Using Forecast Ensembles to Assess Boundary Layer Uncertainty and Characteristics

While much of the United States and Europe have well developed weather networks that can provide accurate realtime weather information. Much of the world still lacks accurate representation of numerical weather data. With advances in both ensemble modeling and computing power, is it now possible to create accurate mesonet networks that can accurately forecast boundary layer dynamics for entire remote areas?

As part of projects in biomimicry in the built environment and ensemble regional-scale modeling we are exploring the use model ensembles to assess forecast confidence in basic meteorological parameters and extracting surface and boundary layer traits. Here, we present applying regional- and global-scale models to estimating the range and uncertainty in surface boundary layer traits. Specifically, we will focus on those parameters to be integrated into CFL models applicable to the built environment.