• Baumgardner, D., 1983: An analysis and comparison of five water drop measuring instruments. J. Climate Appl. Meteor., 22 , 891910.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baumgardner, D., , and Spowart M. , 1990: Evaluation of the Forward Scattering Spectrometer Probe. Part III: Time response and laser inhomogeneity limitations. J. Atmos. Oceanic Technol., 7 , 6667672.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baumgardner, D., , Strapp W. , , and Dye J. E. , 1985: Evaluation of the Forward Scattering Spectrometer Probe. Part II: Corrections for coincidence and dead-time losses. J. Atmos. Oceanic Technol., 2 , 626632.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dong, X., , Ackerman T. P. , , Clothiaux E. E. , , Pilewskie P. , , and Han Y. , 1997: Microphysical and radiative properties of boundary layer stratiform clouds deduced from ground-based measurements. J. Geophys. Res., 102 , 2382923843.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dong, X., , Ackerman T. P. , , and Clothiaux E. E. , 1998: Parameterizations of microphysical and shortwave radiative properties of boundary layer stratus from ground-based measurements. J. Geophys. Res., 103 , 3168131693.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dong, X., , Minnis P. , , Ackerman T. P. , , Clothiaux E. E. , , Mace G. G. , , Long C. N. , , and Liljegren J. C. , 2000: A 25-month database of stratus cloud properties generated from ground-based measurements at the ARM SGP site. J. Geophys. Res., 105 , 45294537.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dong, X., , Minnis P. , , Mace G. G. , , Smith W. L. Jr., , Poellot M. , , Marchand R. , , and Rapp A. , 2002: Comparison of stratus cloud properties deduced from surface, GOES, and aircraft data during the March 2000 ARM Cloud IOP. J. Atmos. Sci., 59 , 32653284.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Duynkerke, P. G., , Zhang H. , , and Jonker P. J. , 1995: Microphysical and turbulent structure of nocturnal stratocumulus as observed during ASTEX. J. Atmos. Sci., 52 , 27632777.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dye, J. E., , and Baumgardner D. , 1984: Evaluation of the Forward Scattering Spectrometer Probe. Part I: Electronic and optical studies. J. Atmos. Oceanic Technol., 1 , 329344.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frisch, A., , Fairall C. W. , , and Snider J. B. , 1995: Measurement of stratus cloud and drizzle parameters in ASTEX with a K-band Doppler radar and a microwave radiometer. J. Atmos. Sci., 52 , 27882799.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frisch, A., , Feingold G. , , Fairall C. W. , , and Uttal T. , 1998: On cloud radar and microwave radiometer measurements of stratus cloud liquid water profiles. J. Geophys. Res., 103 , 2319523197.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liljegren, J. C., , Clothiaux E. E. , , Mace G. G. , , Kato S. , , and Dong X. , 2001: A new retrieval for cloud liquid water path using a ground-based microwave radiometer and measurements of cloud temperature. J. Geophys. Res., 106 , 1448514500.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mace, G. G., , and Sassen K. , 2000: A constrained algorithm for retrieval of stratocumulus cloud properties using solar radiation, microwave radiometer, and millimeter cloud radar data. J. Geophys. Res., 105 , 2909929108.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Miles, N. L., , Verlinde J. , , and Clothiaux E. E. , 2000: Cloud-droplet size distributions in low-level stratiform clouds. J. Atmos. Sci., 57 , 295311.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Moran, K. P., , Martner B. E. , , Post M. J. , , Kropfli R. A. , , Welsh D. C. , , and Widener K. B. , 1998: An unattended cloud-profiling radar for use in climate research. Bull. Amer. Meteor. Soc., 79 , 443455.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stokes, G. M., , and Schwartz S. E. , 1994: The Atmospheric Radiation Measurement (ARM) program: Programmatic background and design of the cloud and radiation testbed. Bull. Amer. Meteor. Soc., 8 , 12511256.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 249 249 14
PDF Downloads 45 45 4

Profiles of Low-Level Stratus Cloud Microphysics Deduced from Ground-Based Measurements

View More View Less
  • 1 Meteorology Department, University of Utah, Salt Lake City, Utah
© Get Permissions Rent on DeepDyve
Restricted access

Abstract

The microwave radiometer–derived cloud liquid water path (LWP) and a profile of radar reflectivity are used to derive a profile of cloud liquid water content (LWC). Two methods (M1 and M2) have been developed for inferring the profile of cloud-droplet effective radius (re) in liquid phase or liquid dominant mixed phase stratocumulus clouds. The M1-inferred re profile is proportional to a previously derived layer-mean re and to the ratio of the radar reflectivity to the integrated radar reflectivity. This algorithm is independent of the radar calibration and is applicable to overcast low-level stratus clouds that occur during the day because it is dependent on solar transmission observations. In order to extend the retrieval algorithm to a wider range of conditions, a second method is described that uses an empirical relationship between effective radius and radar reflectivity based on theory and the results of M1. Sensitivity studies show that the surface-retrieved re is more sensitive to the variation of radar reflectivity when the radar reflectivity is large, and the uncertainties of retrieved re related to the assumed vertically constant cloud-droplet number concentration and shape of the size distribution are about 9% and 2%, respectively. For validation, a total of 10 h of aircraft data and 36 h of surface data were collected over the Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site during the March 2000 cloud intensive observational period (IOP). More detailed comparisons in two cases quantify the agreement between the aircraft data and the surface retrievals. When the temporal averages of the two datasets increase from 1 min to 30 min, the means and standard deviations of differences between the two datasets decrease from −2.5% ± 84% to 1.3% ± 42.6% and their corresponding correlation coefficients increase from 0.47 to 0.8 for LWC; and decrease from −4.8% ± 36.4% to −3.3% ± 22.5% with increased coefficients from 0.64 to 0.94 for re (both M1 and M2). The agreement between the aircraft and surface data in the 30-min averages suggests that the two platforms are capable of characterizing the cloud microphysics over this temporal scale. On average, the surface retrievals are unbiased relative to the aircraft in situ measurements. However, when only the 1-min averaged aircraft data within 3 km of the surface site were selected, the means and standard deviations of differences between the two datasets are larger (23.4% ± 113% for LWC and 28.3% ± 60.7% for re) and their correlation coefficients are smaller (0.32 for LWC and 0.3 for re) than those from all 1-min samples. This result suggests that restricting the comparison to the samples better matched in space and time between the surface and aircraft data does not result in a better comparison.

* Current affiliation: Department of Atmospheric Sciences, University of North Dakota, Grand Forks, North Dakota

Corresponding author address: Dr. Xiquan Dong, Department of Atmospheric Sciences, University of North Dakota, 4149 Campus Road, Clifford Hall 400, Box 9006, Grand Forks, ND 58202-9006. Email: dong@aero.und.edu

Abstract

The microwave radiometer–derived cloud liquid water path (LWP) and a profile of radar reflectivity are used to derive a profile of cloud liquid water content (LWC). Two methods (M1 and M2) have been developed for inferring the profile of cloud-droplet effective radius (re) in liquid phase or liquid dominant mixed phase stratocumulus clouds. The M1-inferred re profile is proportional to a previously derived layer-mean re and to the ratio of the radar reflectivity to the integrated radar reflectivity. This algorithm is independent of the radar calibration and is applicable to overcast low-level stratus clouds that occur during the day because it is dependent on solar transmission observations. In order to extend the retrieval algorithm to a wider range of conditions, a second method is described that uses an empirical relationship between effective radius and radar reflectivity based on theory and the results of M1. Sensitivity studies show that the surface-retrieved re is more sensitive to the variation of radar reflectivity when the radar reflectivity is large, and the uncertainties of retrieved re related to the assumed vertically constant cloud-droplet number concentration and shape of the size distribution are about 9% and 2%, respectively. For validation, a total of 10 h of aircraft data and 36 h of surface data were collected over the Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site during the March 2000 cloud intensive observational period (IOP). More detailed comparisons in two cases quantify the agreement between the aircraft data and the surface retrievals. When the temporal averages of the two datasets increase from 1 min to 30 min, the means and standard deviations of differences between the two datasets decrease from −2.5% ± 84% to 1.3% ± 42.6% and their corresponding correlation coefficients increase from 0.47 to 0.8 for LWC; and decrease from −4.8% ± 36.4% to −3.3% ± 22.5% with increased coefficients from 0.64 to 0.94 for re (both M1 and M2). The agreement between the aircraft and surface data in the 30-min averages suggests that the two platforms are capable of characterizing the cloud microphysics over this temporal scale. On average, the surface retrievals are unbiased relative to the aircraft in situ measurements. However, when only the 1-min averaged aircraft data within 3 km of the surface site were selected, the means and standard deviations of differences between the two datasets are larger (23.4% ± 113% for LWC and 28.3% ± 60.7% for re) and their correlation coefficients are smaller (0.32 for LWC and 0.3 for re) than those from all 1-min samples. This result suggests that restricting the comparison to the samples better matched in space and time between the surface and aircraft data does not result in a better comparison.

* Current affiliation: Department of Atmospheric Sciences, University of North Dakota, Grand Forks, North Dakota

Corresponding author address: Dr. Xiquan Dong, Department of Atmospheric Sciences, University of North Dakota, 4149 Campus Road, Clifford Hall 400, Box 9006, Grand Forks, ND 58202-9006. Email: dong@aero.und.edu

Save