Integrated database of cloud microphysical properties derived from in situ observations obtained during M-PACE, TWP-ICE, ISDAC, and RACORO
Poster PDF
Authors
Michael R. Poellot — University of North Dakota
Greg McFarquhar — University of Oklahoma
Haflidi H. Jonsson — Naval Postgraduate School - CIRPAS
Gong Zhang — University of Illinois, Urbana
J. Walter Strapp — Environment Canada
Matt Freer — University of Illinois, Urbana
Alexei Korolev — Environment Canada
Hee Jung Yang — University of Illinois, Urbana
Kenny Bae — University of Illinois, Urbana
Robert Jackson — Argonne National Laboratory
Description
Comprehensive databases of cloud microphysical properties are required for evaluation of model simulations and remote sensing retrievals, for process-oriented studies of how aerosols impact clouds, and for studies of fundamental cloud-radiation interactions. In this study, the development of such databases for arctic boundary-layer clouds, arctic and tropical cirrus, and low-level mid-latitude boundary layer clouds is described using in situ data collected during the Mixed-Phase Arctic Cloud Experiment (M-PACE), the Tropical Warm Pool-International Cloud Experiment (TWP-ICE), the Indirect and Semi-Direct Aerosol Campaign (ISDAC), and the Routine AAF Clouds with Low Optical Water Depths Optical Radiative Observations (RACORO). Distributions of microphysical quantities (i.e., total number concentration of water drops and ice crystals, effective radii of water drops and ice crystals, ice and liquid water contents, ice and liquid extinctions, size distributions and representations of size distributions as modified gamma functions, mean diameters and median mass diameters of ice and liquid clouds, equivalent reflectivity, habit distributions) are calculated using data from both size-resolved and bulk cloud probes. Consistency tests and closure tests, whereby mass and extinction computed from size-resolved measurements are compared against comparable values measured by bulk probes, are used to determine the optimum combinations of probes for determining the microphysical parameters. Uncertainties in the derived parameters are estimated from the variability of the probe data, paying particular attention to the possibility of artificial amplification of small crystal concentrations from the shattering of large ice crystals on probe inlets and shrouds. Parameters such as the mean fall velocities and single-scattering parameters are derived from the database. Applications to cloud modeling and remote sensing studies are discussed.
