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Development of high-resolution daily gridded temperature datasets for the central north region of Egypt

This study developed 0.05° × 0.05° land-only datasets of daily maximum and minimum temperatures in the densely populated Central North region of Egypt (CNE) for the period 1981–2017. Existing coarse-resolution datasets were evaluated to find the best dataset for the study area to use as a base of th...

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Autores principales: Nashwan, Mohamed Salem, Shahid, Shamsuddin, Chung, Eun-Sung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6668447/
https://www.ncbi.nlm.nih.gov/pubmed/31366936
http://dx.doi.org/10.1038/s41597-019-0144-0
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author Nashwan, Mohamed Salem
Shahid, Shamsuddin
Chung, Eun-Sung
author_facet Nashwan, Mohamed Salem
Shahid, Shamsuddin
Chung, Eun-Sung
author_sort Nashwan, Mohamed Salem
collection PubMed
description This study developed 0.05° × 0.05° land-only datasets of daily maximum and minimum temperatures in the densely populated Central North region of Egypt (CNE) for the period 1981–2017. Existing coarse-resolution datasets were evaluated to find the best dataset for the study area to use as a base of the new datasets. The Climate Prediction Centre (CPC) global temperature dataset was found to be the best. The CPC data were interpolated to a spatial resolution of 0.05° latitude/longitude using linear interpolation technique considering the flat topography of the study area. The robust kernel density distribution mapping method was used to correct the bias using observations, and WorldClim v.2 temperature climatology was used to adjust the spatial variability in temperature. The validation of CNE datasets using probability density function skill score and hot and cold extremes tail skill scores showed remarkable improvement in replicating the spatial and temporal variability in observed temperature. Because CNE datasets are the best available high-resolution estimate of daily temperatures, they will be beneficial for climatic and hydrological studies.
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spelling pubmed-66684472019-08-01 Development of high-resolution daily gridded temperature datasets for the central north region of Egypt Nashwan, Mohamed Salem Shahid, Shamsuddin Chung, Eun-Sung Sci Data Data Descriptor This study developed 0.05° × 0.05° land-only datasets of daily maximum and minimum temperatures in the densely populated Central North region of Egypt (CNE) for the period 1981–2017. Existing coarse-resolution datasets were evaluated to find the best dataset for the study area to use as a base of the new datasets. The Climate Prediction Centre (CPC) global temperature dataset was found to be the best. The CPC data were interpolated to a spatial resolution of 0.05° latitude/longitude using linear interpolation technique considering the flat topography of the study area. The robust kernel density distribution mapping method was used to correct the bias using observations, and WorldClim v.2 temperature climatology was used to adjust the spatial variability in temperature. The validation of CNE datasets using probability density function skill score and hot and cold extremes tail skill scores showed remarkable improvement in replicating the spatial and temporal variability in observed temperature. Because CNE datasets are the best available high-resolution estimate of daily temperatures, they will be beneficial for climatic and hydrological studies. Nature Publishing Group UK 2019-07-31 /pmc/articles/PMC6668447/ /pubmed/31366936 http://dx.doi.org/10.1038/s41597-019-0144-0 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Nashwan, Mohamed Salem
Shahid, Shamsuddin
Chung, Eun-Sung
Development of high-resolution daily gridded temperature datasets for the central north region of Egypt
title Development of high-resolution daily gridded temperature datasets for the central north region of Egypt
title_full Development of high-resolution daily gridded temperature datasets for the central north region of Egypt
title_fullStr Development of high-resolution daily gridded temperature datasets for the central north region of Egypt
title_full_unstemmed Development of high-resolution daily gridded temperature datasets for the central north region of Egypt
title_short Development of high-resolution daily gridded temperature datasets for the central north region of Egypt
title_sort development of high-resolution daily gridded temperature datasets for the central north region of egypt
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6668447/
https://www.ncbi.nlm.nih.gov/pubmed/31366936
http://dx.doi.org/10.1038/s41597-019-0144-0
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