A comprehensive five-year evaluation of IMERG late run precipitation estimates over the Netherlands

Journal Article (2021)
Author(s)

L. Bogerd (Royal Netherlands Meteorological Institute (KNMI), Wageningen University & Research)

A. Overeem (Wageningen University & Research, Royal Netherlands Meteorological Institute (KNMI))

Hidde Leijnse (Royal Netherlands Meteorological Institute (KNMI), Wageningen University & Research)

Remko Uijlenhoet (Wageningen University & Research, TU Delft - Water Resources)

Research Group
Water Resources
Copyright
© 2021 Linda Bogerd, Aart Overeem, Hidde Leijnse, R. Uijlenhoet
DOI related publication
https://doi.org/10.1175/JHM-D-21-0002.1
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 Linda Bogerd, Aart Overeem, Hidde Leijnse, R. Uijlenhoet
Research Group
Water Resources
Issue number
7
Volume number
22
Pages (from-to)
1855-1868
Reuse Rights

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Abstract

Applications like drought monitoring and forecasting can profit from the global and near-real-time availability of satellite-based precipitation estimates once their related uncertainties and challenges are identified and treated. To this end, this study evaluates the IMERG V06B Late Run precipitation product from the Global Precipitation Measurement mission (GPM), a multisatellite product that combines space-based radar, passive microwave (PMW), and infrared (IR) data into gridded precipitation estimates. The evaluation is performed on the spatiotemporal resolution of IMERG (0.1° × 0.1°, 30 min) over the Netherlands over a 5-yr period. A gauge-adjusted radar precipitation product from the Royal NetherlandsMeteorological Institute (KNMI) is used as reference, against which IMERG shows a large positive bias. To find the origin of this systematic overestimation, the data are divided into seasons, rainfall intensity ranges, echo top height (ETH) ranges, and categories based on the relative contributions of IR, morphing, and PMW data to the IMERG estimates. Furthermore, the specific radiometer is identified for each PMW-based estimate. IMERG’s detection performance improves with higher ETH and rainfall intensity, but the associated error and relative bias increase as well. Severe overestimation occurs during low-intensity rainfall events and is especially linked to PMW observations. All individual PMW instruments show the same pattern: overestimation of low-intensity events and underestimation of high-intensity events. IMERG misses a large fraction of shallow rainfall events, which is amplified when IR data are included. Space-based retrieval of shallow and low-intensity precipitation events should improve before IMERG can become accurate over the middle and high latitudes.

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