From rain to data: A review of the creation of monthly and daily station-based gridded precipitation datasets

Monthly and daily gridded precipitation datasets are one of the most demanded products in climatology and hydrology. These datasets describe the high spatial and temporal variability of precipitation as a continuous surface and for defined periods. However, due to the complex characteristics of prec...

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Bibliographic Details
Authors: Serrano Notivoli, Roberto, Tejedor, Ernesto
Format: article
Publication Date:2021
Country:España
Institution:Universidad Autónoma de Madrid
Repository:Biblos-e Archivo. Repositorio Institucional de la UAM
Language:English
OAI Identifier:oai:repositorio.uam.es:10486/700717
Online Access:http://hdl.handle.net/10486/700717
https://dx.doi.org/10.1002/wat2.1555
Access Level:Open access
Keyword:grid
interpolation
precipitation
quality control
reconstruction
Geografía
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spelling From rain to data: A review of the creation of monthly and daily station-based gridded precipitation datasetsSerrano Notivoli, RobertoTejedor, Ernestogridinterpolationprecipitationquality controlreconstructionGeografíaMonthly and daily gridded precipitation datasets are one of the most demanded products in climatology and hydrology. These datasets describe the high spatial and temporal variability of precipitation as a continuous surface and for defined periods. However, due to the complex characteristics of precipitation, it is difficult to obtain accurate estimations. Thus, the creation of a gridded dataset from observations requires the comprehensive and precise application of quality control, reconstruction, and gridding procedures. Yet, despite multiple advances, most of the gridded datasets created and published since the mid-1990s to the present use a wide variety of techniques, methods, and outputs, which can completely change the final representativity of the data. It is, therefore, critical to provide general guidelines for the development of future and more robust gridded datasets based on the data characteristics, geographical factors, and advanced statistical techniques. We identified gaps and challenges for near-future perspectives and provide guidelines for implementing improved approaches based on the performance of 48 products. Finally, we concluded that, despite better spatial and temporal resolutions, data access, and data processing capabilities, observational coverage remains a challenge. Moreover, scientists should adopt tailored strategies to improve the representativity and uncertainty of the estimates. This article is categorized under: Science of Water > Hydrological Processes Science of Water > Water Extremes Science of Water > MethodsThis work was supported by the Government of Aragón through the “Program of research groups” (group H09_20R, “Climate, Water, Global Change, and Natural Systems”). Ernesto Tejedor is partially funded by the NSF-PIRE (OISE- 1743738)WileyDepartamento de GeografíaFacultad de Filosofía y Letras20212021-08-26research articlehttp://purl.org/coar/resource_type/c_2df8fbb1VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10486/700717https://dx.doi.org/10.1002/wat2.1555reponame:Biblos-e Archivo. Repositorio Institucional de la UAMinstname:Universidad Autónoma de MadridInglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:repositorio.uam.es:10486/7007172026-06-23T12:46:27Z
dc.title.none.fl_str_mv From rain to data: A review of the creation of monthly and daily station-based gridded precipitation datasets
title From rain to data: A review of the creation of monthly and daily station-based gridded precipitation datasets
spellingShingle From rain to data: A review of the creation of monthly and daily station-based gridded precipitation datasets
Serrano Notivoli, Roberto
grid
interpolation
precipitation
quality control
reconstruction
Geografía
title_short From rain to data: A review of the creation of monthly and daily station-based gridded precipitation datasets
title_full From rain to data: A review of the creation of monthly and daily station-based gridded precipitation datasets
title_fullStr From rain to data: A review of the creation of monthly and daily station-based gridded precipitation datasets
title_full_unstemmed From rain to data: A review of the creation of monthly and daily station-based gridded precipitation datasets
title_sort From rain to data: A review of the creation of monthly and daily station-based gridded precipitation datasets
dc.creator.none.fl_str_mv Serrano Notivoli, Roberto
Tejedor, Ernesto
author Serrano Notivoli, Roberto
author_facet Serrano Notivoli, Roberto
Tejedor, Ernesto
author_role author
author2 Tejedor, Ernesto
author2_role author
dc.contributor.none.fl_str_mv Departamento de Geografía
Facultad de Filosofía y Letras
dc.subject.none.fl_str_mv grid
interpolation
precipitation
quality control
reconstruction
Geografía
topic grid
interpolation
precipitation
quality control
reconstruction
Geografía
description Monthly and daily gridded precipitation datasets are one of the most demanded products in climatology and hydrology. These datasets describe the high spatial and temporal variability of precipitation as a continuous surface and for defined periods. However, due to the complex characteristics of precipitation, it is difficult to obtain accurate estimations. Thus, the creation of a gridded dataset from observations requires the comprehensive and precise application of quality control, reconstruction, and gridding procedures. Yet, despite multiple advances, most of the gridded datasets created and published since the mid-1990s to the present use a wide variety of techniques, methods, and outputs, which can completely change the final representativity of the data. It is, therefore, critical to provide general guidelines for the development of future and more robust gridded datasets based on the data characteristics, geographical factors, and advanced statistical techniques. We identified gaps and challenges for near-future perspectives and provide guidelines for implementing improved approaches based on the performance of 48 products. Finally, we concluded that, despite better spatial and temporal resolutions, data access, and data processing capabilities, observational coverage remains a challenge. Moreover, scientists should adopt tailored strategies to improve the representativity and uncertainty of the estimates. This article is categorized under: Science of Water > Hydrological Processes Science of Water > Water Extremes Science of Water > Methods
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-08-26
dc.type.none.fl_str_mv research article
http://purl.org/coar/resource_type/c_2df8fbb1
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10486/700717
https://dx.doi.org/10.1002/wat2.1555
url http://hdl.handle.net/10486/700717
https://dx.doi.org/10.1002/wat2.1555
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv reponame:Biblos-e Archivo. Repositorio Institucional de la UAM
instname:Universidad Autónoma de Madrid
instname_str Universidad Autónoma de Madrid
reponame_str Biblos-e Archivo. Repositorio Institucional de la UAM
collection Biblos-e Archivo. Repositorio Institucional de la UAM
repository.name.fl_str_mv
repository.mail.fl_str_mv
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