| 1. |
- Dengel, S., et al.
(författare)
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Testing the applicability of neural networks as a gap-filling method using CH4 flux data from high latitude wetlands
- 2013
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Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4189. ; 10, s. 8185-8200
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Tidskriftsartikel (refereegranskat)abstract
- Since the advancement in CH4 gas analyser technology and its applicability to eddy covariance flux measurements, monitoring of CH4 emissions is becoming more widespread. In order to accurately determine the greenhouse gas balance, high quality gap-free data is required. Currently there is still no consensus on CH4 gap-filling methods, and methods applied are still study-dependent and often carried out on low resolution, daily data. In the current study, we applied artificial neural networks to six distinctively different CH4 time series from high latitudes, explain the method and test its functionality. We discuss the applicability of neural networks in CH4 flux studies, the advantages and disadvantages of this method, and what information we were able to extract from such models. Three different approaches were tested by including drivers such as air and soil temperature, barometric air pressure, solar radiation, wind direction (indicator of source location) and in addition the lagged effect of water table depth and precipitation. In keeping with the principle of parsimony, we included up to five of these variables traditionally measured at CH4 flux measurement sites. Fuzzy sets were included representing the seasonal change and time of day. High Pearson correlation coefficients (r) of up to 0.97 achieved in the final analysis are indicative for the high performance of neural networks and their applicability as a gap-filling method for CH4 flux data time series. This novel approach which we show to be appropriate for CH4 fluxes is a step towards standardising CH4 gap-filling protocols.
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| 2. |
- Mbufong, H. N., et al.
(författare)
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Assessing the spatial variability in peak season CO2 exchange characteristics across the Arctic tundra using a light response curve parameterization
- 2014
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Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4189. ; 11:17, s. 4897-4912
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Tidskriftsartikel (refereegranskat)abstract
- This paper aims to assess the spatial variability in the response of CO2 exchange to irradiance across the Arctic tundra during peak season using light response curve (LRC) parameters. This investigation allows us to better understand the future response of Arctic tundra under climatic change. Peak season data were collected during different years (between 1998 and 2010) using the micrometeorological eddy covariance technique from 12 circumpolar Arctic tundra sites, in the range of 64-74 degrees N. The LRCs were generated for 14 days with peak net ecosystem exchange (NEE) using an NEE-irradiance model. Parameters from LRCs represent site-specific traits and characteristics describing the following: (a) NEE at light saturation (F-csat), (b) dark respiration (Rd), (c) light use efficiency (alpha), (d) NEE when light is at 1000 mu molm(-2) s(-1) (F-c1000), (e) potential photosynthesis at light saturation (P-sat) and (f) the light compensation point (LCP). Parameterization of LRCs was successful in predicting CO2 flux dynamics across the Arctic tundra. We did not find any trends in LRC parameters across the whole Arctic tundra but there were indications for temperature and latitudinal differences within sub-regions like Russia and Greenland. Together, leaf area index (LAI) and July temperature had a high explanatory power of the variance in assimilation parameters (F-csat, F-c1000 and P-sat), thus illustrating the potential for upscaling CO2 exchange for the whole Arctic tundra. Dark respiration was more variable and less correlated to environmental drivers than were assimilation parameters. This indicates the inherent need to include other parameters such as nutrient availability, substrate quantity and quality in flux monitoring activities.
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| 3. |
- Natali, S. M., et al.
(författare)
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Large loss of CO2 in winter observed across the northern permafrost region
- 2019
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Ingår i: Nature Climate Change. - : Springer Science and Business Media LLC. - 1758-678X .- 1758-6798. ; 9:11, s. 852-857
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Tidskriftsartikel (refereegranskat)abstract
- Recent warming in the Arctic, which has been amplified during the winter(1-3), greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)(4). However, the amount of CO2 released in winter is not known and has not been well represented by ecosystem models or empirically based estimates(5,6). Here we synthesize regional in situ observations of CO2 flux from Arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1,662 TgC per year from the permafrost region during the winter season (October-April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (-1,032 TgC per year). Extending model predictions to warmer conditions up to 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario-Representative Concentration Pathway 4.5-and 41% under business-as-usual emissions scenario-Representative Concentration Pathway 8.5. Our results provide a baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.
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| 4. |
- Watts, J. D., et al.
(författare)
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A satellite data driven biophysical modeling approach for estimating northern peatland and tundra CO2 and CH4 fluxes
- 2014
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Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4189. ; 11:7, s. 1961-1980
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Tidskriftsartikel (refereegranskat)abstract
- The northern terrestrial net ecosystem carbon balance (NECB) is contingent on inputs from vegetation gross primary productivity (GPP) to offset the ecosystem respiration (R-eco) of carbon dioxide (CO2) and methane (CH4) emissions, but an effective framework to monitor the regional Arctic NECB is lacking. We modified a terrestrial carbon flux (TCF) model developed for satellite remote sensing applications to evaluate wetland CO2 and CH4 fluxes over pan-Arctic eddy covariance (EC) flux tower sites. The TCF model estimates GPP, CO2 and CH4 emissions using in situ or remote sensing and reanalysis-based climate data as inputs. The TCF model simulations using in situ data explained >70% of the r(2) variability in the 8 day cumulative EC measured fluxes. Model simulations using coarser satellite (MODIS) and reanalysis (MERRA) Records accounted for approximately 69% and 75% of the respective r(2) variability in the tower CO2 and CH4 records, with corresponding RMSE uncertainties of <= 1.3 gCm(-2) d(-1) (CO2) and 18.2 mg Cm-2 d(-1) (CH4). Although the estimated annual CH4 emissions were small (<18 gCm(-2) yr(-1)) relative to R-eco (>180 gCm(-2) yr(-1)), they reduced the across-site NECB by 23% and contributed to a global warming potential of approximately 165 +/- 128 gCO(2)eqm(-2) yr(-1) when considered over a 100 year time span. This model evaluation indi-cates a strong potential for using the TCF model approach to document landscape-scale variability in CO2 and CH4 fluxes, and to estimate the NECB for northern peatland and tundra ecosystems.
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