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Abstract On 5 March 2023, Professor Lev Gutman would have been 100 years old. This article describes Professor Gutman’s legacy in the field of dynamic mesoscale meteorology and numerical weather prediction. Gutman developed his career as a mathematician and meteorologist in the Soviet Union, where he built a school of specialists in mesoscale meteorology from the 1950s through the 1970s. He primarily worked on analytical methods to solve complex nonlinear problems, such as the structure of sea breezes, mountain–valley circulations, and thermal convection over heated terrain. Gutman pioneered the development of theories of cumulus clouds, tornadoes, and other atmospheric phenomena. In the 1960s, he carried out numerous research investigations on these topics with his doctoral students and collaborators at the High-Altitude Geophysical Institute in Nalchik in the northern Caucasus and later at the Siberian Scientific Center near Novosibirsk. Gutman compiled the results from these studies into a monograph titled “Introduction to the Nonlinear Theory of Mesoscale Meteorological Processes,” which was published in Russian in 1969 and later translated into English, Chinese, and Japanese. This monograph became a major textbook for specialists in mesoscale meteorology, remaining relevant to this day. After Professor Gutman immigrated to Israel in 1978, his collaborations expanded to include Israeli and western scientists from Europe and the United States. Gutman did not receive the recognition he deserved due to the political realities of the time. His book and his seminal analytical solutions should still be useful for early career scientists in mesoscale meteorology and atmospheric dynamics. 

Abstract Aerosols are important environmental factors that can influence deep convective clouds (DCCs) by serving as cloud condensation nuclei. Due to complications in DCC dynamics and microphysics, and aerosol size distribution and composition, understanding aerosol‐DCC interactions has been a daunting challenge. Recently, the convective invigoration mechanisms through enhancing latent heating in condensation and ice‐related processes that have been proposed in literature are debated for their significance qualitatively and quantitatively. A salient issue arising from these debates is the imperative need to clarify essential knowledge and methodologies in investigating aerosol impacts on deep convection. Here we have presented our view of key aspects on investigating and understanding these invigoration mechanisms as well as the aerosol and meteorological conditions under which these mechanisms may be significant based on new findings. For example, the condensational invigoration is most significant under a clean condition with an introduction of a large number of ultrafine particles, and the freezing‐induced invigoration can be significant in a clean condition with a large number of relatively large‐size particles being added. We have made practical recommendations on approaches for investigating aerosol impacts on convection with both modeling and observations. We note that the feedback induced by the invigoration via the enhanced latent heating to circulation and meteorology can be an important part of aerosol impacts but is very complicated and varies with different convective storm types. This is an important future direction for studying aerosol‐DCC interactions. 

Abstract Bin microphysics schemes are useful tools for cloud simulations and are often considered to provide a benchmark for model intercomparison. However, they may experience issues with numerical diffusion, which are not well quantified, and the transport of hydrometeors depends on the choice of advection scheme, which can also change cloud simulation results. Here, an atmospheric large‐eddy simulation model is adapted to simulate a statistically steady‐state cloud in a convection cloud chamber under well‐constrained conditions. Two bin microphysics schemes, a spectral bin method and the method of moments, as well as several advection methods for the transport of the microphysical variables are employed for model intercomparison. Results show that different combinations of microphysics and advection schemes can lead to considerable differences in simulated cloud properties, such as cloud droplet number concentration. We find that simulations using the advection scheme that suffers more from numerical diffusion tends to have a smaller droplet number concentration and liquid water content, while simulation with the microphysics scheme that suffers more from numerical diffusion tends to have a broader size distribution and thus larger mean droplet sizes. Sensitivities of simulations to bin resolution, spatial resolution, and temporal resolution are also tested. We find that refining the microphysical bin resolution leads to a broader cloud droplet size distribution due to the advection of hydrometeors. Our results provide insight for using different advection and microphysics schemes in cloud chamber simulations, which might also help understand the uncertainties of the schemes used in atmospheric cloud simulations.