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Assessment of NASA/POWER satellite‐based weather system for Brazilian conditions and its impact on sugarcane yield simulation
Abstract
The gridded database provided by National Aeronautics and Space Administration/Prediction of World Wide Energy Resources (NASA/POWER) presents a global coverage of complete weather data at horizontal resolution of 1° latitude–longitude, becoming a potential source for agrometeorological studies. Once Brazil is a country with continental dimensions and the major sugarcane world producer, and its density of ground weather stations suitable for an efficient agricultural planning is sparse, the objectives of this study were to test how robust is the NASA/POWER database through its comparison with the Brazilian ground weather stations network records (INMET) and to quantify the impacts on potential ( Y p ) and attainable ( Y att ) sugarcane yield simulations when setting NASA/POWER as source of input weather data. The comparisons for weather data records and sugarcane yield simulations were carried out from 1997 to 2016. Statistical indices presented a satisfactory performance for average air temperature ( R 2 = 0.73; d = 0.91), minimum air temperature ( R 2 = 0.72; d = 0.91), maximum air temperature ( R 2 = 0.57; d = 0.84), solar radiation (SR) ( R 2 = 0.71; d = 0.92), sunshine hours ( R 2 = 0.68; d = 0.90) and reference evapotranspiration, when calculated through Priestley–Taylor (ETo‐PT) method ( R 2 = 0.76; d = 0.93). When the weather variables were aggregated and compared with a 10‐day time scale, a strong improvement of statistical indices was obtained. Y p presented root me…
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“Furthermore, satellite data like those obtained from the NASA POWER (National Aeronautics and Space Administration, Prediction Of Worldwide Energy Resources) project allow environmental characterization of any location on earth (Monteiro et al. , 2017).”
From REML implementations of kernel-based genomic prediction models for genotype x environment x management interactions (2025) · cites this paper as Monteiro et al. , 2017
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Tomar, S., & Kadaverugu, R. (2025) · Disaster Resilience and Green Growth · doi:10.1007/978-981-95-1588-2_5 · Cited by 2
Melsen, K. A. C., Gezan, S., Tolhurst, D. J., van Eeuwijk, F. A., & Peeters, C. F. W. (2025) · arXiv · doi:10.48550/arxiv.2501.06844 · Cited by 3
“Furthermore, satellite data like those obtained from the NASA POWER (National Aeronautics and Space Administration, Prediction Of Worldwide Energy Resources) project allow environmental characterization of any location on earth (Monteiro et al. , 2017).”
Metadata
- Authors
- Monteiro, L. A., Sentelhas, P. C., & Pedra, G. U.
- Affiliations
- World Meteorological Organization (CH)
- Universidade de São Paulo (BR)
- Corresponding author
- Sentelhas, Paulo C.
- Venue
- International Journal of Climatology
- Publisher
- Wiley
- Published
- 2017-09-07
- Volume
- 38
- Issue
- 3
- Pages
- 1571-1581
- ISSN
- 0899-8418 (ISSN-L)
- 1097-0088
- OpenAlex
- W2752126604
- Cited by
- 150
- References
- 1
- Citations by year
- 2026: 24 · 2025: 18 · 2024: 21 · 2023: 32 · 2022: 17 · 2021: 23 · 2020: 5 · 2019: 5 · 2018: 5
- FWCI
- 3.10
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Climatology (publishedVersion)
- Topics
- Physical Sciences › Environmental Science › Ecology › Remote Sensing in Agriculture
- Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Climate change impacts on agriculture
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Sugarcane Cultivation and Processing
- Keywords
- NASA POWER, satellite weather data, agrometeorology, air temperature, solar radiation, sunshine duration, reference evapotranspiration, Priestley-Taylor method, Brazil
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