Seasonal pattern of regional carbon balance in the central Rocky Mountains from surface and airborne measurements

[1] High-elevation forests represent a large fraction of potential carbon uptake in North America, but this uptake is not well constrained by observations. Additionally, forests in the Rocky Mountains have recently been severely damaged by drought, fire, and insect outbreaks, which have been quantified at local scales but not assessed in terms of carbon uptake at regional scales. The Airborne Carbon in the Mountains Experiment was carried out in 2007 partly to assess carbon uptake in western U.S. mountain ecosystems. The magnitude and seasonal change of carbon uptake were quantified by (1) paired upwind-downwind airborne CO2 observations applied in a boundary layer budget, (2) a spatially explicit ecosystem model constrained using remote sensing and flux tower observations, and (3) a downscaled global tracer transport inversion. Top-down approaches had mean carbon uptake equivalent to flux tower observations at a subalpine forest, while the ecosystem model showed less. The techniques disagreed on temporal evolution. Regional carbon uptake was greatest in the early summer immediately following snowmelt and tended to lessen as the region experienced dry summer conditions. This reduction was more pronounced in the airborne budget and inversion than in flux tower or upscaling, possibly related to lower snow water availability in forests sampled by the aircraft, which were lower in elevation than the tower site. Changes in vegetative greenness associated with insect outbreaks were detected using satellite reflectance observations, but impacts on regional carbon cycling were unclear, highlighting the need to better quantify this emerging disturbance effect on montane forest carbon cycling.

Holm Oak (Quercus ilex L.) canopy as interceptor of airborne trace elements and their accumulation in the litter and topsoil

We investigated the role of urban Holm Oak (Quercus ilex L.) trees as airborne metal accumulators and metals' environmental fate. Analyses confirmed Pb, Cd, Cu and Zn as main contaminants in Siena's urban environment; only Pb concentrations decreased significantly compared to earlier surveys. Additionally, we determined chemical composition of tree leaves, litter and topsoil (underneath/outside tree crown) in urban and extra-urban oak stands. Most notably, litter in urban samples collected outside the canopy had significantly lower concentrations of organic matter and higher concentrations of Pb, Cu, Cd and Zn than litter collected underneath the canopy. There was a greater metals' accumulation in topsoil, in samples collected under the tree canopy and especially near the trunk ('stemflow area'). Thus, in urban ecosystems the Holm Oak stands likely increase the soil capability to bind metals.

Modeling image motion in airborne Three-Line-Array (TLA) push-broom cameras

This paper presents an image motion model for airborne three-line-array (TLA) push-broom cameras. Both aircraft velocity and attitude instability are taken into account in modeling image motion. Effects of aircraft pitch, roll, and yaw on image motion are analyzed based on geometric relations in designated coordinate systems. The image motion is mathematically modeled by image motion velocity multiplied by exposure time. Quantitative analysis to image motion velocity is then conducted in simulation experiments. The results have shown that image motion caused by aircraft velocity is space invariant while image motion caused by aircraft attitude instability is more complicated. Pitch,roll and yaw all contribute to image motion to different extents. Pitch dominates the along-track image motion and both roll and yaw greatly contribute to the cross-track image motion. These results provide a valuable base for image motion compensation to ensure high accuracy imagery in aerial photogrammetry.

An effective approach for land-cover classification from airborne lidar fused with co-registered data

Airborne lidar provides accurate height information of objects on the earth and has been recognized as a reliable and accurate surveying tool in many applications. In particular, lidar data offer vital and significant features for urban land-cover classification, which is an important task in urban land-use studies. In this article, we present an effective approach in which lidar data fused with its co-registered images (i.e. aerial colour images containing red, green and blue (RGB) bands and near-infrared (NIR) images) and other derived features are used effectively for accurate urban land-cover classification. The proposed approach begins with an initial classification performed by the Dempster–Shafer theory of evidence with a specifically designed basic probability assignment function. It outputs two results, i.e. the initial classification and pseudo-training samples, which are selected automatically according to the combined probability masses. Second, a support vector machine (SVM)-based probability estimator is adopted to compute the class conditional probability (CCP) for each pixel from the pseudo-training samples. Finally, a Markov random field (MRF) model is established to combine spatial contextual information into the classification. In this stage, the initial classification result and the CCP are exploited. An efficient belief propagation (EBP) algorithm is developed to search for the global minimum-energy solution for the maximum a posteriori (MAP)-MRF framework in which three techniques are developed to speed up the standard belief propagation (BP) algorithm. Lidar and its co-registered data acquired by Toposys Falcon II are used in performance tests. The experimental results prove that fusing the height data and optical images is particularly suited for urban land-cover classification. There is no training sample needed in the proposed approach, and the computational cost is relatively low. An average classification accuracy of 93.63% is achieved.

Heat and moisture budgets from airborne measurements and high-resolution model simulations

High-resolution simulations with a mesoscale model are performed to estimate heat and moisture budgets of a well-mixed boundary layer. The model budgets are validated against energy budgets obtained from airborne measurements over heterogeneous terrain in Western Germany. Time rate of change, vertical divergence, and horizontal advection for an atmospheric column of air are estimated. Results show that the time trend of specific humidity exhibits some deficiencies, while the potential temperature trend is matched accurately. Furthermore, the simulated turbulent surface fluxes of sensible and latent heat are comparable to the measured fluxes, leading to similar values of the vertical divergence. The analysis of different horizontal model resolutions exhibits improved surface fluxes with increased resolution, a fact attributed to a reduced aggregation effect. Scale-interaction effects could be identified: while time trends and advection are strongly influenced by mesoscale forcing, the turbulent surface fluxes are mainly controlled by microscale processes.

Spatial and radiometric fidelity of airborne multispectral imagery in the context of land-cover change analyses

The goal was to quantitatively estimate and compare the fidelity of images acquired with a digital imaging system (ADAR 5500) and generated through scanning of color infrared aerial photographs (SCIRAP) using image-based metrics. Images were collected nearly simultaneously in two repetitive flights to generate multi-temporal datasets. Spatial fidelity of ADAR was lower than that of SCIRAP images. Radiometric noise was higher for SCIRAP than for ADAR images, even though noise from misregistration effects was lower. These results suggest that with careful control of film scanning, the overall fidelity of SCIRAP imagery can be comparable to that of digital multispectral camera data. Therefore, SCIRAP images can likely be used in conjunction with digital metric camera imagery in long-term landcover change analyses.

Modelling of urban sensible heat flux at multiple spatial scales : a demonstration using airborne hyperspectral imagery of Shanghai and a temperature–emissivity separation approach

Urbanization related alterations to the surface energy balance impact urban warming (‘heat islands’), the growth of the boundary layer, and many other biophysical processes. Traditionally, in situ heat flux measures have been used to quantify such processes, but these typically represent only a small local-scale area within the heterogeneous urban environment. For this reason, remote sensing approaches are very attractive for elucidating more spatially representative information. Here we use hyperspectral imagery from a new airborne sensor, the Operative Modular Imaging Spectrometer (OMIS), along with a survey map and meteorological data, to derive the land cover information and surface parameters required to map spatial variations in turbulent sensible heat flux (QH). The results from two spatially-explicit flux retrieval methods which use contrasting approaches and, to a large degree, different input data are compared for a central urban area of Shanghai, China: (1) the Local-scale Urban Meteorological Parameterization Scheme (LUMPS) and (2) an Aerodynamic Resistance Method (ARM). Sensible heat fluxes are determined at the full 6 m spatial resolution of the OMIS sensor, and at lower resolutions via pixel aggregation and spatial averaging. At the 6 m spatial resolution, the sensible heat flux of rooftop dominated pixels exceeds that of roads, water and vegetated areas, with values peaking at ∼ 350 W m− 2, whilst the storage heat flux is greatest for road dominated pixels (peaking at around 420 W m− 2). We investigate the use of both OMIS-derived land surface temperatures made using a Temperature–Emissivity Separation (TES) approach, and land surface temperatures estimated from air temperature measures. Sensible heat flux differences from the two approaches over the entire 2 × 2 km study area are less than 30 W m− 2, suggesting that methods employing either strategy maybe practica1 when operated using low spatial resolution (e.g. 1 km) data. Due to the differing methodologies, direct comparisons between results obtained with the LUMPS and ARM methods are most sensibly made at reduced spatial scales. At 30 m spatial resolution, both approaches produce similar results, with the smallest difference being less than 15 W m− 2 in mean QH averaged over the entire study area. This is encouraging given the differing architecture and data requirements of the LUMPS and ARM methods. Furthermore, in terms of mean study QH, the results obtained by averaging the original 6 m spatial resolution LUMPS-derived QH values to 30 and 90 m spatial resolution are within ∼ 5 W m− 2 of those derived from averaging the original surface parameter maps prior to input into LUMPS, suggesting that that use of much lower spatial resolution spaceborne imagery data, for example from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is likely to be a practical solution for heat flux determination in urban areas.

Horizontal and vertical structure of the Eyjafjallajökull ash cloud over the UK: a comparison of airborne lidar observations and simulations

During April and May 2010 the ash cloud from the eruption of the Icelandic volcano Eyjafjallajökull caused widespread disruption to aviation over northern Europe. The location and impact of the eruption led to a wealth of observations of the ash cloud were being obtained which can be used to assess modelling of the long range transport of ash in the troposphere. The UK FAAM (Facility for Airborne Atmospheric Measurements) BAe-146-301 research aircraft overflew the ash cloud on a number of days during May. The aircraft carries a downward looking lidar which detected the ash layer through the backscatter of the laser light. In this study ash concentrations derived from the lidar are compared with simulations of the ash cloud made with NAME (Numerical Atmospheric-dispersion Modelling Environment), a general purpose atmospheric transport and dispersion model. The simulated ash clouds are compared to the lidar data to determine how well NAME simulates the horizontal and vertical structure of the ash clouds. Comparison between the ash concentrations derived from the lidar and those from NAME is used to define the fraction of ash emitted in the eruption that is transported over long distances compared to the total emission of tephra. In making these comparisons possible position errors in the simulated ash clouds are identified and accounted for. The ash layers seen by the lidar considered in this study were thin, with typical depths of 550–750 m. The vertical structure of the ash cloud simulated by NAME was generally consistent with the observed ash layers, although the layers in the simulated ash clouds that are identified with observed ash layers are about twice the depth of the observed layers. The structure of the simulated ash clouds were sensitive to the profile of ash emissions that was assumed. In terms of horizontal and vertical structure the best results were obtained by assuming that the emission occurred at the top of the eruption plume, consistent with the observed structure of eruption plumes. However, early in the period when the intensity of the eruption was low, assuming that the emission of ash was uniform with height gives better guidance on the horizontal and vertical structure of the ash cloud. Comparison of the lidar concentrations with those from NAME show that 2–5% of the total mass erupted by the volcano remained in the ash cloud over the United Kingdom.

Daytime CO2 urban surface fluxes from airborne measurements, eddy-covariance observations and emissions inventory in Greater London

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.

A study on the sensitivities of simulated aerosol optical properties to composition and size distribution using airborne measurements

We present a flexible framework to calculate the optical properties of atmospheric aerosols at a given relative humidity based on their composition and size distribution. The similarity of this framework to climate model parameterisations allows rapid and extensive sensitivity tests of the impact of uncertainties in data or of new measurements on climate relevant aerosol properties. The data collected by the FAAM BAe-146 aircraft during the EUCAARI-LONGREX and VOCALS-REx campaigns have been used in a closure study to analyse the agreement between calculated and measured aerosol optical properties for two very different aerosol types. The agreement achieved for the EUCAARI-LONGREX flights is within the measurement uncertainties for both scattering and absorption. However, there is poor agreement between the calculated and the measured scattering for the VOCALS-REx flights. The high concentration of sulphate, which is a scattering aerosol with no absorption in the visible spectrum, made the absorption measurements during VOCALS-REx unreliable, and thus no closure study was possible for the absorption. The calculated hygroscopic scattering growth factor overestimates the measured values during EUCAARI-LONGREX and VOCALS-REx by ∼30% and ∼20%, respectively. We have also tested the sensitivity of the calculated aerosol optical properties to the uncertainties in the refractive indices, the hygroscopic growth factors and the aerosol size distribution. The largest source of uncertainty in the calculated scattering is the aerosol size distribution (∼35%), followed by the assumed hygroscopic growth factor for organic aerosol (∼15%), while the predominant source of uncertainty in the calculated absorption is the refractive index of organic aerosol (28–60%), although we would expect the refractive index of black carbon to be important for aerosol with a higher black carbon fraction.

Aerosol scattering and absorption during the EUCAARI-LONGREX flights of the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146: can measurements and models agree?

Scattering and absorption by aerosol in anthropogenically perturbed air masses over Europe has been measured using instrumentation flown on the UK’s BAe-146-301 large Atmospheric Research Aircraft (ARA) operated by the Facility for Airborne Atmospheric Measurements (FAAM) on 14 flights during the EUCAARI-LONGREX campaign in May 2008. The geographical and temporal variations of the derived shortwave optical properties of aerosol are presented. Values of single scattering albedo of dry aerosol at 550 nm varied considerably from 0.86 to near unity, with a campaign average of 0.93 ± 0.03. Dry aerosol optical depths ranged from 0.030 ± 0.009 to 0.24 ± 0.07. An optical properties closure study comparing calculations from composition data and Mie scattering code with the measured properties is presented. Agreement to within measurement uncertainties of 30% can be achieved for both scattering and absorption,but the latter is shown to be sensitive to the refractive indices chosen for organic aerosols, and to a lesser extent black carbon, as well as being highly dependent on the accuracy of the absorption measurements. Agreement with the measured absorption can be achieved either if organic carbon is assumed to be weakly absorbing, or if the organic aerosol is purely scattering and the absorption measurement is an overestimate due to the presence of large amounts of organic carbon. Refractive indices could not be inferred conclusively due to this uncertainty, despite the enhancement in methodology compared to previous studies that derived from the use of the black carbon measurements. Hygroscopic growth curves derived from the wet nephelometer indicate moderate water uptake by the aerosol with a campaign mean f (RH) value (ratio in scattering) of 1.5 (range from 1.23 to 1.63) at 80% relative humidity. This value is qualitatively consistent with the major chemical components of the aerosol measured by the aerosol mass spectrometer, which are primarily mixed organics and nitrate and some sulphate.

Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment

A Canopy Height Profile (CHP) procedure presented in Harding et al. (2001) for large footprint LiDAR data was tested in a closed canopy environment as a way of extracting vertical foliage profiles from LiDAR raw-waveform. In this study, an adaptation of this method to small-footprint data has been shown, tested and validated in an Australian sparse canopy forest at plot- and site-level. Further, the methodology itself has been enhanced by implementing a dataset-adjusted reflectance ratio calculation according to Armston et al. (2013) in the processing chain, and tested against a fixed ratio of 0.5 estimated for the laser wavelength of 1550nm. As a by-product of the methodology, effective leaf area index (LAIe) estimates were derived and compared to hemispherical photography-derived values. To assess the influence of LiDAR aggregation area size on the estimates in a sparse canopy environment, LiDAR CHPs and LAIes were generated by aggregating waveforms to plot- and site-level footprints (plot/site-aggregated) as well as in 5m grids (grid-processed). LiDAR profiles were then compared to leaf biomass field profiles generated based on field tree measurements. The correlation between field and LiDAR profiles was very high, with a mean R2 of 0.75 at plot-level and 0.86 at site-level for 55 plots and the corresponding 11 sites. Gridding had almost no impact on the correlation between LiDAR and field profiles (only marginally improvement), nor did the dataset-adjusted reflectance ratio. However, gridding and the dataset-adjusted reflectance ratio were found to improve the correlation between raw-waveform LiDAR and hemispherical photography LAIe estimates, yielding the highest correlations of 0.61 at plot-level and of 0.83 at site-level. This proved the validity of the approach and superiority of dataset-adjusted reflectance ratio of Armston et al. (2013) over a fixed ratio of 0.5 for LAIe estimation, as well as showed the adequacy of small-footprint LiDAR data for LAIe estimation in discontinuous canopy forests.

Preliminary leaf area index estimates from airborne small footprint full-waveform LiDAR data

This study has compared preliminary estimates of effective leaf area index (LAI) derived from fish-eye lens photographs to those estimated from airborne full-waveform small-footprint LiDAR data for a forest dataset in Australia. The full-waveform data was decomposed and optimized using a trust-region-reflective algorithm to extract denser point clouds. LAI LiDAR estimates were derived in two ways (1) from the probability of discrete pulses reaching the ground without being intercepted (point method) and (2) from raw waveform canopy height profile processing adapted to small-footprint laser altimetry (waveform method) accounting for reflectance ratio between vegetation and ground. The best results, that matched hemispherical photography estimates, were achieved for the waveform method with a study area-adjusted reflectance ratio of 0.4 (RMSE of 0.15 and 0.03 at plot and site level, respectively). The point method generally overestimated, whereas the waveform method with an arbitrary reflectance ratio of 0.5 underestimated the fish-eye lens LAI estimates.

Airborne measurements of trace gases and aerosols over the London metropolitan region

The Emissions around the M25 motorway (EM25) campaign took place over the megacity of London in the United Kingdom in June 2009 with the aim of characterising trace gas and aerosol composition and properties entering and emitted from the urban region. It featured two mobile platforms, the UK BAe-146 Facility for Airborne Atmospheric Measurements (FAAM) research aircraft and a ground-based mobile lidar van, both travelling in circuits around London, roughly following the path of the M25 motorway circling the city. We present an overview of findings from the project, which took place during typical UK summertime pollution conditions. Emission ratios of volatile organic compounds (VOCs) to acetylene and carbon monoxide emitted from the London region were consistent with measurements in and downwind of other large urban areas and indicated traffic and associated fuel evaporation were major sources. Sub-micron aerosol composition was dominated by secondary species including sulphate (24% of sub-micron mass in the London plume and 29% in the non-plume regional aerosol), nitrate (24% plume; 20% regional) and organic aerosol (29% plume; 31% regional). The primary sub-micron aerosol emissions from London were minor compared to the larger regional background, with only limited increases in aerosol mass in the urban plume compared to the background (~12% mass increase on average). Black carbon mass was the major exception and more than doubled in the urban plume, leading to a decrease in the single scattering albedo from 0.91 in the regional aerosol to 0.86 in the London plume, on average. Our observations indicated that regional aerosol plays a major role on aerosol concentrations around London, at least during typical summertime conditions, meaning future efforts to reduce PM levels in London must account for regional as well as local aerosol sources.

Benchmarking 2D hydraulic models for urban flooding

This paper describes benchmark testing of six two-dimensional (2D) hydraulic models (DIVAST, DIVASTTVD, TUFLOW, JFLOW, TRENT and LISFLOOD-FP) in terms of their ability to simulate surface flows in a densely urbanised area. The models are applied to a 1·0 km × 0·4 km urban catchment within the city of Glasgow, Scotland, UK, and are used to simulate a flood event that occurred at this site on 30 July 2002. An identical numerical grid describing the underlying topography is constructed for each model, using a combination of airborne laser altimetry (LiDAR) fused with digital map data, and used to run a benchmark simulation. Two numerical experiments were then conducted to test the response of each model to topographic error and uncertainty over friction parameterisation. While all the models tested produce plausible results, subtle differences between particular groups of codes give considerable insight into both the practice and science of urban hydraulic modelling. In particular, the results show that the terrain data available from modern LiDAR systems are sufficiently accurate and resolved for simulating urban flows, but such data need to be fused with digital map data of building topology and land use to gain maximum benefit from the information contained therein. When such terrain data are available, uncertainty in friction parameters becomes a more dominant factor than topographic error for typical problems. The simulations also show that flows in urban environments are characterised by numerous transitions to supercritical flow and numerical shocks. However, the effects of these are localised and they do not appear to affect overall wave propagation. In contrast, inertia terms are shown to be important in this particular case, but the specific characteristics of the test site may mean that this does not hold more generally.