High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset

被引:8
作者
Huerta, Adrian [1 ,2 ,6 ,9 ]
Aybar, Cesar [3 ,4 ]
Imfeld, Noemi [5 ,6 ]
Correa, Kris [1 ]
Felipe-Obando, Oscar [1 ]
Rau, Pedro [7 ]
Drenkhan, Fabian [8 ]
Lavado-Casimiro, Waldo [1 ]
机构
[1] Serv Nacl Meteorol & Hidrol SENAMHI, Lima, Peru
[2] Univ Nacl Agr La Molina UNALM, Dept Fis & Meteorol, Lima, Peru
[3] Univ Valencia, Image Proc Lab, Valencia 46980, Spain
[4] Natl Univ San Marcos, High Mt Ecosyst Res Grp, Lima 15081, Peru
[5] Univ Bern, Inst Geog, Bern, Switzerland
[6] Univ Bern, Oeschger Ctr Climate Change Res, Bern, Switzerland
[7] Univ Ingn & Tecnol UTEC, Ctr Invest & Tecnol Agua CITA, Dept Ingn Ambiental, Lima, Peru
[8] Pontificia Univ Catolica Peru, Dept Humanities, Geog & Environm, Lima, Peru
[9] Univ Bern, Inst Geog, Bern, Switzerland
关键词
DAILY PRECIPITATION; TIME-SERIES; DATA SET; SPATIOTEMPORAL INTERPOLATION; REFINED INDEX; CLIMATE DATA; HOMOGENIZATION; VARIABILITY; DATABASE; SPAIN;
D O I
10.1038/s41597-023-02777-w
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 degrees) 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 degrees C and 1.2 degrees 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.
引用
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页数:22
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