Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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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 0,37ºC in the mean, 1,37ºC in the maximum and 0,18ºC 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.

Original languageEnglish
Title of host publication19th International Multidisciplinary Scientific Geoconference, SGEM 2019
Subtitle of host publicationConference Proceedings.
Pages915-922
Number of pages8
Volume19
Edition2.2
DOIs
Publication statusPublished - 1 Jan 2019
Event19th International Multidisciplinary Scientific Geoconference, SGEM 2019 - Albena, Bulgaria
Duration: 30 Jun 20196 Jul 2019

Publication series

NameInternational Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM
PublisherInternational Multidisciplinary Scientific Geoconference
ISSN (Print)1314-2704

Conference

Conference19th International Multidisciplinary Scientific Geoconference, SGEM 2019
CountryBulgaria
CityAlbena
Period30/06/196/07/19

Fingerprint

air temperature
Air
modeling
temperature
Temperature
kriging
twenty first century
Error statistics
spatial data
interpolation
environmental conditions
Ecosystems
Interpolation
ecosystem
Statistics
prediction

Keywords

  • Brazil
  • Climate variability
  • Interpolation
  • Ordinary kriging

Cite this

Moraes, D., Ribeiro, S., & Costa, A. C. (2019). Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017. In 19th International Multidisciplinary Scientific Geoconference, SGEM 2019: Conference Proceedings. (2.2 ed., Vol. 19, pp. 915-922). (International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM). https://doi.org/10.5593/sgem2019/2.2/S11.113
Moraes, Daniel ; Ribeiro, Sara ; Costa, Ana Cristina. / Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017. 19th International Multidisciplinary Scientific Geoconference, SGEM 2019: Conference Proceedings. . Vol. 19 2.2. ed. 2019. pp. 915-922 (International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM).
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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 0,37ºC in the mean, 1,37ºC in the maximum and 0,18ºC 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.",
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Moraes, D, Ribeiro, S & Costa, AC 2019, Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017. in 19th International Multidisciplinary Scientific Geoconference, SGEM 2019: Conference Proceedings. . 2.2 edn, vol. 19, International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM, pp. 915-922, 19th International Multidisciplinary Scientific Geoconference, SGEM 2019, Albena, Bulgaria, 30/06/19. https://doi.org/10.5593/sgem2019/2.2/S11.113

Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017. / Moraes, Daniel; Ribeiro, Sara; Costa, Ana Cristina.

19th International Multidisciplinary Scientific Geoconference, SGEM 2019: Conference Proceedings. . Vol. 19 2.2. ed. 2019. p. 915-922 (International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017

AU - Moraes, Daniel

AU - Ribeiro, Sara

AU - Costa, Ana Cristina

N1 - Moraes, D., Ribeiro, S., & Costa, A. C. (2019). Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017. In 19th International Multidisciplinary Scientific Geoconference, SGEM 2019: Conference Proceedings. (2.2 ed., Vol. 19, pp. 915-922). (International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM). https://doi.org/10.5593/sgem2019/2.2/S11.113

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N2 - 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 0,37ºC in the mean, 1,37ºC in the maximum and 0,18ºC 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.

AB - 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 0,37ºC in the mean, 1,37ºC in the maximum and 0,18ºC 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.

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Moraes D, Ribeiro S, Costa AC. Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017. In 19th International Multidisciplinary Scientific Geoconference, SGEM 2019: Conference Proceedings. . 2.2 ed. Vol. 19. 2019. p. 915-922. (International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM). https://doi.org/10.5593/sgem2019/2.2/S11.113