Abstract

A statistical analysis of applying continuous and discrete Haar wavelets to predict planetary boundary layer height.

The modeling of the planetary boundary layer (PBL) is essential to the prediction of local weather phenomena; however, the complexities of the PBL make it very difficult and computationally expensive to model. Adding planetary boundary layer height as a known quantity for parametrization would allow for more reliable modeling. Measuring the mixing layers through active remote sensing has proven to be a robust method given an adequate algorithm. However, these algorithms tend to be very complicated and computationally dense, and most LiDAR data is too sparse to determine spatial and temporal resolution. Using a Haar wavelet, a simplified algorithm was produced. The algorithm’s output is tested against hand derived PBLH from co-located dropsondes, and found to be approximately equivalent for both continuous and discrete methods in both 1D and 2D versions.