4.5 Article

Validation of GPM IMERG Extreme Precipitation in the Maritime Continent by Station and Radar Data

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EARTH AND SPACE SCIENCE
卷 8, 期 7, 页码 -

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AMER GEOPHYSICAL UNION
DOI: 10.1029/2021EA001738

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资金

  1. Research Computing Service at the University of East Anglia
  2. Forecasting in Southeast Asia (FORSEA) project - Newton Fund through the Weather and Climate Science for Service Partnership (WCSSP) of the UK Met Office [DN373682]

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The Maritime Continent region is prone to high impact weather events, which are still poorly predicted by numerical weather prediction models. Evaluating extreme precipitation using the Global Precipitation Measurement (GPM) data set is recommended to improve predictability of these events. The study found that IMERG daily precipitation is similar to station precipitation between the 85th and 95th percentile, but tends to overestimate above the 95th, suggesting caution when dealing with more extreme precipitation at higher percentiles.
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 needs 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) data set 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 in Malaysia and the Philippines. We find that the high intragrid spatial variability of precipitation extremes results in large spatial sampling errors when each IMERG grid box 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.

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