Assessment of parametric approaches to calculate the Evaporative Demand Drought Index
Financiación H2020 / H2020 Funds
Resumen: The 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.
Idioma: Inglés
DOI: 10.1002/joc.7275
Año: 2021
Publicado en: International Journal of Climatology 42 (2021), 834–849
ISSN: 0899-8418

Factor impacto JCR: 3.651 (2021)
Categ. JCR: METEOROLOGY & ATMOSPHERIC SCIENCES rank: 45 / 94 = 0.479 (2021) - Q2 - T2
Factor impacto CITESCORE: 6.7 - Earth and Planetary Sciences (Q1)

Factor impacto SCIMAGO: 1.179 - Atmospheric Science (Q2)

Financiación: info:eu-repo/grantAgreement/EC/H2020/690462/EU/European Research Area for Climate Services/ERA4CS
Financiación: info:eu-repo/grantAgreement/ES/MICINN-FEDER/CGL2017-82216-R
Financiación: info:eu-repo/grantAgreement/ES/MICINN-FEDER/PCI2019-103631
Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2019-108589RA-I00
Tipo y forma: Article (Published version)

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