990 resultados para Calculated, eddy covariance method
Resumo:
The summer water balance of a typical Siberian polygonal tundra catchment is investigated in order to identify the spatial and temporal dynamics of its main hydrological processes. The results show that, besides precipitation and evapotranspiration, lateral flow considerably influences the site-specific hydrological conditions. The prominent microtopography of the polygonal tundra strongly controls lateral flow and storage behaviour of the investigated catchment. Intact rims of low-centred polygons build hydrological barriers, which release storage water later in summer than polygons with degraded rims and troughs above degraded ice wedges. The barrier function of rims is strongly controlled by soil thaw, which opens new subsurface flow paths and increases subsurface hydrological connectivity. Therefore, soil thaw dynamics determine the magnitude and timing of subsurface outflow and the redistribution of storage within the catchment. Hydraulic conductivities in the elevated polygonal rims sharply decrease with the transition from organic to mineral layers. This interface causes a rapid shallow subsurface drainage of rainwater towards the depressed polygon centres and troughs. The re-release of storage water from the centres through deeper and less conductive layers helps maintain a high water table in the surface drainage network of troughs throughout the summer.
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Samoylov Island is centrally located within the Lena River Delta at 72° N, 126° E and lies within the Siberian zone of continuous permafrost. The landscape on Samoylov Island consists mainly of late Holocene river terraces with polygonal tundra, ponds and lakes, and an active floodplain. The island has been the focus of numerous multidisciplinary studies since 1993, which have focused on climate, land cover, ecology, hydrology, permafrost and limnology. This paper aims to provide a framework for future studies by describing the characteristics of the island's meteorological parameters (temperature, radiation and snow cover), soil temperature, and soil moisture. The land surface characteristics have been described using high resolution aerial images in combination with data from ground-based observations. Of note is that deeper permafrost temperatures have increased between 0.3 to 1.3 °C over the last five years. However, no clear warming of air and active layer temperatures is detected since 1998, though winter air temperatures during recent years have not been as cold as in earlier years.
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Airborne measurements within the urban mixing layer (360 m) over Greater London are used to quantify CO2 emissions at the meso-scale. Daytime CO2 fluxes, calculated by the Integrative Mass Boundary Layer (IMBL) method, ranged from 46 to 104 μmol CO2 m−2 s−1 for four days in October 2011. The day-to-day variability of IMBL fluxes is at the same order of magnitude as for surface eddy-covariance fluxes observed in central London. Compared to fluxes derived from emissions inventory, the IMBL method gives both lower (by −37%) and higher (by 19%) estimates. The sources of uncertainty of applying the IMBL method in urban areas are discussed and guidance for future studies is given.
Resumo:
Anthropogenic emissions of heat and exhaust gases play an important role in the atmospheric boundary layer, altering air quality, greenhouse gas concentrations and the transport of heat and moisture at various scales. This is particularly evident in urban areas where emission sources are integrated in the highly heterogeneous urban canopy layer and directly linked to human activities which exhibit significant temporal variability. It is common practice to use eddy covariance observations to estimate turbulent surface fluxes of latent heat, sensible heat and carbon dioxide, which can be attributed to a local scale source area. This study provides a method to assess the influence of micro-scale anthropogenic emissions on heat, moisture and carbon dioxide exchange in a highly urbanized environment for two sites in central London, UK. A new algorithm for the Identification of Micro-scale Anthropogenic Sources (IMAS) is presented, with two aims. Firstly, IMAS filters out the influence of micro-scale emissions and allows for the analysis of the turbulent fluxes representative of the local scale source area. Secondly, it is used to give a first order estimate of anthropogenic heat flux and carbon dioxide flux representative of the building scale. The algorithm is evaluated using directional and temporal analysis. The algorithm is then used at a second site which was not incorporated in its development. The spatial and temporal local scale patterns, as well as micro-scale fluxes, appear physically reasonable and can be incorporated in the analysis of long-term eddy covariance measurements at the sites in central London. In addition to the new IMAS-technique, further steps in quality control and quality assurance used for the flux processing are presented. The methods and results have implications for urban flux measurements in dense urbanised settings with significant sources of heat and greenhouse gases.
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The estimation of the carbon dioxide (CO2) fluxes above the open ocean plays an important role for the determination of the global carbon cycle. A frequently used method therefore is the eddy-covariance technique, which is based on the theory of the Prandl-layer with height-constant fluxes in the atmospheric boundary layer. To test the assumption of the constant flux layer, in 2008 measurements of turbulent heat and CO2 fluxes were started within the project Surface Ocean Processes in the Anthropocene (SOPRAN) at the research platform FINO2. The FINO2 platform is situated in the South-west of the Baltic Sea, in the tri-border region between Germany, Denmark, and Sweden. In the frame of the Research project SOPRAN, the platform was equipped with additional sensors in June 2008. A combination of 3-component sonic anemometers (USA-1) and open-path infrared gas analyzers for absolute humidity (H2O) and CO2 (LICOR 7500) were installed at a 9m long boom directed southward of the platform in two heights, at 6.8 and 13.8m above sea surface. Additionally slow temperature and humidity sensors were installed at each height. The gas analyzer systems were calibrated before the installation and worked permanently without any calibration during the first measurement period of one and a half years. The comparison with the measurements of the slow sensors showed for both instruments no significant long-term drift in H2O and CO2. Drifts on smaller time scales (in the order of days) due to the contamination with sea salt, were cleaned naturally by rain. The drift of both quantities had no influence on the fluctuation, which, in contrast to the mean values, are important for the flux estimation. All data were filtered due to spikes, rain, and the influence of the mast. The data set includes the measurements of all sensors as average over 30 minutes each for one and a half years, June 2008 to December 2009, and 10 month from November 2011 to August 2012. Additionally derived quantities for 30 minutes intervals each, like the variances for the fast-sensor variables, as well as the momentum, sensible and latent heat, and CO2 flux are presented.
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We present the first ecosystem-scale methane flux data from a northern Siberian tundra ecosystem covering the entire snow-free period from spring thaw until initial freeze-back. Eddy covariance measurements of methane emission were carried out from the beginning of June until the end of September in the southern central part of the Lena River Delta (72°22' N, 126°30' E). The study site is located in the zone of continuous permafrost and is characterized by Arctic continental climate with very low precipitation and a mean annual temperature of -14.7°C. We found relatively low fluxes of on average 18.7 mg/m**2/d, which we consider to be because of (1) extremely cold permafrost, (2) substrate limitation of the methanogenic archaea, and (3) a relatively high surface coverage of noninundated, moderately moist areas. Near-surface turbulence as measured by the eddy covariance system in 4 m above the ground surface was identified as the most important control on ecosystem-scale methane emission and explained about 60% of the variance in emissions, while soil temperature explained only 8%. In addition, atmospheric pressure was found to significantly improve an exponential model based on turbulence and soil temperature. Ebullition from waterlogged areas triggered by decreasing atmospheric pressure and near-surface turbulence is thought to be an important pathway that warrants more attention in future studies. The close coupling of methane fluxes and atmospheric parameters demonstrated here raises questions regarding the reliability of enclosure-based measurements, which inherently exclude these parameters.
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In this study, we concentrate on modelling gross primary productivity using two simple approaches to simulate canopy photosynthesis: "big leaf" and "sun/shade" models. Two approaches for calibration are used: scaling up of canopy photosynthetic parameters from the leaf to the canopy level and fitting canopy biochemistry to eddy covariance fluxes. Validation of the models is achieved by using eddy covariance data from the LBA site C14. Comparing the performance of both models we conclude that numerically (in terms of goodness of fit) and qualitatively, (in terms of residual response to different environmental variables) sun/shade does a better job. Compared to the sun/shade model, the big leaf model shows a lower goodness of fit and fails to respond to variations in the diffuse fraction, also having skewed responses to temperature and VPD. The separate treatment of sun and shade leaves in combination with the separation of the incoming light into direct beam and diffuse make sun/shade a strong modelling tool that catches more of the observed variability in canopy fluxes as measured by eddy covariance. In conclusion, the sun/shade approach is a relatively simple and effective tool for modelling photosynthetic carbon uptake that could be easily included in many terrestrial carbon models.
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We describe a model-data fusion (MDF) inter-comparison project (REFLEX), which compared various algorithms for estimating carbon (C) model parameters consistent with both measured carbon fluxes and states and a simple C model. Participants were provided with the model and with both synthetic net ecosystem exchange (NEE) of CO2 and leaf area index (LAI) data, generated from the model with added noise, and observed NEE and LAI data from two eddy covariance sites. Participants endeavoured to estimate model parameters and states consistent with the model for all cases over the two years for which data were provided, and generate predictions for one additional year without observations. Nine participants contributed results using Metropolis algorithms, Kalman filters and a genetic algorithm. For the synthetic data case, parameter estimates compared well with the true values. The results of the analyses indicated that parameters linked directly to gross primary production (GPP) and ecosystem respiration, such as those related to foliage allocation and turnover, or temperature sensitivity of heterotrophic respiration, were best constrained and characterised. Poorly estimated parameters were those related to the allocation to and turnover of fine root/wood pools. Estimates of confidence intervals varied among algorithms, but several algorithms successfully located the true values of annual fluxes from synthetic experiments within relatively narrow 90% confidence intervals, achieving >80% success rate and mean NEE confidence intervals <110 gC m−2 year−1 for the synthetic case. Annual C flux estimates generated by participants generally agreed with gap-filling approaches using half-hourly data. The estimation of ecosystem respiration and GPP through MDF agreed well with outputs from partitioning studies using half-hourly data. Confidence limits on annual NEE increased by an average of 88% in the prediction year compared to the previous year, when data were available. Confidence intervals on annual NEE increased by 30% when observed data were used instead of synthetic data, reflecting and quantifying the addition of model error. Finally, our analyses indicated that incorporating additional constraints, using data on C pools (wood, soil and fine roots) would help to reduce uncertainties for model parameters poorly served by eddy covariance data.
Resumo:
Eddy covariance measurements of the turbulent sensible heat, latent heat and carbon dioxide fluxes for 12 months (2011–2012) are reported for the first time for a suburban area in the UK. The results from Swindon are comparable to suburban studies of similar surface cover elsewhere but reveal large seasonal variability. Energy partitioning favours turbulent sensible heat during summer (midday Bowen ratio 1.4–1.6) and latent heat in winter (0.05–0.7). A significant proportion of energy is stored (and released) by the urban fabric and the estimated anthropogenic heat flux is small but non-negligible (0.5–0.9 MJ m−2 day−1). The sensible heat flux is negative at night and for much of winter daytimes, reflecting the suburban nature of the site (44% vegetation) and relatively low built fraction (16%). Latent heat fluxes appear to be water limited during a dry spring in both 2011 and 2012, when the response of the surface to moisture availability can be seen on a daily timescale. Energy and other factors are more relevant controls at other times; at night the wind speed is important. On average, surface conductance follows a smooth, asymmetrical diurnal course peaking at around 6–9 mm s−1, but values are larger and highly variable in wet conditions. The combination of natural (vegetative) and anthropogenic (emission) processes is most evident in the temporal variation of the carbon flux: significant photosynthetic uptake is seen during summer, whilst traffic and building emissions explain peak release in winter (9.5 g C m−2 day−1). The area is a net source of CO2 annually. Analysis by wind direction highlights the role of urban vegetation in promoting evapotranspiration and offsetting CO2 emissions, especially when contrasted against peak traffic emissions from sectors with more roads. Given the extent of suburban land use, these results have important implications for understanding urban energy, water and carbon dynamics.