Evaluation of PBL Parameterization Schemes in WRF Model Predictions during the Dry Season of the Central Amazon Basin

Journal Article · 10 May 2023 · Atmosphere (Basel)

DOI: https://doi.org/10.3390/atmos14050850 · OSTI ID:1984456

Mantovani Júnior, José Antonio  ^[1]; Aravéquia, José Antonio  ^[1]; Carneiro, Rayonil Gomes  ^[1]; Fisch, Gilberto ^[1]

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1. National Institute for Space Research (INPE) (Brazil)

Planetary Boundary Layer (PBL) parameterization schemes are employed to handle subgrid-scale processes on atmospheric models, playing a key role in accurately representing the atmosphere. Recent studies have shown that PBL schemes are particularly fundamental to the depiction of PBL height (PBLH), especially over the Amazon. In the present study, we investigated the performance of PBL schemes on the representation of meteorological variables, turbulent fluxes, PBL vertical structures, and PBLH over the central Amazon basin under dry conditions, taking advantage of observations from the Observations and Modeling of the Green Ocean Amazon campaign (GoAmazon2014/5) for validation and evaluation. Numerical experiments were carried out within the WRF model using eight PBL schemes for two dry periods from 2014 (typical year) and 2015 (El-Niño year), and results from the 1-km resolution domain were directly compared to hourly in situ observations. In general, all PBL schemes present good performance to reproduce meteorological variables, with nonlocal (local) PBL schemes producing better performance in the 2014 (2015) study period. All PBL schemes in general overestimate (>100%) daytime turbulent fluxes. Thermodynamic (daytime) vertical structures are better predicted than mechanical (nocturnal) ones. The local MYNN2.5 scheme showed the overall best performance for PBLH prediction, mainly at night.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Data Center
• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER)
• Contributing Organization: Pacific Northwest National Laboratory (PNNL); Brookhaven National Laboratory (BNL); Argonne National Laboratory (ANL); Oak Ridge National Laboratory (ORNL)
• Grant/Contract Number: AC05-76RL01830
• OSTI ID: 1984456
• Journal Information: Atmosphere (Basel), Vol. 14, Issue 5; ISSN 2073-4433
• Publisher: MDPICopyright Statement
• Country of Publication: United States
• Language: English