Scholarly record
MODELLING AIR TEMPERATURE IN BRAZILIAN NORTHEAST TO EVALUATE CHANGE PATTERNS FROM 2000 TO 2017
Abstract
Air temperature influences a variety of environmental processes, having a significant impact on the conditions of living of humans and other life forms. The Brazilian Northeast is a region that comprises a diversity of ecosystems, but it is most known as a semi-arid area characterized by severe environmental conditions. This work proposes to model air temperature in Brazilian Northeast to evaluate changing patterns between 2000 and 2017 using two interpolation techniques and comparing them. Monthly average temperature data from meteorological stations were gathered and used to compute the average annual temperature. Then, the timeframe was divided into 2 periods: 2000 to 2008 (1) and 2009 to 2017 (2), and the average temperature of each period was computed based on the annual average. Descriptive statistics analysis and exploratory spatial data analysis were performed, providing insights on the temperature patterns and distribution. In addition, interpolated surfaces were generated using the Inverse Distance Weighting and Ordinary Kriging methods for each period, and results were compared using error statistics derived with cross-validation. The results revealed that for both periods the highest temperatures are exhibited in the northern and central regions, whereas the lowest values occur in the south and east. In terms of change, an overall increase in the average temperature was noticed from period 1 to 2, although in some areas the increase was greater than in others. There was an increase of 0,37?C in the mean, 1,37?C in the maximum and 0,18?C in the minimum temperature over the study region. Furthermore, Ordinary Kriging produced better results in terms of the bias of the predictions. The interpolated surfaces allow to visually notice the change in the average temperature between the periods. This study contributes to a better understanding of the temperature variability in the Brazilian Northeast in the 21st century.
Publication Impact Profile
Publication details
References10
Cristóbal, J., Ninyerola, M., Pons, X., Modeling air temperature through a combination of remote sensing and GIS data, Journal of Geophysical Research: Atmospheres, 113(D13106), 2008.
Burrough, P. A., McDonnell, R. A., Principles of Geographical Information Systems, Oxford University Press, 1998.
Bhowmik, A. K., Costa, A. C., Representativeness impacts on accuracy and precision of climate spatial interpolation in data‐scarce regions, Meteorological Applications, vol. 22/issue 3, pp. 368-377, 2015.
Martínez-Cob, A., Multivariate geostatistical analysis of evapotranspiration and precipitation in mountainous terrain, Journal of Hydrology, vol. 174/issue 1-2, pp 19-35, 1996.
Goovaerts, P., Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall, Journal of Hydrology, vol. 228/issue 1-2, pp 113- 129, 2000.
Haberlandt, U., Geostatistical interpolation of hourly precipitation from rain gauges and radar for a large-scale extreme rainfall event, Journal of Hydrology, vol. 332/issue 1-2, pp 144-157, 2007.
Marengo, J., Alves Lincoln, M., Alyala, C. S., Cunha, A., Brito, S., Moraes, O., Climatic characteristics of the 2010-2016 drought in the semiarid Northeast Brazil region, Anais da Academia Brasileira de Ciências, vol. 90/issue 2, pp. 1973-1985, 2018.
Selvaraju, R., Baas, S., Climate variability and change: adaptation to drought in Bangladesh: A resource book and training guide, Italy, vol. 9, 2007.
Marengo, J., Torres, R. R., Alves, L. M., Drought in Northeast Brazil – past, present and future, Theoretical and Applied Climatology, vol. 129/issue 3-4, pp. 1189-1200, 2017.
Instituto Brasileiro de Geografia e Estatística, Estimativas da População Residente no Brasil e Unidades da Federação, available online at ftp://ftp.ibge.gov.br/Estimativas_de_Populacao/Estimativas_2018/estimativa_dou _2018_20181019.pdf (Accessed 26th December 2018), 2018.
View or Download full articleAccess options
SWS access login
Login as SWS Scientific CommitteeLogin as SWS Scientific PartnerLogin as SWS AuthorAuthors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.
For librarian assistance: [email protected]
Purchase Instant Access
- Article can be downloaded after successful payment.
- Article may be used according to SWS library access terms.
- Article cannot be redistributed.
