Can the GPM IMERG Final Product Accurately Represent MCSs’ Precipitation Characteristics over the Central and Eastern United States?

Mesoscale convective systems (MCSs) play an important role in water and energy cycles as they produce heavy rainfall and modify the radiative profile in the tropics and midlatitudes. An accurate representation of MCSs’ rainfall is therefore crucial in understanding their impact on the climate system...

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Bibliographic Details
Published in:Journal of hydrometeorology Vol. 21; no. 1; pp. 39 - 57
Main Authors: Cui, Wenjun, Dong, Xiquan, Xi, Baike, Feng, Zhe, Fan, Jiwen
Format: Journal Article
Language:English
Published: Boston American Meteorological Society 01.01.2020
Subjects:
Algorithms
Atmospheric precipitations
Bias
Climate
Climate system
Datasets
Diurnal
Diurnal cycle
Diurnal variations
ENVIRONMENTAL SCIENCES
Estimates
Evaporation
False alarms
Global precipitation
Heavy rainfall
Hydrologic cycle
Hydrology
Mean precipitation
Mesoscale convective systems
Mesoscale systems
Observatories
Performance evaluation
Pixels
Precipitation
Radar
Radars/Radar observations
Rain
Rainfall
Relative humidity
Satellite observations
Satellites
Seasonal distribution
Seasons
Sensors
Spatial distribution
SPECIAL Precipitation Measurement (GPM) COLLECTION
Studies
Tropical environments
United States > US
Eastern states
ISSN:1525-755X, 1525-7541
Online Access:Get full text
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Summary:Mesoscale convective systems (MCSs) play an important role in water and energy cycles as they produce heavy rainfall and modify the radiative profile in the tropics and midlatitudes. An accurate representation of MCSs’ rainfall is therefore crucial in understanding their impact on the climate system. The V06B Integrated Multisatellite Retrievals from Global Precipitation Measurement (IMERG) half-hourly precipitation final product is a useful tool to study the precipitation characteristics of MCSs because of its global coverage and fine spatiotemporal resolutions. However, errors and uncertainties in IMERG should be quantified before applying it to hydrology and climate applications. This study evaluates IMERG performance on capturing and detecting MCSs’ precipitation in the central and eastern United States during a 3-yr study period against the radar-based Stage IV product. The tracked MCSs are divided into four seasons and are analyzed separately for both datasets. IMERG shows a wet bias in total precipitation but a dry bias in hourly mean precipitation during all seasons due to the false classification of nonprecipitating pixels as precipitating. These false alarm events are possibly caused by evaporation under the cloud base or the misrepresentation of MCS cold anvil regions as precipitating clouds by the algorithm. IMERG agrees reasonably well with Stage IV in terms of the seasonal spatial distribution and diurnal cycle of MCSs precipitation. A relative humidity (RH)- based correction has been applied to the IMERG precipitation product, which helps reduce the number of false alarm pixels and improves the overall performance of IMERG with respect to Stage IV.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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AC05-76RL01830; SC0017015
PNNL-SA-149317
USDOE Office of Science (SC), Biological and Environmental Research (BER)
ISSN:1525-755X
1525-7541
DOI:10.1175/JHM-D-19-0123.1