Abstract/Summary

The Maritime Continent (MC) is a region subject to high impact weather (HIW) events, which are still poorly predicted by numerical weather prediction (NWP) models. To improve predictability of such events, NWP need to be evaluated against accurate measures of extreme precipitation across the whole MC. With its global spatial coverage at high spatio-temporal resolution, the Global Precipitation Measurement (GPM) dataset is a suitable candidate. Here we evaluate extreme precipitation in the Integrated Multi-Satellite Retrieval for GPM (IMERG) V06B product against station data from the Global Historical Climatology Network (GHCN) in Malaysia and the Philippines. We find that the high intra-grid spatial variability of precipitation extremes results in large spatial sampling errors when each IMERG gridbox is compared with individual co-located precipitation measurements, a result that may explain discrepancies found in earlier studies in the MC. Overall, IMERG daily precipitation is similar to station precipitation between the 85th and 95th percentile, but tends to overestimate above the 95th. IMERG data were also compared with radar data in western Peninsular Malaysia for sub-daily timescales. Allowing for uncertainties in radar data, the analysis suggests that the 95th percentile is still suitable for NWP evaluation of extreme sub-daily precipitation, but that the rainfall rates diverge at higher percentiles. Hence, our overall recommendation is that the 95th percentile be used to evaluate NWP forecasts of HIW on daily and sub-daily time scales against IMERG data, but that higher percentiles (i.e., more extreme precipitation) be treated with caution.