The Performance of Seven WRF Planetary Boundary Layer/Surface Layer Physics Schemes over Complex Terrain

The Weather Research and Forecasting model (WRF) model includes a wide array of physics packages that can be selected by the user, parameterizing sub grid scale processes. WRF v.3.8.1 includes twelve planetary boundary layer (PBL), eight surface layer (SL), and a number of radiation, microphysics, and cumulus parameterization options selectable by the user. Spatially, the model physics are capable of resolving large scale synoptic weather systems, mesoscale phenomena such as severe storms, and sub-km scale phenomena down to larger boundary layer eddies. Using an adequate resolution grid, WRF is capable of providing forecasts of atmospheric conditions over fine scale complex topography

The present study focuses on comparing the performance of seven of the PBL/SL combinations since surface and near surface properties are of primary importance for military operations, including ground forces operations, artillery meteorology impacts, and land mobility. The model domain chosen for these analyses is over Southern California domain, approximately centered near San Diego, California. The domain was chosen primarily because of the availability of high density surface observations, and variety of complex terrain and land use. A triple nest configuration (9-3-1km) of WRF v3.8.1 was run, and we focus on a single day in which conditions were quiescent in order to observe the evolution of the PBL in the absence of rapidly changing synoptic scale weather influences.

The Mellor-Yamada Nakanishi and Niino (MYNN), Mellor-Yamada-Janjic (MYJ), Yonsei University (YSU), Asymmetric Convection Model (ACM2), Quasi-Normal Scale Elimination (QNSE), Bougeault-Lacarrère (Boulac) and Shin-Hong (SH) PBL/SL options were compared, representing both local and non-local physics, and a hybrid approach. Post processing was performed using the Model Evaluation Tools (MET) package and the R statistical analysis package. In the case of the daytime convective boundary layer (CBL), the difference in performance between the schemes is relatively small. However, in the case of the largely stable nocturnal boundary layer, the differences between the schemes are notably larger. The increased model spread between the schemes during the nighttime can be attributed to differences in the formulations in the nocturnal boundary layer formulations and assumptions. During the daytime, no single scheme stands out as the best to use in our complex terrain environment. At nighttime, the best performing scheme is dependent upon the meteorological parameter. Consistent among all schemes is the model’s difficulty in capturing the transition between daytime and nighttime boundary layers. The surface variables, vertical profiles, and boundary layer depth are important for our application, and for the prediction of weather effects on Army operations using weather impacts decision aids (WIDAs). Both the YSU and MYJ schemes, used in the common WRE-N configurations and in operational configurations, appear to perform reasonably well. The scale-aware scheme (Shin and Hong, 2013) addresses the scale dependency problem, however, for a 1 km inner grid, we see no notable improvement compared to the other schemes from which this scheme was based (YSU, MRF). Aside from the analysis of surface parameters, we also briefly examine the PBL depth and horizontal distribution of both temperature and PBL depth in our analyses. Statistical analysis shows that the PBL scheme accounts for about 3-4% of the total variance (Smith and Penc, 2016), and we conclude that any physics based ensemble must consider more than PBL/SL options. Research looking into the relative contributions to model uncertainty due to the other physics schemes, and initialization data are addressed in the Design of Experiments approach described by Smith and Penc (2016) and Smith et al (2018).

References:

Shin, H., and S. Hong, 2013: Analysis of Resolved and Parameterized Vertical Transports in Convective Boundary Layers at Gray-Zone Resolutions. J. Atmos. Sci., 70, 3248-3261.

Smith, J.A. and R.S. Penc, 2016: A Design of Experiments Approach to Evaluating Parameterization Schemes for Numerical Weather Prediction: Problem Definition and Proposed Solution Approach. Joint Statistical Meetings Proceedings, Section on Statistics in Defense and National Security, Conference on Applied Statistics in Defense, p. 4183-4192.

Smith, J.A., R. Penc, and J.W. Raby, 2018: Statistical Design of Experiments in Numerical Weather Prediction: Emerging Results, in 98th Annual AMS Meeting, Joint with 25th Conference on Probability and Statistics. American Meteorological Society: Austin, TX. Paper 6.1.