J5B.2 Investigation of Coastal Orographic Snow Clouds Microphysics with the Super-Droplet Method

Tuesday, 30 January 2024: 8:45 AM
329 (The Baltimore Convention Center)
Anu Gupta, Univ. of Hyogo, Kobe, Japan; and R. Taniguchi, S. I. Shima, and A. Hashimoto

The understanding of snow clouds and their microphysics holds significant implications for comprehending their influence on the climate. However, the intricate nature of cloud microphysics has led to the formulation of simplified numerical models. The microphysical schemes used in these classical models are not able to provide the details of the microphysical properties of snow clouds. Addressing this limitation, the emergence of cloud particle-based modeling techniques, such as the Super-Droplet Method (SDM) have been developed, providing the precise and efficient microphysical attributes of snow clouds. In this particular investigation, our focus resides on conducting ideal simulations to unravel the distinctive characteristics of snow clouds in the coastal orographic Hokuriku region of Japan. Our research delves into the role of variables, particularly the impact of riming ratios on the growth of ice particles in clouds and snowfall. Additionally, we focus on the mechanisms underlying the influence of atmospheric aerosol species, such as mineral dust, on cloud development. Using the SDM, we are successfully able to simulate how the increase in the amount of aerosol species and their size causes the increase in snowfall. Further, we compared the results with the observations and found that the distribution of riming ratios closely matched the observational results when simulating realistic values for the diameter and amount of aerosol species. Further, investigation is required to understand the influence of mixing of more realistic aerosol species on the microphysics of snow clouds and their corresponding snowfall.
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