Air temperature perturbation in La Malinche volcano area, Tlaxcala, Mexican Highland
Contenido principal del artículo
Resumen
La evaluación de la perturbación de la temperatura del aire es muy importante para conocer el efecto de las actividades antrópicas en el sistema ambiental. El área de estudio fue el ambiente urbano, agrícola y forestal en la zona del volcán La Malinche. Utilizamos cinco estadísticas de datos de temperatura del aire y se examinaron mediante el análisis de componentes principales (PCA) y la prueba de Kruskal Wallis. El trabajo se realizó sobre una base diurna (tasas de calentamiento y enfriamiento), diaria y mensual. La prueba K-W mostró que las tasas de calentamiento y enfriamiento son significativamente diferentes entre las zonas agrícolas, urbanas y forestales, incluso, los lados norte y sur del volcán La Malinche tuvieron diferencias significativas. El PCA indicó que había más perturbación en relación con las tasas de enfriamiento de la temperatura del aire entre los ambientes que con las tasas de calentamiento. La temperatura del aire promedio, máxima y mínima de un ambiente urbano y la desviación estándar y el rango de un ambiente agrícola fueron las más altas. La tem- peratura mínima del aire cambia más que la máxima del lado sur urbano, agrícola y forestal del volcán. La prueba K-W mostró que las condiciones ambientales eran significativamente diferentes según el promedio y el máximo. La temperatura del aire diaria en el lado norte de la Malinche difirió significativamente de la del lado sur. El PCA con promedio, máximo, mínimo, desviación estándar y rango, mostró que los ambientes se encuentran perturbados. La temperatura media mensual del aire en las zonas agrícolas y forestales fue inferior a lo normal. El aumento de la temperatura mínima del aire fue más acentuado en las zonas urbanas que en las zonas agrícolas y forestales y aumentó más que el máximo.
Detalles del artículo
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
Citas
Abid A., Zhang M. J., Bagaria V. K., & Zou J. (2018). Exploring patterns enriched in a dataset with contrastive principal components. Nature Communications, 9(1), 1-7. doi: https://doi.org/10.1038/s41467-018-04608-8
Ayandale A. (2017). Variations in urban surface temperature: an assessment of land use change impacts over Lagos metropolis. Weather. 72(10), 315-319. doi: https://doi.org/10.1002/wea.3178
Bernhardt J., Carleton A. M., & LaMagna C. (2018). A comparison of daily temperature-averaging methods: spatial variability and recent change for the CONUS. Journal of Climate, 31, 979-996. doi: https://doi.org/10.1175/JCLI-D-17-0089.1
Bethere L., Sennikovs J., & Batheres U. (2017). Climate indices for the Baltic states from principal component analysis. Earth System Dynamics, 8(4), 951-962. doi: https://doi.org/10.5194/esd-8-951-2017
Bloomer C, & Rehm G. (2014). Using Principal Component Analysis to find correlations and patterns at diamond light source (pp 19-21). Proceedings of IPAC, Dresden, Germany.
Braganza K, Karoly DJ, Arblaster. (2004). Diurnal temperature range as an index of global climate change during the twentieth century. Geophysical Research Letters, 31(13), L13217. doi: https://doi.org/10.1029/2004GL019998
Castro-Govea R, Siebe C. (2007). Late Pleistocene–Holocene stratigraphy and radiocarbon dating of La Malinche volcano, Central Mexico. Journal of Volcanology and Geothermal Research. 162(1-2), 20-42. doi: https://doi.org/10.1016/j.jvolgeores.2007.01.002
Chen BX, Sun YF, Zhang HB, Han ZH, Wang JS, Li YK, Yang XL. (2018). Temperature change along elevation and its effect on the alpine timberline tree growth in the southeast of the Tibetan Plateau. Advances in Climate Change Research, 9(3), 185-191. doi: https://doi.org/10.1016/j.accre.2018.05.001
Chinchorkar SS, Vaidya VB, Vyas P. (2013). Monthly, seasonal and annual air temperature variability and trends- a case study to assess climate change on Anand (Gujarat State). Spring. 1(1), 20-25.
Colunga ML, Cambrón-Sandoval VH, Suzán-Azpiri H, Guevara-Escobar A, Luna-Soria H. (2015). The role of urban vegetation in temperature and heat island effects in Querétaro City, Mexico. Atmósfera. 28(3), 205-218. doi: https://doi.org/10.20937/ATM.2015.28.03.05
Daultrey S. (1976). Principal components analysis: CATMOG Series. Geo Abstracts Ltd. University of East Anglia Norwich. https://alexsingleton.files.wordpress.com/2014/09/8-principle-components-analysis.pdf
De Frenne P, Zellweger F, Rodríguez-Sánchez F, Scheffers BR, Hylander K, Luoto M, Vellend M, Verheyen K, Lenoir J. (2019). Global buffering of temperatures under forest canopies. Nature Ecology and Evolution, 3, 744-749. doi: https://doi.org/10.1038/s41559-019-0842-1
Duffy KA, Schwalm CR, Arcus VL, Koch GW, Liang LL, Schipper LA. (2021). How close are we to the temperature tipping point of the terrestrial biosphere? Science Advances, 7(3), 1-8. doi: https://doi.org/10.1126/sciadv.aay1052
Dutta PN, Karlo T, Dutta P. (2017). Some features of surface air temperature: a statistical viewpoint. Environment and Ecology Research, 5(5), 367-376. doi: https://doi.org/10.13189/eer.2017.050506
Fernández EA, Romero CR, Zavala HJ. (2015). Redes de observación atmosférica y ambiental. Unidad de Informática para las Ciencias Atmosféricas y Ambientales (UNIATMOS). Red Universitaria de Observatorios Atmosféricos (RUOA). Centro de Ciencias de la Atmósfera, Universidad Nacional Autónoma de México. https://atlasclimatico.unam.mx/acdm/visualizador
Fuelner G, Rahmstorf S, Leverman A, Volkwardt S. (2013). On the origin of the surface air temperature difference between the Hemispheres in Earth's present-day climate. Journal of Climate, 26(18), 7136-7150. doi: https://doi.org/10.1175/JCLI-D-12-00636.1
García CF, Bestion E, Warfield R, Yvon-Durocher G. (2018). Changes in temperature alter the relationship between biodiversity and ecosystem functioning. Proceedings of the National Academy of Sciences of the United States of America. 115(43), 10989-10994. doi: https://doi.org/10.1073/pnas.1805518115
Good E. (2015). Daily minimum and maximum surface air temperatures from geostationary satellite data. Journal of Geophysical Research: Atmospheres. Journal of Geophysical Research: Atmospheres, 120(6), 2306-2324. doi: https://doi.org/10.1002/2014JD022438
Hajrya R, Mechbal N. (2013). Principal component analysis and perturbation theory-based robust damage detection of multifunctional aircraft structure. Structural Health Monitoring, 12(3), 263-277. doi: https://doi.org/10.1177/1475921713481015
Hemond HF, Fechner EJ. (2015). The atmosphere. En Academic Press (Ed.), Chemical fate and transport in the environment (311-354 pp.). Academic Press.
Hu Y, Mskey S, Uhlenbrook S. (2012). Trends in temperature and rainfall extremes in the Yellow River source region, China. Climatic Change. 110, 403-429. doi: https://doi.org/10.1007/s10584-011-0056-2
Hurth R and Pokorna L. (2005). Simultaneous analysis of climatic trends in multiple variables: an example of application of multivariate statistical methods. International Journal of Climatology (. 25, 469-484. doi: https://doi.org/10.1002/joc.1146
Imtiaz H, and Sarwate AD. (2016). Symmetric matrix perturbation for differentially-private principal component analysis. [Presentación de paper]. International Conference on Acoustics, Speech and Signal Processing, Shanghai, China. doi: https://doi.org/10.1109/ICASSP.2016.7472095.
Isaak DJ, Luce CH, Chandler GL, Horan DL, Wollrab SP. (2018). Principal components of thermal regimes in mountain river networks. Hydrology and Earth System Sciences, 22, 6225-6240. doi: https://doi.org/10.5194/hess-22-6225-2018
Joliffe IT, Cadima J. (2016). Principal components analysis: a review and recent developments. Philosophical Transactions A, 374(2065), 2-16. doi: https://doi.org/10.1098/rsta.2015.0202
Lee X, Goulden ML, Hollinger DV, Barr A, Black TA, Bohrer G, et al. (2011). Observed increase in the local cooling effect of deforestation at higher latitudes. Nature, 479, 384-387. doi: https://doi.org/10.1038/nature10588
Li D, Bou-Zeid E. (2013). Synergistic interactions between urban heat islands and heat waves: the impact in cities is larger than the sum of its parts. Journal of Applied Meteorology and Climatology, 52, 2051-2064. doi: https://doi.org/10.1175/JAMC-D-13-02.1
Li Y, Zhao M, Motesharrei S, Mu Q, Kalnay E, Li S. (2015). Local cooling and warming effects of forest based on satellite observations. Nature Communications, 6, 6603. doi: https://doi.org/10.1038/ncomms7603
López-Díaz F, Conde C, Sánchez O. (2013). Analysis of indices of extreme temperature events at Apizaco, Tlaxcala, Mexico: 1952-2003. Atmósfera. 26(3), 349-358.
Machiwal D, Gupta A, Jha MK, Kamble T. (2019). Analysis of trend in temperature and rainfall time series of an Indian arid region: comparative evaluation of salient techniques. Theoretical and Applied Climatology, 136, 301-320. doi: https://doi.org/10.1007/s00704-018-2487-4
Martínez R, Zambrano E, Nieto JJ, Costa F. (2017). Evolución, vulnerabilidad e impactos económicos y sociales de El Niño 2015-2016 en América Latina. Investigaciones Geográficas, 68, 65–78.
McBean EA and Rovers FA. (1998). Statistical procedures for analysis of environmental monitoring data and risk assessment. New Jersey: Prentice Hall.
Norma Mexicana: NMX-AA-166/1-SCFI-2013. (4 de septiembre 2013). Diario Oficial de la Federación, México. https://www.gob.mx/cms/uploads/attachment/file/166835/nmx-aa-166-1-scfi-2013_1_.pdf
Nwofor OK, Dike VN. (2010). Daytime surface air temperature variations at locations in Owerri Capital City: indications or urban heat island build-up? Advances in Science and Technology, 4(2), 91-97. https://advanscitech.com/nwofordike42.pdf
Oleson K. (2012). Contrasts between urban and rural climate in CCSM4 CMIP5 climate change scenarios. Journal of Climate, 25, 1390-1412. doi: https://doi.org/10.1175/JCLI-D-11-00098.1
Pascual RR, López QM, Chablé PLA, Espejo MAZ, Loranca DY, Ledesma LJI, Quintero VEY. (2019). Reporte del clima en México: Reporte anual 2019. CONAGUA, México. https://smn.conagua.gob.mx/es/reporte-del-clima-en-mexico
Pascual RR, López QM, Martínez SJN, Chablé PLA, Espejo MAZ, Ledezma LJI. (2018). Reporte del clima en México: Reporte anual 2018. CONAGUA, México. https://smn.conagua.gob.mx/es/reporte-del-clima-en-mexico
Peterson TC. (2003). Assessment of urban versus rural in situ surface temperatures in the Contiguous United States: No difference found. Journal of Climate, 26(18), 2941-2959. doi: https://doi.org/10.1175/1520-0442(2003)016<2941:AOUVRI>2.0.CO;2
Protsiv M, Ley C, Lankester J, Hastie T, Parsonnet J. (2020). Decreasing human body temperature in the United States since the Industrial Revolution. eLIFE, 9(e49555). doi: https://doi.org/10.7554/eLife.49555
Qu M, Wan J, Hao X. (2014). Analysis of diurnal air temperature range in the continental United States. Weather and Climate Extremes, 4, 86-95. doi: https://doi.org/10.1016/j.wace.2014.05.002
Radons SZ, Heldwein AB, Loose LH, Bortoluzzi MP, Brand SI, Engers LBO. (2019). Modeling hourly air temperature based on internationally agreed times and the daily minimum temperature. Revista Brasileira de Engenharia Agrícola e Ambiental, 23 (11), 807-811
Rahman MA, Kang S, Nagabhatla N, Macnee R. (2017). Impacts of temperature and rainfall variations on rice productivity in major ecosystems of Bangladesh. Agriculture and Food Security, 6(10). doi: https://doi.org/10.1186/s40066-017-0089-5
Rosenzweig C, Solecki W, Parshall L, Gaffin S, Lynn B, Goldberg R. et al. (2006). Mitigating New York City's heat island with urban forestry, living roofs, and light surfaces. 86th AMS Annual Meeting.
Roy and Balling Jr. (2005). Analysis of trends in maximum and minimum temperature, diurnal temperature range, and cloud cover over India. Geophysical Research Letters, 32(12), L12702. doi: https://doi.org/10.1029/2004GL022201
Ruíz AO, Espejel TD, Ontiveros CRE, Enciso JM, Galindo RMA, Quesada PML et al. (2016). Monthly trend of maximum and minimum temperatures in Aguascalientes, Mexico. Revista Mexicana de Ciencias Agrícolas, 13, 2535-2549.
Rushayati SB, Shamila AD, Prasetyo. (2018). The role of vegetation in controlling air temperature resulting from urban heat island. Forum Geografi, 32(1), 1-11. doi: https://doi.org/10.23917/forgeo.v32i1.5289
Schuenemeyer JH, Drew LJ. (2011). Statistics for earth and environmental scientists. New Jersey: John Wiley and Sons. https://www.wiley.com/en-us/Statistics+for+Earth+and+Environmental+Scientists-p-9780470584699
Shiflett SA, Liang LL, Crum SM, Feyisa GL, Wang J, Janerette GD. (2017). Variation in the urban vegetation, surface temperature, air temperature nexus. Science of the Total Environment, 579, 495-505. doi: https://doi.org/10.1016/j.scitotenv.2016.11.069
Sun L. (2016). Distribution of the temperature field in a pavement structure. L. Sun (Ed.). In: Structural behavior of asphalt pavements (pp. 61-177). Butterworth-Heinemann. doi: https://doi.org/10.1016/B978-0-12-849908-5.00002-X.
Suomi J, Käyhkö J. (2012). The impact of environmental factors on urban temperature variability in the coastal city of Turku, SW Finland. International Journal of Climatology, 32(3): 451-463. doi: https://doi.org/10.1002/joc.2277
Vitt R, Gulyás Á, Matzarakis A. (2015). Temporal differences or urban-rural human biometeorological factors for planning and tourism in Szeged, Hungary. Advances in Meteorology, 25, 987576. doi: https://doi.org/10.1155/2015/987576
Vuckovic M, Kiesel K, Mahdavi A. (2017). The extent and implications of the microclimatic conditions in the urban environment: a Vienna case study. Sustainability. 9, 177. doi: https://doi.org/10.3390/su9020177
Waldock C, Dornelas M, Bates AE. (2018). Temperature-driven biodiversity change: disentangling space and time. BioScience, 68(11), 873-884. doi: https://doi.org/10.1093/biosci/biy096
Wiesner S, Eschenbach A, Ament F. (2014). Urban air temperature anomalies and their relation to soil moisture observed in the city of Hamburg. Meteorologische Zeitschrift, 23(2), 143-157. doi: https://doi.org/10.1127/0941-2948/2014/0571
Wong N. H., & Peck T.T. (2005). The impact of vegetation on the environmental conditions of housing estates in Singapore. International Journal on Architectural Science, 6(1), 31-37. https://www.bse.polyu.edu.hk/researchCentre/Fire_Engineering/summary_of_output/journal/journal_AS.html
Yang Q., Huang X., & Li J. (2017). Assessing the relationship between surface urban heat islands and landscape patterns across climatic zones in China. Scientific Report, 7, 9337. doi: https://doi.org/10.1038/s41598-017-09628-w
Zeleňáková M., Purcz P., Hlavatá H., & Blišt’an. (2015). Climate change in urban versus rural areas. Procedia Engineering, 119, 1171-1180. doi: https://doi.org/10.1016/j.proeng.2015.08.968
Zhuo B., Rybski D., & Kropp J. P. (2017). The role of city size and urban form in the surface urban heat island. Scientific Reports, 7, 4791. doi: https://doi.org/10.1038/s41598-017-04242-2
Zuśka Z., Kopcińska J., Dacewicz E., Skowera B., Wojkowski J., & Ziernicka-Wojtaszek A. (2019). Application of the principal components analysis (PCA) method to assess the impact of meteorological elements on concentrations of particulate matter (PM10): A case study on the Mountain Valley (the Sącz Basin, Poland). Sustainability, 11, 6740. doi: https://doi.org/10.3390/su11236740
