EVALUATION OF TRMM 3B43V7 SATELLITE PRECIPITATION IN THE PANTANAL OF MATO GROSSO DO SUL IN THE YEARS 1998 TO 2019

Abstract

Remote sensing can assist in the acquisition of scarce surface data. The analyzes for validation of the precipitation product estimated by the TRMM satellite (Tropical Rainfall Measuring Mission) were carried out with the precipitation data observed on the surface during the period from 1998 to 2019. For this purpose, precipitation data from the Pantanal biome meteorological stations were used, located between the 16 and 22°S parallels and the 55 and 58°W meridians, and compared with the data from the TRMM 3B42 V7 product algorithms. Statistical analysis was performed based on the correlation coefficient, root mean square error (RMSE), and relative bias (BIAS) between the monthly precipitation data observed on the surface and the estimated precipitation data. The results found for product 3B43 V7 indicated that the precipitation estimates were representative when compared to the surface observations. However, when compared for the rainy and dry periods, there was underestimation and overestimation, respectively, of the product. The product 3B42 V7 satisfactorily represents the precipitation that occurs on the surface.

Keywords: Tropical Rainfall, Remote Sensing, Conventional Meteorological Observation Precipitation Estimate.

Author Biographies

Amaury de Souza, Federal University of Mato Grosso do Sul, Campo Grande (MS), Brazil

PhD in Environmental Technologies Federal University of Mato Grosso do Sul (2013).

Laura Thebit Almeida, Federal University of Visoça, Visoça (CE), Brazil

Master's degree in Applied Meteorology from the Federal University of Viçosa (UFV), city of Viçosa, completed in 2017. Today he is in the doctoral program in Applied Meteorology, from the Federal University of Viçosa (UFV), with a research line in Hydroclimatology. In this segment, he has sought specialization in the area of water resources, water and soil conservation, GIS and data geoprocessing.

Marcel Carvalho Abreu, University of Rio de Janeiro, Seropédica (RJ), Brazil

PhD in Agronomy (Applied Meteorology) from the Federal University of Viçosa (2018). He is currently an adjunct professor at the Institute of Forestry at the Federal Rural University of Rio de Janeiro, working at the Department of Environmental Sciences. He works mainly in the areas of agrometeorology, modeling of plant growth and production, hydroclimatology and watershed management.

José Francisco de Júnior Oliveira Júnior, Federal University of Alagoas, Maceió, (AL), Brazil

PhD in Atmospheric Sciences, in Civil Engineering from the Federal University of Rio de Janeiro - COPPE (2008) and Post-Doctorate in Mechanical Engineering - COPPE/UFRJ (2011) in the area of Transport Phenomena (Fluid Mechanics). Founding member of UNEMET (National Union of Scholars in Meteorology - http://www.unemet.org.br/) - (2002). She acted as Supervisory Internship Advisor linked to the CIEC (Intergrade Coordination of Internships and Contest) of projects with Escola Pública de Seropédica. Participation as Advisor in the Project Young Talents for Science financed by FAPERJ (2004). Participation as an Advisor in the Supervised Guidance Project at UFRRJ through SINTEEG (School/Company/Government Integration Sector) (2011). Participation in Extension Projects at UFRJ, called (1) El Nio: Extending Horizons and Frontiers of Time; (2) FEEL: Discovering the Signs of the Time; (3) Living Atmosphere and (4) GIS-Schools - Extension Activities of the Department of Meteorology - UFRJ (2010). Scholarship holder for Industrial Technological Development in categories DTI/7B and 7A (CNPq-MCT) at the National Nuclear Energy Commission - CNEN, in the areas of Radiological Safety in Mining-Industrial Installations and in Radioactive Waste Deposits, from 2005 to 2010. Participation in the Air Quality Prognosis and Interdisciplinary Research Groups on Remote Sensing, Meteorology, Oceanography and Applications - UFRJ. Participation as Research Associate in the Universities of UBU (University of Burgos - Spain) - PKNU (Purkyong National University - South Korea). Participation as Researcher-Collaborator in the Laboratory of Modeling of Marine and Atmospheric Processes (LAMMA) - Computational Nucleus for the Study of Air Quality - NCQAr-UFRJ (Federal University of Rio de Janeiro - Rio de Janeiro). Member of the European Geophysical Society - COSIS.net. Currently, Associate Professor I at the Institute of Atmospheric Sciences (ICAT) at the Federal University of Alagoas (UFAL) and leader of the Laboratory of Environment and Applied Meteorology (LAMMA). Former Professor at the Instituto de Floresta (IF) - Department of Environmental Sciences (DCA) at the Federal Rural University of Rio de Janeiro (UFRRJ) from 2011 to 2017. Professor of the Postgraduate Courses in Biosystems Engineering at the Fluminense Federal University (PGEB) - UFF, of the Postgraduate Studies in Sustainable Development Practices (PPGPDS) - UFRRJ, of the Postgraduate Studies in Meteorology (PPGMET) - UFAL and Ex- Professor of the Graduate Program in Environmental and Forestry Sciences (PPGCAF) - (Collaborator). As supervisor and co-supervisor he has already formed (13) Masters and (2) Doctors. Reviewer for national (12) and international (22) journals. Currently, I participate in the Applied Geotechnology Group in Agriculture and Forestry (GAAF) as a guest researcher at the State University of Mato Grosso (UNEMAT) and Associate Editor of the Journal of Agro-Environmental Sciences (http://periodicos.unemat.br/index .php/rcaa/index) from UNEMAT. Editor-in-Chief of Meteorology and Climatology of the Journal of Atmospheric Science Research (http://ojs.bilpublishing.com/index.php/jasr/). ICAT/UFAL Extension Coordinator (2018). He has experience in Geosciences, with emphasis on Environmental Meteorology, Micrometeorology, Atmospheric Modeling, Mountain and Coastal Meteorology, Agrometeorology, Urban Meteorology, Climatology and Fire Meteorology, working mainly on the following topics: Climate and Health, Catastrophes and Natural Disasters, Layer Atmospheric Limit, Statistical Methods, GIS Tools, Meteorological Radar, Computational Modeling, Air Quality, Atmospheric Pollution.

Ivana Pobocikova, University of Žilina, Žilina, Slovakia

Professor, Department of Applied Mathematics, University of Žilina. Univerzitna 8215/1, 01026, Žilina, Slovakia. 79070-900.

Renata Graf, . Adam Mickiewicz University, Poznań, Poland.

Ph.D., D.Sc. Professor UAM, Department of Hydrology and Water Management, Institute of Physical Geography and Environmental Planning, Adam Mickiewicz University, Bogumiła Krygowskiego 10 str., 61-680 Poznań, Poland

References

Aires, U.R.V.; Neto, J.O.M. & Mello, C.R. - Estimativas de precipitação derivadas do satélite TRMM para a bacia hidrográfica do rio Paraopeba, MG. Revista Scientia Agraria, (2016), vol. 17, n. 2, p. 57-66. http://dx.doi.org/10.5380/rsa.v17i2.46384
Alho CJR, Mamede SB, Benites M, Andrade BS and Sepúlveda JJO. (2019). Threats to the biodiversity of the Brazilian Pantanal due to land use and occupation. Ambiente & Sociedade, 22, 1-22.
Almazroui M. Calibration of TRMM rainfall climatology over Saudi Arabia during 1998–2009. Atmospheric Research. 2011, 99: 400– 414, DOI: 10.1016/j.atmosres.2010.11.006

Almeida, C.T.; Delgado, R.C.; Oliveira Junior, J.F.; Gois, G. & Cavalcanti, A.S. Avaliação das Estimativas de Precipitação do Produto 3B43-TRMM do Estado do Amazonas. Revista Floresta e Ambiente. 2015, vol. 22, n. 3, p. 279-286. http://dx.doi.org/10.1590/2179-8087.112114

Alvares, C.A., Stape, J.L., Sentelhas, P.C., De Moraes Gonçalves, J.L., Sparovek, G., 2013. Köppen’s climate classification map for Brazil. Meteorol. Zeitschrift 22, 711–728. https://doi.org/10.1127/0941-2948/2013/0507

Camparotto, L.B.; Blain, G.C.; Giarolla, A.; Adami, M. & Camargo, M.B. - Validação de dados termopluviométricos obtidos via sensoriamento remoto para o Estado de São Paulo. Revista Brasileira de Engenharia Agricola e Ambiental. 2013, vol. 17, n. 6, p. 665-671. http://dx.doi.org/10.1590/S1415-43662013000600013

Chen FR, Li X. Evaluation of IMERG and TRMM 3B43 monthly precipitation products over mainland China. Remote Sensing. 2016;8(6) doi: 10.3390/rs8060472.


Chen S, Gourley JJ, Hong Y, Kirstetter PE, Zhang J, Howard K, Flamig ZL, Hu JJ, Qi YC. Evaluation and uncertainty estimation of NOAA/NSSL next-generation National mosaic quantitative precipitation estimation product (Q2) over the continental United States. Journal of Hydrometeorology. 2013a;14:1308–1322. doi: 10.1175/JHM-D-12-0150.1.

Chen S, Hong Y, Cao Q, Gourley JJ, Kirstetter PE, Yong B, Tian YD, Zhang ZX, Shen Y, Hu JJ. Similarity and difference of the two successive V6 and V7 TRMM multisatellite precipitation analysis performance over China. Journal of Geophysical Research: Atmospheres. 2013b;118:13060–13074. doi: 10.1002/2013JD019964.
Chian-Yi Liu, Putu Aryastana, Gin-Rong Liu, Wan-Ru Huang, Assessment of satellite precipitation product estimates over Bali Island, Atmospheric Research, Volume 244, 2020, 105032, https://doi.org/10.1016/j.atmosres.2020.105032.
Collischonn B., Allasia D., Collsischonn W. et Tucci C. E. M,: Desempenho do satelite TRMM na estimativa de precipitação sobre a bacia do Paraguai superior. Revista Brasileira de Cartografia, 2007, 59, 93-99.
de Almeida, K.N., dos Reis, J.A.T., Buarque, D.C. et al. Performance analysis of TRMM satellite in precipitation estimation for the Itapemirim River basin, Espirito Santo state, Brazil. Theor Appl Climatol 141, 791–802 (2020). https://doi.org/10.1007/s00704-020-03204-5
Dubreuil V., Jallet A., Ronchail r. et Maitelli g.,: Estimation des précipitations par télédétection au Mato Grosso (Brésil). Annales de I'Association Internationale de Climatologie, 2004, 1, 133-156.
Fleming, K.; Awange, J.L.; Kuhn, M. & Featherstone, W.E. - Evaluating the TRMM 3B43 monthly precipitation product using gridded raingauge data over Australia. Australian Meteorological and Oceanographic Journal, (2011), vol. 61, p. 171-184.
Franca, R. R. Climatologia das chuvas em Rondônia–período 1981-2011. Revista Geografias, v. 1, n. 20, p. 44-58, 2015.

Gois, G.; Delgado, R. C.; Oliveira-Júnior, J. F. Modelos teóricos transitivos aplicados na interpolação espacial do standardized precipitation index (SPI) para os episódios de El Niño forte no estado do Tocantins, Brasil. Irriga, 2015, v. 20, n. 2, p. 371-387.

Gonzalez, R. A.; Andreoli, R. V.; Candido, L. A.; Kayano, M. T.; Souza, R. A. F. A influência do evento El Niño –Oscilação Sul e Atlântico Equatorial na precipitação sobre as regiões norte e nordeste da América do Sul. Acta Amazônica, 2013, v. 43, n. 4, p.469-480.

Guo H, Chen S, Bao AM, Behrangi A, Hong Y, Ndayisaba F, Hu JJ, Stepanian PM. Early assessment of integrated multi-satellite retrievals for global precipitation measurement over China. AtmosphericResearchs. 2016;176–177:121–133. doi: 10.1016/j.atmosres.2016.02.020.

Habib E, Haile AT, Tian YD, Joyce RJ. Evaluation of the high-resolution CMORPH satellite rainfall product using dense rain gauge observations and radar-based estimates. Journal of Hydrometeorology. 2012;13:1784–1798. doi: 10.1175/JHM-D-12-017.1.

Huffman GJ, Bolvin DT, Nelkin EJ, Wolff DB, Adler RF, Gu G, Hong Y, Bowman KP, Stocker EF. The TRMM multisatellite precipitation analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. Journal of Hydrometeorology. 2007;8:38–55. doi: 10.1175/JHM560.1.

Kidd C, Bauer P, Turk J, Huffman GJ, Joyce R, Hsu KL, Braithwaite D. Intercomparison of high-resolution precipitation products over northwest Europe. Journal of Hydrometeorology. 2012;13:67–83. doi: 10.1175/JHM-D-11-042.1.

Kummerow C, Barnes W, Kozu T, Shiue J, Simpson J. The tropical rainfall measuring mission (TRMM) sensor package. Journal of Atmospheric and Oceanic Technology. 1998; 15:809–817. doi: 10.1175/1520-0426(1998)015<0809:TTRMMT>2.0.CO;2.

Kummerow C, Hong Y, Olson W, Yang S, Adler R, McCollum J, Ferraro R, Petty G, Shin D-B, Wilheit T. The evolution of the goddard profiling algorithm (GPROF) for rainfall estimation from passive microwave sensors. Journal of Applied Meteorology. 2001; 40:1801–1820. doi: 10.1175/1520-0450(2001)040<1801:TEOTGP>2.0.CO;2.

Limberger, L.; Silva, M. E. S. Precipitação na bacia amazônica e sua associação à variabilidade da temperatura da superfície dos oceanos Pacífico e Atlântico: uma revisão. Geousp –Espaço e Tempo, 2016, v. 20, n. 3, p. 657-675.

Liu Z. Comparison of versions 6 and 7 3-hourly TRMM multi-satellite precipitation analysis (TMPA) research products. Atmospheric Research. 2015;163:91–101. doi: 10.1016/j.atmosres.2014.12.015.

Lyra, G. B.; Oliveira-Júnior, J. F.; Gois, G.; Cunha-Zeri, G.; Zeri, M. Rainfall variability over Alagoas under the influences of SST anomalies. Meteorology and Atmospheric Physics, 2017, v. 129, n. 1, p. 157-171.

Ma Y, Tang G, Long D, Yong B, Zhong L, Wan W, Hong Y. Similarity and error intercomparison of the GPM and its predecessor-TRMM multisatellite precipitation analysis using the best available hourly gauge network over the Tibetan Plateau. Remote Sensing. 2016;8 doi: 10.3390/rs8070569.Article 569.

Maggioni V, Meyers PC, Robinson MD. A review of merged high-resolution satellite precipitation product accuracy during the Tropical Rainfall Measuring Mission (TRMM) era. Journal of Hydrometeorology. 2016;17:1101–1117. doi: 10.1175/jhm-d-15-0190.1.

Mantas VM, Liu Z, Caro C, Pereira AJSC. Validation of TRMM multi-satellite precipitation analysis (TMPA) products in the Peruvian Andes. Atmospheric Research. 2015;163:132–145. doi: 10.1016/j.atmosres.2014.11.012.

Mehta AV, Yang S. Precipitation climatology over Mediterranean Basin from ten years of TRMM measurements. Advances in Geosciences. 2008;17:87–91. doi: 10.5194/adgeo-17-87-2008.

Nair S, Srinivasan G, Nemani R. Evaluation of multi-satellite TRMM derived rainfall estimates over a western state of India. Journal of the Meteorological Society of Japan. 2010; 87:927–939. doi: 10.2151/jmsj.87.927.
Nóbrega, R.S.; Souza, E.P. & Galvíncio, J.D. - Análise da estimativa de precipitação do TRMM em uma sub-bacia da Amazônia Ocidental. Revista de Geografia, (2008), vol. 25, n. 1, p. 6-20.
Oliveira-Júnior, J. F., Xavier, F. M. G., Teodoro, P. E., Gois, G., Delgado, R. C. Cluster analysis identified rainfall homogeneous regions in Tocantins state, Brazil. Bioscience Journal (On line), 2017, v.33, n. 2, p. 333-340.
Oliveira, A. S. Interações entre Sistemas Frontais e a atividade convectiva na Amazônia. 1986. Dissertação (Mestrado em Meteorologia) - INPE, São José dos Campos, 1986.
Oliveira, R.J. & Angelis, C.F. - Análise do comportamento de precipitação estimada por satélite sobre áreas de intenso desmatamento na Amazônia Legal. In: XVI Congresso Brasileiro de Meteorologia. Belém, Brasil, CBMet. (2010) http://www.cbmet2010.com/anais/artigos/781_45961.pdf .
Pereira, G.; Silva, M. E. S.; Moraes, E. C.; Cardozo, F. S. Avaliação dos Dados de Precipitação Estimados pelo Satélite TRMM para o Brasil. RBRH – Revista Brasileira de Recursos Hídricos, set. 2013, v. 18, n. 3, p.139-148. http://dx.doi. org/10.21168/rbrh.v18n3, p139-148
Pessi , D.D.et al. Validation of the monitors of the TRMM soil satellite in the State of Mato Grosso, Brazil. Rev. de Ciências Agrárias vol.42 no.1 Lisboa mar. 20192019. http://dx.doi.org/10.19084/RCA18217
Rozante, J.R.; Moreira, D.S.; Gonçalves, L.G.G. & Vila, D. - Combining TRMM and surface observation of precipitation: technique and validation over South America. Weather and Forecasting, (2010) , p. 885-894. https:// doi.org/10.1175/2010WAF2222325.1
Seyyedi H, Anagnostou EN, Beighley E, Mccollum J. Hydrologic evaluation of satellite and reanalysis precipitation datasets over a mid-latitude basin. Atmospheric Research. 2015;164–165:37–48. doi: 10.1016/j.atmosres.2015.03.019.

Shrivastava R, Dash SK, Hegde MN, Pradeepkumar KS, Sharma DN. Validation of the TRMM multi satellite rainfall product 3B42 and estimation of scavenging coefficients for 131 I and 137 Cs using TRMM 3B42 rainfall data. Journal of Environmental Radioactivity. 2014;138:132–136. doi: 10.1016/j.jenvrad.2014.08.011.

Silva-Fuzzo, D.F. & Rocha, J.V. - Validação dos dados de precipitação estimados pelo TRMM, para o Estado do Paraná, e sua contribuição ao monitoramento agrometeorológico. Revista Formação (ONLINE). 2016, vol. 3, n. 23, p. 301-316.
Soares, A. S. D.; Paz, A. R.; Piccilli, D. G. A. Avaliação das estimativas de chuva do satélite TRMM no estado da Paraíba. RBRH, 2016, v. 21, p. 288-299.
Soetania, et al,. Spatiotemporal characterization of precipitation in Mato Grosso do Sul: rainfall distribution and anomaly(rai) Analysis for climate phenomena. Revista Brasileira de Climatologia. 2020, p. 181-201. doi.org/10.5380/abclima.v27i0.69407

Souza, A.; Abreu, M. C.; De Oliveira-Júnior, J. F. ; Dos Santos, C. M.; Pobocikova, I. ; Fernandes, W. A. ; Torsen, E. ; Da Silva, E. B. ; Mbaga, Y. V. . Study of Aerosol Optical Depth Climatology Using Modis Remote Sensing Data. European Chemical Bulletin, 2020, v. 9, p. 291. DOI: 10.17628/ecb.2020.9.291-299

Tang L, Tian YD, Yan F, Habib E. An improved procedure for the validation of satellite-based precipitation estimates. Atmospheric Research. 2015;163:61–73. doi: 10.1016/j.atmosres.2014.12.016.

Teodoro PE, Oliveira-Júnior JF, Cunha ER, Correa CCG, Torres FE, Bacani VM, Gois G, Ribeiro LP Cluster analysis applied to the spatial and temporal variability of monthly rainfall in Mato Grosso do Sul State. Brazil Meteorol Atmos Phys. 2015, 128:197–209. https://doi.org/10.1007/s00703-015-0408-y
Van Liew, M.; Veith, T.; Bosch, D.; Arnald, J. Suitability of SWAT for the Conservation Effects Assessment Project: Comparison on USDA Agricultural Research Service Watersheds. Journal of Hydrological Research, London, 2007, v.12, n.2, p. 173-189.
Viana, D.R.; Ferreira, N.J. & Conforte, J.C. - Avaliação das estimativas de precipitação 3B42 e 3B43 do satélite TRMM na Região Sul do Brasil. In: XVI Congresso brasileiro de Meteorologia. Belém, Brasil, CBMet. http://www.cbmet2010.com/anais/. (2010)
Xie P, Arkin PA. Analyses of global monthly precipitation using gauge observations, satellite estimates, and numerical model predictions. Journal of Climate. 1996;9(4):840–858. doi: 10.1175/15200442(1996)009<0840:AOGMPU>2.0.CO;2.

Yang S, Smith EA. Convective-stratiform precipitation variability at seasonal scale from eight years of TRMM observations: implications for multiple modes of diurnal variability. Journal of Climate. 2008;21(16):4087–4114. doi: 10.1175/2008JCLI2096.1.

Yang, Y., Luo, Y. Evaluating the performance of remote sensing precipitation products CMORPH, PERSIANN, and TMPA, in the arid region of northwest China. Theor Appl Climatol 118, 429–445 (2014). https://doi.org/10.1007/s00704-013-1072-0

Zhao HG, Yang B, Yang ST, Huang YC, Dong GT, Bai J, Wang ZW. Systematical estimation of GPM-based global satellite mapping of precipitation products over China. Atmospheric Research. 2018;201:206–217. doi: 10.1016/j.atmosres.2017.11.005.

Zhu GF, Qin DH, Liu YF, Chen FL, Hu PF, Chen DF, Wang K. Accuracy of TRMM precipitation data in the southwest monsoon region of China. Theoretical and Applied Climatology. 2017;129:353–362. doi: 10.1007/s00704-016-1791-0.
Published
04/02/2023
How to Cite
SOUZA, Amaury de et al. EVALUATION OF TRMM 3B43V7 SATELLITE PRECIPITATION IN THE PANTANAL OF MATO GROSSO DO SUL IN THE YEARS 1998 TO 2019. Mercator, Fortaleza, v. 21, feb. 2023. ISSN 1984-2201. Available at: <http://www.mercator.ufc.br/mercator/article/view/e21023>. Date accessed: 26 apr. 2024. doi: https://doi.org/10.4215/rm2022.e21023.
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