Resultados de investigación

[EN] The dataset is a collection of data based on geostatistical interpolation techniques (universal kriging or Gaussian process regression), supported by external variables such as elevation and continentality, the latter quantified through the distance to seas and oceans. These methods interpolate the daily observations available from AEMET. This dataset provides high-resolution information produced from a very dense observation network and is particularly suitable for climatological and climate trend studies. In this dataset, daily data have been consolidated for the period from 1961 to the present., [ES] El dataset es un conjunto de datos basado en técnicas geoestadísticas de interpolación (kriging universal o regresión de proceso gaussiano, apoyado por variables externas como la elevación o la continentalidad, cuantificada esta última mediante la distancia a mares y océanos) que interpolan las observaciones diarias disponibles de AEMET. Este conjunto de datos proporciona información de alta resolución producida con una red muy densa de observaciones y es idónea para realizar estudios climatológicos y de tendencias del clima. En este dataset se ha consolidado el dato diario para el período 1961-presente., [ES] Este trabajo de investigación ha sido financiado por el Ministerio para la Transición Ecológica y el Reto Demográfico (MITECO) y la Comisión Europea - NextGenerationEU (Reglamento UE 2020/2094), a través de la Plataforma Temática Interdisciplinar Clima (PTI Clima) / Desarrollo de Servicios Climáticos Operativos del CSIC., [EN] This research work was funded by the Ministry for the Ecological Transition and the Demographic Challenge (MITECO) and the European Commission NextGenerationEU (Regulation EU 2020/2094), through CSIC's Interdisciplinary Thematic Platform Clima (PTI-Clima)., No, Sin experimentacion animal ni uso de NAMs

El conjunto de datos se compone de 96 archivos NetCDF, comprimidos en formato zip, representando una escala temporal distinta que abarca desde 1 hasta 48 meses. Se puede acceder y manipular estos archivos utilizando diversas herramientas de software, incluidas aplicaciones SIG como QGIS y ArcMap, aplicaciones especializadas como Panoply (https://www.giss.nasa.gov/tools/panoply/), y librerías específicas como ncdf4, raster o terra en R, así como netCDF4 o xarray en Python, entre otras. Cada archivo NetCDF contiene una matriz tridimensional con dimensiones de 720x360x1476. Los píxeles de tierra se identifican con el valor 1.0x10^30 y los errores de cálculo con valores NaN. El conjunto de datos se ha generado en R utilizando el paquete SPEI (http://cran.r-project.org/web/packages/SPEI)., [EN] 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: https://spei.csic.es/database.html, [ES] Se presenta un conjunto de datos globales mensuales de un índice de sequía multiescalar y se compara en términos de variabilidad espacial y temporal con los conjuntos de datos de sequía continentales y globales existentes basados en el índice de severidad de la sequía de Palmer (PDSI, scPDSI, por su acrónimo en inglés). El nuevo conjunto de datos se basa en el índice estandarizado de evapotranspiración de las precipitaciones (SPEI, por su acrónimo en inglés). El índice se obtuvo a partir de los datos del CRU TS3.0, cubre escalas temporales de 1 a 48 meses para el periodo 1901-2006 y tiene una resolución espacial de 0,5°. Las ventajas del nuevo conjunto de datos son que: i) mejora la resolución espacial del único conjunto de datos mundial sobre sequía a escala global; ii) es comparable espacial y temporalmente con otros conjuntos de datos, dada la naturaleza probabilística del SPEI, y, en particular; iii) permite identificar varios tipos de sequía, dado el carácter multiescalar del SPEI. Más detalles en: https://spei.csic.es/database.html, This work was not supported by any external funding., 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

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., [EN] Global gridded dataset of the Standardised Precipitation-Evapotranspiration Index (SPEI) at time scales between 1 and 48 months. Spatial resolution of 0.5º lat/lon. Temporal coverage between January 1901 and December 2009. This is an update of a previous version of SPEIbase (http://hdl.handle.net/10261/22449). What’s new in version 2.0: 1) Data has been extended to the period 1901-2009 (it was 1901-2006 in v 1.0). 2) The FAO-56 Penman-Monteith's method has been used for computing PET instead of Thornthwaite. 3) Unbiased probability weighted moments (ub-pwm) method has been used for fitting the log-Logistic distribution, instead of the sub-optimal plotting-position pwm method used in version 1.0. 4) The whole world is put in one single netCDF file. For more details on the SPEI visit https://spei.csic.es/., This work was not supported by any external funding., 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., 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. Temporal coverage between January 1901 and December 2011. This is an update of a previous version of SPEIbase v2 (http://hdl.handle.net/10261/48169). What’s new in version 2.2: 1) Data has been extended to the period 1901-2011 (it was 1901-2009 in v 2.0). 2) The FAO grass reference evapotranspiration from the CRU TS3.2 dataset has been used as PET input for the SPEI (http://badc.nerc.ac.uk/browse/badc/cru/data/cru_ts_3.20). Precipitation is also obtained from the same CRU TS3.2 dataset. 3) Unbiased probability weighted moments (ub-pwm) method has been used for fitting the log-Logistic distribution, instead of the sub-optimal plotting-position pwm method used in version 1.0. For more details on the SPEI visit https://spei.csic.es/., This work was not supported by any external funding., Peer reviewed

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., [EN] 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 v2.2 (http://hdl.handle.net/10261/72264).-- What’s new in version 2.3: 1) Data has been extended to the period 1901-2013 (it was 1901-2011 in v 2.0), based on the CRU TS3.22 dataset.-- For more details on the SPEI visit https://spei.csic.es/., This work was not supported by any external funding., No

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 https://spei.csic.es/., This work was not supported by any external funding., 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