Zhu et al. (2025) Cascading impacts of compound drought-heat extremes on global gross primary production

Identification

• Journal: Climatic Change
• Year: 2025
• Date: 2025-11-01
• Authors: Xiufang Zhu, Shizhe Zhang, Qiang Zhang, Dongyan Lu, Mingxiu Tang, Chunhua Guo
• DOI: 10.1007/s10584-025-04052-w

Research Groups

• State Key Laboratory of Remote Sensing and Digital Earth, Beijing Normal University, Beijing, China
• Zhejiang Institute of Geosciences, Hangzhou, Zhejiang, China
• Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing, China
• Advanced Interdisciplinary Institute of Environment and Ecology, Beijing Normal University, Zhuhai, China

Short Summary

This study evaluates the probability of extreme negative anomalies in Gross Primary Production (GPP) for various vegetation types under different intensities of drought, heat, and compound drought-heat events, considering future warming levels of 2 °C, 3 °C, and 4 °C. It finds that compound drought-heat events significantly increase the likelihood of GPP reduction, particularly in low-latitude regions, with these impacts intensifying as global warming progresses.

Objective

• Quantify the negative anomalies of vegetation productivity under different levels of drought, heat, and compound drought-heat.
• Analyze the impact of drought, heat, and compound drought-heat on global ecosystem GPP.
• Evaluate the impact of drought, heat, and compound drought-heat on global ecosystem GPP under warming levels of 2 °C, 3 °C, and 4 °C.
• Identify the vegetation types and areas most affected by drought and heat.

Study Configuration

• Spatial Scale: Global, with a grid resolution of 0.5 degrees.
• Temporal Scale: Historical period from 1985 to 2014 for GPP and climate data. Future projections for 30-year periods centered on the attainment of 2 °C, 3 °C, and 4 °C global warming levels relative to the 1850–1900 pre-industrial baseline.

Methodology and Data

• Models used:
  • Copula functions (Normal, t-, and Frank Archimede) for constructing 2D/3D joint distributions between GPP anomalies and extreme climate indicators.
  • Bias correction methods: Robust empirical quantile method for precipitation and Quantile Delta Mapping for temperature.
  • Extreme climate indicators: Standardized Precipitation Index (SPI) for drought and Standardized Temperature Index (STI) for heat.
  • Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models (14 selected models).
• Data sources:
  • Global Gross Primary Production (GPP): NIRv-GPP dataset (0.05° monthly, aggregated to 0.5°).
  • Climate data: CRU TS 4.05 dataset (monthly mean temperature and precipitation, 0.5°).
  • Future climate data: CMIP6 outputs under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios.
  • Auxiliary data: MODIS MCD12C1 land cover dynamics product (IGBP classification, 0.05°) and MODIS MCD12Q2 land surface phenology metrics product (500 m).

Main Results

• Under warming levels from 2 °C to 4 °C, the probability of globally-averaged extreme negative anomalies of GPP (ENAG) is projected to increase by 0.54% under drought, 0.82% under heat, and 1.12% under compound drought-heat conditions.
• Compound drought-heat (CHD) events generally have a greater impact on global GPP than single stressors, with the global average ENAG probability ranging from 6.07% (mild drought + mild heat) to 8.87% (extreme drought + extreme heat).
• The additive effect of heat on drought varies regionally: it significantly enhances ENAG probability in low-latitude regions (30°S–30°N), but is less significant or even reduces it under mild heat in middle-to-high latitudes. Conversely, the additive effect of drought on heat decreases with increasing heat intensity.
• Evergreen broadleaf forests, savannas, and grasslands are identified as the most vulnerable vegetation types to drought and heat, with evergreen broadleaf forests and closed shrublands being most susceptible to CHD. These four vegetation types account for 62.81% of global vegetation area.
• Typical vulnerable regions to drought, heat, and CHD under different warming levels include central North America, central Africa, central Europe, Northwest Asia, East Asia, Southeast Asia, and southwestern and southeastern Australia.
• The impact of future heat stress on GPP is projected to be greater than that of drought stress, and the compound impact of CHD is greater than any single stressor globally.

Contributions

• Provided a probabilistic assessment of vegetation productivity anomalies under specific extreme climate conditions, particularly compound drought-heat, offering a more objective evaluation than traditional non-probabilistic methods.
• Investigated the differential impacts and complex interactions between heat and drought on GPP at a global scale, revealing regional variations in their additive effects.
• Assessed the vegetation response to future extreme climate at specific global warming levels (2 °C, 3 °C, 4 °C), addressing a gap in studies that often rely on fixed future time periods.
• Employed assessment models developed using historical data for future predictions, reducing reliance on highly uncertain future carbon flux data from Earth System Models (ESMs).

Funding

• National Natural Science Foundation of China (Grant No. 42077436)
• National Key R&D Program of China (Grant No. 2019YFA0606901)

Citation

@article{Zhu2025Cascading,
  author = {Zhu, Xiufang and Zhang, Shizhe and Zhang, Qiang and Lu, Dongyan and Tang, Mingxiu and Guo, Chunhua},
  title = {Cascading impacts of compound drought-heat extremes on global gross primary production},
  journal = {Climatic Change},
  year = {2025},
  doi = {10.1007/s10584-025-04052-w},
  url = {https://doi.org/10.1007/s10584-025-04052-w}
}