A process-oriented analysis of the summertime diurnal cycle of precipitation and diabatic heating over China in three reanalyses

Abstract. We conduct a process-oriented analysis of the summertime diurnal cycle of precipitation (DCP) over China by comparing three widely used reanalyses (ERA5, JRA-55, and MERRA-2) with satellite observations. While all reanalyses capture the observed nocturnal precipitation peak related to elevated convection, they differ substantially in simulating the daytime rainfall timing. JRA-55 and MERRA-2 better capture the observed timing, whereas ERA5 exhibits a systematic 3 h phase advance. The superior performance of JRA-55 is attributed to its gradual development of deep convection, supported by sustained heating and convective eddy transport. In contrast, ERA5 develops deep convection too rapidly, resulting in premature peaks in heating and precipitation. MERRA-2 also produces early-peaking convective rainfall, but with notably weaker intensity, suggesting that its better diurnal cycle is achieved largely through the suppression of convective precipitation. Diurnal cloud structures further corroborate these differences. Whereas JRA-55 exhibits a slowly developing, upward-tilting cloud structure from morning to afternoon, ERA5 and MERRA-2 peak earlier and have a shorter duration. The role of large-scale forcing, quantified by CAPE and dynamic CAPE (dCAPE), is further tied to the performance of the convection schemes. Results show the peak timing of dCAPE lags that of CAPE and aligns more closely with the observed precipitation. While convective precipitation in ERA5 and MERRA-2 tracks CAPE more closely, in JRA-55 it aligns better with dCAPE, thereby yielding a more realistic DCP. This contrast highlights the critical influence of triggering choice on cumulus convection.

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Publication Details

Journal
Atmospheric chemistry and physics
Published
2026-05-19
DOI
https://doi.org/10.5194/acp-26-6763-2026
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
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article

A process-oriented analysis of the summertime diurnal cycle of precipitation and diabatic heating over China in three reanalyses

Atmospheric chemistry and physics
Climate variability and models
article

A process-oriented analysis of the summertime diurnal cycle of precipitation and diabatic heating over China in three reanalyses

article en

Abstract

Abstract. We conduct a process-oriented analysis of the summertime diurnal cycle of precipitation (DCP) over China by comparing three widely used reanalyses (ERA5, JRA-55, and MERRA-2) with satellite observations. While all reanalyses capture the observed nocturnal precipitation peak related to elevated convection, they differ substantially in simulating the daytime rainfall timing. JRA-55 and MERRA-2 better capture the observed timing, whereas ERA5 exhibits a systematic 3 h phase advance. The superior performance of JRA-55 is attributed to its gradual development of deep convection, supported by sustained heating and convective eddy transport. In contrast, ERA5 develops deep convection too rapidly, resulting in premature peaks in heating and precipitation. MERRA-2 also produces early-peaking convective rainfall, but with notably weaker intensity, suggesting that its better diurnal cycle is achieved largely through the suppression of convective precipitation. Diurnal cloud structures further corroborate these differences. Whereas JRA-55 exhibits a slowly developing, upward-tilting cloud structure from morning to afternoon, ERA5 and MERRA-2 peak earlier and have a shorter duration. The role of large-scale forcing, quantified by CAPE and dynamic CAPE (dCAPE), is further tied to the performance of the convection schemes. Results show the peak timing of dCAPE lags that of CAPE and aligns more closely with the observed precipitation. While convective precipitation in ERA5 and MERRA-2 tracks CAPE more closely, in JRA-55 it aligns better with dCAPE, thereby yielding a more realistic DCP. This contrast highlights the critical influence of triggering choice on cumulus convection.

Atmospheric chemistry and physicsVol. 26(10)
Chinese Academy of Sciences (CN), Jiangsu Institute of Meteorological Sciences (CN), Institute of Atmospheric Physics (CN), University of Chinese Academy of Sciences (CN), Nanjing University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 5%
Climate variability and models
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