SPEIbase v.2.9 [Dataset]
[EN] The dataset is comprised of 48 NetCDF files, each representing a distinct temporal scale spanning from 1 to 48 months. It can be accessed and manipulated using various software tools, including GIS applications like QGIS and ArcMap, specialized applications like Panoply (https://www.giss.nasa.g...
| Autores: | , , , |
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| Formato: | conjunto de datos |
| Fecha de publicación: | 2023 |
| País: | España |
| Recursos: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/332007 |
| Acesso em linha: | http://hdl.handle.net/10261/332007 https://doi.org/10.20350/digitalCSIC/15470 |
| Access Level: | acceso abierto |
| Palavra-chave: | SPEI Drought Drought Index Standardized Precipitation-Evapotranspiration Index Precipitation Evapotranspiration Global Warming Climate change Climatology Climate data Global data http://metadata.un.org/sdg/13 Take urgent action to combat climate change and its impacts global warming climate change climate services meteorological observations |
| Resumo: | [EN] The dataset is comprised of 48 NetCDF files, each representing a distinct temporal scale spanning from 1 to 48 months. It can be accessed and manipulated using various software tools, including GIS applications like QGIS and ArcMap, specialized applications like Panoply (https://www.giss.nasa.gov/tools/panoply/), and dedicated libraries such as ncdf4, raster, or terra in R, as well as netCDF4 or xarray in Python, among others. Each NetCDF file contains a 3-dimensional matrix with dimensions of 720x360x1476. Land pixels are marked with the value 1.0x10^30, and occasionally, calculation errors may lead to NaN values. The dataset has been generated in R using the SPEI package (http://cran.r-project.org/web/packages/SPEI). [ES] El conjunto de datos se compone de 48 archivos NetCDF, cada uno 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). |
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