Abstract
Abstract. This study uses aircraft measurements of relative humidity and ice crystal size distribution collected during the SPARTICUS (Small PARTicles In CirrUS) field campaign to evaluate and constrain ice cloud parameterizations in the Community Atmosphere Model version 5. About 200 h of data were collected during the campaign between January and June 2010, providing the longest aircraft measurements available so far for cirrus clouds in the midlatitudes. The probability density function (PDF) of ice crystal number concentration (Ni) derived from the high-frequency (1 Hz) measurements features a strong dependence on ambient temperature. As temperature decreases from −35 °C to −62 °C, the peak in the PDF shifts from 10–20 L−1 to 200–1000 L−1, while Ni shows a factor of 6–7 increase. Model simulations are performed with two different ice nucleation schemes for pure ice-phase clouds. One of the schemes can reproduce a clear increase of Ni with decreasing temperature by using either an observation-based ice nuclei spectrum or a classical-theory-based spectrum with a relatively low (5–10%) maximum freezing ratio for dust aerosols. The simulation with the other scheme, which assumes a high maximum freezing ratio (100%), shows much weaker temperature dependence of Ni. Simulations are also performed to test empirical parameters related to water vapor deposition and the autoconversion of ice crystals to snow. Results show that a value between 0.05 and 0.1 for the water vapor deposition coefficient, and 250 μm for the critical diameter that distinguishes ice crystals from snow, can produce good agreement between model simulation and the SPARTICUS measurements in terms of Ni and effective radius. The climate impact of perturbing these parameters is also discussed.
Highlights
June 2010, providing the longest aircraft measurements available so far for cirrus clouds in the midlatitudes
Ni in the Southern Great Plain (SGP) area measured during the SPARTICUS campaign and simulated with the LP05 and BN09 ice nucleation schemes are presented in Fig. 2 for four temperature ranges
To check whether this is the cause of the differences between the LP and BN simulations, Fig. 6 compares the simulated and observed bivariate probability density function (PDF) of RHi and ambient temperature in different cases distinguished by the ice crystal number concentration
Summary
Methods and and June 2010, providing the longest aircraft measurements available so far for cirrus clouds in the midlatitudes. For mineral dust particles (which are efficient ice nuclei), Liu et al (2007) and Hoose et al (2010) assumed the maximum ice-nucleating fraction (a concept very similar to fmax) to be 100 % for immersion freezing, while Barahona and Nenes (2009b) used a fmax value of 5 % Another example of uncertain parameters is the deposition coefficient α ( called the mass accommodation coefficient) of water vapor on ice, which determines the diffusional growth efficiency of ice crystals. 3.2) in a global climate model and to constrain three empirical parameters: the maximum freezing fraction fmax of dust aerosols, the deposition coefficient of water vapor on ice crystals (α), and the critical diameter Dcs that distinguishes cloud ice and snow as two classes of icephase hydrometeors
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