Insights into Atmospheric Predictability through Global Convection-Permitting Model
Simulations in: Journal of the Atmospheric Sciences Volume 75 Issue 5 (2018) Jump to …

This article summarizes the progress made in predictability studies of weather and climate in
recent years in China, with a main focus on advances in methods to study error growth …

Intrinsic versus Practical Limits of Atmospheric Predictability and the Significance of the
Butterfly Effect in: Journal of the Atmospheric Sciences Volume 73 Issue 3 (2016) Jump to …

Predictability of Deep Convection in Idealized and Operational Forecasts: Effects of Radar
Data Assimilation, Orography, and Synoptic Weather Regime in: Monthly Weather Review …

Warm‐sector torrential rainfall (WR) in the South China monsoon region has long been a
forecasting challenge because of the limited capability of numerical models in heavy rainfall …

A 25-member ensemble of relatively high-resolution (75-m horizontal grid spacing)
numerical simulations of tornadic supercell storms is used to obtain insight on their intrinsic …

Despite recent advances in storm-scale ensemble NWP, short-term (0–90 min) explicit
forecasts of severe hail remain a major challenge as a result of the fast evolution and short …

Deep convection represents a classic example of limited predictability on the convective
scale. We investigate the potential impact of assimilating radar reflectivity and velocity …

Using a high-resolution convection-allowing numerical weather prediction model, this study
seeks to explore the intrinsic predictability of the severe tornadic thunderstorm event on 20 …

A deep‐learning neural network (DLNN) model was developed to predict thunderstorm
occurrence within 400 km2 South Texas domains for up to 15 hr (±2 hr accuracy) in …