444 research outputs found
Strong geologic methane emissions from discontinuous terrestrial permafrost in the Mackenzie Delta, Canada
Arctic permafrost caps vast amounts of old, geologic methane (CH4) in subsurface reservoirs. Thawing permafrost opens pathways for this CH4 to migrate to the surface. However, the occurrence of geologic emissions and their contribution to the CH4 budget in addition to recent, biogenic CH4 is uncertain. Here we present a high-resolution (100 m × 100 m) regional (10,000 km²) CH4 flux map of the Mackenzie Delta, Canada, based on airborne CH4 flux data from July 2012 and 2013. We identify strong, likely geologic emissions solely where the permafrost is discontinuous. These peaks are 13 times larger than typical biogenic emissions. Whereas microbial CH4 production largely depends on recent air and soil temperature, geologic CH4 was produced over millions of years and can be released year-round provided open pathways exist. Therefore, even though they only occur on about 1% of the area, geologic hotspots contribute 17% to the annual CH4 emission estimate of our study area. We suggest that this share may increase if ongoing permafrost thaw opens new pathways. We conclude that, due to permafrost thaw, hydrocarbon-rich areas, prevalent in the Arctic, may see increased emission of geologic CH4 in the future, in addition to enhanced microbial CH4 production
Permafrost - physical aspects and carbon cycling, databases and uncertainties
Permafrost is defined as ground that remains below 0°C for at least 2 consecutive years. About 24% of the northern hemisphere land area is underlain by permafrost. The thawing of permafrost has the potential to influence the climate system through the release of carbon (C) from northern high latitude terrestrial ecosystems, but there is substantial uncertainty about the sensitivity of the C cycle to thawing permafrost. Soil C can be mobilized from permafrost in response to changes in air temperature, directional changes in water balance, fire, thermokarst, and flooding. Observation networks need to be implemented to understand responses of
permafrost and C at a range of temporal and spatial scales. The understanding gained from these observation networks needs to be integrated into modeling frameworks capable of representing how the responses of permafrost C will influence the trajectory of climate in the future
Spatial variability of aircraft-measured surface energy fluxes in permafrost landscapes
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.
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 and fast temperature and humidity sensors to measure turbulent energy fluxes along flight tracks across the Alaskan North Slope with the aim to extrapolate the airborne eddy covariance flux measurements from their specific footprint to the entire North Slope.
After thorough data pre-processing, wavelet transforms are used to improve spatial discretization of flux observations in order to relate them to biophysically relevant surface properties in the flux footprint. Boosted regression trees are then employed to extract and quantify the functional relationships between the energy fluxes and environmental drivers. Finally, the resulting environmental response functions are used to extrapolate the sensible heat and water vapor exchange over spatio-temporally explicit grids of the Alaskan North Slope. Additionally, simulations from the Weather Research and Forecasting (WRF) model were used to explore the dynamics of the atmospheric boundary layer and to examine results of our extrapolation
Winter Daytime Warming and Shift in Summer Monsoon Increase Plant Cover and Net CO2 Uptake in a Central Tibetan Alpine Steppe Ecosystem
Over the past decades, human-induced climate change has led to a widespread wetting and warming of the Tibetan Plateau (TP), affecting both ecosystems and the carbon cycling therein. Whether the previously observed climate changes stimulate carbon uptake via enhanced photosynthesis or carbon loss via enhanced soil respiration remains unclear. Here we present 14 years of observations of carbon fluxes, meteorological variables and remotely sensed plant cover estimations from a central Tibetan alpine steppe ecosystem at Nam Co, the third largest lake on the TP. Using modified Mann-Kendall trend tests, we found a significant increasing daily net carbon uptake of 0.5 g C m−2 decade−1, which can be explained by a widespread greening at the southern shore of lake Nam Co. The Plateau-wide changes in temperature and precipitation are locally expressed as an increasing diurnal temperature range during winter, higher water availability during spring, higher cloud cover during early summer and less water availability during late summer. While these changes differ over the course of the year, they tend to stimulate plant growth more than microbial respiration, leading to an increased carbon uptake during all seasons. This study indicates that during the 14 years study period, a higher amplitude in winter temperatures and an earlier summer monsoon promote carbon uptake in a central Tibetan alpine steppe ecosystem
Assessing the Local Nature of Arctic Nearhore Environments using Bio-Oprical Parameters. A Case Study from Herschel Island, Western Canadian Arctic
The Arctic is subject to substantial changes due to the greenhouse gas induced climate change. While impacts on lateral transport pathways such as rivers have been extensively studied yet, there is little knowledge about ecological and geological reactions of nearshore environments, even though those are of high importance for native communities. Here we present an extensive dataset of bio-optical parameters collected in the nearshore zone of Herschel Island, western Canadian Arctic in summer 2018, containing suspended particulate matter concentration (SPM), turbidity, sea surface temperature (SST) and the water leaving reflectance (RRS). Our results clearly indicate that recently published bio-optical models using validation data from the Canadian Beaufort Shelf are not able to reflect the local nature of Herschel Islands nearshore environment and strongly underestimate reality. Accurate bio-optical models of Arctic nearshore environments are necessary to enhance the knowledge of Arctic marine dynamics and recently published bio-optical models need an adjustment
Impetuous CO2 release from eroding permafrost coasts
see pdf of extended abstrac
Variability of surface energy fluxes over high latitude permafrost wetlands
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
([email protected]), (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
Rapid CO2 release from eroding permafrost in seawater
Permafrost is thawing extensively due to climate warming. When permafrost thaws, previously frozen organic carbon (OC) is converted into carbon dioxide (CO2) or methane, leading to further warming. This process is included in models as gradual deepening of the seasonal non‐frozen layer. Yet, models neglect abrupt OC mobilization along rapidly eroding Arctic coastlines. We mimicked erosion in an experiment by incubating permafrost with seawater for an average Arctic open‐water season. We found that CO2 production from permafrost OC is as efficient in seawater as without. For each gram (dry weight) of eroding permafrost, up to 4.3 ± 1.0 mg CO2 will be released and 6.2 ± 1.2% of initial OC mineralized at 4 °C. Our results indicate that potentially large amounts of CO2 are produced along eroding permafrost coastlines, onshore and within nearshore waters. We conclude that coastal erosion could play an important role in carbon cycling and the climate system
eddy4R 0.2.0: a DevOps model for community-extensible processing and analysis of eddy-covariance data based on R, Git, Docker, and HDF5
Large differences in instrumentation, site setup, data format, and operating system stymie the adoption of a universal computational environment for processing and analyzing eddy-covariance (EC) data. This results in limited software applicability and extensibility in addition to often substantial inconsistencies in flux estimates. Addressing these concerns, this paper presents the systematic development of portable, reproducible, and extensible EC software achieved by adopting a development and systems operation (DevOps) approach. This software development model is used for the creation of the eddy4R family of EC code packages in the open-source R language for statistical computing. These packages are community developed, iterated via the Git distributed version control system, and wrapped into a portable and reproducible Docker filesystem that is independent of the underlying host operating system. The HDF5 hierarchical data format then provides a streamlined mechanism for highly compressed and fully self-documented data ingest and output.
The usefulness of the DevOps approach was evaluated for three test applications. First, the resultant EC processing software was used to analyze standard flux tower data from the first EC instruments installed at a National Ecological Observatory (NEON) field site. Second, through an aircraft test application, we demonstrate the modular extensibility of eddy4R to analyze EC data from other platforms. Third, an intercomparison with commercial-grade software showed excellent agreement (R2 = 1.0 for CO2 flux). In conjunction with this study, a Docker image containing the first two eddy4R packages and an executable example workflow, as well as first NEON EC data products are released publicly. We conclude by describing the work remaining to arrive at the automated generation of science-grade EC fluxes and benefits to the science community at large.
This software development model is applicable beyond EC and more generally builds the capacity to deploy complex algorithms developed by scientists in an efficient and scalable manner. In addition, modularity permits meeting project milestones while retaining extensibility with time
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