Comparison of parameterized cloud variability to ARM data.

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Cloud parameterizations in large-scale models often try to predict the amount of sub-grid scale variability in cloud properties to address the significant non-linear effects of radiation and precipitation. Statistical cloud schemes provide an attractive framework to self-consistently predict the variability in radiation and microphysics but require accurate predictions of the width and asymmetry of the distribution of cloud properties. Data from the Atmospheric Radiation Measurement (ARM) program are used to assess the variability in boundary layer cloud properties for a well- mixed stratocumulus observed at the Oklahoma ARM site during the March 2000 Intensive Observing Period. Cloud boundaries, liquid water ... continued below

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Klein, Stephen A. & Norris, Joel R. June 23, 2003.

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Cloud parameterizations in large-scale models often try to predict the amount of sub-grid scale variability in cloud properties to address the significant non-linear effects of radiation and precipitation. Statistical cloud schemes provide an attractive framework to self-consistently predict the variability in radiation and microphysics but require accurate predictions of the width and asymmetry of the distribution of cloud properties. Data from the Atmospheric Radiation Measurement (ARM) program are used to assess the variability in boundary layer cloud properties for a well- mixed stratocumulus observed at the Oklahoma ARM site during the March 2000 Intensive Observing Period. Cloud boundaries, liquid water content, and liquid water path are retrieved from the millimeter wavelength cloud radar and the microwave radiometer. Balloon soundings, aircraft data, and satellite observations provide complementary views on the horizontal cloud inhomogeneity. It is shown that the width of the liquid water path probability distribution function is consistent with a model in which horizontal fluctuations in liquid water content are vertically coherent throughout the depth of the cloud. Variability in cloud base is overestimated by this model, however; perhaps because an additional assumption that the variance of total water is constant with altitude throughout the depth of the boundary layer is incorrect.

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OSTI as DE00821596

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  • In Proceedings of the Thirteenth Atmospheric Radiation Measurement Science Team Meeting, Conference location not supplied, Conference dates not supplied; Other Information: Proceedings were edited by D.A. Carrothers, Department of Energy, Richland, WA

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  • Report No.: DOE/ER/62934-3
  • Grant Number: AI02-00ER62934
  • Office of Scientific & Technical Information Report Number: 821596
  • Archival Resource Key: ark:/67531/metadc783590

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  • June 23, 2003

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  • Dec. 3, 2015, 9:30 a.m.

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  • Aug. 3, 2016, 8:20 p.m.

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Klein, Stephen A. & Norris, Joel R. Comparison of parameterized cloud variability to ARM data., article, June 23, 2003; United States. (digital.library.unt.edu/ark:/67531/metadc783590/: accessed August 23, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.