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The photographs of glasses containing wine were acquired by researchers with different smartphones equipped with high-resolution cameras (12 or 48 MP). Photographs were previously designed considering usual photographic parameters (see DATA-SPECIFIC INFORMATION for details).-- The data have not been processed., The DATASET compiles 1.945 files corresponding to individual images of glasses containing red wine. The photographs of glasses containing wine were acquired by researchers with different smartphones equipped with high-resolution cameras (12 or 48 MP). Photographs were previously designed considering usual photographic parameters. Each file name is unique and contains information of the parameters under which the photograph was taken., This study was supported by MCIN (Ministerio de Ciencia e Innovación)/AEI (Agencia Estatal de Investigación)/10 .13039 /501100011033through the projects PID2019-108851RB-C21 & PID2019-108851RB-C22. The authors would like to thank CSIC Interdisciplinary Thematic Platform (PTI+) Digital Science and Innovation., The DATASET compiles 1.945 files corresponding to individual images of glasses containing red wine. Each file name is unique and contains information of the parameters under which the photograph was taken (see DATA-SPECIFIC INFOR-MATION for details). For example: The file Rea_Rio_C_Bor_175_nd_nd_fr10_nd_nd_ar2 corresponds to an almost real image (Rea), taken in La Rioja (Rio), of a “crianza wine”(C), in a Bourgogne wine glass (Bor), with a volume of 175 mL (175), taken at none defined time (nd) and undefined lighting (nd), with a real back-ground (fr10) and without reference (nd) nor distance (nd) considerations, and upper angle (ar2)., Peer reviewed

The photographs of glasses containing wine were acquired by wine consumers with different smartphones equipped with high-resolution cameras (12 or 48 MP). Photographs were previously designed considering usual photographic parameters (see DATA-SPECIFIC INFORMATION for details).-- The data have not been processed., The DATASET compiles 229 files corresponding to individual images of glasses containing red wine. The photographs of glasses containing wine were acquired by wine consumers with different smartphones equipped with high-resolution cameras (12 or 48 MP). Each file name is unique and contains information of the parameters under which the photo-graph was taken., This study was supported by MCIN (Ministerio de Ciencia e Innovación)/AEI (Agencia Estatal de Investigación)/10 .13039 /501100011033through the projects PID2019-108851RB-C21 & PID2019-108851RB-C22. The authors would like to thank CSIC Interdisciplinary Thematic Platform (PTI+) Digital Science and Innovation., The DATASET compiles 229 files corresponding to individual images of glasses containing red wine. Each file name is unique and contains information of the parameters under which the photograph was taken (see DATA-SPECIFIC INFOR-MATION for details). For example: The file Vol_Mad_C_Bor_175_Cena_nd_nd_nd_nd_nd corresponds to a real image taken by a consumer(#Vol), taken in Madrid (Mad), of a “crianza wine”(C), in a Bourgogne wine glass (Bor), with a volume of 175 mL (175), taken at dinner (Cena) with undefined lighting (nd) and a random real background (nd), and without reference (nd) nor distance (nd), nor angle (nd) considerations., 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 v2.6 (https://digital.csic.es/handle/10261/202305).-- What’s new in version 2.7: 1) Based on the CRU TS 4.05 dataset, spanning the period between January 1901 to December 2020. Using TLMoments::PWM instead of lmomco::pwm.ub for calculating distribution parameters. For more details on the SPEI visit http://sac.csic.es/spei, No

General information, experimental procedures, new compound characterization, crystallographic data, HPLC chromatograms, NMR spectra, DFT calculations, and STM data., Peer reviewed

[EN] SPI01 grid: plain text. 5219 rows (excluding the header) and 1261 columns (excluding the X and Y coordinates). SPI12 grid: plain text. 5219 rows (excluding the header) and 1250 columns (excluding the X and Y coordinates). Episode descriptive files: duration and intensity integral maps, SPI01 and SPI12 averages, and spatial propagation maps., [ES] Malla SPI01: texto plano. 5219 filas -descontando el encabezado- y 1261 columnas -descontando las coordenadas X e Y-. Malla SPI12: texto plano. 5219 filas -descontando el encabezado- y 1250 columnas -descontando las coordenadas X e Y-. Archivos descriptivos de los episodios: mapas integrales de duración e intensidad, promedios de SPI’1 y SPI12 y mapas de la propagación espacial., Open Data Commons Attribution (ODC-By 1.0)., [EN] The database consists of two files in .txt format with the precipitation anomaly grids (Standardized Precipitation Index) calculated at 1 and 12 months over the Spanish peninsular domain, covering the period 2015/12_2020/12. These have been calculated from the monthly data of the MOPREDAScentury precipitation grid (https://doi.org/10.20350/digitalCSIC/15136). In addition, a descriptive analysis of the 40 drought episodes identified according to the criteria of drought intensity (SPI12 =< -0.84) and affected area (>20 % of the grid area) is included. For each episode we include the time series of the SPI01 and SPI12 average of the whole grid (expressed in anomalies); the area of the grid under drought conditions (SPI12 =< -0.84) (expressed in percent per one); the integral maps of the episode according to its duration (expressed in number of months) and intensity (average of the cells under drought conditions); and the maps representing the spatial propagation of the episode. This record corresponds to version 1.0.0 of the dataset. The database is distributed under an open license (Open Data Commons Attribution, ODC-By)., [ES] La base de datos consta de dos archivos en formato .txt con las mallas de anomalías de precipitación (Standardized Precipitation Index) calculadas a 1 y 12 meses sobre el dominio peninsular español, cubriendo el periodo 12/2015_12/2020. Estas han sido calculadas a partir de los datos mensuales de la malla de precipitación MOPREDAScentury (https://doi.org/10.20350/digitalCSIC/15136). Además, se incluye un análisis descriptivo de los 40 episodios de sequía identificados según los criterios de intensidad de la sequía (SPI12 =< -0.84) y superficie afectada (>20 % de la superficie de la malla). Para cada episodio se incluyen las series temporales del SPI01 y SPI12 promedio de toda la malla (expresadas en anomalías); el área de la malla en condiciones de sequía (SPI12 =< -0.84) (expresada en tanto por uno); los mapas integrales del episodio atendiendo a su duración (expresada en número de meses) e intensidad (promedio de las celdas en condiciones de sequía); y los mapas que representan la propagación espacial del episodio. Este registro se corresponde con la versión 1.0.0 del conjunto de datos. La base de datos se distribuye bajo una licencia abierta (Open Data Commons Attribution, ODC-By)., Project PID2020-116860RB-C22: Extremos térmicos y pluviométricos en la España peninsular 1916-2020), funded by the Spanish Ministry of Science., Peer reviewed

[EN] It contains a collection of .csv files by country and a netCDF file. Last one need specific data analyse software. [ES] Contiene una colección de archivos .csv por país y un archivo netCDF. Este último necesita software de análisis de datos específico., [EN] This database includes the representative Standardized Precipitation Evapotranspiration Index (SPEI) series for the different countries of the world from 1901 at the time scales from 1 to 48 months. The data is based on the average precipitation and reference evapotranspiration series from the Climatic Research Unit (last version) for the different world countries., [ES] Esta base de datos incluye la serie representativa del Índice Estandarizado de Precipitación y Evapotranspiración (SPEI) para los diferentes países del mundo desde 1901 en las escalas de tiempo de 1 a 48 meses. Los datos se basan en las series de precipitación media y evapotranspiración de referencia de la Unidad de Investigación Climática (última versión) para los diferentes países del mundo., Peer reviewed

[EN] It contains a netCDF file which needs specific data analysis software. [ES] Contiene un fichero netCDF que necesita software de análisis de datos específico., [EN] It is a gridded dataset for the whole of Europe, which employed a set of 125 climate indices from 1950. Climate indices were computed at different temporal scales (i.e. monthly, seasonal and annual) and mapped at a grid interval of 0.25°., [ES] Es una rejilla de 125 índices climáticos con una resolución espacial de 0.25 grados calculados para toda Europa desde 1950. Los índices climáticos han sido calculados a diferentes escalas temporales (mensual, estacional y anual)., Spanish Commission of Science and Technology and FEDER by the research projects PCIN-2015-220, CGL2017-82216-R and CGL2017-83866-C3-1-R, AXIS (Assessment of Cross(X) - sectorial climate Impacts and pathways for Sustainable transformation), JPI-Climate co-funded call of the European Commission by the project CROSSDRO, FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462) by the reserach project INDECIS which is part of ERA4CS, an ERA-NET initiated by JPI Climate, Peer reviewed

[EN] It contains a netCDF file which needs specific data analysis software. [ES] Contiene un fichero netCDF que necesita software de análisis de datos específico., [EN] ECTACI database contains four statistical parameters (climatology, coefficient of variation, slope, and significant trend) from 125 standard climate indices for the whole Europe at 0.25° grid intervals from 1979 to 2017 at various temporal scales (monthly, seasonal, and annual)., [ES] La base de datos ECTACI proporciona cuatro parámetros estadísticos (climatología, coeficiente de variación, pendiente y significatividad de tendencia) de 125 índices climáticos para toda Europa con una resolución espacial de 0.25 grados desde 1979 a 2017 a tres escalas temporales (mensual, estacional y anual)., Spanish Commission of Science and Technology and FEDER by the research projects CGL2017‐82216‐R, CGL2017‐83866‐C3‐1‐R and PCI2019‐103631, the AXIS (Assessment of Cross(X) ‐ sectorial climate Impacts and pathways for Sustainable transformation), JPI‐Climate cofunded call of the European Commission by the research projects CROSSDRO, FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), and ANR (FR) with cofunding by the European Union (grant 690462) by the research projects INDECIS which is part of ERA4CS, an ERA‐NET, Peer reviewed

Series temporales mensuales de caudal., [EN] This dataset includes series of monthly streamflow of 3224 gauging stations throughout Europe with reconstructed data for the period 1962-2017., [ES] Base de datos de caudal mensual de 3224 estaciones de aforo a lo largo de Europa con datos reconstruidos para el periodo 1962-2017., Spanish Commission of Science and Technology and FEDER by the research projects CGL2017‐82216‐R and CGL2017‐83866‐C3‐1‐R and PCI2019‐103631, AXIS (Assessment of Cross(X) ‐ sectorial climate Impacts and pathways for Sustainable transformation), JPI‐Climate cofunded call of the European Commission by the research project CROSSDRO, FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), and ANR (FR) with cofunding by the European Union (grant 690462) by the research project INDECIS which is part of ERA4CS, an ERA‐NET initiated by JPI Climate, Peer reviewed

Modelizaciones ecohidrológicas en parques continentales de España, [EN] This dataset provide information about evapotranspiration, leaf area index, net primary productivity, precipitation, potential evapotranspiration, soil moisture, maximum and minimum temperature at 7 National Parks from peninsular Spain., [ES] Esta base de datos proporciona información de evapotranspiración, índice de área foliar, producción primaria neta, precipitación, evapotranspiración potencial, humedad del suelo, temperatura máxima y mínima para 7 parques nacionales de la España peninsular., Parques Naturales - Ministerio de agricutura y medio ambiente, a través del proyecto: Herramientas de monitorización de la vegetación mediante modelización ecohidrológica en parques continentales: Evolución reciente y proyecciones futuras (ECOHIDRO, 1560/2105), Peer reviewed