TY - JOUR
T1 - The Brazilian Global Atmospheric Model (BAM)
T2 - Performance for tropical rainfall forecasting and sensitivity to convective scheme and horizontal resolution
AU - Figueroa, Silvio N.
AU - Bonatti, José P.
AU - Kubota, Paulo Y.
AU - Grell, Georg A.
AU - Morrison, Hugh
AU - Barros, Saulo R.M.
AU - Fernandez, Julio P.R.
AU - Ramirez, Enver
AU - Siqueira, Leo
AU - Luzia, Graziela
AU - Silva, Josiane
AU - Silva, Juliana R.
AU - Pendharkar, Jayant
AU - Capistrano, Vinicius B.
AU - Alvim, Débora S.
AU - Enoré, Diego P.
AU - Fábio, L. R.Diniz
AU - Satyamurti, Praki
AU - Cavalcanti, Iracema F.A.
AU - Nobre, Paulo
AU - Barbosa, Henrique M.J.
AU - Mendes, Celso L.
AU - Panetta, Jairo
N1 - Funding Information:
The authors acknowledge NCEP for providing the analysis dataset used in this study as well as forecasts from the NCEP/GFS model. The authors thank Dr. Fedor Mesinger and the reviewers for a critical review of this manuscript and constructive comments. This research was partially funded by the following Brazilian agencies: FAPESP, CNPq, and the Brazilian Research Network on Global Climate Change FINEP/Rede CLIMA (Grant 01.13.0353-00).
PY - 2016
Y1 - 2016
N2 - This article describes the main features of the Brazilian Global Atmospheric Model (BAM), analyses of its performance for tropical rainfall forecasting, and its sensitivity to convective scheme and horizontal resolution. BAM is the new global atmospheric model of the Center for Weather Forecasting and Climate Research [Centro de Previsão de Tempo e Estudos Climáticos (CPTEC)], which includes a new dynamical core and state-of-the-art parameterization schemes. BAM's dynamical core incorporates a monotonic two-time-level semi-Lagrangian scheme, which is carried out completely on the model grid for the tridimensional transport of moisture, microphysical prognostic variables, and tracers. The performance of the quantitative precipitation forecasts (QPFs) from two convective schemes, the Grell-Dévényi (GD) scheme and its modified version (GDM), and two different horizontal resolutions are evaluated against the daily TRMM Multisatellite Precipitation Analysis over different tropical regions. Three main results are 1) the QPF skill was improved substantially with GDM in comparison to GD; 2) the increase in the horizontal resolution without any ad hoc tuning improves the variance of precipitation over continents with complex orography, such as Africa and South America, whereas over oceans there are no significant differences; and 3) the systematic errors (dry or wet biases) remain virtually unchanged for 5-day forecasts. Despite improvements in the tropical precipitation forecasts, especially over southeastern Brazil, dry biases over the Amazon and La Plata remain in BAM. Improving the precipitation forecasts over these regions remains a challenge for the future development of the model to be used not only for numerical weather prediction over South America but also for global climate simulations.
AB - This article describes the main features of the Brazilian Global Atmospheric Model (BAM), analyses of its performance for tropical rainfall forecasting, and its sensitivity to convective scheme and horizontal resolution. BAM is the new global atmospheric model of the Center for Weather Forecasting and Climate Research [Centro de Previsão de Tempo e Estudos Climáticos (CPTEC)], which includes a new dynamical core and state-of-the-art parameterization schemes. BAM's dynamical core incorporates a monotonic two-time-level semi-Lagrangian scheme, which is carried out completely on the model grid for the tridimensional transport of moisture, microphysical prognostic variables, and tracers. The performance of the quantitative precipitation forecasts (QPFs) from two convective schemes, the Grell-Dévényi (GD) scheme and its modified version (GDM), and two different horizontal resolutions are evaluated against the daily TRMM Multisatellite Precipitation Analysis over different tropical regions. Three main results are 1) the QPF skill was improved substantially with GDM in comparison to GD; 2) the increase in the horizontal resolution without any ad hoc tuning improves the variance of precipitation over continents with complex orography, such as Africa and South America, whereas over oceans there are no significant differences; and 3) the systematic errors (dry or wet biases) remain virtually unchanged for 5-day forecasts. Despite improvements in the tropical precipitation forecasts, especially over southeastern Brazil, dry biases over the Amazon and La Plata remain in BAM. Improving the precipitation forecasts over these regions remains a challenge for the future development of the model to be used not only for numerical weather prediction over South America but also for global climate simulations.
KW - Convective parameterization
KW - Forecast verification/skill
KW - Forecasting
KW - General circulation models
KW - Model evaluation/performance
KW - Models and modeling
KW - Numerical weather prediction/forecasting
KW - Operational forecasting
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U2 - 10.1175/WAF-D-16-0062.1
DO - 10.1175/WAF-D-16-0062.1
M3 - Article
AN - SCOPUS:84994174601
SN - 0882-8156
VL - 31
SP - 1547
EP - 1572
JO - Weather and Forecasting
JF - Weather and Forecasting
IS - 5
ER -