Influence of Planetary Boundary Layer (PBL) Parameterizations in the Weather Research and Forecasting (WRF) Model on the Retrieval of Surface Meteorological Variables over the Kenyan Highlands

Regional climate models (RCMs) are crucial for climate studies and may be an alternative source of meteorological data in data-scarce regions. However, the effectiveness of the numerical weather prediction (NWP) models applied in RCMs is hampered by the parameterization of unresolved physical proces...

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Bibliographic Details
Published in:Atmosphere 2022-02, Vol.13 (2), p.169
Main Authors: Njuki, Sammy M., Mannaerts, Chris M., Su, Zhongbo
Format: Article
Language:English
Subjects:
Atmospheric models
Boundary conditions
Boundary layers
Climate
Climate change
Climate models
Climate studies
Datasets
General circulation models
Highlands
Hydrometeorology
Kenyan highlands
Meteorological data
Modelling
Numerical prediction
Numerical weather forecasting
NWP
Parameterization
Planetary boundary layer
Precipitation
Rain
Rainfall
Rainfall simulators
RCMs
Regional climate models
Regional climates
Regions
Relative humidity
Retrieval
Simulation
Surface boundary layer
Surface layers
Variables
Weather
Weather forecasting
Wind speed
WRF
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Summary:Regional climate models (RCMs) are crucial for climate studies and may be an alternative source of meteorological data in data-scarce regions. However, the effectiveness of the numerical weather prediction (NWP) models applied in RCMs is hampered by the parameterization of unresolved physical processes in the model. A major source of uncertainties in NWP models is the parameterization of the planetary boundary layer (PBL). This study evaluates the influence of seven PBL parameterization schemes in the Weather Research and Forecasting (WRF) model on the retrieval of four meteorological variables over the Kenyan highlands. The seven PBL schemes consist of four local schemes: the Mellor-Yamada-Janjic (MYJ), Mellor-Yamada-Nakanishi-Niino (MYNN), Bougeault-Lacarrere (BouLac), quasinormal scale elimination (QNSE), and three nonlocal schemes: asymmetrical convective model version 2 (ACM2), Shin and Hong (SHIN) and Yonsei University (YSU). The forcing data for the WRF model was obtained from the fifth generation of the European ReAnalysis (ERA5) dataset. The results were validated against observational data from the Trans-African Hydro-Meteorological Observatory (TAHMO). WRF was found to simulate surface meteorological variables with spatial details coherent with the complex topography within the Kenyan highlands, irrespective of the PBL scheme. A comparison between 2-meter temperature (T2) derived from the YSU scheme and T2 from the land component of ERA5 (ERA5-Land) indicates that surface meteorological variables derived from WRF are better suited for applications over the Kenyan highlands. The choice of the PBL scheme was found to primarily influence the simulation of the 10-meter wind speed (WS10) and rainfall as opposed to T2 and the 2-meter relative humidity (RH2). The insensitivity of the 2-meter variables to the choice of the PBL scheme is attributed to the influence of the surface layer parameterization near the surface. Results from the rainfall simulation indicate that the YSU scheme provides a more realistic depiction of PBL dynamics within the study area. Hence, the YSU scheme is best suited for simulating surface meteorological variables over the Kenyan highlands.
ISSN:2073-4433
2073-4433
DOI:10.3390/atmos13020169