Abstract
Satellite-based precipitation estimates represent a potential alternative source of input data in a plethora of meteorological and hydrological applications, especially in regions characterized by a low density of rain gauge stations. Paraguay provides a good example of a case where the use of satellite-based precipitation could be advantageous. This study aims to evaluate the version 7 of the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TMPA V7; 3B42 V7) and the version 1.0 of the purely satellite-based product of the Climate Prediction Center Morphing Technique (CMORPH RAW) through their comparison with daily in situ precipitation measurements from 1998 to 2012 over Paraguay. The statistical assessment is conducted with several commonly used indexes. Specifically, to evaluate the accuracy of daily precipitation amounts, mean error (ME), root mean square error (RMSE), BIAS, and coefficient of determination (R2) are used, and to analyze the capability to correctly detect different precipitation intensities, false alarm ratio (FAR), frequency bias index (FBI), and probability of detection (POD) are applied to various rainfall rates (0, 0.1, 0.5, 1, 2, 5, 10, 20, 40, 60, and 80 mm/day). Results indicate that TMPA V7 has a better performance than CMORPH RAW over Paraguay. TMPA V7 has higher accuracy in the estimation of daily rainfall volumes and greater precision in the detection of wet days (> 0 mm/day). However, both satellite products show a lower ability to appropriately detect high intensity precipitation events.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Arkin PA, Meisner BN (1987) The relationship between large-scale convective rainfall and cold cloud over the western-hemisphere during 1982–84. Mon Weather Rev 115:51–74. https://doi.org/10.1175/1520-0493(1987)115<0051:TRBLSC>2.0.CO;2
Blacutt LA, Herdies DL, de Gonçalves LGG, Vila DA, Andrade M (2015) Precipitation comparison for the CFSR, MERRA, TRMM3B42 and combined scheme datasets in Bolivia. Atmos Res 163:117–131. https://doi.org/10.1016/j.atmosres.2015.02.002
Braun SA (2011) TRMM senior review proposal 2011. NASA Goddard Space Flight Center. pp 55. https://pmm.nasa.gov/resources/documents/trmm-senior-review-proposal-2011. Accessed 10 May 2017
Buarque DC, De Paiva RCD, Clarke RT, Mendes CAB (2011) A comparison of Amazon rainfall characteristics derived from TRMM, CMORPH and the Brazilian national rain gauge network. J Geophys Res Atmos 116(19):1–12. https://doi.org/10.1029/2011JD016060
Cabrera J, Yupanqui RT, Rau P (2016) Validation of TRMM daily precipitation data for extreme events analysis. The case of piura watershed in Peru. Proc Eng 154:154–157. https://doi.org/10.1016/j.proeng.2016.07.436
Collischonn B, Collischonn W, Tucci CEM (2001) Daily hydrological modeling in the Amazon basin using TRMM rainfall estimates. J Hydrol 360(1-4):207–216. https://doi.org/10.1016/j.jhydrol.2008.07.032
De Almeida CT, Delgado RC, De Oliveira JF, Gois G, Cavalcanti AS (2015) Avaliação das estimativas de precipitação do produto 3B43-TRMM do estado do Amazonas. Floresta e Ambiente 22(3):279–286. https://doi.org/10.1590/2179-8087.112114
de Goncalves LGG, Shuttleworth WJ, Nijssen B, Burke EJ, Marengo JA, Chou SC, Toll DL (2006) Evaluation of model-derived and remotely sensed precipitation products for continental South America. J Geophys Res 111:D16113. https://doi.org/10.1029/2005JD006276
Dinku T, Ruiz F, Connor SJ, Ceccato P (2010) Validation and intercomparison of satellite rainfall estimates over Colombia. J Appl Meteorol Climatol 49(5):1004–1014. https://doi.org/10.1175/2009JAMC2260.1
dos Reis J, Rennó C, Lopes E (2017) Validation of satellite rainfall products over a mountainous watershed in a humid subtropical climate region of Brazil. Remote Sens 9(12):1240. https://doi.org/10.3390/rs9121240
Duan Z, Liu J, Tuo Y, Chiogna G, Disse M (2016) Evaluation of eight high spatial resolution gridded precipitation products in Adige Basin (Italy) at multiple temporal and spatial scales. Sci Total Environ 573:1536–1553. https://doi.org/10.1016/j.scitotenv.2016.08.213
Ebert EE, Janowiak JE, Kidd C (2007) Comparison of near-real-time precipitation estimates from satellite observations and numerical models. Bull Am Meteorol Soc 88(1):47–64. https://doi.org/10.1175/BAMS-88-1-47
Federal Research Division of the Library of Congress of the United States Government (1990) Paraguay: a country study. In: Hanratty DM, Meditz SW (eds) Library of Congress, Washington. http://countrystudies.us/paraguay/2.htm. Accessed 10 July 2017
Ferraro RR (1997) Special sensor microwave imager derived global rainfall estimates for climatological applications. J Geophys Res 102:16715–16735. https://doi.org/10.1029/97JD01210
Hobouchian MP, Salio P, García Skabar Y, Vila D, Garreaud R (2017) Assessment of satellite precipitation estimates over the slopes of the subtropical Andes. Atmos Res 190:43–54. https://doi.org/10.1016/j.atmosres.2017.02.006
Huffman GJ (2013) Algorithm 3B42: TRMM merged HQ/infrared precipitation. https://trmm.gsfc.nasa.gov/3b42.html. Accessed 24 June 2017
Huffman GJ (2016) The transition in multi-satellite products from TRMM to GPM (TMPA to IMERG). https://pmm.nasa.gov/sites/default/files/document_files/TMPA-to-IMERG_transition_161025.pdf. Accessed 10 May 2017
Huffman GJ, Bolvin DT (2017) TRMM and other data precipitation data set documentation. ftp://meso-a.gsfc.nasa.gov/pub/trmmdocs/3B42_3B43_doc.pdf. Accessed 27 July 2017
Huffman GJ, Bolvin DT, Nelkin EJ, Wolff DB, Adler RF, Gu G, Stocker EF (2007) The TRMM Multisatellite Precipitation Analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J Hydrometeorol 8(1):38–55. https://doi.org/10.1175/JHM560.1
Jiang S, Zhou M, Ren LL, Cheng XR, Cheng X, Zhang PJ (2016) Evaluation of latest TMPA and CMORPH satellite precipitation products over Yellow River Basin. Water Sci Eng 9(2):87–96. https://doi.org/10.1016/j.wse.2016.06.002
Jiang S, Liu S, Ren L, Yong B, Zhang L, Wang M, He Y (2017) Hydrologic evaluation of six high resolution satellite precipitation products in capturing extreme precipitation and streamflow over a medium-sized basin in China. Water (Switzerland) 10(1):1–17. https://doi.org/10.3390/w10010025
Joyce RJ, Janowiak JE, Arkin PA, Xie P (2004) CMORPH: a method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J Hydrometeorol 5(3):487–503. https://doi.org/10.1175/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2
Manz B, Buytaert W, Zulkafli Z, Lavado W, Willems B, Robles LA, Rodríguez-Sánchez JP (2016) High-resolution satellite-gauge merged precipitation climatologies of the tropical andes. J Geophys Res 121(3):1190–1207. https://doi.org/10.1002/2015JD023788
Melo DDC, Xavier AC, Bianchi T, Oliveira PTS, Scanlon BR, Lucas MC, Wendland E (2016) Performance evaluation of rainfall estimates by TRMM Multi-satellite Precipitation Analysis 3B42V6 and V7 over Brazil. J Geophys Res Atmos 120:9426–9436. https://doi.org/10.1002/2015JD023797
National Aeronautics and Space Administration (2016) TRMM SATELLITE AND INSTRUMENTS—GES DISC—Goddard Earth Sciences Data and Information Services Center. https://pmm.nasa.gov/TRMM/trmm-instruments. Accessed 24 June 2017
National Space Development Agency of Japan (2001) TRMM data users handbook. http://www.eorc.jaxa.jp/TRMM/document/text/handbook_e.pdf. Accessed 10 Mar 2017
Prakash S, Mitra AK, AghaKouchak A, Liu Z, Norouzi H, Pai DS (2018) A preliminary assessment of GPM-based multi-satellite precipitation estimates over a monsoon dominated region. J Hydrol 556:865–876. https://doi.org/10.1016/j.jhydrol.2016.01.029
Quirino DT, Casaroli D, Jucá Oliveira RA, Mesquita M, Pego Evangelista AW, Alves Júnior J (2017) Evaluation of TRMM satellite rainfall estimates (algorithms 3B42 V7 & RT) over the Santo Antônio county (Goiás, Brazil). Revista Facultad Nacional de Agronomía 70(3):8251–8261. https://doi.org/10.15446/rfna.v70n3.61805
Ringard J, Becker M, Seyler F, Linguet L (2015) Temporal and spatial assessment of four satellite rainfall estimates over French Guiana and north Brazil. Remote Sens 7(12):16441–16459. https://doi.org/10.3390/rs71215831
Ruiz JJ (2009) Evaluación de Diferentes Metodologías para la Calibración de Precipitación CMORPH sobre Sudamérica. Revista Brasileira de Meteorología 24(4):473–488. https://doi.org/10.1590/S0102-77862009000400009
Ruiz J, Saulo C, Kalnay E (2009) Comparison of methods used to generate probabilistic quantitative precipitation forecasts over South America. Weather Forecast 24(1):319–336. https://doi.org/10.1175/2008WAF2007098.1
Salio P, Hobouchian MP, García Skabar Y, Vila D (2015) Evaluation of high-resolution satellite precipitation estimates over southern South America using a dense rain gauge network. Atmos Res 163:146–161. https://doi.org/10.1016/J.ATMOSRES.2014.11.017
Scheel MLM, Rohrer M, Huggel C, Santos Villar D, Silvestre E, Huffman GJ (2011) Evaluation of TRMM Multi-satellite Precipitation Analysis (TMPA) performance in the Central Andes region and its dependency on spatial and temporal resolution. Hydrol Earth Syst Sci 15(8):2649–2663. https://doi.org/10.5194/hess-15-2649-2011
Sepulcri MG, Di Bella CM, Moschini RC (2009) Validación de la Ocurrencia de Lluvia Estimada a partir del Algoritmo 3B42 de TRMM con Datos Pluviométricos en la Región Pampeana. XIII Latin American and Iberian Congress of Meteorology and X Argentine Congress of Meteorology, 5–9 Oct 2009, Buenos Aires, Argentina
Su F, Hong Y, Lettenmaier DP (2008) Evaluation of TRMM Multisatellite Precipitation Analysis (TMPA) and its utility in hydrologic prediction in the La Plata Basin. J Hydrometeorol 9(4):622–640. https://doi.org/10.1175/2007JHM944.1
Sun R, Yuan H, Liu X, Jiang X (2016) Evaluation of the latest satellite-gauge precipitation products and their hydrologic applications over the Huaihe River basin. J Hydrol 536(March):302–319. https://doi.org/10.1016/j.jhydrol.2016.02.054
Wilheit T, Alder R, Avery S, Barrett E, Bauer P, Berg W et al (1994) Algorithms for the retrieval of rainfall from passive microwave measurements. Remote Sens Rev 11:163–194. https://doi.org/10.1080/02757259409532264
Wilks DS (2006) Statistical methods in the atmospheric sciences. Int Geophys Ser (Elsevier). https://doi.org/10.1002/met.16
Wu L, Zhai P (2012) Validation of daily precipitation from two high-resolution satellite precipitation datasets over the Tibetan Plateau and the regions to its east. Acta Meteorol Sin 26(6):735–745. https://doi.org/10.1007/s13351-012-0605-2
Xie P, Joyce R, Wu S, Yoo S-H, Yarosh Y, Sun F, Lin R (2017) Reprocessed, bias-corrected CMORPH global high-resolution precipitation estimates from 1998. J Hydrometeorol 18(6):1617–1641. https://doi.org/10.1175/JHM-D-16-0168.1
Zambrano-Bigiarini M, Nauditt A, Birkel C, Verbist K, Ribbe L (2017) Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile. Hydrol Earth Syst Sci 21(2):1295–1320. https://doi.org/10.5194/hess-21-1295-2017
Zeng Q, Wang Y, Chen L, Wang Z, Zhu H, Li B (2018) Inter-comparison and evaluation of remote sensing precipitation products over China from 2005 to 2013. Remote Sens 10(3):168. https://doi.org/10.3390/rs10020168
Zubieta R, Getirana A, Espinoza JC, Lavado W (2015) Impacts of satellite-based precipitation datasets on rainfall-runoff modelling of the Western Amazon basin of Peru and Ecuador. J Hydrol 528:599–612. https://doi.org/10.1016/j.jhydrol.2015.06.064
Acknowledgements
This work was supported by the Inter-American Institute for Global Change Research (IAI) through the Collaborative Research Network (CRN-3035). The authors acknowledge the Paraguayan Directorate of Meteorology and Hydrology (DMH/DINAC) for the provision of rain gauge data, and NASA and NOAA for their ongoing efforts to develop high quality precipitation estimates.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Oreggioni Weiberlen, F., Báez Benítez, J. Assessment of satellite-based precipitation estimates over Paraguay. Acta Geophys. 66, 369–379 (2018). https://doi.org/10.1007/s11600-018-0146-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11600-018-0146-x