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- Title
Avaliação do Modelo OLAMv.3.3 na Simulação da Precipitação sobre o Nordeste Setentrional Brasileiro.
- Authors
da Silva, Maria Leidinice; Lima, Kellen Carla; Prestrelo de Oliveira, Cristiano; Barros Barbosa, Augusto Cesar; Santana dos Santos, Antônio Carlos
- Abstract
The global model of numerical forecasting of weather and climate, Ocean Land Atmosphere Model, is currently considered as the new state-of-the-art in numerical modeling due to its ability to represent phenomena of global and regional scales simultaneously. Thus, the research aims to evaluate the performance of this model about the best radiation scheme (Chen or Harrington) to represent precipitation in the Northern area of Northeast Brazil. Thus, the model was configured with a global grid and another grid more refined and centered in South America. The initial atmospheric condition, originating from Reanalysis II of the National Center for Environmental Prediction, was January 1, 1982, at 06 UTC, and the model was integrated until December 31, 2012, at 18 UTC. For the bottom boundary conditions, Sea Surface Temperature data obtained from the second version of the Optimum Interpolation Sea Surface Temperature was used. The model results for the two different types of radiation parameterization were compared with the precipitation data from the Climate Research Unit Time-Series Version 3.22 for the period 1982-2012. The results of the simulations showed that the model, for the two parameters, managed to follow the climatology of precipitation throughout the annual cycle, but underestimating the observed averages. In the June-July-August quarter, the experiment with Harrington parameterization obtained a better correlation (0.855). In contrast, the March-April-May quarter, the experiment with parameterization Chen showed a higher correlation (0.842). As for bias errors, both experiments underestimated precipitation in the March-April-May and June-July-August quarters, to a greater extent the Chen experiment, which overestimated the September-October-November and December-January-February quarters. According to the efficiency index, none of the experiments obtained good accuracy compared to the observational data. In general, the experiments represented the large-scale aspects, but to obtain significant improvements in the precipitation estimate, it is necessary to adopt grids with higher spatial resolution.
- Subjects
SOUTH America; NUMERICAL weather forecasting; OCEAN temperature; CLIMATE research; WEATHER; ATMOSPHERIC models
- Publication
Anuario do Instituto de Geociencias, 2020, Vol 43, Issue 3, p475
- ISSN
0101-9759
- Publication type
Article
- DOI
10.11137/2020_3_475_487