DOI: 10.5285/19c230b2-415b-456a-9e93-7b00b730a465
title: Standardised Precipitation Evapotranspiration Index time series for Integrated Hydrological Units Hydrometric Areas (1961-2012)

description: Standardised Precipitation Evapotranspiration Index (SPEI) data for Integrated Hydrological Units (IHU) Hydrometric Areas (Kral et al. [1]). SPEI is a drought index based on the probability of occurrence of the Climatic Water Balance (CWB) - which is equivalent to the amount of precipitation minus the amount of evapotranspiration - for a given accumulation period as defined by Vicente-Serrano et al. [2]. SPEI is calculated for different accumulation periods: 1, 3, 6, 12, 18, 24 months. Each of these is in turn calculated for each of the twelve calendar months. Note that values in monthly (and for longer accumulation periods also annual) time series of the data therefore are likely to be autocorrelated. The standard period which was used to fit the gamma distribution is 1961-2010. The dataset covers the period from 1961 to 2012.

[1] Kral, F., Fry, M., Dixon, H. (2015). Integrated Hydrological Units of the United Kingdom: Hydrometric Areas without Coastline. NERC-Environmental Information Data Centre https://doi.org/10.5285/3a4e94fc-4c68-47eb-a217-adee2a6b02b3
[2] Vicente-Serrano, S. M., Beguería, S., & López-Moreno, J. I. (2010) A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. J. Climate, 23, 1696-1718. https://doi.org/10.1175/2009JCLI2909.1
description: SPEI is calculated as originally defined in Vicente-Serrano et al. [1]. SPEI is based on the cumulative probability of a given Climatic Water Balance (CWB) - which is equivalent to the amount of precipitation minus the amount of evapotranspiration - occurring at a location. The historic CWB data of the station is fitted to a statistical distribution. For this dataset, the statistical distribution used is the generalised logistic distribution. The maximum likelihood method was used to estimate the generalised logistic distribution parameters. To calculate SPEI, the R package SCI was used (Gudmundsson & Stagge [2]). The input data used is the monthly rainfall grids from CEH-Gridded Estimates of Areal Rainfall [CEH-GEAR] (Tanguy et al. [3], Keller et al. [4]) and CHESS potential evapotranspiration dataset (Robinson et al. [5], [6]) which have been area-averaged over each of the Integrated Hydrological Units (IHU) Hydrometric Areas (Kral et al. [7]).

[1] Vicente-Serrano, S. M., Beguería, S., López-Moreno, J. I. (2010) A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. J. Climate, 23, 1696-1718. https://doi.org/10.1175/2009JCLI2909.1
[2] Gudmundsson, L. & Stagge, J. H. (2014). Package 'SCI': Standardized Climate Indices such as SPI, SRI or SPEI. Repository CRAN, http://cran.r-project.org/web/packages/SCI/SCI.pd
[3] Tanguy, M., Dixon, H., Prosdocimi, I., Morris, D. G., Keller, V. D. J. (2014). Gridded estimates of daily and monthly areal rainfall for the United Kingdom (1890-2012) [CEH-GEAR]. NERC-Environmental Information Data Centre https://doi.org/10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e
[4] Keller, V. D. J., Tanguy, M. , Prosdocimi, I. , Terry, J. A. , Hitt, O., Cole, S. J. , Fry, M., Morris, D. G., Dixon, H. (2015) CEH-GEAR: 1km resolution daily and monthly areal rainfall estimates for the UK for hydrological use. Earth Syst. Sci. Data Discuss., 8, 83-112, www.earth-syst-sci-data-discuss.net/8/83/2015/ doi:10.5194/essdd-8-83-2015
[5] Robinson, E. L., Blyth, E., Clark, D. B., Finch, J., Rudd, A. C. (in preparation), Trends in evaporative demand in Great Britain using high-resolution meteorological data
[6] Robinson, E. L., Blyth, E., Clark, D. B., Finch, J., Rudd, A. C. (2015). Climate hydrology and ecology research support system potential evapotranspiration dataset for Great Britain (1961-2012) [CHESS-PE]. NERC-Environmental Information Data Centre
[7] Kral, F., Fry, M., Dixon, H. (2015). Integrated Hydrological Units of the United Kingdom: Hydrometric Areas without Coastline. NERC-Environmental Information Data Centre https://doi.org/10.5285/3a4e94fc-4c68-47eb-a217-adee2a6b02b3