Results revealed that all SREs performed best in Central-Southern Chile (32.18-36.4°S), in particular at lowand mid-elevation zones (0-1000 m a.s.l.). Seasonally, all products performed best in terms of KGE0 during the wet autumn and winter seasons (MAM-JJA) compared to summer (DJF). In addition, all SREs were able to correctly identify no rain events, but during rainy days all SREs that did not use a local dataset of precipitation to recalibrate their estimates presented a low skill in providing an accurate classification of different precipitation intensities. Overall, MSWPEPv22 showed the best performance at all time scales and country-wide, due to the use of a Chilean dataset of daily data for calibrating its precipitation estimates, making it a good candidate for hydrological applications in Chile. Finally, we conclude that when the in situ precipitation dataset used in the evaluation of different SREs does not cover the headwaters of the catchments, the obtained performances should only be considered as first guess about how well a given SRE represent the real amount of water in an area. |
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Cited by 1 scholarly publication.
Satellites
Meteorology
Climatology
Spatial resolution
Temporal resolution
Calibration
Data centers