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- Title
Evaluation of Surface Data Simulation Performance with the Brazilian Global Atmospheric Model (BAM).
- Authors
Herdies, Dirceu Luis; Silva, Fabrício Daniel dos Santos; Gomes, Helber Barros; Silva, Maria Cristina Lemos da; Gomes, Heliofábio Barros; Costa, Rafaela Lisboa; Lins, Mayara Christine Correia; Reis, Jean Souza dos; Kubota, Paulo Yoshio; Souza, Dayana Castilho de; Melo, Maria Luciene Dias de; Mariano, Glauber Lopes
- Abstract
In this study, we evaluated the performance of the Brazilian Global Atmospheric Model (BAM), in its version 2.2.1, in the representation of the surface variables solar radiation, temperature (maximum, minimum, and average), and wind speed. Three experiments were carried out for the period from 2016 to 2022 under three different aerosol conditions (constant (CTE), climatological (CLIM), and equal to zero (ZERO)), discarding the first year as a spin-up period. The observations came from a high-resolution gridded analysis that provides Brazil with robust data based on observations from surface stations on a daily scale from 1961 to 2020; therefore, combining the BAM outputs with the observations, our intercomparison period took place from 2017 to 2020, for three timescales: daily, 10-day average, and monthly, targeting different applications. In its different simulations, BAM overestimated solar radiation throughout Brazil, especially in the Amazon; underestimated temperature in most of the northeast, southeast, and south regions; and overestimated in parts of the north and mid-west; while wind speed was only not overestimated in the Amazon region. In relative terms, the simulations with constant aerosol showed better performance than the others, followed by climatological conditions and zero aerosol. The dexterity indices applied in the intercomparison between BAM and observations indicate that BAM needs adjustments and calibration to better represent these surface variables. Where model deficiencies have been identified, these can be used to drive model development and further improve the predictive capabilities.
- Subjects
BRAZIL; ATMOSPHERIC models; SOLAR radiation; WIND speed; SOLAR surface; AEROSOLS
- Publication
Atmosphere, 2023, Vol 14, Issue 1, p125
- ISSN
2073-4433
- Publication type
Article
- DOI
10.3390/atmos14010125