Showing papers by "Kenneth Sassen published in 1999"

Continental Stratus Clouds: A Case Study Using Coordinated Remote Sensing and Aircraft Measurements

Abstract: A continental stratus cloud layer was studied by advanced ground-based remote sensing instruments and aircraft probes on 30 April 1994 from the Cloud and Radiation Testbed site in north-central Oklahoma. The boundary layer structure clearly resembled that of a cloud-topped mixed layer, and the cloud content is shown to be near adiabatic up to the cloud-top entrainment zone. A cloud retrieval algorithm using the radar reflectivity and cloud droplet concentration (either measured in situ or deduced using dual-channel microwave radiometer data) is applied to construct uniquely high-resolution cross sections of liquid water content and mean droplet radius. The combined evidence indicates that the 350–600 m deep, slightly supercooled (2.0° to −2.0°C) cloud, which failed to produce any detectable ice or drizzle particles, contained an average droplet concentration of 347 cm−3, and a maximum liquid water content of 0.8 g m−3 and mean droplet radius of 9 μm near cloud top. Lidar data indicate that the Ka...

Cirrus clouds and halos: A closer look

Abstract: What's the connection between cirrus clouds, halos, coronas, and arcs/circles? It appears to be more complex than previously thought, and may depend in large part on the geographic locations of the clouds.

The Need for a Universal Cloud Property Algorithm for Active Remote Sensors

Abstract: Lidar and radar measurements of cloud properties (e.g., cloud boundaries, phase, vertically resolved and integrated mass content, optical depth, etc.) are increasingly being relied on in modern climate-related research programs and are a keystone of the Atmospheric Radiation Measurement (ARM) Cloud and Radiation Testbed (CART) atmospheric measurement philosophy, to provide, relatively inexpensively, crucial cloud characterizations on a more or less routine continuous basis. As a result, a variety of data interpretation schemes and specific algorithms have been developed and are being applied to remote sensing data sets, but it must be recognized that a helter-skelter approach involves dangers as well as promise. It is clear that remote sensors can have vastly different operating characteristics and sensitivities to hydrometeors, so the derived data quantities in any particular case may be quite specific to the instrument and analysis method employed. This has the potential of misleading data users in the theoretical community. As our ice, water, and mixed-phase cloud algorithm developmental research continues, an important step we are currently taking is to provide to the community a “universal” cloud boundary (i.e., cloud base and top, along with cloud phase separation for precipitating clouds) algorithm. We briefly outline this algorithm here.