Net Radiation in the Semiarid Region of the States of Paraíba and Rio Grande do Norte Using the MODIS Sensor

Autores

  • Madson Tavares Silva Universidade Federal de Campina Grande (UFCG) no Centro de Tecnologia e Recursos Naturais (CTRN), lotado na Unidade Acadêmica de Ciências Atmosféricas (UACA). http://orcid.org/0000-0003-1823-2742
  • Verônica Gabriella de Oliveira Federal University of Campina Grande, Academic Unit of Atmospheric Sciences, Center for Technology and Natural Resources http://orcid.org/0000-0002-5854-9261
  • Carlos Antonio Costa dos Santos Federal University of Campina Grande, Academic Unit of Atmospheric Sciences, Center for Technology and Natural Resources http://orcid.org/0000-0003-2414-2911
  • Lindenberg Lucena da Silva Federal University of Campina Grande, Academic Unit of Atmospheric Sciences, Center for Technology and Natural Resources http://orcid.org/0000-0001-7564-3455
  • Francineide Amorim Costa Santos Institute for Training of Educators, Federal University of Cariri, Brejo Santo, CE, Brazil. http://orcid.org/0000-0002-1290-0386
  • Edivaldo Afonso de Oliveira Serrão Federal University of Campina Grande, Academic Unit of Atmospheric Sciences, Center for Technology and Natural Resources http://orcid.org/0000-0003-2376-847X

DOI:

https://doi.org/10.11137/1982-3908_2022_45_42790

Palavras-chave:

Remote sensing, Albedo, Caatinga

Resumo

This study aimed to estimate the surface net radiation (Rn) for the States of Paraíba and Rio Grande do Norte and validate the results with data measured in validate the results with measurements in experimental recovering (CRec), degraded (CDeg), and preserved (CPres) areas of Caatinga. Seventeen images of the MODIS sensor on board the Terra satellite were selected for CRec and CDeg in the State of Paraíba and twenty-eight images for CPres in the state of Rio Grande do Norte, corresponding to the period of January to December 2014. The MODIS-Terra MOD09A1 and MOD11A2 products were used. Parametric (Shapiro-Wilk) and non-parametric (Kolmogorov-Smirnov and Wilcoxon-Mann-Whitney) tests were applied to understand the patterns. Statistical error indices were applied to verify the accuracy of the estimates in relation to the observed values. Only the measured albedo (α_meas) met the assumption of normality. According to mean absolute percentage error statistics, the model used to estimate the albedo was classified as inappropriate for CPres and CRec (> 25%), while it was satisfactory for CDeg (15-25%). Significant differences between observed and estimated values were absent only for the variable Rn in the three observation sites. The good performance of Rn estimates confirms the efficiency of the application of the method in semiarid regions.

Biografia do Autor

Madson Tavares Silva, Universidade Federal de Campina Grande (UFCG) no Centro de Tecnologia e Recursos Naturais (CTRN), lotado na Unidade Acadêmica de Ciências Atmosféricas (UACA).

Graduado em Meteorologia pela Universidade Federal de Campina Grande (2008). Mestre em Meteorologia, com área de concentração em Agrometeorologia e Micrometeorologia pela Universidade Federal de Campina Grande (2010). Doutor em Meteorologia pela Universidade Federal de Campina Grande (2014). Atualmente é Professor Adjunto Nível II da Universidade Federal de Campina Grande (UFCG) no Centro de Tecnologia e Recursos Naturais (CTRN), lotado na Unidade Acadêmica de Ciências Atmosféricas (UACA). Professor permanente dos Programas de Pós-Graduação em Meteorologia (PPGMET) e Recursos Naturais (PPGRN) da UFCG. Líder do Grupo de Pesquisas em Geotecnologias e modelagem de risco ambiental. Tem experiência na área de Meteorologia e Meio Ambiente, com ênfase em Agrometeorologia, Climatologia, Estatística Descritiva e Multivariada, Geoprocessamento e Sensoriamento Remoto (QGIS), atuando principalmente nos seguintes temas: séries temporais, modelagem agrometeorológica e hidrológica (SWAT), mudanças climáticas, zoneamento de risco climático, consumo hídrico de culturas e sensoriamento remoto aplicado à agricultura e clima urbano.

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Anuário do Instituto de Geociências volume 45. Ano 2022

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2022-07-01

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v. 45 (2022)

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Meteorologia

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