Gregory Thompson

TL;DR: In this article, a new bulk microphysical parameterization (BMP) was developed for use with the Weather Research and Forecasting (WRF) Model or other mesoscale models.

TL;DR: A two-moment cloud microphysics scheme predicting the mixing ratios and number concentrations of five species (i.e., cloud droplets, cloud ice, snow, rain, and graupel) has been implemented into the Weather Research and Forecasting model (WRF) as discussed by the authors.

TL;DR: In this paper, the authors evaluated the sensitivity of winter precipitation to various aspects of a bulk, mixed-phase microphysical parameterization found in three widely used mesoscale models [the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5), the Rapid Update Cycle (RUC), and the Weather Research and Forecast (WRF) model].

TL;DR: In this paper, the authors describe the implementation, testing, and results of a newly modified bulk microphysical parameterization with explicit cloud droplet nucleation and ice activation by aerosols and show that increased aerosol number concentration results in more numerous cloud droplets of overall smaller size and delays precipitation development.

TL;DR: In this article, a coupled high-resolution climate-runoff model was used to simulate the annual snowfall in the Colorado Headwaters region and the results showed that the proper spatial and temporal depiction of snowfall adequate for water resource and climate change purposes can be achieved with the appropriate choice of model grid spacing and parameterizations.