cloud properties to those obtained by Mace et al. using the ARM SGP cloud radar. When determining the SCM cirrus and thin cirrus properties, we included both non-precipitating ice ("cloud ice") and precipitating ice ("snow"). This is necessary because the cloud radar detects both types of ice particles. Regardless of the cloud overlap assumption used, when compared to Mace et al.'s (2001) cirrus properties, our preliminary analysis indicates that the SCM's thin cirrus IWP, layer-mean IWC, and the layer-mean IWC as a function of layer-mean temperature are all too large. In addition, the SCM's layer-mean thin cirrus IWC decreases as cloud physical thickness increases, which is opposite to what was observed. We suspect that some of the apparently unrealistic aspects of the SCM's cirrus properties are due to the parameterized detrainment of cloud ice from deep convection, which is more intermittent and occurs in thinner layers than in the corresponding CRM simulation. Further investigation is underway; results will be reported at the meeting.
Note: This is the poster abstract presented at the meeting; an extended version was not provided by the author(s).
