Skip to main navigation Skip to search Skip to main content

Cirrus cloud ice water content radar algorithm evaluation using an explicit cloud microphysical model

  • Kenneth Sassen
  • , Zhien Wang
  • , Vitaly I. Khvorostyanov
  • , Graeme L. Stephens
  • , Angela Bennedetti
  • University of Alaska Fairbanks

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

A series of cirrus cloud simulations performed using a model with explicit cloud microphysics applied to testing ice water content retrieval algorithms based on millimeter-wave radar reflectivity measurements. The simulated ice particle size spectra over a 12-h growth/dissipation life cycle are converted to equivalent radar reflectivity factors Ze and visible optical extinction coefficients σ, which are used as a test dataset to intercompare the results of various algorithms. This approach shows that radar Ze-only approaches suffer from significant problems related to basic temperature-dependent cirrus cloud processes, although most algorithms work well under limited conditions (presumably similar to those of the empirical datasets from which each was derived). However, when lidar or radiometric measurements of σ or cloud optical depth are used to constrain the radar data, excellent agreement with the modeled contents can be achieved under the conditions simulated. Implications for the satellite-based active remote sensing of cirrus clouds are discussed. In addition to showing the utility of sophisticated cloud-resolving models for testing remote sensing algorithms, the results of the simulations for cloud-top temperatures of -50°, -60°, and -70°C illustrate some fundamental properties of cirrus clouds that are regulated by the adiabatic process.

Original languageEnglish
Pages (from-to)620-628
Number of pages9
JournalJournal of Applied Meteorology
Volume41
Issue number6
DOIs
StatePublished - 2002

Fingerprint

Dive into the research topics of 'Cirrus cloud ice water content radar algorithm evaluation using an explicit cloud microphysical model'. Together they form a unique fingerprint.

Cite this