000063010 001__ 63010
000063010 005__ 20240124152520.0
000063010 0247_ $$2doi$$a10.5194/essd-9-721-2017
000063010 0248_ $$2sideral$$a101617
000063010 037__ $$aART-2017-101617
000063010 041__ $$aeng
000063010 100__ $$0(orcid)0000-0001-7663-1202$$aSerrano-Notivoli, Roberto$$uUniversidad de Zaragoza
000063010 245__ $$aSPREAD: A high-resolution daily gridded precipitation dataset for Spain – an extreme events frequency and intensity overview
000063010 260__ $$c2017
000063010 5060_ $$aAccess copy available to the general public$$fUnrestricted
000063010 5203_ $$aA high-resolution daily gridded precipitation dataset was built from raw data of 12 858 observatories covering a period from 1950 to 2012 in peninsular Spain and 1971 to 2012 in Balearic and Canary islands. The original data were quality-controlled and gaps were filled on each day and location independently. Using the serially complete dataset, a grid with a 5 × 5 km spatial resolution was constructed by estimating daily precipitation amounts and their corresponding uncertainty at each grid node. Daily precipitation estimations were compared to original observations to assess the quality of the gridded dataset. Four daily precipitation indices were computed to characterise the spatial distribution of daily precipitation and nine extreme precipitation indices were used to describe the frequency and intensity of extreme precipitation events. The Mediterranean coast and the Central Range showed the highest frequency and intensity of extreme events, while the number of wet days and dry and wet spells followed a north-west to south-east gradient in peninsular Spain, from high to low values in the number of wet days and wet spells and reverse in dry spells. The use of the total available data in Spain, the independent estimation of precipitation for each day and the high spatial resolution of the grid allowed for a precise spatial and temporal assessment of daily precipitation that is difficult to achieve when using other methods, pre-selected long-term stations or global gridded datasets. SPREAD dataset is publicly available at https://doi.org/10.20350/digitalCSIC/7393.
000063010 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/CGL2015-69985-R$$9info:eu-repo/grantAgreement/ES/MINECO/CGL2014-52135-C3-1-R$$9info:eu-repo/grantAgreement/ES/DGA-FSE/H38$$9info:eu-repo/grantAgreement/ES/DGA/E68
000063010 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000063010 590__ $$a8.792$$b2017
000063010 591__ $$aMETEOROLOGY & ATMOSPHERIC SCIENCES$$b2 / 85 = 0.024$$c2017$$dQ1$$eT1
000063010 591__ $$aGEOSCIENCES, MULTIDISCIPLINARY$$b3 / 189 = 0.016$$c2017$$dQ1$$eT1
000063010 592__ $$a4.885$$b2017
000063010 593__ $$aEarth and Planetary Sciences (miscellaneous)$$c2017$$dQ1
000063010 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000063010 700__ $$aBeguería, Santiago
000063010 700__ $$0(orcid)0000-0001-8979-0253$$aSaz, Miguel Ángel$$uUniversidad de Zaragoza
000063010 700__ $$0(orcid)0000-0002-9558-1308$$aLongares, Luis Alberto$$uUniversidad de Zaragoza
000063010 700__ $$0(orcid)0000-0002-7585-3636$$aLuis, Martín de$$uUniversidad de Zaragoza
000063010 7102_ $$13006$$2430$$aUniversidad de Zaragoza$$bDpto. Geograf. Ordenac.Territ.$$cÁrea Geografía Física
000063010 7102_ $$13006$$2010$$aUniversidad de Zaragoza$$bDpto. Geograf. Ordenac.Territ.$$cÁrea Análisis Geográfico Regi.
000063010 773__ $$g9, 2 (2017), 721-738$$pEarth syst. sci. data$$tEARTH SYSTEM SCIENCE DATA$$x1866-3508
000063010 8564_ $$s11945945$$uhttps://zaguan.unizar.es/record/63010/files/texto_completo.pdf$$yVersión publicada
000063010 8564_ $$s101982$$uhttps://zaguan.unizar.es/record/63010/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000063010 909CO $$ooai:zaguan.unizar.es:63010$$particulos$$pdriver
000063010 951__ $$a2024-01-24-15:16:55
000063010 980__ $$aARTICLE