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

Huerta A.; Aybar C.; Imfeld N.; Correa K.; Felipe-Obando O.; Rau P.; Drenkhan F.; Lavado-Casimiro W. · Scientific Data (2023) · DOI: 10.1038/s41597-023-02777-w

Resumen

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.

Instituciones: Universidad Nacional Mayor de San Marcos; Pontificia Universidad Católica del Perú; Universidad Nacional Agraria La Molina; Universidad de Ingeniería y Tecnología