Nocturnal Extreme Rainfall over the Central Yungui Plateau under Cold and Warm Upper-Level Anomaly Backgrounds during Warm Seasons in 1980–2020

The spatiotemporal and cloud features of the extreme rainfall under the warm and cold upper-level anomalies over the central Yungui Plateau (YGP) were investigated using the hourly rain gauge records, ERA5 reanalysis data, TRMM, and Fengyun satellite data, aiming to refine the understanding of different types of extreme rainfall. Extreme rainfall under an upper-level negative temperature anomaly (cold events) presents stronger convective cloud features when compared with the positive temperature anomaly (warm events). The maximum rainfall intensity and duration in cold events is much larger than that of warm events, while the brightness temperature of the cloud top is lower, and the ratio of convective rainfall is higher. In cold events, the middle-to-upper troposphere is dominated by a cold anomaly, and an unstable configuration with upper (lower) cold (warm) anomalies is observed around the central YGP. Although the upper-level temperature anomaly is positive, the anomalous divergence and convergence of southerly and northerly winds, as well as the strong moisture center and upward motions, are also found over the central YGP in warm events. The stronger atmospheric instability and higher convective energy under the upper-level cold anomalous circulation are closely associated with the rainfall features over the central YGP. The results indicate that the upper tropospheric temperature has significant influences on extreme rainfall, and thus more attention should be paid to the upper tropospheric temperature in future analyses.

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Publication Details

Journal
Atmosphere
Published
2024-09-01
DOI
https://doi.org/10.3390/atmos15091057
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
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article

Nocturnal Extreme Rainfall over the Central Yungui Plateau under Cold and Warm Upper-Level Anomaly Backgrounds during Warm Seasons in 1980–2020

Zhi Li, Weihua Yuan
Atmosphere
Climate variability and models
article

Nocturnal Extreme Rainfall over the Central Yungui Plateau under Cold and Warm Upper-Level Anomaly Backgrounds during Warm Seasons in 1980–2020

Zhi Li, Weihua Yuan
article en

Abstract

The spatiotemporal and cloud features of the extreme rainfall under the warm and cold upper-level anomalies over the central Yungui Plateau (YGP) were investigated using the hourly rain gauge records, ERA5 reanalysis data, TRMM, and Fengyun satellite data, aiming to refine the understanding of different types of extreme rainfall. Extreme rainfall under an upper-level negative temperature anomaly (cold events) presents stronger convective cloud features when compared with the positive temperature anomaly (warm events). The maximum rainfall intensity and duration in cold events is much larger than that of warm events, while the brightness temperature of the cloud top is lower, and the ratio of convective rainfall is higher. In cold events, the middle-to-upper troposphere is dominated by a cold anomaly, and an unstable configuration with upper (lower) cold (warm) anomalies is observed around the central YGP. Although the upper-level temperature anomaly is positive, the anomalous divergence and convergence of southerly and northerly winds, as well as the strong moisture center and upward motions, are also found over the central YGP in warm events. The stronger atmospheric instability and higher convective energy under the upper-level cold anomalous circulation are closely associated with the rainfall features over the central YGP. The results indicate that the upper tropospheric temperature has significant influences on extreme rainfall, and thus more attention should be paid to the upper tropospheric temperature in future analyses.

AtmosphereVol. 15(9)
Chinese Academy of Sciences (CN), Chengdu University of Information Technology (CN), Institute of Atmospheric Physics (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 87%
Climate variability and models
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