Heat waves lead to major impacts on human health, food production, and ecosystems.To assess their predictability and how they are projected to change under global warming, it is crucial to improve our understanding of the underlying processes affecting their occurrence and intensity under present-day climate conditions. Beside greenhouse gas forcing, processes in the different components of the climate system-in particular the land surface, atmospheric circulation, and the oceans-may play a key role in changing the odds for a particular event. This study aims to identify the role of the individual drivers for five heat waves (and, in some cases, of concurrent droughts) in the recent decade. Simulations are performed with the Community Earth System Model using nudging of horizontal atmospheric circulation and prescription of soil moisture. The fully constrained model accurately reproduces how anomalous an event was. Factorial experiments, which force the model toward observations for one or several key components at a time, allow us to identify how much of the observed temperature anomaly of each event can be attributed to each driver. Considering all analyzed events, atmospheric circulation and soil moisture play similarly important roles, each contributing between 20% and 70% to the events' anomalies. This highlights that the role of thermodynamics can be just as important as that of the dynamics for temperature extremes, a possibly underestimated feature. In addition, recent climate change amplified the events and contributed between 10% and 40% of the events' anomalies.
Global climate models present systematic biases, among others, a tendency to overestimate hot and dry summers in midlatitude regions. Here we investigate the origin of such biases in the Community Earth System Model. To disentangle the contribution of dynamics and thermodynamics, we perform simulations that include nudging of horizontal wind and compare them to simulations with a free atmosphere. Prescribing the observed large‐scale circulation improves the modeled weather patterns as well as many related fields. However, the larger part of the temperature and precipitation biases of the free atmosphere configuration remains after nudging, in particular, for extremes. Our results suggest that thermodynamical processes, including land‐atmosphere coupling and atmospheric parameterizations, drive the errors present in Community Earth System Model. Our result may apply to other climate models and highlight the importance of distinguishing thermodynamic and dynamic sources of biases in present‐day global climate models.
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