Validating the University of Delaware’s precipitation and temperature database for northern South America

Vast sections of the planet face either a dearth of ground-based weather stations or are hampered by the poor quality of those in service. In response, researchers are forced to turn to climate field databases, as they constitute a source of reliable information for local studies. Insofar as the Ama...

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Autores:
Santos-Gómez, José David
Fontalvo-García, Juan Sebastián
Giraldo Osorio, Juan Diego
Tipo de recurso:
Article of journal
Fecha de publicación:
2015
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/60617
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/60617
http://bdigital.unal.edu.co/58949/
Palabra clave:
62 Ingeniería y operaciones afines / Engineering
time series of interpolated climate fields
precipitation
temperature
South America
Amazon region.
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
Description
Summary:Vast sections of the planet face either a dearth of ground-based weather stations or are hampered by the poor quality of those in service. In response, researchers are forced to turn to climate field databases, as they constitute a source of reliable information for local studies. Insofar as the Amazon region, these databases prove to be valuable given their open-access platform and the fact that this expansive region possesses few quality stations (coupled with insufficient temporal coverage). However, before basing research on such archives, this information should be compared against in situ station measurements. Then, the present study assesses the validity of temperature and precipitation information furnished by University of Delaware’s database (UD-ATP) by means of a comparison with the open-access information available from Climate Explorer project (CLIMEXP). Results show that UD-ATP database offers better precipitation data representation, especially on Brazil, which is perhaps the effect of higher-quality and larger-quantity observed data.