Impact of the similarity functions of surface layer parametrization in a climate model over the Indian region

Abstract

Impact of the similarity functions of surface layer parametrization in National Centre for Atmospheric Research Community Atmosphere Model version 5 (NCAR-CAM5) is examined over the Indian region. The surface layer parametrization is based on the Monin-Obukhov similarity theory (MOST),which uses momentum and heat similarity functions to parametrize surface turbulent fluxes. In the present study, some of the well-established similarity functions under stable as well as unstable stratification have been incorporated in the surface layer scheme of NCAR-CAM5. Eight simulations have been conducted using different similarity functions with and without a limit on stability parameter along with the simulation using the default surface layer scheme. The impact of the incorporated functions on surface fluxes, near-surface variables, and precipitation has been assessed in this climate model over different climatic zones for the boreal winter and summer seasons. The model represents the timing of diurnal variation of 2 m temperature and turbulent fluxes accurately with higher correlation in all simulations, but the performance of the schemes is found to be sensitive to the climatic zones and seasons. During the winter season, most of the schemes overestimate the night-time surface air temperature over different climatic zones, but the simulation having a model performance index (MPI) of about 0.91 alleviates the bias. Under unstable stratification, the default scheme performs better than incorporated schemes in the winter season, whereas in boreal summer under unstable (stable) stratification, the incorporated functional form having an MPI of about 0.94 (0.97) does better than default and other schemes. As the performance of the functions is spatially and temporally dependent, based on the region and season of interest, the schemes may judiciously be chosen for the climate simulations.

An Updated Parameterization of the Unstable Atmospheric Surface Layer in WRF Modeling System

“…As a result, this scheme is not appropriate in producing CD consistent with its observed behaviour, specifically over the Indian land as stated above. Recently Namdev et al (2023) argue that the performance of NWP models varies a lot over different seasons and surface types depending upon the functional behaviour of φ m and φ h . Thus, to enhance the potential applicability of WRF modeling framework, this study attempted to incorporate all the commonly used similarity functions under convective conditions along with KY90 as well as existing functional forms in the revised MM5 surface layer scheme of WRFv4.2.2.…”