Assessment of SM2RAIN-Derived and State-of-the-Art Satellite Rainfall Products over Northeastern Brazil
Microwave-based satellite rainfall products offer an opportunity to assess rainfall-related events for regions where rain-gauge stations are sparse, such as in Northeast Brazil (NEB). Accurate measurement of rainfall is vital for water resource managers in this semiarid region. In this work, the SM2...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-07-01
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| Series: | Remote Sensing |
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| Online Access: | http://www.mdpi.com/2072-4292/10/7/1093 |
| _version_ | 1798017606591971328 |
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| author | Franklin Paredes-Trejo Humberto Alves Barbosa Luciana Rossato Spatafora |
| author_facet | Franklin Paredes-Trejo Humberto Alves Barbosa Luciana Rossato Spatafora |
| author_sort | Franklin Paredes-Trejo |
| collection | DOAJ |
| description | Microwave-based satellite rainfall products offer an opportunity to assess rainfall-related events for regions where rain-gauge stations are sparse, such as in Northeast Brazil (NEB). Accurate measurement of rainfall is vital for water resource managers in this semiarid region. In this work, the SM2RAIN-CCI rainfall data obtained from the inversion of the microwave-based satellite soil moisture (SM) observations derived from the European Space Agency (ESA) Climate Change Initiative (CCI), and ones from three state-of-the-art rainfall products (Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), Climate Prediction Center Morphing Technique (CMORPH), and Multi-SourceWeighted-Ensemble Precipitation (MSWEP)) were evaluated against in situ rainfall observations under different bioclimatic conditions at the NEB (e.g., AMZ, Amazônia; CER, Cerrado; MAT, Mata Atlântica; and CAAT, Caatinga). Comparisons were made at daily, 5-day, and 0.25° scales, during the time-span of 1998 to 2015. It was found that 5-day SM2RAIN-CCI has a reasonably good performance in terms of the correlation coefficient over the CER biome (R median: 0.75). In terms of the root mean square error (RMSE), it exhibits better performance in the CAAT biome (RMSE median: 12.57 mm). In terms of bias (B), the MSWEP, SM2RAIN-CCI, and CHIRPS datasets show the best performance in MAT (B median: −8.50%), AMZ (B median: −0.65%), and CER (B median: 0.30%), respectively. Conversely, CMORPH poorly represents the rainfall variability in all biomes, particularly in the MAT biome (R median: 0.43; B median: −67.50%). In terms of detection of rainfall events, all products show good performance (Probability of detection (POD) median > 0.90). The performance of SM2RAIN-CCI suggests that the SM2RAIN algorithm fails to estimate the amount of rainfall under very dry or very wet conditions. Overall, results highlight the feasibility of SM2RAIN-CCI in those poorly gauged regions in the semiarid region of NEB. |
| first_indexed | 2024-04-11T16:10:00Z |
| format | Article |
| id | doaj.art-c15b639915774b129988b4685bb2c02d |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-04-11T16:10:00Z |
| publishDate | 2018-07-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj.art-c15b639915774b129988b4685bb2c02d2022-12-22T04:14:44ZengMDPI AGRemote Sensing2072-42922018-07-01107109310.3390/rs10071093rs10071093Assessment of SM2RAIN-Derived and State-of-the-Art Satellite Rainfall Products over Northeastern BrazilFranklin Paredes-Trejo0Humberto Alves Barbosa1Luciana Rossato Spatafora2Department of Civil Engineering, University of the Western Plains ‘Ezequiel Zamora’, San Carlos Campus 2201, VenezuelaLaboratório de Análise e processamento de Imagens de Satélites (LAPIS), Instituto de Ciências Atmosféricas, Universidade Federal de Alagoas, A. C. Simões Campus, 57072-900 Maceió, Alagoas, BrazilIEEC/UPC and SMOS Barcelona Expert Centre, Universitat Politècnica de Catalunya, Jordi Girona 1-3UPC Campus Nord, Building D3, 08034 Barcelona, SpainMicrowave-based satellite rainfall products offer an opportunity to assess rainfall-related events for regions where rain-gauge stations are sparse, such as in Northeast Brazil (NEB). Accurate measurement of rainfall is vital for water resource managers in this semiarid region. In this work, the SM2RAIN-CCI rainfall data obtained from the inversion of the microwave-based satellite soil moisture (SM) observations derived from the European Space Agency (ESA) Climate Change Initiative (CCI), and ones from three state-of-the-art rainfall products (Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), Climate Prediction Center Morphing Technique (CMORPH), and Multi-SourceWeighted-Ensemble Precipitation (MSWEP)) were evaluated against in situ rainfall observations under different bioclimatic conditions at the NEB (e.g., AMZ, Amazônia; CER, Cerrado; MAT, Mata Atlântica; and CAAT, Caatinga). Comparisons were made at daily, 5-day, and 0.25° scales, during the time-span of 1998 to 2015. It was found that 5-day SM2RAIN-CCI has a reasonably good performance in terms of the correlation coefficient over the CER biome (R median: 0.75). In terms of the root mean square error (RMSE), it exhibits better performance in the CAAT biome (RMSE median: 12.57 mm). In terms of bias (B), the MSWEP, SM2RAIN-CCI, and CHIRPS datasets show the best performance in MAT (B median: −8.50%), AMZ (B median: −0.65%), and CER (B median: 0.30%), respectively. Conversely, CMORPH poorly represents the rainfall variability in all biomes, particularly in the MAT biome (R median: 0.43; B median: −67.50%). In terms of detection of rainfall events, all products show good performance (Probability of detection (POD) median > 0.90). The performance of SM2RAIN-CCI suggests that the SM2RAIN algorithm fails to estimate the amount of rainfall under very dry or very wet conditions. Overall, results highlight the feasibility of SM2RAIN-CCI in those poorly gauged regions in the semiarid region of NEB.http://www.mdpi.com/2072-4292/10/7/1093satellite rainfallsoil moistureSM2RAINCHIRPSMSWEPmicrowave sensorsNortheast BrazilCMORPH |
| spellingShingle | Franklin Paredes-Trejo Humberto Alves Barbosa Luciana Rossato Spatafora Assessment of SM2RAIN-Derived and State-of-the-Art Satellite Rainfall Products over Northeastern Brazil Remote Sensing satellite rainfall soil moisture SM2RAIN CHIRPS MSWEP microwave sensors Northeast Brazil CMORPH |
| title | Assessment of SM2RAIN-Derived and State-of-the-Art Satellite Rainfall Products over Northeastern Brazil |
| title_full | Assessment of SM2RAIN-Derived and State-of-the-Art Satellite Rainfall Products over Northeastern Brazil |
| title_fullStr | Assessment of SM2RAIN-Derived and State-of-the-Art Satellite Rainfall Products over Northeastern Brazil |
| title_full_unstemmed | Assessment of SM2RAIN-Derived and State-of-the-Art Satellite Rainfall Products over Northeastern Brazil |
| title_short | Assessment of SM2RAIN-Derived and State-of-the-Art Satellite Rainfall Products over Northeastern Brazil |
| title_sort | assessment of sm2rain derived and state of the art satellite rainfall products over northeastern brazil |
| topic | satellite rainfall soil moisture SM2RAIN CHIRPS MSWEP microwave sensors Northeast Brazil CMORPH |
| url | http://www.mdpi.com/2072-4292/10/7/1093 |
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