Feasibility of Retrieving Cloud Condensation Nucleus Properties from Doppler Cloud Radar, Microwave Radiometer, and Lidar

G. Feingold Cooperative Institute for Research in the Atmosphere, NOAA/Environmental Technology Laboratory, Boulder, Colorado

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S. Yang Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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R. M. Hardesty NOAA/Environmental Technology Laboratory, Boulder, Colorado

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W. R. Cotton Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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Abstract

This paper explores the possibilities of using Ka-band Doppler radar, microwave radiometer, and lidar as a means of retrieving cloud condensation nucleus (CCN) properties in the stratocumulus-capped marine boundary layer. The retrieval is based on the intimate relationship between the cloud drop number concentration, the vertical air motion at cloud base, and the CCN activation spectrum parameters. The CCN properties that are sought are the C and k parameters in the N = CSk relationship, although activation spectra based on the lognormal distribution of particles is also straightforward. Cloud droplet concentration at cloud base is retrieved from a Doppler cloud radar combined with a microwave radiometer following a previously published technique. Cloud base is determined from a lidar or ceilometer. Vertical velocity just above cloud base is determined from the vertically pointing Doppler cloud radar. By combining the simultaneous retrievals of drop number and vertical velocity, and assuming theoretical relationships between these parameters and the subcloud aerosol parameters, the C parameter can be derived, under the assumption of a fixed k. If a calibrated backscatter lidar measurement is available, retrieval of both C and k parameters is possible. The retrieval is demonstrated for a dataset acquired during the Atlantic Stratocumulus Transition Experiment using a least squares minimization technique. Sensitivity to assumptions used in the retrieval is investigated. It is suggested that this technique may afford the acquisition of long-term datasets for climate monitoring purposes. Further investigation with focused experiments designed to address the issue more rigorously is required.

Corresponding author address: Graham Feingold, NOAA/CIRA, 325 Broadway, Boulder, CO 80303.

Email: gfeingold@etl.noaa.gov

Abstract

This paper explores the possibilities of using Ka-band Doppler radar, microwave radiometer, and lidar as a means of retrieving cloud condensation nucleus (CCN) properties in the stratocumulus-capped marine boundary layer. The retrieval is based on the intimate relationship between the cloud drop number concentration, the vertical air motion at cloud base, and the CCN activation spectrum parameters. The CCN properties that are sought are the C and k parameters in the N = CSk relationship, although activation spectra based on the lognormal distribution of particles is also straightforward. Cloud droplet concentration at cloud base is retrieved from a Doppler cloud radar combined with a microwave radiometer following a previously published technique. Cloud base is determined from a lidar or ceilometer. Vertical velocity just above cloud base is determined from the vertically pointing Doppler cloud radar. By combining the simultaneous retrievals of drop number and vertical velocity, and assuming theoretical relationships between these parameters and the subcloud aerosol parameters, the C parameter can be derived, under the assumption of a fixed k. If a calibrated backscatter lidar measurement is available, retrieval of both C and k parameters is possible. The retrieval is demonstrated for a dataset acquired during the Atlantic Stratocumulus Transition Experiment using a least squares minimization technique. Sensitivity to assumptions used in the retrieval is investigated. It is suggested that this technique may afford the acquisition of long-term datasets for climate monitoring purposes. Further investigation with focused experiments designed to address the issue more rigorously is required.

Corresponding author address: Graham Feingold, NOAA/CIRA, 325 Broadway, Boulder, CO 80303.

Email: gfeingold@etl.noaa.gov

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