John S. Kain

TL;DR: Modifications to the Kain‐Fritsch convective parameterization evolved from an effort to produce desired effects in numerical weather prediction while also rendering the scheme more faithful to observations and cloud-resolving modeling studies.

TL;DR: In this article, the utility of the Weather Research and Forecast (WRF) model was evaluated during the 2004 Storm Prediction Center-National Severe Storms Laboratory Spring Program in a simulated severe weather forecasting environment.

TL;DR: In this article, the sensitivity of various accuracy measures to displacement error, bias, and event frequency is analyzed for a simple hypothetical forecasting situation, and a newly devised measure, called the bias-adjusted threat score, does not change with varying event frequency and is relatively insensitive to bias.

TL;DR: This study confirms that convection-allowing models with grid spacing ~ 4 km38 represent many aspects of the formation and development of deep convection clouds explicitly and with predictive utility and shows that automated algorithms can skillfully identify the CI process during model integration.

TL;DR: In this paper, the authors examined the process of atmospheric cooling due to melting precipitation to evaluate its contribution to determining precipitation type and found that melting effect is typically of second-order importance compared to other processes that influence the lower-tropospheric air temperature and hence the type of precipitation that reaches the ground.