Ítem
Acceso Abierto

Daily dataset of precipitation and temperature in the Department of Cauca, Colombia

Mostrar el registro sencillo de la publicación
dc.creatorBlanco Mantilla, Kspa
dc.creatorVillamizar, Sspa
dc.creatorAvila Diaz, Alvaro Javierspa
dc.creatorMarcelo, Cspa
dc.creatorSantamaria, Espa
dc.creatorLesmes, Maria Camilaspa
dc.date.accessioned2024-01-31T18:23:09Z
dc.date.available2024-01-31T18:23:09Z
dc.date.created2023-10-01spa
dc.date.issued2023spa
dc.descriptionThis study used the geostatistical Kriging methodology to reduce the spatial scale of a host of daily meteorological variables in the Department of Cauca (Colombia), namely, total precipitation and maximum, minimum, and average temperature. The objective was to supply a high-resolution database from 01/01/2015 to 31/12/2021 in order to support the climate component in a project led by the National Institute of Health (INS) named “Spatial Stratification of dengue based on the identification of risk factors: a pilot study in the Department of Cauca”. The scaling process was applied to available databases from satellite information and reanalysis sources, specifically, CHIRPS (Climate Hazards Group InfraRed Precipitation with Station Data), ERA5-Land (European Centre for Medium-Range Weather Forecasts), and MSWX (Multi-Source Weather). The 0.1° resolution offered by both the MSWX and ERA5-Land databases and the 0.05° resolution found in CHIRPS, was successfully reduced to a scale of 0.01° across all variables. Statistical metrics such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Person Correlation Coefficient (r), and Mean Bias Error (MBE) were used to select the database that best estimated each variable. As a result, it was determined that the scaled ERA5-Land database yielded the best performance for precipitation and minimum daily temperature. On the other hand, the scaled MSWX database showed the best behavior for the other two variables of maximum temperature and daily average temperature. Additionally, using the scaled meteorological databases improved the performance of the regression models implemented by the INS for constructing a dengue early warning system.spa
dc.format.mimetypeapplication/pdfspa
dc.identifier.doi10.1016/j.dib.2023.109542spa
dc.identifier.issn2352-3409spa
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/42107
dc.language.isoengspa
dc.publisherUniversidad del Rosariospa
dc.relation.urihttps://pubmed.ncbi.nlm.nih.gov/37743883/spa
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 Internationalspa
dc.rights.accesRightsinfo:eu-repo/semantics/openAccessspa
dc.rights.accesoAbierto (Texto Completo)spa
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/spa
dc.sourceData in Briefspa
dc.source.instnameinstname:Universidad del Rosariospa
dc.source.reponamereponame:Repositorio Institucional EdocURspa
dc.subjectSpatial downscalingspa
dc.subjectERA5-Landspa
dc.subjectCHIRPSspa
dc.subjectMSWXspa
dc.subjectKrigingspa
dc.titleDaily dataset of precipitation and temperature in the Department of Cauca, Colombiaspa
dc.typearticlespa
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersionspa
dc.type.spaArtículospa
Archivos
Bloque original
Mostrando1 - 1 de 1
Miniatura
Nombre:
Daily dataset of precipitation.pdf
Tamaño:
5.16 MB
Formato:
Adobe Portable Document Format
Descripción:
Descargar
Colecciones
Artículos