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How Does Plant CO2 Physiological Forcing Amplify Amazon Warming in CMIP6 Earth System Models?

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Title
How Does Plant CO2 Physiological Forcing Amplify Amazon Warming in CMIP6 Earth System Models?
Other Titles
CMIP6 실험에서 식생의 이산화탄소 생리학적 강제력이 아마존 온난화를 강화시키는 메커니즘의 이해
Authors
Kimm, Haechan
Park So-Won
Jun, Sang-Yoon
Kug Jong-Seong
Keywords
Amazon WarmingCO2 Physiological ForcingEarth System Model
Issue Date
2024
Citation
Kimm, Haechan, et al. 2024. "How Does Plant CO2 Physiological Forcing Amplify Amazon Warming in CMIP6 Earth System Models?". EARTHS FUTURE, 12(6): 0-0.
Abstract
The physiological response to increasing CO2 concentrations will lead to land surface warming through a redistribution of the energy balance. As the Amazon is one of the most plant-rich regions, the increase in surface temperature, caused by plant CO2 physiological forcing, is particularly large compared to other regions. In this study, we analyze the outputs of the 11 models in the Coupled Model Intercomparison Project Phase 6 to find out how CO2 physiological forcing amplifies Amazonian warming under elevated CO2 levels. With the CO2 concentration increase from 285 to 823 ppm, the Amazon temperature increased by 0.48 +/- 0.42 K as a result of plant physiological forcing. Moreover, we assess the contributions of each climate feedback to the surface warming due to physiological forcing by quantifying climate feedbacks based on radiative kernels. Lapse rate feedback and cloud feedback, analyzed as the primary contributors, accounted for 53% and 37% of Amazon warming, respectively. The warming contributions of these two feedbacks also exhibit a significant spread, which contributes to the predictive uncertainty. The surface warming due to reduced evapotranspiration is larger than the upper tropospheric warming in the Amazon, resulting in surface warming by lapse rate feedback. In addition, cloud cover in the Amazon region decreases due to the reduced evapotranspiration. Decreased cloud cover amplifies surface warming through the shortwave cloud feedback. Furthermore, differences in circulation and local convection caused by physiological effect contribute to the inter-model spread of the cloud feedback.
URI
https://repository.kopri.re.kr/handle/201206/16312
DOI
http://dx.doi.org/10.1029/2023EF004223
Type
Article
Station
기타()
Indexed
SCIE
Appears in Collections  
2024-2024, 남극 기후 환경 변화 이해와 전지구 영향 평가 (24-24) / 정의석 (PE24030)
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