Improving Modeled Cloud Properties Using Southern Great Plain’s ARM Data


Regional models used for weather prediction have an ongoing need for testing and improvement, particularly for capturing cloud and radiation properties. In a recent study, DOE researchers from Brookhaven National Laboratory used data from the decade-long (1997 to 2008) DOE Atmospheric Radiation Measurement (ARM) surface-based continuous measurements over the Southern Great Plains (SGP) site to evaluate the ability of three major Numerical Weather Prediction models to simulate cloud radiative behaviors, cloud fraction, and cloud albedo. Like the observations, all the reanalyses show a strong annual cycle and relatively weak diurnal or interannual variations of the cloud properties. Further examination shows that the cloud properties are strongly related to near-surface relative humidity, and the model behaviors and biases relative to change in relative humidity, temperature, and other meteorological features were evaluated. A combined statistical analysis is presented and used to quantify the overall model performance in simulating the mean, standard deviation, and correlation with observations and a ranking of model performances in simulating different quantities. The study presents an evaluation tool applying ARM measurements to models that will be useful for ongoing and future model developments.


Wu, W., Y. Liu, and A. K. Betts. 2012. “Observationally Based Evaluation of NWP Reanalyses in Modeling Cloud Properties over the Southern Great Plains,” Journal of Geophysical Research 117, D12202. DOI: 10.1029/2011JD016971.