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Midlatitude surface meteorological conditions are embedded within—and affected by—synoptic‐scale systems, including the movement and persistence of air masses (AMs). Changes in AM frequencies (number of daily occurrences) over the past several decades could have large effects on ecosystems: each organism is exposed to the synergistic effects of the entire suite of atmospheric variables acting upon it—an inherently multivariate environment—which is best captured using AMs. Utilizing a global‐scale AM classification system and a large network of tree‐ring chronologies, we investigate how variation in AM frequency impacts tree growth at over 900 locations. We find that AM frequencies are well‐correlated with tree growth, especially in the 12‐month period from July in the year prior to growth through June in the year of growth. The most impactful AMs are Dry‐Warm and Humid‐Cool AMs, which exhibit average correlations ofρ = −0.4 andρ = +0.4 with tree growth, respectively, for certain tree species, with correlations at some sites exceedingρ =  ±0.8 in some seasons. Compared to empirical models based solely on temperature and precipitation, modeling using only AM frequencies proved superior at nearly 60% of the sites and for over 80% of the well‐sampled (n ≥ 10) species. These results should provide a foundation for using AMs to improve forecasts of tree growth, tree stress and wildfire potential. Long‐term reconstructions of AM frequencies back several centuries may also be feasible using tree‐ring data, which will help contextualize and temporally extend multivariate perspectives of climate change that utilize such air masses.

 

The timing and intensity of precipitation varies from year‐to‐year and is expected to change in the future. Assessing the impacts of this moisture delivery variability on tree growth is important both for future forest health and for our interpretation of pre‐instrumental tree‐ring records. Here, we used the Vaganov‐Shashkin model to investigate how changes in precipitation delivery impact tree growth at five sites representing four species in two North American river basins with high precipitation variability but different seasonal cycles. Evenly distributed precipitation increased tree growth in the Lower Sacramento watershed, while the water‐limited South Platte benefited from concentrated precipitation early in the growing season. Although most experimental simulations retained the pattern of high‐ and low‐growth years, tree growth was reduced with fewer, more intense precipitation events, which could affect interpretation of past climate extremes. Under the RCP4.5 scenario, projected warming offset the potential benefits of increased precipitation on tree growth.

 

Abstract Process-based models of tree-ring width are used both for reconstructing past climates and for projecting changes in growth due to climate change. Since soil moisture observations are unavailable at appropriate spatial and temporal scales, these models generally rely on simple water budgets driven in part by temperature-based potential evapotranspiration (PET) estimates, but the choice of PET model could have large effects on simulated soil moisture, moisture stress, and radial growth. Here, I use four different PET models to drive the VS-Lite model and evaluate the extent to which they differ in both their ability to replicate observed growth variability and their simulated responses to projected 21st century warming. Across more than 1200 tree-ring width chronologies in the conterminous United States, there were no significant differences among the four PET models in their ability to replicate observed radial growth, but the models differed in their responses to 21st century warming. The temperature-driven empirical PET models (Thornthwaite and Hargreaves) simulated much larger warming-induced increases in PET and decreases in soil moisture than the more physically realistic PET models (Priestley–Taylor and Penman–Monteith). In cooler and more mesic regions with relatively minimal moisture constraints to growth, the models simulated similarly small reductions in growth with increased warming. However, in dry regions, the Thornthwaite- and Hargreaves-driven VS-Lite models simulated an increase in moisture stress roughly double that of the Priestley–Taylor and Penman–Monteith models, which also translated to larger simulated declines in radial growth under warming. While the lack of difference in the models’ ability to replicate observed radial growth variability is an encouraging sign for some applications (e.g. attributing changes in growth to specific climatic drivers), the large differences in model responses to warming suggest that caution is needed when applying the temperature-driven PET models to climatic conditions with large trends in temperature.