Abstract The increasing frequency of heatwaves over East Asia (EA) is impacting agriculture, water management, and people’s livelihood. However, the effect of humidity on high-temperature events has not yet been fully explored. Using observations and future climate change projections conducted with the latest generation of Earth System models, we examine the mechanisms of dry and moist heatwaves over EA. In the dry heatwave region, anticyclonic circulation has been amplified after the onset of heatwaves under the influence of the convergence of anomalous wave activity flux over northern EA, resulting in surface warming via adiabatic processes. In contrast, the moist heatwaves are triggered by the locally generated anticyclonic anomalies, with the surface warming amplified by cloud and water vapor feedback. Model simulations from phase six of the Coupled Model Intercomparison Project projected display intensification of dry heatwaves and increased moist heatwave days in response to projected increases in greenhouse gas concentrations.
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The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP7
Abstract. Cloud processes constitute one of the key uncertainties for climate change projections. The fourth iteration of the Cloud Feedback Model Intercomparison Project, CFMIP4, contributes to the Coupled Model Intercomparison Project phase 7 (CMIP7), by providing a set of global climate model experiments aiming to enhance our understanding of clouds, circulation and climate sensitivity, thereby informing improved projections of future climate change. CFMIP4 targets four knowledge gaps: (1) Physical mechanisms of cloud feedback and adjustment; (2) Dependence of cloud feedback and adjustment on climate base state and on the nature of the forcing; (3) Coupled mechanisms of the sea-surface temperature pattern effect; and (4) Coupling of clouds with circulation and precipitation. CFMIP4 contributes four CMIP7 Assessment Fast Track experiments that are central to the quantification of climate feedback and sensitivity in past, present and future climates, essential for process understanding and model evaluation. Furthermore, CFMIP4 supports the joint analysis of models and observations through a data request that includes process and satellite simulator output.
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- Award ID(s):
- 2331199
- PAR ID:
- 10667136
- Publisher / Repository:
- EGU Sphere
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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