Insights into the Challenges of Modeling the Atmospheric Boundary Layer

• Main Author: Tastula, Esa-Matti
• Format: Doctoral or Postdoctoral Thesis
• Language: unknown
• Published: Digital Commons @ University of South Florida 2015
• Subjects: stable stratification; reanalysis; shallow convection; WRF; QNSE; EDMF; Meteorology; Antarctic; The Antarctic; Weddell; Deacon; Antarc*; Sea ice
• Online Access: https://digitalcommons.usf.edu/etd/5782; https://digitalcommons.usf.edu/context/etd/article/6980/viewcontent/Tastula_usf_0206D_12972.pdf

This work approaches the topic of modeling the atmospheric boundary layer in four research projects, which are summarized below. i) The diurnal cycles of near-surface meteorological parameters over Antarctic sea ice in six widely used atmospheric reanalyses were validated against observations from Ice Station Weddell. The station drifted from February through May 1992 and provided the most extensive set of meteorological observations ever collected in the Antarctic sea ice zone. For the radiative and turbulent surface fluxes, both the amplitude and shape of the diurnal cycles varied considerably among different reanalyses. Near-surface temperature, specific humidity, and wind speed in the reanalyses all featured small diurnal ranges, which, in most cases, fell within the uncertainties of the observed cycle. A skill score approach revealed the superiority of the ERA-Interim reanalysis in reproducing the observed diurnal cycles. An explanation for the shortcomings in the reanalyses is their failure to capture the diurnal cycle in cloud cover fraction, which leads to errors in other quantities as well. Apart from the diurnal cycles, NCEP-CFSR gave the best error statistics. ii) The accuracy of prediction of stable atmospheric boundary layers depends on the parameterization of the surface layer which is usually derived from the Monin-Obukhov similarity theory. In this study, several surface-layer models in the format of velocity and potential temperature Deacon numbers were compared to observations from CASES-99, Cardington, and Halley datasets. The comparisons were hindered by a large amount of scatter within and among datasets. Tests utilizing R2 demonstrated that the Quasi-Normal Scale Elimination (QNSE) theory exhibits the best overall performance. Further proof of this was provided by 1D simulations with the Weather Research and Forecasting (WRF) model. iii) The increasing number of physics parameterization schemes adopted in numerical weather forecasting models has resulted in a proliferation of ...