Sensitivity of Precipitation and Structure of Typhoon Hato to Bulk and Explicit Spectral Bin Microphysics Schemes

Abstract

This study simulated the evolution of Typhoon Hato (2017) with the Weather Research and Forecasting model using three bulk schemes and one bin scheme. It was found that the track of the typhoon was insensitive to the microphysics scheme, whereas the degree of correspondence between the simulated precipitation and the cloud structure of the typhoon was closest to the observations when using the bin scheme. The different microphysical structure of the bin and three bulk schemes was reflected mainly in the cloud water and snow content. The three bulk schemes were found to produce more cloud water because the application of saturation adjustment condensed all the water vapor at the end of each time step. The production of more snow by the bin scheme could be attributed to several causes: (1) the calculations of cloud condensation nucleus size distributions and supersaturation at every grid point that cause small droplets to form at high levels, (2) different fall velocities of different sizes of particles that mean small particles remain at a significant height, (3) sufficient water vapor at high levels, and (4) smaller amounts of cloud water that reduce the rates of riming and conversion of snow to graupel. The distribution of hydrometeors affects the thermal and dynamical structure of the typhoon. The saturation adjustment hypothesis in the bulk schemes overestimates the condensate mass. Thus, the additional latent heat makes the typhoon structure warmer, which increases vertical velocity and enhances convective precipitation in the eyewall region.

Development of Stacked Long Short-Term Memory Neural Networks with Numerical Solutions for Wind Velocity Predictions

“…Hence, feature enhancement from RNNs has been explored in wind prediction. e widespread application of ensembles in numerical weather prediction (NWP) has helped researchers improve weather forecasts [25][26][27][28][29][30]. Numerical models can be used to calculate all climate parameters through atmospheric dynamics and numerical methods, allowing for simulated results to be explained in terms of physical relationships.…”