A parameterization has been developed for mean effective size D ge in terms of ice water content (IWC) and temperature using in situ measurements of ice crystal spectra, cloud particle shapes and particle cross-sectional area A from four research projects conducted in latitudes north of 45°N. The cloud microphysical measurements were made using PMS 2D optical probes, a PMS forward scattering spectrometer probe (FSSP), and Nevzorov total water and liquid water content probes. The IWCs derived from particle spectra using three different methods were compared with IWC measured with the Nevzorov probe (IWC Nev ). The contribution of small particles to the total mass was estimated by integrating a gamma distribution function that was fitted to match the measured FSSP concentrations. The D ge was calculated from the derived IWC and total cross-sectional area per unit volume A c .This analysis indicates that there are significant differences among the schemes used to derive the IWC. It was found that the IWC derived based on the Cunningham scheme and IWC Nev have the highest correlation: r 2 = 0.78. After considering small particles, the derived IWC almost matched the IWC Nev . The average estimated contribution of small particles to the A c was 43%. The average estimated contribution of small particles to the total IWC, however, was 20%. Since D ge is directly proportional to the ratio IWC/A c , the addition of small particles reduced the derived D ge considerably. The largest changes in D ge associated with small particles, however, occur at the coldest temperature and at low IWC, reaching up to 45% for temperatures less than −25°C. Generally, D ge and IWC increase with increasing temperature. Good agreement between the parameterized D ge and derived D ge from measurements were found when small particles were included.

[1] Several parameterizations of extinction coefficient (s) and visibility (l v ) as a function of temperature (T), liquid water equivalent snowfall rate (S), have been developed assuming a gamma size distribution for ice particles and using aircraft data collected in extratropical stratiform clouds. Using surface-based measurements (SBM) of S, T, relative humidity (RH), cloud ceiling (l ce ), and s during the winter months in 2005, 2006, and 2007 at the Centre for Atmospheric Research Experiments site in Ontario, Canada, other parameterizations have been developed and compared with that based on the aircraft data. The analysis of the SBM data indicates that low l v is mainly associated with S. Both aircraft and SBM data indicate that there is a significant dependence of l v on S and a relatively weaker dependence on T. The observed l v is correlated with l ce , but the dependence of l v on RH is relatively weak. There is some nonlinear dependence of l v on wind speed. Using SBM, several parameterizations of s have been developed using a multiple linear regression method by increasing the number of terms starting with S. The addition of T increases the correlation coefficient (CC) r from 0.85 to 0.87. The addition of RH has no significant effect, but the inclusion of l ce further improves the CC from 0.87 to 0.9. It was also found that both l v and l ce can be described well using the inverse Gaussian probability density function. Model predictions using these parameterizations show that, when the model correctly forecasts the precipitation field, the predicted l v agreed well with observations.

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SUMMARYLiquid fractions in mixed-phase clouds have been analysed using aircraft measurements taken in mid-and high latitude stratiform clouds. The liquid fraction generally increases with temperature but has a minimum at about −15 • C, where the maximum ice crystal growth based on vapour deposition would be expected. The mean liquid fraction also depends on total water content. This suggests that segregation of cloud phase based on a simple linear relationship of phase fraction (ice or liquid) with temperature, as is used in some climate models, may be unrealistic. Parametrizations of mean liquid fraction in terms of temperature and total water content, and in terms of temperature alone, have been developed based on data averaged at 10 s resolution (1 km). These parametrizations agree reasonably well with the observations.