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 of
Changes in individual climate variables have been widely documented over the past century. However, assessments that consider changes in the collective interaction amongst multiple climate variables are relevant for understanding climate impacts on ecological and human systems yet are less well documented than univariate changes. We calculate annual multivariate climate departures during 1958–2017 relative to a baseline 1958–1987 period that account for covariance among four variables important to Earth’s biota and associated systems: annual climatic water deficit, annual evapotranspiration, average minimum temperature of the coldest month, and average maximum temperature of the warmest month. Results show positive trends in multivariate climate departures that were nearly three times that of univariate climate departures across global lands. Annual multivariate climate departures exceeded two standard deviations over the past decade for approximately 30% of global lands. Positive trends in climate departures over the last six decades were found to be primarily the result of changes in mean climate conditions consistent with the modeled effects of anthropogenic climate change rather than changes in variability. These results highlight the increasing novelty of annual climatic conditions viewed through a multivariate lens and suggest that changes in multivariate climate departures have generally outpaced univariate departures in recent decades.
more » « less- Award ID(s):
- 1633831
- NSF-PAR ID:
- 10154067
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Scientific Reports
- Volume:
- 10
- Issue:
- 1
- ISSN:
- 2045-2322
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract ρ = −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. -
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Taxon High‐elevation tree species—
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