Climatology of Warm Boundary Layer Clouds at the ARM SGP Site and Their Comparison to Models

Abstract

Abstract A 4-yr climatology (1997–2000) of warm boundary layer cloud properties is developed for the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) site. Parameters in the climatology include cloud liquid water path, cloud-base height, and surface solar flux. These parameters are retrieved from measurements produced by a dual-channel microwave radiometer, a millimeter-wave cloud radar, a micropulse lidar, a Belfort ceilometer, shortwave radiometers, and atmospheric temperature profiles amalgamated from multiple sources, including radiosondes. While no significant interannual differences are observed in the datasets, there are diurnal variations with nighttime liquid water paths consistently higher than daytime values. The summer months of June, July, and August have the lowest liquid water paths and the highest cloud-base heights. Model outputs of cloud liquid water paths from the European Centre for Medium-Range Weather Forecasts (ECMWF) model and the Eta Model for 104 model output location time series (MOLTS) stations in the environs of the SGP central facility are compared to observations. The ECMWF and MOLTS median liquid water paths are greater than 3 times the observed values. The MOLTS data show lower liquid water paths in summer, which is consistent with observations, while the ECMWF data exhibit the opposite tendency. A parameterization of normalized cloud forcing that requires only cloud liquid water path and solar zenith angle is developed from the observations. The parameterization, which has a correlation coefficient of 0.81 with the observations, provides estimates of surface solar flux that are comparable to values obtained from explicit radiative transfer calculations based on plane-parallel theory. This parameterization is used to estimate the impact on the surface solar flux of differences in the liquid water paths between models and observations. Overall, there is a low bias of 50% in modeled normalized cloud forcing resulting from the excess liquid water paths in the two models. Splitting the liquid water path into two components, cloud thickness and liquid water content, shows that the higher liquid water paths in the model outputs are primarily a result of higher liquid water contents, although cloud thickness may a play a role, especially for the ECMWF model results.