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.

Abstract. Extreme temperatures were experienced over a large part of the Northern Hemisphere during the 2018 boreal summer (hereafter referred to as “NH2018 event”), leading to major impacts on agriculture and society in the affected countries. Previous studies highlighted both the anomalous atmospheric circulation patterns during the event and the background warming due to human greenhouse gas emissions as main drivers of the event. In this study, we present Earth system model experiments investigating different storylines of the NH2018 event given the same atmospheric circulation and alternative background global warming for no human imprint, the 2018 conditions, and different mean global warming levels 1.5, 2, 3 and 4 ∘C. The results reveal that the human-induced background warming was a strong contributor to the intensity of the NH2018 event, and that resulting extremes under similar atmospheric circulation conditions at higher levels of global warming would reach dangerous levels. Compared to 9 % during the NH2018 event, about 13 % (34 %) of the inhabited or agricultural area in the investigated region would reach daily maximum temperatures over 40 ∘C under 2 ∘C (4 ∘C) of global warming and similar atmospheric circulation conditions.

Three sets of model experiments are performed with the Community Earth System Model to study the role of soil moisture anomalies as a boundary forcing for the formation of upper-level Rossby wave patterns during Southern Hemisphere summer. In the experiments, soil moisture over Australia is set to ±1STD of an ERA-Interim reanalysis derived soil moisture reconstruction for the years 2009 to 2016 and 50 ensemble members are run. The local response is a positive heating anomaly in the dry simulations that results in a thermal low-like circulation anomaly with an anomalous surface low and upper-level anticyclone. Significant differences in convective rainfall over Australia are related to differences in convective instability and associated with changes in near surface moisture and moisture advection patterns. A circum-hemispheric flow response is identified both in the upper-level flow and in the surface storm tracks that overall resembles a positive Southern Annular Mode-like flow anomaly in the dry simulations. The structure of this atmospheric response strongly depends on the background flow. The results point to a modulation of the hemispheric flow response to the forcing over Australia by the El Niño Southern Oscillation. Significant changes of precipitation over the Maritime continent and South Africa are found and significant differences in the frequency of surface cyclones are present all along the storm tracks.

Abstract. The mechanisms leading to the occurrence of extreme weather and climate events are varied and complex. They generally encompass a combination of dynamic and thermodynamic processes, as well as drivers external to the climate system, such as anthropogenic greenhouse gas emissions and land use change. Here we present the ExtremeX multi-model intercomparison experiment, which was designed to investigate the contribution of dynamic and thermodynamic processes to recent weather and climate extremes. The numerical experiments are performed with three Earth system models: CESM, MIROC, and EC-Earth. They include control experiments with interactive atmosphere and land surface conditions, as well as experiments wherein the atmospheric circulation, soil moisture, or both are constrained using observation-based data. The temporal evolution and magnitude of temperature anomalies during heatwaves are well represented in the experiments with a constrained atmosphere. However, the magnitude of mean climatological biases in temperature and precipitation are not greatly reduced in any of the constrained experiments due to persistent or newly introduced biases. This highlights the importance of error compensations and tuning in the standard model versions. To show one possible application, ExtremeX is used to identify the main drivers of heatwaves and warm spells. The results reveal that both atmospheric circulation patterns and soil moisture conditions substantially contribute to the occurrence of these events. Soil moisture effects are particularly important in the tropics, the monsoon areas, and the Great Plains of the United States, whereas atmospheric circulation effects are major drivers in other midlatitude and high-latitude regions.