Spatially-distributed Intensity-Duration-Frequency (IDF) curves for Chile using sub-daily gridded datasets

In this work, we computed IDF curves for the climatically and topographically diverse Chilean territory (17-56ºS) using both stationary and non-stationary approaches based on three state-of-the-art gridded datasets: i) the Integrated Multi-Satellite Retrievals for GPM (IMERGv06B), ii) the fifth generation ECMWF ERA5 reanalysis, and iii) ERA5-Land, the high-resolution reanalysis from ECMWF. The three gridded datasets were used to compute the annual maximum intensities for 12 durations (1, 2, 4, 6, 8, 10, 12, 18, 24, 48, and 72 h) and six return periods (T=2, 5, 10, 25, 50, and 100 years), for the period 2001-2021, using a common spatial resolution of 0.10° and hourly temporal resolution. Data from 161 quality-checked hourly rain gauges are used to calculate IDF curves that serve as a benchmark for the curves derived from the gridded datasets. First, we calculated a bias correction factor for the annual maximum intensities for each duration, based on the comparison of the gridded value with the point one. Second, the previous correction factors were applied to the annual maximum intensities derived from each gridded dataset, using splines over the entire spatial domain. Third, the bias-corrected annual maximum intensities were calculated for each duration and return period using the Gumbel probability distribution, assuming stationary conditions. Then, the same annual maximum intensities were calculated for each duration and return period using a non-stationary Gumbel probability distribution with a varying mean. Fifth, we used the non-parametric Mann-Kendall test to assess the existence of trends in annual maximum intensities. Finally, 41 (1981-2021) and 21 (2001-2021) years of hourly precipitation data from ERA5 and ERA5-Land were used to test the effects of data length on the resulting stationary and non-stationary IDF curves. Our results reveal how the bias of annual maximum intensities changes in space, with generally smaller biases for longer periods. In addition, minor differences were found between the maximum annual intensities calculated using the stationary and non-stationary approaches for 2001-2021. Unexpectedly, we found some significant decreasing trends (p-value < 0.05) in Central-Southern Chile (32-43ºS) for the annual maximum intensities derived from ERA5 and ERA5-Land, while these trends were more localised and divergent (increasing and decreasing) for IMERG. Finally, there were only minor differences between the annual maximum intensities derived from ERA5 and ERA5-Land when using 21 years compared to 41 years of hourly records, for both the stationary and non-stationary approaches. We gratefully acknowledge the financial support of ANID-Fondecyt Regular 1212071,  ANID-PCI NSFC 190018, and ANID-Fondecyt Iniciación 111908064.