Emergent Constraint on the Projection of Compound Dry and Hot Events in Guangdong Province by CMIP6 Models

In the context of global warming, compound dry-hot events (CDHEs) are intensifying in Guangdong, yet CMIP6 projections remain uncertain. This study employs CMIP6 data and the Standardized Compound Event Indicator (SCEI) to quantify CDHEs severity, applying an observational constraint approach to reduce inter-model uncertainty. The results show that, after observational constraint, uncertainties decrease by about 63% and 77% in Period I and II under SSP126 and by about 57% and 59% under SSP585, greatly improving projection robustness. CDHE risk is highest in SSP585-Period II. Future dry-hot intensification in Guangdong generally increases from north to south, with western Guangdong most strongly affected. Although CDHEs weaken in other periods, western Guangdong shows persistent aggravation. Mechanism analyses indicate that SSP585-Period I is mainly linked to cold sea surface temperature (SST) anomalies in the South Atlantic and waters near Australia. After correction, dry-hot conditions show a marked weakening across Guangdong, although slight intensification persists over the Leizhou Peninsula. SSP585-Period II is primarily influenced by warm SST anomalies in the eastern Pacific and South Atlantic and cold anomalies in the North Pacific. The two SSP126 periods are associated with warm SST anomalies in the South Atlantic and waters near Australia and with cold anomalies in the South Atlantic, North Pacific, and North Atlantic, respectively. After correction, CDHEs generally weaken across Guangdong, although southern and south-central areas remain relatively severe. These findings indicate that historical key SST biases can strongly influence future CDHEs projections in Guangdong by modulating large-scale atmospheric circulation, including the Pacific-South American wave train, Indian Ocean SST anomalies, and the Western North Pacific Subtropical Anticyclone.

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Publication Details

Journal
Atmosphere
Published
2026-03-22
DOI
https://doi.org/10.3390/atmos17030327
Primary Topic
Climate variability and models
Type
article
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article

Emergent Constraint on the Projection of Compound Dry and Hot Events in Guangdong Province by CMIP6 Models

Feng Xu, Liying Peng, Hui Yang, Jingqi Miao et al.
Atmosphere
Climate variability and models
article

Emergent Constraint on the Projection of Compound Dry and Hot Events in Guangdong Province by CMIP6 Models

Feng Xu, Liying Peng, Hui Yang, Jingqi Miao, Quancheng Hao, Yu Zhang
article en

Abstract

In the context of global warming, compound dry-hot events (CDHEs) are intensifying in Guangdong, yet CMIP6 projections remain uncertain. This study employs CMIP6 data and the Standardized Compound Event Indicator (SCEI) to quantify CDHEs severity, applying an observational constraint approach to reduce inter-model uncertainty. The results show that, after observational constraint, uncertainties decrease by about 63% and 77% in Period I and II under SSP126 and by about 57% and 59% under SSP585, greatly improving projection robustness. CDHE risk is highest in SSP585-Period II. Future dry-hot intensification in Guangdong generally increases from north to south, with western Guangdong most strongly affected. Although CDHEs weaken in other periods, western Guangdong shows persistent aggravation. Mechanism analyses indicate that SSP585-Period I is mainly linked to cold sea surface temperature (SST) anomalies in the South Atlantic and waters near Australia. After correction, dry-hot conditions show a marked weakening across Guangdong, although slight intensification persists over the Leizhou Peninsula. SSP585-Period II is primarily influenced by warm SST anomalies in the eastern Pacific and South Atlantic and cold anomalies in the North Pacific. The two SSP126 periods are associated with warm SST anomalies in the South Atlantic and waters near Australia and with cold anomalies in the South Atlantic, North Pacific, and North Atlantic, respectively. After correction, CDHEs generally weaken across Guangdong, although southern and south-central areas remain relatively severe. These findings indicate that historical key SST biases can strongly influence future CDHEs projections in Guangdong by modulating large-scale atmospheric circulation, including the Pacific-South American wave train, Indian Ocean SST anomalies, and the Western North Pacific Subtropical Anticyclone.

AtmosphereVol. 17(3)
Guangzhou Education Bureau (CN), Guangdong Ocean University (CN)
Life below water
Openalex Percentile: Top 10%
Climate variability and models
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