On Thin Ice: Retrieval Algorithms for Ice Clouds Examined for Improvements

Comstock, J. M., Pacific Northwest National Laboratory

Cloud Distributions/Characterizations

Cloud Properties

An Intercomparison of Microphysical Retrieval Algorithms for Upper Tropospheric Ice Clouds. Jennifer M. Comstock, Robert d'Entremont, Daniel DeSlover, Gerald G. Mace, Sergey Y. Matrosov, Sally A. McFarlane, Patrick Minnis, David Mitchell,Kenneth Sassen, Matthew D. Shupe, David D. Turner, and Zhien Wang. Accepted by the Bulletin of the American Meteorological Society (in press, February 2007).


Radar reflectivity and lidar backscatter of cirrus clouds observed on 9 March 2000 at the ARM Southern Great Plains Climate Research Facility. These measurements demonstrate the optical depth range of cirrus clouds, which creates a unique challenge to retrieving their microphysical properties.


Comparison of ground-based retrievals of ice water path (IWP) and visible optical depth (t) obtained on 9 March 2000 with satellite (VISST) and aircraft based measurements. The blue shading and red line indicate the range and average, respectively, of the cloud properties retrieved by the various ground-based algorithms. The largest discrepancies are apparent when t<0.3.


Radar reflectivity and lidar backscatter of cirrus clouds observed on 9 March 2000 at the ARM Southern Great Plains Climate Research Facility. These measurements demonstrate the optical depth range of cirrus clouds, which creates a unique challenge to retrieving their microphysical properties.

Comparison of ground-based retrievals of ice water path (IWP) and visible optical depth (t) obtained on 9 March 2000 with satellite (VISST) and aircraft based measurements. The blue shading and red line indicate the range and average, respectively, of the cloud properties retrieved by the various ground-based algorithms. The largest discrepancies are apparent when t<0.3.

One of the key uncertainties in climate model simulations is the feedback of upper-tropospheric ice clouds on the Earth's radiation budget. An important aspect of understanding the radiative feedbacks of these clouds is the characterization of their microphysical properties. The microphysical properties of cirrus clouds—which reside in the upper troposphere and are primarily composed of hexagonal-shaped ice crystals—are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. However, these clouds are important modulators of the Earth’s radiation budget and climate because they reflect less incoming solar radiation and absorb more infrared radiation than water clouds, in essence enhancing the "greenhouse effect." Members of the ARM Cloud Properties Working Group who specialize in ice cloud properties are conducting an ongoing intercomparison of retrieval algorithms for upper tropospheric ice clouds. Their most recent efforts are summarized in the February 2007 issue of the Bulletin of the American Meteorological Society.

A number of passive and active remote sensing retrieval algorithms exist for estimating the microphysical properties of upper tropospheric clouds. By examining the ice water path and optical depth derived from each algorithm, the researchers found that optically thin clouds (optical depth < 0.3) are often below the detection level of most remote sensors, yet may contribute significantly to radiative heating in the upper troposphere, particularly in tropical regions where cirrus clouds persist at extremely cold temperatures. Additional challenges facing the improvement of these algorithms lie in the characterization of the ice crystal size distribution and particle shape.

Though significant progress has been made in the evolution of these algorithms in the last decade, the addition of satellite based lidar and radar capabilities enforce the need to understand the uncertainties and assumptions that underlie the algorithms that will be used to characterize the global distribution of clouds.