Gridded daily precipitation data for Iran: A comparison of different methods

Study region: Iran Study focus: Gridded precipitation products are of great interest for hydrological applications. The inhomogeneous geography and uneven spatial distribution of rain gauges in Iran make it difficult to estimate valuable interpolated precipitation with daily or monthly resolutions....

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Autores principales:	András Bárdossy, Ehsan Modiri, Faizan Anwar, Geoffrey Pegram
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Daily precipitation Iran Interpolation Kriging Clustering Atmospheric circulation patterns Physical geography GB3-5030 Geology QE1-996.5
Acceso en línea:	https://doaj.org/article/be037d497b324406b862d19435679bbb
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spelling	oai:doaj.org-article:be037d497b324406b862d19435679bbb2021-11-06T04:29:04ZGridded daily precipitation data for Iran: A comparison of different methods2214-581810.1016/j.ejrh.2021.100958https://doaj.org/article/be037d497b324406b862d19435679bbb2021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2214581821001877https://doaj.org/toc/2214-5818Study region: Iran Study focus: Gridded precipitation products are of great interest for hydrological applications. The inhomogeneous geography and uneven spatial distribution of rain gauges in Iran make it difficult to estimate valuable interpolated precipitation with daily or monthly resolutions. Therefore, we evaluated the performance of two empirical and four geostatistical interpolation methods. New hydrological insights for the region: Atmospheric circulation pattern (CP) classification was used to understand precipitation behavior and to improve interpolation. Based on 500 hPa geopotential fields, six CPs were identified, in order to explain large scale precipitation behavior. Variograms were normed and clustered to reduce the computational effort of the geostatistical methods.Leave-one-out cross-validation shows that the geostatistical methods outperform the empirical ones, and the differences among the geostatistical methods are small.The difference among all the methodologies decreased substantially for spatial aggregation to coarser resolutions. In contrast, temporal aggregation reduced the difference to a much lower extent.A large dataset consisting of 1561 locations with daily observations was used for this study. Comparison with the GPCC daily dataset shows that the data used for interpolation has a larger influence than the choice of the interpolation method.András BárdossyEhsan ModiriFaizan AnwarGeoffrey PegramElsevierarticleDaily precipitationIranInterpolationKrigingClusteringAtmospheric circulation patternsPhysical geographyGB3-5030GeologyQE1-996.5ENJournal of Hydrology: Regional Studies, Vol 38, Iss , Pp 100958- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Daily precipitation Iran Interpolation Kriging Clustering Atmospheric circulation patterns Physical geography GB3-5030 Geology QE1-996.5
spellingShingle	Daily precipitation Iran Interpolation Kriging Clustering Atmospheric circulation patterns Physical geography GB3-5030 Geology QE1-996.5 András Bárdossy Ehsan Modiri Faizan Anwar Geoffrey Pegram Gridded daily precipitation data for Iran: A comparison of different methods
description	Study region: Iran Study focus: Gridded precipitation products are of great interest for hydrological applications. The inhomogeneous geography and uneven spatial distribution of rain gauges in Iran make it difficult to estimate valuable interpolated precipitation with daily or monthly resolutions. Therefore, we evaluated the performance of two empirical and four geostatistical interpolation methods. New hydrological insights for the region: Atmospheric circulation pattern (CP) classification was used to understand precipitation behavior and to improve interpolation. Based on 500 hPa geopotential fields, six CPs were identified, in order to explain large scale precipitation behavior. Variograms were normed and clustered to reduce the computational effort of the geostatistical methods.Leave-one-out cross-validation shows that the geostatistical methods outperform the empirical ones, and the differences among the geostatistical methods are small.The difference among all the methodologies decreased substantially for spatial aggregation to coarser resolutions. In contrast, temporal aggregation reduced the difference to a much lower extent.A large dataset consisting of 1561 locations with daily observations was used for this study. Comparison with the GPCC daily dataset shows that the data used for interpolation has a larger influence than the choice of the interpolation method.
format	article
author	András Bárdossy Ehsan Modiri Faizan Anwar Geoffrey Pegram
author_facet	András Bárdossy Ehsan Modiri Faizan Anwar Geoffrey Pegram
author_sort	András Bárdossy
title	Gridded daily precipitation data for Iran: A comparison of different methods
title_short	Gridded daily precipitation data for Iran: A comparison of different methods
title_full	Gridded daily precipitation data for Iran: A comparison of different methods
title_fullStr	Gridded daily precipitation data for Iran: A comparison of different methods
title_full_unstemmed	Gridded daily precipitation data for Iran: A comparison of different methods
title_sort	gridded daily precipitation data for iran: a comparison of different methods
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/be037d497b324406b862d19435679bbb
work_keys_str_mv	AT andrasbardossy griddeddailyprecipitationdataforiranacomparisonofdifferentmethods AT ehsanmodiri griddeddailyprecipitationdataforiranacomparisonofdifferentmethods AT faizananwar griddeddailyprecipitationdataforiranacomparisonofdifferentmethods AT geoffreypegram griddeddailyprecipitationdataforiranacomparisonofdifferentmethods
_version_	1718443940991991808

Gridded daily precipitation data for Iran: A comparison of different methods

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