Abstract
Long-term precipitation data with high temporal-spatial resolution and high precision is crucial for the monitoring of tropical cyclone (TC) precipitation and the understanding of its response to global climate change. The performance of the Final run of Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) V06B product to characterize the TC precipitation is evaluated during the TC season (May to September) from 2014 to 2019 against a dense network of gauges over eastern China, considering the impact of land cover types (LCTs), different techniques (morphing) and instruments, i.e., passive microwave (PMW) and infrared (IR) sensors. Overall, IMERG captures well the spatial pattern and temporal variations of mean TC rainfall rate (RR) over eastern China but shows underestimations of mean TC RR compared to gauge observations, with the mean error (ME) being −0.78 mm/h, which are mainly contributed by the underestimations of heavy TC RR (ME: −12.1 mm/h). Moreover, the IMERG performance shows dependence on the LCTs and IMERG components (i.e., morph, IR + morph, and PMW sensors). The overestimation/underestimation of light/heavy TC precipitation events is most obvious over water/evergreen broadleaf forests, with the bias being 1.2/0.5. Differently, IMERG even slightly underestimates light TC precipitation events over grasslands (bias = 0.88). Among four IMERG components, Microwave Humidity Sounder (MHS) performs the best in characterizing all TC precipitation events, followed by morph, Special Sensor Microwave Imager/Sounder (SSMIS), and finally IR + morph, indicating that IR algorithms might need to be further improved. The mean TC RR is slightly overestimated by MHS over most regions of eastern China with positive ME exceeding 2.8 mm/h, while is largely underestimated by IR + morph among four components with most MEs lower than −1.2 mm/h. This study may provide an observational reference for the continued development and future improvement of the IMERG product.
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