Sally A. McFarlane — U.S. Department of Energy
Jennifer M. Comstock — Pacific Northwest National Laboratory
Samson M Hagos — Pacific Northwest National Laboratory
Category
Cloud Properties
Description
Frequency distributions of radar reflectivity from the C-POL precipitation radar for convective systems that pass over Darwin. Distributions are calculated separately for pixels identified as convective (left), cold anvil (center), and warm anvil (right) based on satellite brightness temperatures.
Tropical convective clouds are important elements of the hydrological cycle and produce extensive cirrus anvils that strongly affect the tropical radiative energy balance. To improve simulations of the global water and energy cycles and accurately predict both precipitation and cloud radiative feedbacks, models need to realistically simulate the life cycle of tropical convection, including the formation and radiative properties of cirrus anvils. By combining remote sensing data sets from precipitation and cloud radars at the ARM Darwin site with geostationary satellite data, we can develop observational understanding of the lifetime of convective systems and the links between the properties of convective systems and their associated anvil clouds. The relationships between convection and anvil in model simulations can then be compared to those seen in the observations to identify areas for improvement in the model simulations.
We identify and track tropical convective systems in the Tropical Western Pacific using geostationary satellite observations. We present statistics of the tropical convective systems including size, age, and intensity and classify the life cycle stage of each system as developing, mature, or dissipating. For systems that cross over the ARM Darwin site, information on convective intensity and anvil properties are obtained from the C-POL precipitation radar and MMCR cloud radar, respectively, and are examined as a function of the system life cycle. We also present initial results from applying the convective identification and tracking algorithm to a tropical simulation from the Weather Research and Forecasting (WRF) model run to evaluate the convective life cycle in the model.
