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  • Author or Editor: G. M. McFarquhar x
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A. Protat, G. M. McFarquhar, J. Um, and J. Delanoë


Best estimates of the bulk microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration) are derived for three case studies of tropical ice clouds sampled during the Tropical Warm Pool International Cloud Experiment (TWP-ICE). Two case studies are aged cirrus clouds produced by deep convection (the so-called 27/01 and 29/01 cases), and the third (“02/02”) is a fresh anvil produced by deep convective activity over the Tiwi Islands. Using crystal images obtained by a Cloud Particle Imager (CPI), it is observed that small ice particles (with maximum dimension D < 50–100 μm) were predominantly quasi spherical, with the degree of nonsphericity increasing rapidly in the 50 < D < 100-μm range. For D > 100 μm, the aged cirrus clouds were predominantly characterized by bullet rosettes and aggregates of bullet rosettes, plates, and columns. In contrast, the fresh anvil had more frequent occurrences of plates, columns, aggregates of plates, and occasionally capped columns. The impact of shattering of large ice crystals on probe tips and the overall quality of the TWP-ICE in situ microphysical measurements are assessed. It is suggested that shattering has a relatively small impact on the CPI and cloud droplet probe (CDP) TWP-ICE data and a large impact on the Cloud Aerosol Spectrometer data, as already documented by others. It is also shown that the CPI size distributions must be multiplied by a factor of 4 to match those of the cloud imaging probe (CIP) for maximum dimension larger than 100 μm (taken as a reference). A technique [named Best Estimate of Area and Density (BEAD)] to minimize errors associated with the density (ρ)–D and projected area (A)–D assumptions in bulk microphysics calculation is introduced and applied to the TWP-ICE data. The method makes direct use of the frequency of occurrence of each particle habit as classified from the CPI data and prescribed ρD and AD relationships from the literature. This approach produces ice water content (IWC) estimates that are virtually unbiased relative to bulk measures obtained from a counterflow spectrometer and impactor (CSI) probe. In contrast, the use of ρD and AD relationships for single habits does produce large biases relative to the CSI observations: from −50% for bullet rosettes to +70%–80% for aggregates. The so-called width, length, area, and perimeter (WLAP) technique, which also makes use of individual CPI images, is found to produce positively biased IWCs (by 40% or so), and has a standard deviation of the errors similar to the BEAD technique. The impact of the large variability of the size distributions measured by different probe combinations on the bulk microphysical properties is characterized. The mean fractional differences with respect to the CSI measurements are small for the CPI + CIP, CPI, and CDP + CIP combinations (2.2%, −0.8%, and −1.1%, respectively), with standard deviations of the fractional differences ranging from 7% to 9%. This result provides an independent validation of the CPI scaling factor. The fractional differences produced between the CPI + CIP, CPI, and CDP + CIP combinations for extinction, effective radius, and total concentration are 33%, 10%–20%, and 90%, respectively, with relatively small standard deviations of 5%–8%. The fractional difference on total concentration varies greatly over the concentration range though, with values being larger than a factor of 2 for total concentrations smaller than 40 L−1, but reducing to 10%–20% for concentrations larger than 100 L−1. Therefore, caution should be exercised when using total concentrations smaller than 60–80 L−1 as references for radar–lidar retrieval evaluation.

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P. R. A. Brown, A. J. Illingworth, A. J. Heymsfield, G. M. McFarquhar, K. A. Browning, and M. Gosset


The purpose of this paper is to assess the potential of a spaceborne 94-GHz radar for providing useful measurements of the vertical distribution and water content of ice clouds on a global scale.

Calculations of longwave (LW) fluxes for a number of model ice clouds are performed. These are used to determine the minimum cloud optical depth that will cause changes in the outgoing longwave radiation or flux divergence within a cloud layer greatear than 10 W m−2, and in surface downward LW flux greater than 5 W m−2, compared to the clear-sky value. These optical depth values are used as the definition of a “radiatively significant” cloud. Different “thresholds of radiative significance” are calculated for each of the three radiation parameters and also for tropical and midlatitude cirrus clouds. Extensive observational datasets of ice crystal size spectra from midlatitude and tropical cirrus are then used to assess the capability of a radar to meet these measurement requirements. A radar with a threshold of −30 dBZ should detect 99% (92%) of “radiatively significant” clouds in the midlatitudes (Tropics). This detection efficiency may be reduced significantly for tropical clouds at very low temperatures (−80°C).

The LW flux calculations are also used to establish the required accuracy within which the optical depth should be known in order to estimate LW fluxes or flux divergence to within specified limits of accuracy. Accuracy requirements are also expressed in terms of ice water content (IWC) because of the need to validate cloud parameterization schemes in general circulation models (GCMs). Estimates of IWC derived using radar alone and also using additional information to define the mean crystal size are considered. With crystal size information available, the IWC for samples with a horizontal scale of 1–2 km may be obtained with a bias of less than 8%. For IWC larger than 0.01 g m−3, the random error is in the range +50% to −35%, whereas for a value of 0.001 g m−3 the random error increases to between +80% and −45%. This level of accuracy also represents the best that may be achieved for estimates of the cloud optical depth and meets the requirements derived from LW flux calculations. In the absence of independent particle size information, the random error is within the range +85% to −55% for IWC greater than 0.01 g m−3. For the same IWC range, the estimated bias is few than ±15%. This accuracy is sufficient to provide useful constraints on GCM cloud parameteriation schemes.

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