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High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset
Gridded high-resolution climate datasets are increasingly important for a wide range of modelling applications. Here we present PISCOt (v1.2), a novel high spatial resolution (0.01°) dataset of daily air temperature for entire Peru (1981–2020). The dataset development involves four main steps: (i) q...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10692097/ https://www.ncbi.nlm.nih.gov/pubmed/38040747 http://dx.doi.org/10.1038/s41597-023-02777-w |
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author | Huerta, Adrian Aybar, Cesar Imfeld, Noemi Correa, Kris Felipe-Obando, Oscar Rau, Pedro Drenkhan, Fabian Lavado-Casimiro, Waldo |
author_facet | Huerta, Adrian Aybar, Cesar Imfeld, Noemi Correa, Kris Felipe-Obando, Oscar Rau, Pedro Drenkhan, Fabian Lavado-Casimiro, Waldo |
author_sort | Huerta, Adrian |
collection | PubMed |
description | Gridded high-resolution climate datasets are increasingly important for a wide range of modelling applications. Here we present PISCOt (v1.2), a novel high spatial resolution (0.01°) dataset of daily air temperature for entire Peru (1981–2020). The dataset development involves four main steps: (i) quality control; (ii) gap-filling; (iii) homogenisation of weather stations, and (iv) spatial interpolation using additional data, a revised calculation sequence and an enhanced version control. This improved methodological framework enables capturing complex spatial variability of maximum and minimum air temperature at a more accurate scale compared to other existing datasets (e.g. PISCOt v1.1, ERA5-Land, TerraClimate, CHIRTS). PISCOt performs well with mean absolute errors of 1.4 °C and 1.2 °C for maximum and minimum air temperature, respectively. For the first time, PISCOt v1.2 adequately captures complex climatology at high spatiotemporal resolution and therefore provides a substantial improvement for numerous applications at local-regional level. This is particularly useful in view of data scarcity and urgently needed model-based decision making for climate change, water balance and ecosystem assessment studies in Peru. |
format | Online Article Text |
id | pubmed-10692097 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106920972023-12-03 High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset Huerta, Adrian Aybar, Cesar Imfeld, Noemi Correa, Kris Felipe-Obando, Oscar Rau, Pedro Drenkhan, Fabian Lavado-Casimiro, Waldo Sci Data Data Descriptor Gridded high-resolution climate datasets are increasingly important for a wide range of modelling applications. Here we present PISCOt (v1.2), a novel high spatial resolution (0.01°) dataset of daily air temperature for entire Peru (1981–2020). The dataset development involves four main steps: (i) quality control; (ii) gap-filling; (iii) homogenisation of weather stations, and (iv) spatial interpolation using additional data, a revised calculation sequence and an enhanced version control. This improved methodological framework enables capturing complex spatial variability of maximum and minimum air temperature at a more accurate scale compared to other existing datasets (e.g. PISCOt v1.1, ERA5-Land, TerraClimate, CHIRTS). PISCOt performs well with mean absolute errors of 1.4 °C and 1.2 °C for maximum and minimum air temperature, respectively. For the first time, PISCOt v1.2 adequately captures complex climatology at high spatiotemporal resolution and therefore provides a substantial improvement for numerous applications at local-regional level. This is particularly useful in view of data scarcity and urgently needed model-based decision making for climate change, water balance and ecosystem assessment studies in Peru. Nature Publishing Group UK 2023-12-01 /pmc/articles/PMC10692097/ /pubmed/38040747 http://dx.doi.org/10.1038/s41597-023-02777-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Huerta, Adrian Aybar, Cesar Imfeld, Noemi Correa, Kris Felipe-Obando, Oscar Rau, Pedro Drenkhan, Fabian Lavado-Casimiro, Waldo High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset |
title | High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset |
title_full | High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset |
title_fullStr | High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset |
title_full_unstemmed | High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset |
title_short | High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset |
title_sort | high-resolution grids of daily air temperature for peru - the new piscot v1.2 dataset |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10692097/ https://www.ncbi.nlm.nih.gov/pubmed/38040747 http://dx.doi.org/10.1038/s41597-023-02777-w |
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