A Three-Dimensional Backward Lagrangian Footprint Model For A Wide Range Of Boundary-Layer Stratifications

We present a three-dimensional Lagrangian footprint model with the ability to predict the area of influence (footprint) of a measurement within a wide range of boundary-layer stratifications and receptor heights. The model approach uses stochastic backward trajectories of particles and satisfies the well-mixed condition in inhomogeneous turbulence for continuous transitions from stable to convective stratification. We introduce a spin-up procedure of the model and a statistical treatment of particle touchdowns which leads to a significant reduction of CPU time compared to conventional footprint modelling approaches. A comparison with other footprint models (of the analytical and Lagrangian type) suggests that the present backward Lagrangian model provides valid footprint predictions under any stratification and, moreover, for applications that reach across different similarity scaling domains (e.g., surface layer to mixed layer, for use in connection with aircraft measurements or with observations on high towers

A simple two-dimensional parameterisation for Flux Footprint Prediction (FFP)

Flux footprint models are often used for interpretation of flux tower measurements, to estimate position and size of surface source areas, and the relative contribution of passive scalar sources to measured fluxes. Accurate knowledge of footprints is of crucial importance for any upscaling exercises from single site flux measurements to local or regional scale. Hence, footprint models are ultimately also of considerable importance for improved greenhouse gas budgeting. With increasing numbers of flux towers within large monitoring networks such as FluxNet, ICOS (Integrated Carbon Observation System), NEON (National Ecological Observatory Network), or AmeriFlux, and with increasing temporal range of observations from such towers (of the order of decades) and availability of airborne flux measurements, there has been an increasing demand for reliable footprint estimation. Even though several sophisticated footprint models have been developed in recent years, most are still not suitable for application to long time series, due to their high computational demands. Existing fast footprint models, on the other hand, are based on surface layer theory and hence are of restricted validity for real-case applications. <br><br> To remedy such shortcomings, we present the two-dimensional parameterisation for Flux Footprint Prediction (FFP), based on a novel scaling approach for the crosswind distribution of the flux footprint and on an improved version of the footprint parameterisation of Kljun et al. (2004b). Compared to the latter, FFP now provides not only the extent but also the width and shape of footprint estimates, and explicit consideration of the effects of the surface roughness length. The footprint parameterisation has been developed and evaluated using simulations of the backward Lagrangian stochastic particle dispersion model LPDM-B (Kljun et al., 2002). Like LPDM-B, the parameterisation is valid for a broad range of boundary layer conditions and measurement heights over the entire planetary boundary layer. Thus, it can provide footprint estimates for a wide range of real-case applications. <br><br> The new footprint parameterisation requires input that can be easily determined from, for example, flux tower measurements or airborne flux data. FFP can be applied to data of long-term monitoring programmes as well as be used for quick footprint estimates in the field, or for designing new sites

Vegetation height products between 60° S and 60° N from ICESat GLAS data.

We present new coarse resolution (0.5� ×0.5�)vegetation height and vegetation-cover fraction data sets between 60� S and 60� N for use in climate models and ecological models. The data sets are derived from 2003–2009 measurements collected by the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat), the only LiDAR instrument that provides close to global coverage. Initial vegetation height is calculated from GLAS data using a development of the model of Rosette et al. (2008) with further calibration on desert sites. Filters are developed to identify and eliminate spurious observations in the GLAS data, e.g. data that are affected by clouds, atmosphere and terrain and as such result in erroneous estimates of vegetation height or vegetation cover. Filtered GLAS vegetation height estimates are aggregated in histograms from 0 to 70m in 0.5m intervals for each 0.5�×0.5�. The GLAS vegetation height product is evaluated in four ways. Firstly, the Vegetation height data and data filters are evaluated using aircraft LiDAR measurements of the same for ten sites in the Americas, Europe, and Australia. Application of filters to the GLAS vegetation height estimates increases the correlation with aircraft data from r =0.33 to r =0.78, decreases the root-mean-square error by a factor 3 to about 6m (RMSE) or 4.5m (68% error distribution) and decreases the bias from 5.7m to −1.3 m. Secondly, the global aggregated GLAS vegetation height product is tested for sensitivity towards the choice of data quality filters; areas with frequent cloud cover and areas with steep terrain are the most sensitive to the choice of thresholds for the filters. The changes in height estimates by applying different filters are, for the main part, smaller than the overall uncertainty of 4.5–6m established from the site measurements. Thirdly, the GLAS global vegetation height product is compared with a global vegetation height product typically used in a climate model, a recent global tree height product, and a vegetation greenness product and is shown to produce realistic estimates of vegetation height. Finally, the GLAS bare soil cover fraction is compared globally with the MODIS bare soil fraction (r = 0.65) and with bare soil cover fraction estimates derived from AVHRR NDVI data (r =0.67); the GLAS treecover fraction is compared with the MODIS tree-cover fraction (r =0.79). The evaluation indicates that filters applied to the GLAS data are conservative and eliminate a large proportion of spurious data, while only in a minority of cases at the cost of removing reliable data as well. The new GLAS vegetation height product appears more realistic than previous data sets used in climate models and ecological models and hence should significantly improve simulations that involve the land surface

Response of Net Ecosystem Productivity of Three Boreal Forest Stands to Drought

In 2000-03, continuous eddy covariance measurements of carbon dioxide (CO2) flux were made above mature boreal aspen, black spruce, and jack pine forests in Saskatchewan, Canada, prior to and during a 3-year drought. During the 1st drought year, ecosystem respiration (R) was reduced at the aspen site due to the drying of surface soil layers. Gross ecosystem photosynthesis (GEP) increased as a result of a warm spring and a slow decrease of deep soil moisture. These conditions resulted in the highest annual net ecosystem productivity (NEP) in the 9 years of flux measurements at this site. During 2002 and 2003, a reduction of 6% and 34% in NEP, respectively, compared to 2000 was observed as the result of reductions in both R and GEP, indicating a conservative response to the drought. Although the drought affected most of western Canada, there was considerable spatial variability in summer rainfall over the 100-km extent of the study area; summer rainfalls in 2001 and 2002 at the two conifer sites minimized the impact of the drought. In 2003, however, precipitation was similarly low at all three sites. Due to low topographic position and consequent poor drainage at the black spruce site and the coarse soil with low water-holding capacity at the jack pine site almost no reduction in R, GEP, and NEP was observed at these two sites. This study shows that the impact of drought on carbon sequestration by boreal forest ecosystems strongly depends on rainfall distribution, soil characteristics, topography, and the presence of vegetation that is well adapted to these condition

Monitoring boreal forest biomass and carbon storage change by integrating airborne laser scanning, biometry and eddy covariance data

AbstractThis study presents a comparison and integration of three methods commonly used to estimate the amount of forest ecosystem carbon (C) available for storage. In particular, we examine the representation of living above- and below-ground biomass change (net accumulation) using plot-level biometry and repeat airborne laser scanning (ALS) of three dimensional forest plot structure. These are compared with cumulative net CO2 fluxes (net ecosystem production, NEP) from eddy covariance (EC) over a six-year period within a jack pine chronosequence of four stands (~94, 30, 14 and 3years since establishment from 2005) located in central Saskatchewan, Canada. Combining the results of the two methods yield valuable observations on the partitioning of C within ecosystems. Subtracting total living biomass C accumulation from NEP results in a residual that represents change in soil and litter C storage. When plotted against time for the stands investigated, the curve produced is analogous to the soil C dynamics described in Covington (1981). Here, ALS biomass accumulation exceeds EC-based NEP measured in young stands, with the residual declining with age as stands regenerate and litter decomposition stabilizes. During the 50–70year age-period, NEP and live biomass accumulation come into balance, with the soil and litter pools of stands 70–100years post-disturbance becoming a net store of C. Biomass accumulation was greater in 2008–2011 compared to 2005–2008, with the smallest increase in the 94-year-old “old jack pine” stand and greatest in the 14-year-old “harvested jack pine 1994” stand, with values of 1.4 (±3.2) tCha−1 and 12.0 (±1.6) tCha−1, respectively. The efficiency with which CO2 was stored in accumulated biomass was lowest in the youngest and oldest stands, but peaked during rapid regeneration following harvest (14-year-old stand). The analysis highlights that the primary source of uncertainty in the data integration workflow is in the calculation of biomass expansion factors, and this aspect of the workflow needs to be implemented with caution to avoid large error propagations. We suggest that the adoption of integrated ALS, in situ and atmospheric flux monitoring frameworks is needed to improve spatio-temporal partitioning of C balance components at sub-decadal scale within rapidly changing forest ecosystems and for use in national carbon accounting programs

Carbon uptake and water use in woodlands and forests in southern Australia during an extreme heat wave event in the ‘Angry Summer’ of 2012/2013

As a result of climate change warmer temperatures are projected through the 21st century and are already increasing above modelled predictions. Apart from increases in the mean, warm/hot temperature extremes are expected to become more prevalent in the future, along with an increase in the frequency of droughts. It is crucial to better understand the response of terrestrial ecosystems to such temperature extremes for predicting land-surface feedbacks in a changing climate. While land-surface feedbacks in drought conditions and during heat waves have been reported from Europe and the US, direct observations of the impact of such extremes on the carbon and water cycles in Australia have been lacking. During the 2012/2013 summer, Australia experienced a record-breaking heat wave with an exceptional spatial extent that lasted for several weeks. In this study we synthesised eddy-covariance measurements from seven woodlands and one forest site across three biogeographic regions in southern Australia. These observations were combined with model results from BIOS2 (Haverd et al., 2013a, b) to investigate the effect of the summer heat wave on the carbon and water exchange of terrestrial ecosystems which are known for their resilience toward hot and dry conditions. We found that water-limited woodland and energy-limited forest ecosystems responded differently to the heat wave. During the most intense part of the heat wave, the woodlands experienced decreased latent heat flux (23 % of background value), increased Bowen ratio (154 %) and reduced carbon uptake (60 %). At the same time the forest ecosystem showed increased latent heat flux (151 %), reduced Bowen ratio (19 %) and increased carbon uptake (112 %). Higher temperatures caused increased ecosystem respiration at all sites (up to 139 %). During daytime all ecosystems remained carbon sinks, but carbon uptake was reduced in magnitude. The number of hours during which the ecosystem acted as a carbon sink was also reduced, which switched the woodlands into a carbon source on a daily average. Precipitation occurred after the first, most intense part of the heat wave, and the subsequent cooler temperatures in the temperate woodlands led to recovery of the carbon sink, decreased the Bowen ratio (65 %) and hence increased evaporative cooling. Gross primary productivity in the woodlands recovered quickly with precipitation and cooler temperatures but respiration remained high. While the forest proved relatively resilient to this short-term heat extreme the response of the woodlands is the first direct evidence that the carbon sinks of large areas of Australia may not be sustainable in a future climate with an increased number, intensity and duration of heat waves.Eva van Gorsel, Sebastian Wolf, James Cleverly, Peter Isaac, Vanessa Haverd, Cäcilia Ewenz, Stefan Arndt, Jason Beringer, Víctor Resco de Dios, Bradley J. Evans, Anne Griebel, Lindsay B. Hutley, Trevor Keenan, Natascha Kljun, Craig Macfarlane, Wayne S. Meyer, Ian McHugh, Elise Pendall, Suzanne M. Prober and Richard Silberstei

Methane exchange in a boreal forest estimated by gradient method

Forests are generally considered to be net sinks of atmospheric methane (CH4) because of oxidation by methanotrophic bacteria in well-aerated forests soils. However, emissions from wet forest soils, and sometimes canopy fluxes, are often neglected when quantifying the CH4 budget of a forest. We used a modified Bowen ratio method and combined eddy covariance and gradient methods to estimate net CH4 exchange at a boreal forest site in central Sweden. Results indicate that the site is a net source of CH4. This is in contrast to soil, branch and leaf chamber measurements of uptake of CH4. Wetter soils within the footprint of the canopy are thought to be responsible for the discrepancy. We found no evidence for canopy emissions per se. However, the diel pattern of the CH4 exchange with minimum emissions at daytime correlated well with gross primary production, which supports an uptake in the canopy. More distant source areas could also contribute to the diel pattern; their contribution might be greater at night during stable boundary layer conditions

Upscaling of methane exchange in a boreal forest using soil chamber measurements and high-resolution LiDAR elevation data

Forest soils are generally considered to be net sinks of methane (CH4), but CH4 fluxes vary spatially depending on soil conditions. Measuring CH4 exchange with chambers, which are commonly used for this purpose, might not result in representative fluxes at site scale. Appropriate methods for upscaling CH4 fluxes from point measurements to site scale are therefore needed. At the boreal forest research site, Norunda, chamber measurements of soils and vegetation indicate that the site is a net sink of CH4, while tower gradient measurements indicate that the site is a net source of CH4. We investigated the discrepancy between chamber and tower gradient measurements by upscaling soil CH4 exchange to a 100 ha area based on an empirical model derived from chamber measurements of CH4 exchange and measurements of soil moisture, soil temperature and water table depth. A digital elevation model (DEM) derived from high-resolution airborne Light Detection and Ranging (LiDAR) data was used to generate gridded water table depth and soil moisture data of the study area as input data for the upscaling. Despite the simplistic approach, modeled fluxes were significantly correlated to four out of five chambers with R>0.68. The upscaling resulted in a net soil sink of CH4 of -10 mu mol m(-2) h(-1), averaged over the entire study area and time period June-September, 2010). Our findings suggest that additional contributions from CH4 soil sources outside the upscaling study area and possibly CH4 emissions from vegetation could explain the net emissions measured by tower gradient measurements. (C) 2015 Elsevier B.V. All rights reserved