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Evapotranspiration (ET) is a significant ecosystem flux, governing the partitioning of energy at the land surface. Understanding the seasonal pattern and magnitude ofETis critical for anticipating a range of ecosystem impacts, including drought, heat‐wave events, and plant mortality. In this study, we identified the relative controls of seasonal variability inET, and how these controls vary among ecosystems. We used overlapping AmeriFlux and PhenoCam time series at a daily timestep from 20 sites to explore these linkages (# site‐years >100), and our study area covered a broad climatological aridity gradient in the U.S. and Canada. We focused on disentangling the most important controls of bulk surface conductance (G_s) and evaporative fraction (EF = LE/[H + LE]), whereLEandHrepresent latent and sensible heat fluxes, respectively. Specifically, we investigated how vegetation phenology varied in importance relative to meteorological variables (vapor pressure deficit and antecedent precipitation) as a driver ofG_sandEFusing path analysis, a framework for quantifying and comparing the causal linkages among multiple response and explanatory variables. Our results revealed that the drivers ofG_sandEFseasonality varied significantly between energy‐ and water‐limited ecosystems. Specifically, precipitation had a much higher effect in water‐limited ecosystems, while seasonal patterns in canopy greenness emerged as a stronger control in energy‐limited ecosystems. Given that phenology is expected to shift under future climate, our findings provide key information for understanding and predicting how phenology may impact 21st‐century hydroclimate regimes and the surface‐energy balance.

Large-scale changes in the state of the land surface affect the circulation of the atmosphere and the structure and function of ecosystems alike. As global temperatures increase and regional climates change, the timing of key plant phenophase changes are likely to shift as well. Here we evaluate a suite of phenometrics designed to facilitate an “apples to apples” comparison between remote sensing products and climate model output. Specifically, we derive day-of-year (DOY) thresholds of leaf area index (LAI) from both remote sensing and the Community Land Model (CLM) over the Northern Hemisphere. This systematic approach to comparing phenologically relevant variables reveals appreciable differences in both LAI seasonal cycle and spring onset timing between model simulated phenology and satellite records. For example, phenological spring onset in the model occurs on average 30 days later than observed, especially for evergreen plant functional types. The disagreement in phenology can result in a mean bias of approximately 5% of the total estimated Northern Hemisphere NPP. Further, while the more recent version of CLM (v5.0) exhibits seasonal mean LAI values that are in closer agreement with satellite data than its predecessor (CLM4.5), LAI seasonal cycles in CLM5.0 exhibit poorer agreement. Therefore, despite broad improvements for a range of states and fluxes from CLM4.5 to CLM5.0, degradation of plant phenology occurs in CLM5.0. Therefore, any coupling between the land surface and the atmosphere that depends on vegetation state might not be fully captured by the existing generation of the model. We also discuss several avenues for improving the fidelity between observations and model simulations.

Projected changes in temperature and precipitation are expected to influence spring and autumn vegetation phenology and hence the length of the growing season in many ecosystems. However, the sensitivity of green‐up and senescence to climate remains uncertain. We analyzed 488 site years of canopy greenness measurements from deciduous forest broadleaf forests across North America. We found that the sensitivity of green‐up to temperature anomalies increases with increasing mean annual temperature, suggesting lower temperature sensitivity as we move to higher latitudes. Furthermore, autumn senescence is most sensitive to moisture deficits at dry sites, with decreasing sensitivity as mean annual precipitation increases. Future projections suggest North American deciduous forests will experience higher sensitivity to temperature in the next 50 years, with larger changes expected in northern regions than in southern regions. Our study highlights how interactions between long‐term and short‐term changes in the climate system influence green‐up and senescence.

Evergreen conifer forests are the most prevalent land cover type in North America. Seasonal changes in the color of evergreen forest canopies have been documented with near‐surface remote sensing, but the physiological mechanisms underlying these changes, and the implications for photosynthetic uptake, have not been fully elucidated.