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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. 

Paleoclimate data play a critical role in contextualizing recent hydroclimate extremes, but asymmetries in tree‐ring responses to extreme climate conditions pose challenges for reconstruction and interpretation of past climate. Here we establish the extent to which existing tree‐ring records capture precipitation extremes in western North America and evaluate climate factors hypothesized to lead to asymmetric extreme capture, including timing of precipitation, seasonal temperatures, snowpack, and atmospheric river events. We find that while there is dry‐biased asymmetry in one third of western North American tree‐ring records, 45% of sites capture wet extremes as well as or better than dry extremes. Summer extremes are rarely captured at any sites. Latitude and elevation affect site‐level extreme responses, as do seasonal climate conditions, particularly in the autumn and spring. Directly addressing asymmetric extreme value capture in tree‐ring records can aid our interpretation of past climate and help identify alternative avenues for future reconstructions.

 

Primary production is the entry point of energy and carbon into ecosystems, but modeling responses of primary production to “environmental stress” (i.e., reductions of primary production from nonoptimal environmental conditions) remains a key challenge and source of uncertainty in our understanding of Earth's carbon cycle. Here we develop an approach for estimating annual “environmental stress” from tree rings based on the proportion of the optimal diameter growth rate (from species‐specific allometric equations) that is realized in a given year. We assessed climatic, topographic, and soil drivers of environmental stress, as well as their interactions, using both empirical model experiments and linear mixed effect models. Climate gradients and interannual climate variability dominated spatial and temporal variability of environmental stress in much of the western United States, where the tree‐ring environmental stress index was positively correlated with antecedent climatic water balance (precipitation minus potential evapotranspiration) and negatively correlated with temperature and vapor pressure deficit. Excluding topographic and soil information from empirical models reduced their ability to capture spatial gradients in environmental stress, particularly in the eastern United States, where growth was not as strongly limited by climate. Mean climate conditions and topographic characteristics had significant interaction effects with the climatic water balance, indicating an increasing importance of winter moisture for warmer and drier sites and as elevation and topographic wetness index increased. These results suggest that including effects of antecedent climate (particularly in dry regions) and site topographic and soil characteristics could improve parameterization of environmental stress effects in primary production models.

 

Much of the precipitation delivered to western North America arrives during the cool season via midlatitude Pacific storm tracks, which may experience future shifts in response to climate change. Here, we assess the sensitivity of the hydroclimate and ecosystems of western North America to the latitudinal position of cool‐season Pacific storm tracks. We calculated correlations between storm track variability and three hydroclimatic variables: gridded cool‐season standardized precipitation‐evapotranspiration index, April snow water equivalent, and water year streamflow from a network ofUSGSstream gauges. To assess how historical storm track variability affected ecosystem processes, we derived forest growth estimates from a large network of tree‐ring widths and land surface phenology and wildfire estimates from remote sensing. From 1980 to 2014, cool‐season storm tracks entered western North America between approximately 41°N and 53°N. Cool‐season moisture supply and snowpack responded strongly to storm track position, with positive correlations to storm track latitude in eastern Alaska and northwestern Canada but negative correlations in the northwestern U.S. Ecosystems of the western United States were greener and more productive following winters with south‐shifted storm tracks, while Canadian ecosystems were greener in years when the cool‐season storm track was shifted to the north. On average, larger areas of the northwestern United States were burned by moderate to high severity wildfires when storm tracks were displaced north, and the average burn area per fire also tended to be higher in years with north‐shifted storm tracks. These results suggest that projected shifts of Pacific storm tracks over the 21st century would likely alter hydroclimatic and ecological regimes in western North America, particularly in the northwestern United States, where moisture supply and ecosystem processes are highly sensitive to the position of cool‐season storm tracks.