Tools
Tools
Da Silva, Nicolas A., Webber, Benjamin G. M. 
ORCID: https://orcid.org/0000-0002-8812-5929, Matthews, Adrian J. ORCID: https://orcid.org/0000-0003-0492-1168, Feist, Matthew M., Stein, Thorvald H. M., Holloway, Christopher E. and Abdullah, Muhammad F. A. B.
(2021)
Validation of GPM IMERG extreme precipitation in the Maritime Continent by station and radar data.
Earth and Space Science, 8 (7).
Preview |
PDF (dasilvaetal_accepted)
- Accepted Version
Available under License Creative Commons Attribution. Download (783kB) | Preview |
Preview |
PDF (Published_Version)
- Published Version
Available under License Creative Commons Attribution. Download (3MB) | Preview |
Abstract
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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | precipitation extremes,remote sensing,maritime continent,imerg,south east asia,precipitation evaluation,radar precipitation,environmental science (miscellaneous),earth and planetary sciences(all) ,/dk/atira/pure/subjectarea/asjc/2300/2301 |
| Faculty \ School: | Faculty of Science > School of Environmental Sciences Faculty of Science > School of Natural Sciences (former - to 2024) University of East Anglia Research Groups/Centres > Theme - ClimateUEA |
| UEA Research Groups: | Faculty of Science > Research Groups > Climatic Research Unit Faculty of Science > Research Groups > Centre for Ocean and Atmospheric Sciences Faculty of Science > Research Groups > Fluids & Structures Faculty of Science > Research Groups > Numerical Simulation, Statistics & Data Science |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 12 Jun 2021 12:14 |
| Last Modified: | 07 Nov 2024 12:43 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/80260 |
| DOI: | 10.1029/2021EA001738 |
Downloads
Downloads per month over past year
Actions (login required)
 |
View Item |