A Simple Parameterization to Enhance the Computational Time in the Three Layer Dry Deposition Model for Smooth Surfaces

Abstract

Optimization of dry deposition velocity calculation has been of great interest. Every time, determining the value of the concentration boundary layer (CBL) thickness led to a waste of numerical calculation time, which appears as a huge time in large-scale climate models. The goal of this study is to optimize the numerical calculation time in the three-layer deposition model for smooth surfaces through the development of a MATLAB code that can parameterize the appropriate concentration boundary layer height (y+cbl) and internal integral calculation intervals for each particle diameter Dp (0.01–100 µm) and friction velocity u* (0.01–100 m/s). The particle concentration, as a solution to the particle flux equation, is obtained and modeled numerically by performing the left Riemann sum using MATLAB software. On the other hand, the number of subdivisions N of the Riemann sum was also parameterized for each Dp and u* in order to lessen the numerical calculation time. From a numerical point of view, the new parameterizations were tested by several computers; about 78% on the average of the computation time was saved when compared with the original algorithm. In other words, on average, about 1.2 s/calculation was gained, which is valuable in climate models simulations when millions of dry deposition calculations are needed.

Atmospheric Boundary Layer Processes, Characteristics and Parameterization

“…The paper by Zhang et al proposed using the random forest model to correct the simulation results of the Simple Biosphere Model 2, which improved the coefficient of determination between the calculations and measurements by 13-68% [5]. Nofal et al introduced a more efficient parameterization to obtain the appropriate concentration boundary layer height and internal integral calculation intervals, and the new parameterizations showed an ability to save about 78% of the computation time compared to the original algorithm [6]. Reilly et al put forward their understanding of the performance of different turbulence length-scale parameterization methods in the numerical weather prediction models using turbulence kinetic energy schemes, and they recommended using the turbulence length-scale formulations which considered the boundary layer height, turbulent kinetic energy and stratification, as these formulations had a satisfactory performance in different flow regimes [7].…”