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Abstract:
Arctic ecosystems are undergoing a very rapid
change due to global warming and their response to climate
change has important implications for the global
energy budget. Therefore, it is crucial to understand
how energy fluxes in the Arctic will respond to any
changes in climate related parameters. Attribution
of these responses, however, is challenging because
measured fluxes are the sum of multiple processes
that respond differently to environmental factors.
Ground-based measurements of surface fluxes
provide continuous in-situ observations of the surfaceatmosphere
exchange. But these observations may be
non-representative because of spatial and temporal
heterogeneity, indicating that local observations cannot
easily be extrapolated to represent global scales.
Airborne eddy covariance measurements across large
areas can reduce uncertainty and improve spatial coverage
and spatial representativeness of flux estimates.
Here, we present the potential of environmental response
functions for quantitatively linking energy flux
observations over high latitude permafrost wetlands
to environmental drivers in the flux footprints. We
used the research aircraft Polar 5 equipped with a
turbulence probe as well as fast temperature and humidity
sensors to measure turbulent energy fluxes
across the Alaskan North Slope.
We used wavelet transforms of the original highfrequency
data, which enable much improved spatial
discretization of the flux observations, and determine
biophysically relevant land cover properties in the flux
footprint. A boosted regression trees technique is then
employed to extract and quantify the functional relationships
between energy fluxes and environmental
drivers. Using the extracted environmental response
functions and meteorological fields simulated by the
Weather Research and Forecasting (WRF) model, the
surface energy fluxes were then projected beyond the
measurement footprints across the entire North Slope
of Alaska.
