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Contents: S1 Geographical description of the German Part of the Elbe River basin – S1.-- S2 Drought indices – S9.-- S3 Aspects of the socio-economic drought impacts – S13.-- References, Peer reviewed

The dataset is freely available on the web repository of the Spanish National Research Council (CSIC) in three different formats (NetCDF, binary raster, and plain text)., Format: netcdf The netcdf archive is composed of 96 zipped files containing the spei dataset from 1901 to 2006 at 1 to 48 months time scales, separated for the East hemisphere (i.e. Europa, Africa, Asia and Australia) and the West hemisphere (the Americas). Each zipped file contains one single netCDF file (.nc), i.e. no header files are necessary because all necessary meta-data are self-contained in the .nc file. Naming convention spei_[tempscale]_[hemisphere].zip, where [tempscale] is a number between 1 and 48 indicating the temporal scale of the index (months), and [hemisphere] indicates the fraction of the World covered and can have values eh (East hemisphere) or wh (West hemisphere). Example: spei_12_eh.zip, The Global 0.5° gridded SPEI dataset is made available under the Open Database License. Any rights in individual contents of the database are licensed under the Database Contents License. Users of the dataset are free to share, create and adapt under the conditions of attribution and share-alike. Use of the newest version is recommended. Older versions are still available to allow replicability., All currently available gridded drought datasets at continental and global scales are based on either the PDSI or the sc-PDSI. A new global drought dataset based on the Standardised Precipitation-Evapotranspiration Index (SPEI) has been developed, which covers time scales from 1-48 months at a spatial resolution of 0.5°, and provides temporal coverage for the period 1901-2006. This dataset represents an improvement in spatial resolution and operative capability of previous gridded drought datasets based on the PDSI, and enables identification of various drought types., A monthly global dataset of a multiscalar drought index is presented and compared in terms of spatial and temporal variability with the existing continental and global drought datasets based on the Palmer drought severity index (PDSI, scPDSI). The new dataset is based on the standardized precipitation evapotranspiration index (SPEI). The index was obtained from the CRU TS3.0 data, covering time scales from 1 to 48 months for the period 1901-2006, and has a spatial resolution of 0.5°. The advantages of the new dataset are that: i) it improves the spatial resolution of the unique global drought dataset at a global scale; ii) it is spatially and temporally comparable to other datasets, given the probabilistic nature of the SPEI, and, in particular; iii) it enables identification of various drought types, given the multiscalar character of the SPEI. More details at: http://www.eead.csic.es/spei/spei.html, Peer reviewed

The dataset is freely available on the web repository of the Spanish National Research Council (CSIC) in three different formats (NetCDF, binary raster, and plain text)., Format: raw binary. The raw binary archive is composed of 576 zipped files, corresponding to the SPEI index at time scales between 1 and 48 months for the whole World and divided by decades (except the last file, containing only data for the period 2001-2006). Each zipped file contains three files, one with the data itselt (.img), and two headers (.doc and .hdr). The information contained in the header files is equivalent, and allows direct access to the data using some widely used commercial programs. Naming convention: spei[tempscale]_[decade].zip, where [tempscale] is a number between 1 and 48 indicating the temporal scale of the index (months), and [decade] indicates the years of data contained in the file. Example: spei12_1910-1919.zip. All currently available gridded drought datasets at continental and global scales are based on either the PDSI or the sc-PDSI. A new global drought dataset based on the Standardised Precipitation-Evapotranspiration Index (SPEI) has been developed, which covers time scales from 1-48 months at a spatial resolution of 0.5°, and provides temporal coverage for the period 1901-2006. This dataset represents an improvement in spatial resolution and operative capability of previous gridded drought datasets based on the PDSI, and enables identification of various drought types. A monthly global dataset of a multiscalar drought index is presented and compared in terms of spatial and temporal variability with the existing continental and global drought datasets based on the Palmer drought severity index (PDSI, scPDSI). The new dataset is based on the standardized precipitation evapotranspiration index (SPEI). The index was obtained from the CRU TS3.0 data, covering time scales from 1 to 48 months for the period 1901-2006, and has a spatial resolution of 0.5°. The advantages of the new dataset are that: i) it improves the spatial resolution of the unique global drought dataset at a global scale; ii) it is spatially and temporally comparable to other datasets, given the probabilistic nature of the SPEI, and, in particular; iii) it enables identification of various drought types, given the multiscalar character of the SPEI. More details at: http://www.eead.csic.es/spei/spei.html, The Global 0.5° gridded SPEI dataset is made available under the Open Database License. Any rights in individual contents of the database are licensed under the Database Contents License. Users of the dataset are free to share, create and adapt under the conditions of attribution and share-alike. Use of the newest version is recommended. Older versions are still available to allow replicability., All currently available gridded drought datasets at continental and global scales are based on either the PDSI or the sc-PDSI. A new global drought dataset based on the Standardised Precipitation-Evapotranspiration Index (SPEI) has been developed, which covers time scales from 1-48 months at a spatial resolution of 0.5°, and provides temporal coverage for the period 1901-2006. This dataset represents an improvement in spatial resolution and operative capability of previous gridded drought datasets based on the PDSI, and enables identification of various drought types., A monthly global dataset of a multiscalar drought index is presented and compared in terms of spatial and temporal variability with the existing continental and global drought datasets based on the Palmer drought severity index (PDSI, scPDSI). The new dataset is based on the standardized precipitation evapotranspiration index (SPEI). The index was obtained from the CRU TS3.0 data, covering time scales from 1 to 48 months for the period 1901-2006, and has a spatial resolution of 0.5°. The advantages of the new dataset are that: i) it improves the spatial resolution of the unique global drought dataset at a global scale; ii) it is spatially and temporally comparable to other datasets, given the probabilistic nature of the SPEI, and, in particular; iii) it enables identification of various drought types, given the multiscalar character of the SPEI. More details at: http://www.eead.csic.es/spei/spei.html

The dataset is freely available on the web repository of the Spanish National Research Council (CSIC) in three different formats (NetCDF, binary raster, and plain text)., Format: The plain text archive is composed of 576 zipped files, corresponding to the SPEI index at time scales between 1 and 48 months for the whole World and divided by decades (except the last file, containing only data for the period 2001-2006). Each zipped file contains one plain text file (.csv). Data on those files are separated by commas, ′,'. Naming convention: spei[tempscale]_[decade].zip, where [tempscale] is a number between 1 and 48 indicating the temporal scale of the index (months), and [decade] indicates the years of data contained in the file. Example: spei12_1910-1919.zip. Data are stored as plain text separated by commas, ','. Each file contains the following columns: GRAPH_ID (cell identification), X (longitude coordinate), Y (latitude coordinate), mmmaaaa (the monthly SPEI values, e.g. Jan1910)., The Global 0.5° gridded SPEI dataset is made available under the Open Database License. Any rights in individual contents of the database are licensed under the Database Contents License. Users of the dataset are free to share, create and adapt under the conditions of attribution and share-alike. Use of the newest version is recommended. Older versions are still available to allow replicability., All currently available gridded drought datasets at continental and global scales are based on either the PDSI or the sc-PDSI. A new global drought dataset based on the Standardised Precipitation-Evapotranspiration Index (SPEI) has been developed, which covers time scales from 1-48 months at a spatial resolution of 0.5°, and provides temporal coverage for the period 1901-2006. This dataset represents an improvement in spatial resolution and operative capability of previous gridded drought datasets based on the PDSI, and enables identification of various drought types., A monthly global dataset of a multiscalar drought index is presented and compared in terms of spatial and temporal variability with the existing continental and global drought datasets based on the Palmer drought severity index (PDSI, scPDSI). The new dataset is based on the standardized precipitation evapotranspiration index (SPEI). The index was obtained from the CRU TS3.0 data, covering time scales from 1 to 48 months for the period 1901-2006, and has a spatial resolution of 0.5°. The advantages of the new dataset are that: i) it improves the spatial resolution of the unique global drought dataset at a global scale; ii) it is spatially and temporally comparable to other datasets, given the probabilistic nature of the SPEI, and, in particular; iii) it enables identification of various drought types, given the multiscalar character of the SPEI. More details at: http://www.eead.csic.es/spei/spei.html

This contains five zip files with 13 files each one. The format of the files is ArcGis ASCII, which can be imported or directly opened by different files. The five files are: precipitation.zip, contains the monthly (12) and annual (1) ASCII files for precipitation. tmax.zip, contains the monthly (12) and annual (1) ASCII files for maximum temperature. tmin.zip, contains the monthly (12) and annual (1) ASCII files for minimum temperature. ETo.zip, contains the monthly (12) and annual (1) ASCII files for reference evapotranspiration. balance.zip, contains the monthly (12) and annual (1) ASCII files for water balance. Cordinates are geographic (WGS84) The boundaries of the files are: min. X : -69.6646075000000 max. X : -57.5146075000000 min. Y : -22.9054771000000 max. Y : -9.67547710000000 spatial resolution is 0.009 degrees (about 1 km. of spatial resolution)., The dataset is made available under the Open Database License. Any rights in individual contents of the database are licensed under the Database Contents License. Please, read the full ODbL 1.0 license text for the exact terms that apply. Users of the dataset are free to: Share: copy, distribute and use the database, either commercially or non-commercially. Create: produce derivative works from the database. Adapt: modify, transform and build upon the database. Under the following conditions: Attribution: You must attribute any public use of the database, or works produced from the database. For any use or redistribution of the database, or works produced from it, you must make clear to others the license of the original database. Share-Alike: If you publicly use any adapted version of this database, or works produced from an adapted database, you must also offer that adapted database under the ODbL., This dataset introduces monthly and annual climate maps for relevant hydroclimatic variables in Bolivia. We have used the most complete network of precipitation and temperature stations available in Bolivia, which passed a careful quality control and temporal homogenization procedure. Monthly average maps at the spatial resolution of 1-km are modeled by means of a regression-based approach using topographic and geographic variables as predictors, and adding the residuals between observations and predictions, which were interpolated using the inverse distance weighting algorithm. The monthly average maximum and minimum temperatures, precipitation, and topographically modeled exoatmospheric solar radiation are used to estimate the monthly average atmospheric evaporative demand by means of the Hargreaves model. Finally, the average water balance is estimated on a monthly scale for each 1-km cell size by means of the difference between precipitation and atmospheric evaporative demand. Annual maps are created by averaging monthly values for temperature and adding the monthly values for precipitation, atmospheric evaporative demand and water balance. The digital layers are availablein ArcGIS ASCII format., Fuente de financiación del proyecto en que se encuadran los datos: I-COOP H2O 2013CD0006: “Test multisectorial y actividades demostrativa sobre el potencial desarrollo de sistemas de monitorización de sequías en tiempo real en la región del oeste de Sudamérica”, Peer reviewed

The Global 0.5° gridded SPEI dataset is made available under the Open Database License. Any rights in individual contents of the database are licensed under the Database Contents License. Users of the dataset are free to share, create and adapt under the conditions of attribution and share-alike. The Global SPEI database, SPEIbase, offers long-time, robust information on the drought conditions at the global scale, with a 0.5 degrees spatial resolution and a monthly time resolution. It has a multi-scale character, providing SPEI time-scales between 1 and 48 months. The Standardized Precipitatin-Evapotranspiration Index (SPEI) expresses, as a standardized variate (mean zero and unit variance), the deviations of the current climatic balance (precipitation minus evapotranspiration potential) with respect to the long-term balance. The reference period for the calculation, in the SPEIbase, corresponds to the whole study period. Being a standardized variate means that the SPEI condition can be compared across space and time. Calculation of the evapotranspiration potential in SPEIbase is based on the FAO-56 Penman-Monteith method. Data type: float; units: z-values (standard deviations). No land pixels are assigned a value of 1.0x10^30. In some rare cases it was not possible to achieve a good fit to the log-logistic distribution, resulting in a NAN (not a number) value in the database. Dimensions of the dataset: lon = 720; lat = 360; time = 1356. Resolution of the dataset: lon = 0.5º; lat = 0.5º; time = 1 month. Created in R using the SPEI package (http://cran.r-project.org/web/packages/SPEI)., Global gridded dataset of the Standardized Precipitation-Evapotranspiration Index (SPEI) at time scales between 1 and 48 months.-- Spatial resolution of 0.5º lat/lon.-- This is an update of the SPEIbase v2.3 (http://hdl.handle.net/10261/104742).-- What’s new in version 2.4: 1) Data has been extended to the period 1901-2014 (it was 1901-2013 in v 2.3), based on the CRU TS3.23 dataset.-- For more details on the SPEI visit http://sac.csic.es/spei., Peer reviewed

This contains two zip files with one file each one, corresponding to the maximum and minimum temperatures. The format of the files is netCDF3. Each file contains 282 longitudes, 407 latitudes and 607 times (from January 1964 to July 2014). Projection is Geographic (WGS84). The dataset is made available under the Open Database License. Any rights in individual contents of the database are licensed under the Database Contents License. Please, read the full ODbL 1.0 license text for the exact terms that apply. Users of the dataset are free to: Share: copy, distribute and use the database, either commercially or non-commercially. Create: produce derivative works from the database. Adapt: modify, transform and build upon the database. Under the following conditions: Attribution: You must attribute any public use of the database, or works produced from the database. For any use or redistribution of the database, or works produced from it, you must make clear to others the license of the original database. Share-Alike: If you publicly use any adapted version of this database, or works produced from an adapted database, you must also offer that adapted database under the ODbL., This dataset includes 5 km. spatial resolution time series of maximum and minimum temperatures for the entire Peru. The gridded data has been created using the entire temperature series available for Peru, which were subjected to a quality control and homogenization procedure. Gridded data was created by means of a regression-based approach using terrain and topographic variables as inputs. One independent model was created for each month of the series. Residuals were interpolated by means of a IDW procedure. The data was validated using a jackknife approach., No

Data Set License: ODbL 1.0. © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/), Drought indices are essential metrics for quantifying drought severity and identifying possible changes in the frequency and duration of drought hazards. In this study, we developed a new high spatial resolution dataset of drought indices covering all of Spain. The dataset includes seven drought indices, spans the period 1961–2014, and has a spatial resolution of 1.1 km and a weekly temporal resolution. A web portal has been created to enable download and visualization of the data. The data can be downloaded as single gridded points for each drought index, but the entire drought index dataset can also be downloaded in netCDF4 format. The dataset will be updated for complete years as the raw meteorological data become available., Data Set: http://monitordesequia.csic.es/, This work was supported by research projects PCIN-2015-220, CGL2014-52135-C03-01, CGL2014-52135-C03-02 and CGL2014-52135-C03-03 financed by the Spanish Commission of Science and Technology and FEDER, IMDROFLOOD financed by the Water Works 2014 co-funded call of the European Commission and INDECIS, financed by the European ERA4CS Joint Call for Transnational Collaborative Research Projects., We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI)., Peer reviewed

The dataset contains one zip file corresponding to the SEDI. The format of the file is netCDF3. The file contains 1440 longitudes, 720 latitudes and 444 times (from January 1980 to December 2016). Projection is Geographic (WGS84). The SEDI is in standardized units. The dataset is made available under the Open Database License. Any rights in individual contents of the database are licensed under the Database Contents License. Please, read the full ODbL 1.0 license text for the exact terms that apply. Users of the dataset are free to: Share: copy, distribute and use the database, either commercially or non-commercially. Create: produce derivative works from the database. Adapt: modify, transform and build upon the database. Under the following conditions: Attribution: You must attribute any public use of the database, or works produced from the database. For any use or redistribution of the database, or works produced from it, you must make clear to others the license of the original database. Share-Alike: If you publicly use any adapted version of this database, or works produced from an adapted database, you must also offer that adapted database under the ODbL., This dataset includes 0.25º spatial resolution time series of the Standardized Evapotranspiration Deficit Index. The gridded data has been created using the version 3.1 of the Global Land Evaporation Amsterdam Model (GLEAM) dataset (https://www.gleam.eu/#home). Data covers the period between 1980 and 2016. SEDI is obtained using a log-logistic distribution to fit the Evapotranspiration Deficit., Peer reviewed

Los detalles de la metodología y los resultados se pueden encontrar en: Domínguez-Castro, F., Vicente-Serrano, S.M., Tomás-Burguera, M., Peña-Gallardo M., Beguería S., El Kenawy A., Luna, Y., Morata, A. High-spatial-resolution probability maps of drought duration and magnitude across Spain. https://doi.org/10.5194/nhess-2018-289 Acceso mediante licencia: http://opendatacommons.org/licenses/odbl/1-0/, This dataset includes 1.1 km spatial resolution of the Generalized Pareto parameters (X0, alpha, Kappa) of drought duration and magnitude for SPI and SPEI at 1, 3, 6 and 12 months timescales and the maximum drought duration and magnitude risk maps for 50 and 100 years for SPI and SPEI at 1, 3, 6 and 12 months timescales. This dataset contains two zip files “parameters” and “risk_maps”. Parameters zip file contains 16 netCDF3 (8 for drought magnitude and 8 for drought duration) each one provides the Generalized Pareto parameters (1:X0, 2:alpha, 3:Kappa) for one index (SPI or SPEI) and one timescale (1, 3, 6 and 12 months). Risk_maps zip file contains 8 netCDF3 (4 for maximum drought magnitude and 4 for maximum drought duration) each one provides the risk maps for 4 time scales (1, 3, 6, 12 months) of one index (SPI or SPEI) and one time period (50 or 100 years). Each netCDF file contains 1115 longitudes and 834 latitudes., This work was supported by the following research projects: CGL2014-52135-C03-01 and PCIN-2015-220 financed by the Spanish Commission of Science and Technology and FEDER, 1560/2015; Herramientas de monitorización de la vegetación mediante modelización ecohidrológica en parques continentales financed by the Red de Parques Nacionales. IMDROFLOOD financed by Water Works 2014; a co-funded call of the European Commission and INDECIS, Peer reviewed