{'fraction_non_alphanumeric': 0.02895752895752896, 'fraction_numerical': 0.010810810810810811, 'mean_word_length': 4.70704845814978, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Vertical profiles of droplet effective radius in shallow convective clouds

Abstract. Conventional satellite retrievals can only provide information on cloud-top droplet effective radius ( r e ). Given the fact that cloud ensembles in a satellite snapshot have different cloud-top heights, Rosenfeld and Lensky (1998) used the cloud-top height and the corresponding cloud-top r e from the cloud ensembles in the snapshot to construct a profile of r e representative of that in the individual clouds. This study investigates the robustness of this approach in shallow convective clouds based on results from large-eddy simulations (LES) for clean (aerosol mixing ratio N a = 25 mg −1 ), intermediate ( N a = 100 mg −1 ), and polluted ( N a = 2000 mg −1 ) conditions. The cloud-top height and the cloud-top r e from the modeled cloud ensembles are used to form a constructed r e profile, which is then compared to the in-cloud r e profiles. For the polluted and intermediate cases where precipitation is negligible, the constructed r e profiles represent the in-cloud r e profiles fairly well with a low bias (about 10 %). The method used in Rosenfeld and Lensky (1998) is therefore validated for nonprecipitating shallow cumulus clouds. For the clean, drizzling case, the in-cloud r e can be very large and highly variable, and quantitative profiling based on cloud-top r e is less useful. The differences in r e profiles between clean and polluted conditions derived in this manner are however, distinct. This study also investigates the subadiabatic characteristics of the simulated cumulus clouds to reveal the effect of mixing on r e and its evolution. Results indicate that as polluted and moderately polluted clouds develop into their decaying stage, the subadiabatic fraction f ad becomes smaller, representing a higher degree of mixing, and r e becomes smaller (~10 %) and more variable. However, for the clean case, smaller f ad corresponds to larger r e (and larger r e variability), reflecting the additional influence of droplet collision-coalescence and sedimentation on r e . Finally, profiles of the vertically inhomogeneous clouds as simulated by the LES and those of the vertically homogeneous clouds are used as input to a radiative transfer model to study the effect of cloud vertical inhomogeneity on shortwave radiative forcing. For clouds that have the same liquid water path, r e of a vertically homogeneous cloud must be about 76–90 % of the cloud-top r e of the vertically inhomogeneous cloud in order for the two clouds to have the same shortwave radiative forcing.