Amaury de Souza
Institute of Physics, Federal University of Mato Grosso do Sul, C.P. 549, Campo Grande 79070-900, Brazil
Tropospheric ozone (O₃) is a secondary pollutant whose variability in tropical urban environments is strongly controlled by seasonal meteorology, photochemistry, and episodic emissions such as biomass burning. This study applies Singular Spectrum Analysis (SSA) combined with the Linear Recurrent Formula (LRF) to analyze and forecast daily tropospheric ozone in Campo Grande, Brazil, using SISAM/INPE satellite data from 2000 to 2018. In contrast to previous SSA-based applications, this work introduces a systematic evaluation of embedding window length (L = 30, 60, and 90) to assess the robustness of the decomposition and component separability. In addition, the spectral consistency of reconstructed components is examined to support the identification of dominant temporal modes. For forecasting, a strict out-of-sample framework is adopted, using 2000–2017 for training and 2018 for independent validation, ensuring no information leakage. The LRF model achieved RMSE = 0.79 ppb, MAE = 0.64 ppb, and MAPE = 3.8%, outperforming persistence and seasonal naïve benchmarks. Results indicate that ozone variability is predominantly seasonal, with weak long-term trends and relevant intra-seasonal fluctuations. The proposed framework provides a transparent, computationally efficient, and reproducible approach for diagnosing and forecasting ozone variability in tropical environments.
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Copyright © 2026 Amaury de Souza
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