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) 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.
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dig-senamhi-pe-20.500.12542-30502023-12-29T15:01:44Z High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset Huerta, Adrian Aybar, Cesar Correa, Kris Noemi, Imfeld Correa, Kris Felipe-Obando, Oscar Rau, Pedro Drenkhan, Fabian Climate Change Ecosystem 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. 2023 info:eu-repo/semantics/article https://hdl.handle.net/20.500.12542/3050 spa info:eu-repo/semantics/openAccess application/pdf application/pdf Nature Repositorio Institucional - SENAMHI Servicio Nacional de Meteorología e Hidrología del Perú |
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Climate Change Ecosystem Climate Change Ecosystem Huerta, Adrian Aybar, Cesar Correa, Kris Noemi, Imfeld Correa, Kris Felipe-Obando, Oscar Rau, Pedro Drenkhan, Fabian High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset |
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. |
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info:eu-repo/semantics/article |
topic_facet |
Climate Change Ecosystem |
author |
Huerta, Adrian Aybar, Cesar Correa, Kris Noemi, Imfeld Correa, Kris Felipe-Obando, Oscar Rau, Pedro Drenkhan, Fabian |
author_facet |
Huerta, Adrian Aybar, Cesar Correa, Kris Noemi, Imfeld Correa, Kris Felipe-Obando, Oscar Rau, Pedro Drenkhan, Fabian |
author_sort |
Huerta, Adrian |
title |
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_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_sort |
high-resolution grids of daily air temperature for peru - the new piscot v1.2 dataset |
publisher |
Nature |
url |
https://hdl.handle.net/20.500.12542/3050 |
work_keys_str_mv |
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1792502606986215424 |