JURNAL ILMU FISIKA | UNIVERSITAS ANDALAS · 2021 · 16 citations · 0 references
Natural SciencesEarth SciencesHydrologyHydrometeorologyNumerical Weather PredictionRemote SensingHydrometeorological Observation SystemsPrecipitationPrecipitation EstimationRainfall MeasurementSatellite HydrometeorologySatellite SensorsOptical Rain GaugesPrecipitation Measurement BiasRainfall RetrievalsSatellite Precipitation EstimationSatellite Precipitation RetrievalsSatellite Rainfall EstimationSatellite Rainfall RetrievalStatistical Comparison Of Measurement Results
Satellite-based precipitation estimates play a crucial role in many hydrological and numerical weather models, especially to overcome the scarcity of rain gauge data. Globally gridded rainfall product from Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (GPM) (IMERG) has been used in a wide range of hydrological applications. However, the IMERG is inherently prone to errors and biases. This study evaluated the performance of the IMERG-Final run (IMERG-F) product to estimate rainfall in a mountainous area of Sumatra. Validation was carried out using optical rain gauge (ORG) data for 15 years (2002-2016), at Kototabang, West Sumatra, Indonesia. In general, IMERG-F overestimated rainfall in all time scales. The longer the time scale was, the better the performance of IMERG-F we obtained. This feature was indicated by all quantities of continuous and categorical statistical matrices used. The performance of IMERG-F was lower than in other areas of the Maritime Continent, except for the probability of detection (POD) value. IMERG-F could detect rain very well, including for daily and hourly data, but the false alarm rate (FAR) was also relatively high. Such high FAR value may indicate a significant small-scale spatial rainfall variability in mountainous area of Sumatra.