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Abstract. Low-level flights over tundra wetlands in Alaska and Canada have beenconducted during the Airborne Measurements of Methane Emissions (AirMeth) campaigns to measure turbulent methane fluxesin the atmosphere. In this paper we describe the instrumentation and newcalibration procedures for the essential pressure parameters required forturbulence sensing by aircraft that exploit suitable regular measurementflight legs without the need for dedicated calibration patterns. We estimatethe accuracy of the mean wind and the turbulence measurements. We show thatairborne measurements of turbulent fluxes of methane and carbon dioxide usingcavity ring-down spectroscopy trace gas analysers together with establishedturbulence equipment achieve a relative accuracy similar to that ofmeasurements of sensible heat flux if applied during low-level flights overnatural area sources. The inertial subrange of the trace gas fluctuationscannot be resolved due to insufficient high-frequency precision of theanalyser, but, since this scatter is uncorrelated with the vertical windvelocity, the covariance and thus the flux are reproduced correctly. In thecovariance spectra the -7/3 drop-off in the inertial subrange can bereproduced if sufficient data are available for averaging. For convectiveconditions and flight legs of several tens of kilometres we estimate the fluxdetection limit to be about4 mg m−2 d−1 forw′CH4′‾,1.4 g m−2 d−1 for w′CO2′‾ and4.2 W m−2 for the sensible heat flux. 

Abstract. The objective of this study was to upscale airborne flux measurements ofsensible heat and latent heat and to develop high-resolution flux maps. Inorder to support the evaluation of coupled atmospheric–land-surface models weinvestigated spatial patterns of energy fluxes in relation to land-surfaceproperties. We used airborne eddy-covariance measurements acquired by the Polar 5research aircraft in June–July 2012 to analyze surface fluxes.Footprint-weighted surface properties were then related to 21 529 sensibleheat flux observations and 25 608 latent heat flux observations using bothremote sensing and modeled data. A boosted regression tree technique wasused to estimate environmental response functions between spatially andtemporally resolved flux observations and corresponding biophysical andmeteorological drivers. In order to improve the spatial coverage and spatialrepresentativeness of energy fluxes we used relationships extracted acrossheterogeneous Arctic landscapes to infer high-resolution surface energy fluxmaps, thus directly upscaling the observational data. These maps of projectedsensible heat and latent heat fluxes were used to assess energy partitioningin northern ecosystems and to determine the dominant energy exchangeprocesses in permafrost areas. This allowed us to estimate energy fluxes forspecific types of land cover, taking into account meteorological conditions.Airborne and modeled fluxes were then compared with measurements from aneddy-covariance tower near Atqasuk. Our results are an important contribution for the advanced, scale-dependentquantification of surface energy fluxes and they provide new insights into theprocesses affecting these fluxes for the main vegetation types inhigh-latitude permafrost areas.