Affiliation:
1. Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University, Seoul, South Korea
Abstract
Although clouds are a major factor influencing atmospheric environments in the Arctic, numerical simulations of Arctic clouds are uncertain. In this study, the effects of microphysics scheme and data assimilation (DA) on the simulation of clouds, hydrometeors and radiative fluxes in the Arctic were investigated using the polar weather research and forecasting (WRF) model and three-dimensional variational DA. Compared with the WRF 5-class (WSM5) microphysics scheme, when the Morrison double-moment (Morrison) scheme was used, the simulated amount of cloud ice water decreased by approximately 68%. In contrast, the amount of water vapour, cloud liquid water, snow and rain in the atmosphere increased. With DA, the amount of water vapour increased, leading to increased hydrometeors. The cloud liquid water increased in the middle and low atmospheres when Morrison was used, whereas it increased in the low atmosphere when DA was used. The increase in cloud liquid water by using Morrison resulted in a decrease in the downward short-wave radiative flux at the surface, whereas using DA increased the downward long-wave radiative flux. Changing the microphysics scheme induced redistribution of the region and amounts of hydrometeors, whereas DA induced an increase in hydrometeors in specific regions by adding observation information to the model states.
Funder
Yonsei Signature Research Cluster Program
National Research Foundation of Korea