Description: Lakes in the northern permafrost region are a significant source of atmospheric methane (CH4), a potent greenhouse gas, yet large uncertainties exist in quantifying lake-source CH4. In thermokarst (thaw) lakes, the dominant pathway of CH4, ebullition (bubbling), is sporadic and spatially irregular. These lakes are also generally remote and difficult to access, resulting in challenging and costly field measurements. Scaling up field measurements from a few study lakes to regional and pan-Arctic scales relies on the assumption that the sampled lakes are a fair representation of all lakes across a landscape, which is not always the case. We present an innovative new method of quantifying lake-source CH4 using space-borne synthetic aperture radar (SAR), an instrument which can image at night, through clouds and dry snow, valuable attributes for Arctic remote sensing. Our recent work using satellite-based SAR data showed a significant correlation between polarimetric L-band SAR backscatter from lake ice and field-measured ebullition bubbles: L-band SAR backscatter intensity increases with the amount of ebullition bubbles trapped by early winter lake ice. We developed a regionally robust empirical model based on this correlation to quantify ebullition across surfaces of over 5,000 individual Alaskan lakes in satellite SAR scenes. We produced SAR-based ebullition fluxes from each lake across the landscape and created CH4 maps for five sub-regions in Alaska. Our SAR-based lake-source CH4 fluxes compare favorably with airborne CH4 measurements on the Barrow Peninsula and Atqasuk regions, and with scaled-up field measurements. We examine how our SAR remote sensing application can 1) improve selection of study lakes for field work, 2) provide regional estimates of CH4 ebullition from lakes in remote areas where field work is limited, 3) improve lake-size vs. flux relationships for upscaling field measurements and 4) shed light on the discrepancy of top-down vs. bottom-up CH4 flux estimates in the Arctic. This new approach to estimate lake-source CH4 from ebullition offers a unique opportunity to improve knowledge about CH4 fluxes for seasonally ice-covered lakes globally.

Description: One of the most pressing questions with regard to climate feedback processes in a warming Arctic is the regional-scale greenhouse gas release from Arctic permafrost areas. Ground-based eddy covariance (EC) measurements provide continuous in-situ observations of the surface-atmosphere exchange of energy and matter. However, these observations are rare in the Arctic permafrost zone and site selection is bound by logistical constraints among others. Consequently, these observations cover only small areas that are not necessarily representative of the region of interest. Airborne measurements can overcome this limitation by covering distances of hundreds of kilometers over time periods of a few hours. The Airborne Measurements of Methane Fluxes (AIRMETH) campaigns are designed to quantitatively and spatially explicitly address this question. During the AIRMETH-2012 and AIRMETH-2013 campaigns aboard the research aircraft POLAR 5 we measured turbulent exchange of energy, methane, and (in 2013) carbon dioxide along thousands of kilometers covering the North Slope of Alaska and the Mackenzie Delta, Canada. Time-frequency (wavelet) analysis, footprint modeling, and machine learning techniques are used to (i) determine spatially resolved turbulence statistics, fluxes, and contributions of biophysical surface properties, and (ii) extract regionally valid functional relationships between environmental drivers and the observed fluxes. These environmental response functions (ERF) are used to explain spatial flux patterns and – if drivers are available in temporal resolution – allow for spatio-temporal scaling of the observations. This presentation will focus on 2012 methane fluxes on the North Slope of Alaska and the relevant processes on the regional scale and provide an updated 100 m resolution methane flux map of the North Slope of Alaska.

Description: One of the most pressing questions with regard to climate feedback processes in a warming Arctic is the regional-scale methane release from Arctic permafrost areas. The Airborne Measurements of Methane Fluxes (AIRMETH) campaign is designed to quantitatively and spatially explicitly address this question. Ground-based eddy covariance (EC) measurements provide continuous in-situ observations of the surface-atmosphere exchange of methane. However, these observations are rare in the Arctic permafrost zone and site selection is bound by logistical constraints among others. Consequently, these observations cover only small areas that are not necessarily representative of the region of interest. Airborne measurements can overcome this limitation by covering distances of hundreds of kilometers over time periods of a few hours. Here, we present the potential of environmental response functions (ERFs) for quantitatively linking methane flux observations in the atmospheric surface layer to meteorological and biophysical drivers in the flux footprints. For this purpose thousands of kilometers of AIRMETH data across the Alaskan North Slope are utilized, with the aim to extrapolate the airborne EC methane flux observations to the entire North Slope. The data were collected aboard the research aircraft POLAR 5, using its turbulence nose boom and fast response methane and meteorological sensors. After thorough data pre-processing, Reynolds averaging is used to derive spatially integrated fluxes. To increase spatial resolution and to derive ERFs, we then use wavelet transforms of the original high-frequency data. This enables much improved spatial discretization of the flux observations, and the quantification of continuous and biophysically relevant land cover properties in the flux footprint of each observation. A machine learning technique is then employed to extract and quantify the functional relationships between the methane flux observations and the meteorological and biophysical drivers in the flux footprints. Lastly, the resulting ERFs are used to extrapolate the methane release over spatio-temporally explicit grids of the Alaskan North Slope. Metzger et al. (2013) have demonstrated the efficacy of this technique for regionalizing airborne EC heat flux observations to within an accuracy of ≤18% and a precision of ≤5%. Here, we show for the first time results from applying the ERF procedure to airborne methane EC measurements, and report its potential for spatio-temporally explicit inventories of the regional-scale methane exchange. References: Metzger, S., Junkermann, W., Mauder, M., Butterbach-Bahl, K., Trancón y Widemann, B., Neidl, F., Schäfer, K., Wieneke, S., Zheng, X. H., Schmid, H. P., and Foken, T.: Spatially explicit regionalization of airborne flux measurements using environmental response functions, Biogeosciences, 10, 2193-2217, doi:10.5194/bg-10-2193-2013, 2013. Cite as: Author(s) (2013), Title, Abstract B43G-07 presented at 2013 Fall Meeting, AGU, San Francisco, Calif., 9-13 Dec.

Description: The earth’s surface is tightly coupled to the global climate system by the vertical exchange of energy and matter. Thus, to better understand and potentially predict changes to our climate system, it is critical to quantify the surface-atmosphere exchange of heat, water vapor, and greenhouse gases on climate-relevant spatial and temporal scales. Currently, most flux observations consist of ground-based, continuous but local measurements. These provide a good basis for temporal integration, but may not be representative of the larger regional context. This is particularly true for the Arctic, where site selection is additionally bound by logistical constraints, among others. Airborne measurements can overcome this limitation by covering distances of hundreds of kilometers over time periods of a few hours. The Airborne Measurements of Methane Fluxes (AIRMETH) campaigns are designed to quantitatively and spatially explicitly address this issue: The research aircraft POLAR 5 is used to acquire thousands of kilometers of eddy-covariance flux data. During the AIRMETH-2012 and AIRMETH-2013 campaigns we measured the turbulent exchange of energy, methane, and (in 2013) carbon dioxide over the North Slope of Alaska, USA, and the Mackenzie Delta, Canada. Here, we present the potential of environmental response functions (ERFs) for quantitatively linking flux observations to meteorological and biophysical drivers in the flux footprints. We use wavelet transforms of the original high-frequency data to improve spatial discretization of the flux observations. This also enables the quantification of continuous and biophysically relevant land cover properties in the flux footprint of each observation. A machine learning technique is then employed to extract and quantify the functional relationships between flux observations and the meteorological and biophysical drivers. The resulting ERFs are used to extrapolate fluxes over spatio-temporally explicit grids of the study area. The presentation will focus on 2012 sensible and latent heat fluxes observed over the North Slope of Alaska and the scaling performance of the ERF approach.

Description: Arctic permafrost-associated wetlands and thawing permafrost emit the greenhouse gas methane (CH4), either as a product of recent microbial activity in the active layer or taliks, or from deeper geogenic sources where pathways through the permafrost exist. Current emission estimates vary strongly between different models and there is still disagreement between bottom-up estimates from local field studies and top-down estimates from atmospheric measurements. We use airborne flux data from two campaigns in the Mackenzie River Delta, Canada, in July 2012 and 2013 to directly quantify permafrost CH4 emissions on the regional scale, to analyse the regional pattern of CH4 fluxes and to estimate the contribution of geogenic emissions to the overall CH4 budget of the delta. CH4 fluxes were calculated with a time-frequency resolved version of the eddy covariance technique, resulting in a gridded 100 m x 100 m resolution flux map within the footprints of the flight tracks. We distinguish geogenic gas seeps from biogenic sources by their strength and show that they contribute strongly to the annual CH4 budget of the delta. Our study provides the first estimate of annual CH4 release from the Mackenzie River Delta and the adjacent coastal plain. We show that one percent of the covered area contains the strongest geogenic seeps which contribute disproportionately to the annual emission estimate. Our results show that geogenic CH4 emissions might need more attention, especially in areas where permafrost is vulnerable to thawing sufficiently to create pathways for geogenic gas migration. The presented map can be used as a baseline for future CH4 flux studies in the Mackenzie River Delta.