Publication Date:
2017-10-17
Description:
Variability of surface energy fluxes over high latitude permafrost wetlands
A. Serafimovich (1), S. Metzger (2,3), J. Hartmann (4), S. Wieneke (5), and T. Sachs (1)
(1) GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
(andrei.serafimovich@gfz-potsdam.de), (2) National Ecological Observatory Network, 1685 38th Street, Boulder, CO 80301,
USA, (3) University of Colorado, 1560 30th Street, Boulder, CO 80303, USA, (4) Alfred Wegener Institute for Polar and
Marine Research, Bremerhaven, Germany, (5) Institute of Geophysics and Meteorology, Cologne University, 50969 Cologne,
Germany
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. However, attribution of these responses 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 surface-atmosphere
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, fast temperature and
humidity sensors to measure turbulent energy fluxes across the Alaskan North Slope.
We used wavelet transforms of the original high-frequency 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 extracted environmental response functions and
supplemented simulations from the Weather Research and Forecasting (WRF) model the surface energy fluxes
were then projected beyond measurement footprints across North Slope of Alaska.
Repository Name:
EPIC Alfred Wegener Institut
Type:
Conference
,
notRev
Format:
application/pdf
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