000120909 001__ 120909
000120909 005__ 20230519145622.0
000120909 0247_ $$2doi$$a10.1002/joc.7275
000120909 0248_ $$2sideral$$a126309
000120909 037__ $$aART-2021-126309
000120909 041__ $$aeng
000120909 100__ $$aNoguera I.
000120909 245__ $$aAssessment of parametric approaches to calculate the Evaporative Demand Drought Index
000120909 260__ $$c2021
000120909 5060_ $$aAccess copy available to the general public$$fUnrestricted
000120909 5203_ $$aThe Evaporative Demand Drought Index (EDDI), based on atmospheric evaporative demand, was proposed by Hobbins et al. (2016) to analyse and monitor drought. The EDDI uses a nonparametric approach in which empirically derived probabilities are converted to standardized values. This study evaluates the suitability of eight probability distributions to compute the EDDI at 1-, 3- and 12-month time scales, in order to provide more robust calculations. The results showed that the Log-logistic distribution is the best option for generating standardized values over very different climate conditions. Likewise, we contrasted this new parametric methodology to compute EDDI with the original nonparametric formulation. Our findings demonstrate the advantages of adopting a robust parametric approach based on the Log-logistic distribution for drought analysis, as opposed to the original nonparametric approach. The method proposed in this study enables effective implementation of EDDI in the characterization and monitoring of droughts. © 2021 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society.
000120909 536__ $$9info:eu-repo/grantAgreement/EC/H2020/690462/EU/European Research Area for Climate Services/ERA4CS$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 690462-ERA4CS$$9info:eu-repo/grantAgreement/ES/MICINN-FEDER/CGL2017-82216-R$$9info:eu-repo/grantAgreement/ES/MICINN-FEDER/PCI2019-103631$$9info:eu-repo/grantAgreement/ES/MICINN/PID2019-108589RA-I00
000120909 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000120909 590__ $$a3.651$$b2021
000120909 591__ $$aMETEOROLOGY & ATMOSPHERIC SCIENCES$$b45 / 94 = 0.479$$c2021$$dQ2$$eT2
000120909 592__ $$a1.179$$b2021
000120909 593__ $$aAtmospheric Science$$c2021$$dQ2
000120909 594__ $$a6.7$$b2021
000120909 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000120909 700__ $$aVicente-Serrano S.M.
000120909 700__ $$0(orcid)0000-0003-3085-7040$$aDomínguez-Castro F.
000120909 700__ $$aReig F.
000120909 773__ $$g42 (2021), 834–849$$pInt. j. climatol.$$tInternational Journal of Climatology$$x0899-8418
000120909 8564_ $$s10617581$$uhttps://zaguan.unizar.es/record/120909/files/texto_completo.pdf$$yVersión publicada
000120909 8564_ $$s2460870$$uhttps://zaguan.unizar.es/record/120909/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000120909 909CO $$ooai:zaguan.unizar.es:120909$$particulos$$pdriver
000120909 951__ $$a2023-05-18-16:16:14
000120909 980__ $$aARTICLE