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In the 2022 summer, West-Central Europe and several other northern-hemisphere mid-latitude regions experienced substantial soil moisture deficits in the wake of precipitation shortages and elevated temperatures. Much of Europe has not witnessed a more severe soil drought since at least the mid-20th century, raising the question whether this is a manifestation of our warming climate. Here, we employ a well-established statistical approach to attribute the low 2022 summer soil moisture to human-induced climate change, using observation-driven soil moisture estimates and climate models. We find that in West-Central Europe, a June-August root-zone soil moisture drought such as in 2022 is expected to occur once in 20 years in the present climate, but would have occurred only about once per century during pre-industrial times. The entire northern extratropics show an even stronger global warming imprint with a 20-fold soil drought probability increase or higher, but we note that the underlying uncertainty is large. Reasons are manifold, but include the lack of direct soil moisture observations at the required spatiotemporal scales, the limitations of remotely sensed estimates, and the resulting need to simulate soil moisture with land surface models driven by meteorological data. Nevertheless, observationbased products indicate long-term declining summer soil moisture for both regions, and this tendency is likely fueled by regional warming, while no clear trends emerge for precipitation. Finally, our climate model analysis suggests that in a 2 °C world, 2022-like soil drought conditions would become twice as likely for West-Central Europe compared to today, and would take place nearly every year across the northern extratropics. [ABSTRACT FROM AUTHOR]

Terrestrial climate is influenced by various land-atmosphere interactions that involve numerous land surface state variables. In several regions on Earth, soil moisture plays an important role for climate through its control on the partitioning of net radiation into sensible and latent heat fluxes and, consequently, its impact on temperature and precipitation. The Global Land-Atmosphere Climate Experiment-Coupled Model Intercomparison Project phase 5 (GLACE-CMIP5) aims to quantify the impact of soil moisture on these important climate variables and to trace the individual coupling mechanisms. GLACE-CMIP5 provides experiments with different soil moisture prescriptions that can be used to isolate the effect of soil moisture on climate. Using a theoretical approach that relies on the distinct relation of soil moisture with evaporative fraction (the ratio of latent heat flux over net radiation) and daily maximum near-surface air temperature in different soil moisture regimes, the climate impact of the soil moisture prescriptions in the GLACE-CMIP5 experiments can be emulated and quantified. The theoretical estimation of the soil moisture effect on evaporative fraction agrees very well with estimations obtained directly from the GLACE-CMIP5 experiments (pattern correlation of 0.85). Moreover, the soil moisture effect on daily maximum temperature is well captured in those regions where soil moisture exerts a strong control on latent heat fluxes. The theoretical approach is further applied to quantify the soil moisture contribution to the projected change of the temperature on the hottest day of the year, confirming recent estimations by other studies. Finally, GLACE-style soil moisture prescriptions are emulated in an extended set of CMIP5 models. The results indicate consistency between the soil moisture-climate coupling strength estimated with GLACE-CMIP5 and CMIP5 models. Although the theoretical approach is designed to capture only the local soil moisture-climate coupling strength, it can also help to distinguish non-local from local soil moisture-atmosphere feedbacks where sensitivity experiments (such as GLACE-CMIP5) are available. Overall, the presented theoretical approach constitutes a simple and powerful tool to quantify local soil moisture-climate coupling in both GLACE-CMIP5 and CMIP5 models that can be applied in the absence of dedicated sensitivity experiments. [ABSTRACT FROM AUTHOR]