Advances in Modeling Valley Cold Pools and Fogs

Despite our increased understanding in the relevant physical processes, forecasting radiative cold pools and their associated meteorological phenomena (e.g., fog and freezing rain) remains a challenging problem in mesoscale models. The present study is focused on California's Tule fog where the Weather Research and Forecasting (WRF) model's inability to forecast the event is addressed and substantially improved. An intra-model physics ensemble reveals that no current physics is able to properly capture the Tule fog and that model revisions are necessary. It has been found that revisions to the height of the lowest model level in addition to reconsideration of horizontal diffusion and surface-atmospheric coupling are critical for accurately forecasting the onset and duration of these events.

Not surprisingly, model revisions specifically implemented for cold pools can degrade simulations at other times and places. We have created a new land surface model (LSM) by examining other available schemes and addressing their weaknesses. The new scheme, the Hybrid LSM, convolves the Noah LSM's prognostic soil moisture treatment with the simplicity of the Thermal Diffusion (slab) scheme's heat transfer model. The Hybrid has proven to yield the best forecasts of temperature, dew point and relative humidity for both cold pool and non-cold pool scenarios, in the California Central Valley and across the western United States, for both winter and summer seasons.