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dc.contributor.authorGarcía Arias L.F
dc.contributor.authorEspinosa D
dc.contributor.authorHernández-Leal E
dc.contributor.authorOcampo L
dc.contributor.authorDuque-Méndez N.D.
dc.date.accessioned2023-10-24T19:24:55Z
dc.date.available2023-10-24T19:24:55Z
dc.date.created2022
dc.identifier.isbn9783031199509
dc.identifier.issn18650929
dc.identifier.urihttp://hdl.handle.net/11407/8015
dc.description.abstractThe analysis of air temperature and relative humidity is fundamental in several areas of knowledge. For example, they define the climate, establish the population’s development in a region, and be indicators of climate change. Cross-correlation and autocorrelation analysis are well-known tools to characterize data series. However, the traditional statistical methods cannot be appropriately applied to long-term climatological series since they are non-stationary. The Detrended Fluctuation Analysis (DFA) and the Detrended Cross-Correlation Analysis (DCCA) are tools to find relationships within and between non-stationary series. This work analyzes autocorrelations and cross-correlations for relative humidity and air temperature series of four stations in Manizales. First, a windowed detrended fluctuation analysis was applied to the series to identify the yearly persistence of the series. Then, the DFA shows long-term persistence for all the series. Finally, a matrix-based algorithm was implemented to perform the DCCA; this analysis showed negative correlations between the air temperature and relative humidity series, following their physical behavior. Besides, the DCCA analysis showed positive correlations among the humidity series of different stations. Similar results were obtained and among the air temperature series of different locations. © 2022, Springer Nature Switzerland AG.eng
dc.language.isoeng
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85142749106&doi=10.1007%2f978-3-031-19951-6_5&partnerID=40&md5=2443bed9513d43209c8df80849bdf2f1
dc.sourceCommun. Comput. Info. Sci.
dc.sourceCommunications in Computer and Information Scienceeng
dc.subjectAir temperatureeng
dc.subjectCorrelationseng
dc.subjectCross-correlationseng
dc.subjectDetrended cross-correlation analysis (DCCA)eng
dc.subjectDetrended fluctuation analysis (DFA)eng
dc.subjectRelative humidityeng
dc.titleCorrelations and Cross-Correlations in Temperature and Relative Humidity Temporal Series From Manizales, Colombiaeng
dc.typeConference Paper
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.publisher.programIngeniería de Sistemasspa
dc.type.spaDocumento de conferencia
dc.identifier.doi10.1007/978-3-031-19951-6_5
dc.relation.citationvolume1594 CCIS
dc.relation.citationstartpage65
dc.relation.citationendpage80
dc.publisher.facultyFacultad de Ingenieríasspa
dc.affiliationGarcía Arias, L.F., Universidad Nacional de Colombia, Carrera 27 # 64-60, Manizales, Colombia
dc.affiliationEspinosa, D., Universidad Nacional de Colombia, Carrera 27 # 64-60, Manizales, Colombia
dc.affiliationHernández-Leal, E., Universidad de Medellín, Carrera 87 # 30-65, Medellín, Colombia
dc.affiliationOcampo, L., Universidad Nacional de Colombia, Carrera 27 # 64-60, Manizales, Colombia
dc.affiliationDuque-Méndez, N.D., Universidad Nacional de Colombia, Carrera 27 # 64-60, Manizales, Colombia
dc.relation.referencesAnjos, P.S.D., Silva, A.S.A.D., Stošić, B., Stošić, T., Long-term correlations and cross-correlations in wind speed and solar radiation temporal series from Fernando de Noronha Island, Brazil (2015) Phys. A: Stat. Mech. Appl., 424, pp. 90-96. , https://doi.org/10.1016/J.PHYSA.2015.01.003
dc.relation.referencesCastaño, L.F.C., (2017) Estimación Y análisis De La evapotranspiración En El Municipio De Manizales. Master’s Thesis, , https://repositorio.unal.edu.co/handle/unal/60310
dc.relation.referencesCastiglioni, P., Parati, G., Faini, A., Can the detrended fluctuation analysis reveal nonlinear components of heart rate variability (2019) In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 6351-6354. , https://doi.org/10.1109/EMBC.2019.8856945
dc.relation.referencesColombia, Corpocaldas, U.N., (2021) Cdiac-Centro De Datos E Indicadores Ambientales De Caldas
dc.relation.referencesDelgado, V., Zambrano, J., Vélez, J., (2020) The Knowledge of the Spatial-Temporal Rainfall Patterns as a Tool for Storm-Design. Case Study, , https://doi.org/10.22541/AU.158921470.04015184, Manizales, Colombia. Authorea Preprints
dc.relation.referencesFerreira, L.B., da Cunha, F.F.: New approach to estimate daily reference evapotranspiration based on hourly temperature and relative humidity using machine learning and deep learning. Agri. Water Manag. 234, 106113 (2020). https://doi. org/10.1016/J.AGWAT.2020.106113
dc.relation.referencesFerreira, P., Kristoufek, L., Pereira, E.J.D.A.L., DCCA and DMCA correlations of cryptocurrency markets (2020) Phys. A: Stat. Mech. Appl., 545. , https://doi.org/10.1016/J.PHYSA.2019.123803
dc.relation.referencesGuedes, E., Dionísio, A., Ferreira, P.J., Zebende, G.F., DCCA cross-correlation in blue-chips companies: A view of the 2008 financial crisis in the eurozone (2017) Phys. A: Stat. Mech. Appl., 479 (38-47). , https://doi.org/10.1016/J.PHYSA.2017.02. 065
dc.relation.referencesHekmatmanesh, A., Wu, H., Motie-Nasrabadi, A., Li, M., Handroos, H.: Combination of discrete wavelet packet transform with detrended fluctuation analysis using customized mother wavelet with the aim of an imagery-motor control interface for an exoskeleton. Multimedia Tools Appl. 78, 30503–30522 (2019). https://doi.org/10.1007/S11042-019-7695-0, https://link.springer.com/article/10. 1007/s11042-019-7695-0
dc.relation.referencesHu, K., Ivanov, P.C., Chen, Z., Carpena, P., Stanley, H.E.: Effect of trends on detrended fluctuation analysis. Phys. Rev. E 64(1), 011114 (2001). https://doi.org/10.1103/PhysRevE.64.011114, https://journals.aps.org/pre/abstract/10. 1103/PhysRevE.64.011114
dc.relation.referencesIqbal, J., Lone, K.J., Hussain, L., Rafique, M.: Detrended cross correlation analysis (dcca) of radon, thoron, temperature and pressure time series data. Phys. Scr. 95, 085213 (2020). https://doi.org/10.1088/1402-4896/AB9FB1, https://iopscience.iop.org/article/10.1088/1402-4896/ab9fb1, https://iopscience.iop.org/article/10.1088/1402-4896/ab9fb1/meta
dc.relation.referencesJiang, Z.Q., Zhou, W.X.: Multifractal detrending moving-average cross-correlation analysis. Phys. Rev. E 84(1), 016106 (2011). https://doi.org/10.1103/PhysRevE. 84.016106, https://journals.aps.org/pre/abstract/10.1103/PhysRevE.84.016106
dc.relation.referencesKantelhardt, J.W., Koscielny-Bunde, E., Rego, H.H., Havlin, S., Bunde, A., Detecting long-range correlations with detrended fluctuation analysis (2001) Phys. A: Stat. Mech. Appl., 295, pp. 441-454. , https://doi.org/10.1016/S0378-4371(01)001443
dc.relation.referencesLi, J., Zhang, X., Tang, J., Noise suppression for magnetotelluric using variational mode decomposition and detrended fluctuation analysis (2020) J. Appl. Geophys., 180. , https://doi.org/10.1016/J.JAPPGEO.2020.104127
dc.relation.referencesLópez, O.L.O., Upegui, J.J.V., Análisis climatológico para el departamento de caldas (2015) Entendimiento De Fenómenos Ambientales Mediante Análisis De Datos, pp. 1-66. , Upegui, J.J.V., Alzate, M.O., Méndez, N.D.D., Zuluaga, B.H.A. (eds.) , 1 edn
dc.relation.referencesMiloş, L.R., Haţiegan, C., Miloş, M.C., Barna, F.M., Boțoc, C.: Multifractal Detrended Fluctuation Analysis (MF-DFA) of Stock Market Indexes. Empirical evidence from Seven Central and Eastern European Markets. Sustainability 12(2), 535 (2020). https://doi.org/10.3390/SU12020535, https://www.mdpi.com/2071-1050/12/2/535/htm, https://www.mdpi.com/2071-1050/12/2/535
dc.relation.referencesOrtiz, L.C.C., López, O.L.O., Castro, M.F.A.: Análisis de tendencia de temperatura y precipitación para el departamento de caldas (colombia), mediante wavelets. Ciencia e Ingeniería Neogranadina 31, 37–52 (2021). https://doi.org/10.18359/RCIN.4900, https://revistas.unimilitar.edu.co/index.php/rcin/article/view/4900
dc.relation.referencesPavlov, A.N., Abdurashitov, A.S., Koronovskii, A.A., Pavlova, O.N., Semyachkinaglushkovskaya, O.V., Kurths, J., Detrended fluctuation analysis of cerebrovascular responses to abrupt changes in peripheral arterial pressure in rats (2020) Commun. Nonlin. Sci. Numer. Simul., 85. , https://doi.org/10.1016/J.CNSNS.2020. 105232
dc.relation.referencesPeng, C.K., Buldyrev, S.V., Havlin, S., Simons, M., Stanley, H.E., Goldberger, A.L., Mosaic organization of DNA nucleotides (1994) Phys. Rev. E, 49, p. 1685. , https://doi.org/10.1103/PhysRevE.49.1685
dc.relation.referencesPodobnik, B., Wang, D., Horvatic, D., Grosse, I., Stanley, H.E.: Time-lag cross-correlations in collective phenomena. EPL (Europhysics Letters) 90, 68001 (2010). https://doi.org/10.1209/0295-5075/90/68001, https://iopscience.iop.org/article/10.1209/0295-5075/90/68001, https://iopscience.iop.org/article/10.1209/0295-5075/90/68001/meta
dc.relation.referencesPodobnik, B., Jiang, Z.Q., Zhou, W.X., Stanley, H.E.: Statistical tests for power-law cross-correlated processes. Phys. Rev. E 84, 066118 (2011). https://doi.org/10.1103/PhysRevE.84.066118, https://journals.aps.org/pre/abstract/10. 1103/PhysRevE.84.066118
dc.relation.referencesPodobnik, B., Stanley, H.E.: Detrended cross-correlation analysis: a new method for analyzing two nonstationary time series. Phys. Rev. Lett. 100, 084102 (2008). https://doi.org/10.1103/PhysRevLett.100.084102, https://journals.aps. org/prl/abstract/10.1103/PhysRevLett.100.084102
dc.relation.referencesShrestha, A.K., Thapa, A., Gautam, H., Solar radiation, air temperature, relative humidity, and dew point study: Damak, Jhapa, Nepal (2019) Int. J. Photoenergy, 2019. , https://doi.org/10.1155/2019/8369231
dc.relation.referencesTeng, Y., Shang, P., Detrended fluctuation analysis based on higher-order moments of financial time series (2018) Phys. A: Stat. Mech. Appl., 490, pp. 311-322. , https://doi.org/10.1016/J.PHYSA.2017.08.062
dc.relation.referencesWang, J., Tang, K., Feng, K., Lin, X., Lv, W., Chen, K., Wang, F.: Impact of temperature and relative humidity on the transmission of covid-19: a modelling study in China and the United States. BMJ Open 11, e043863 (2021). https://doi.org/10.1136/BMJOPEN-2020-043863, https://bmjopen.bmj.com/content/11/2/e043863, https://bmjopen.bmj.com/content/11/2/e043863.abstract
dc.relation.referencesXiang, C., Hao, X., Wang, W., Chen, Z., Asymmetric MF-DCCA method based on fluctuation conduction and its application in air pollution in Hangzhou (2019) J. Adv. Comput. Intell. Intell. Informat., 23 (5), pp. 823-830. , https://doi.org/10.20965/JACIII.2019.P0823
dc.relation.referencesZambrano, J., Delgado, V., Upegui, J.J.V.: Short-term temperature variability in a tropical Andean city Manizales, Colombia. Revista vínculos 17, 1–27 (2020). https://doi.org/10.14483/2322939X.17091, https://revistas.udistrital.edu. co/index.php/vinculos/article/view/17091
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellín
dc.identifier.repourlrepourl:https://repository.udem.edu.co/
dc.identifier.instnameinstname:Universidad de Medellín
dc.contributor.event15th Colombian Congress on Advances in Computing, CCC 2021


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