Estimation of Air Temperature Using Climate Factors in Brazilian Sugarcane Regions
Revista Brasileira de Meteorologia, ISSN: 1982-4351, Vol: 37, Issue: 1, Page: 121-140
2022
- 1Citations
- 6Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
This study aimed to estimate the minimum and maximum monthly air temperatures in the sugarcane regions of Brazil. A 30-year historical series (1988-2018) of maximum (Tmax) and minimum (Tmin) air temperatures from the NASA/ POWER platform was used for 62 locations that produce sugarcane in Brazil. Multiple linear regression was used for data modeling, in which the dependent variables were Tmin and Tmax and the independent variables were latitude, longitude, and altitude. The comparison between estimation models and the real data was performed using the statistical indices MAPE (accuracy) and adjusted coefficient of determination (R2adj) (precision). The lowest MAPE values of the models for estimating the minimum air temperature occurred mainly in the North during February, March, and January. Also, the most accurate models for estimating the maximum air temperature occurred in the Southeast region during January, February, and March. The MAPE and R2adj values showed accuracy and precision in the models for estimating both the maximum and minimum temperatures, indicating that the equations can be used to estimate temperatures in sugarcane areas. The Tmin estimation model for the Southeast region in July shows the best performance, with a MAPE value of 1.28 and an R2adj of 0.94. The Tmax model of the North region for September presents higher precision and accuracy, with values of 1.28 and 0.96, respectively.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85134010854&origin=inward; http://dx.doi.org/10.1590/0102-77863710008; http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862022000100121&tlng=en; http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862022000100121&lng=en&tlng=en; http://www.scielo.br/scielo.php?script=sci_abstract&pid=S0102-77862022000100121&lng=en&tlng=en; http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862022000100121; http://www.scielo.br/scielo.php?script=sci_abstract&pid=S0102-77862022000100121; https://dx.doi.org/10.1590/0102-77863710008; https://www.scielo.br/j/rbmet/a/b3qdPkYHkvkppfTZSFgJCmz/?lang=en
FapUNIFESP (SciELO)
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know