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

• Autores: Huerta, Adrian, Aybar, Cesar, Correa, Kris, Noemi, Imfeld, Felipe-Obando, Oscar, Rau, Pedro, Drenkhan, Fabian
• Formato: artículo
• Fecha de Publicación: 2023
• Institución: Servicio Nacional de Meteorología e Hidrología del Perú
• Repositorio: SENAMHI-Institucional
• Lenguaje: español
• OAI Identifier: oai:repositorio.senamhi.gob.pe:20.500.12542/3050
• Enlace del recurso: https://hdl.handle.net/20.500.12542/3050; https://doi.org/10.1038/s41597-023-02777-w
• Nivel de acceso: acceso abierto
• Materia: Climate Change; Ecosystem; https://purl.org/pe-repo/ocde/ford#1.05.09; ecosistemas de transicion - Biodiversidad y Ecosistemas

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.