A Type IIB Matrix Model via non-Abelian T-dualities

We construct a new solution of type IIB supergravity with eight supercharges by applying non-Abelian T-duality to the $AdS_5\times S^5$ solution, along the $SU(2)$ isometries in both the internal and Lorentz symmetries. The study of quantised charges and D-brane embeddings suggests a configuration of D1 and D3'-branes that polarise into concentric, spherical, D3 and D5-branes due to the Myers dielectric effect. We find that our solution is dual to a IIB matrix model with fuzzy sphere vacua characterised by partitions of the number of D1 and D3'-branes. We also study the solution obtained via (Abelian) T-dualities along the $S^1$ fiber angles inside the $S^3$'s of the $AdS_5\times S^5$ solution. In addition, we point out a precise relation between NATD and ATD solutions by considering a double scaling limit in the NATD solutions. In the particular case of the solutions obtained by a single (non-)Abelian T-duality inside the Lorentz symmetries of the $AdS_5\times S^5$ solution, we demonstrate that the double scaling limit provides a supergravity realisation of the relations between the vacua of the half-BPS theories studied by Lin and Maldacena.Comment: 20 pages, 1 figure, 1 tabl

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

Estimating Canopy Gap Fraction Using ICESat GLAS within Australian Forest Ecosystems

Spaceborne laser altimetry waveform estimates of canopy Gap Fraction (GF) vary withrespect to discrete return airborne equivalents due to their greater sensitivity to reflectance differencesbetween canopy and ground surfaces resulting from differences in footprint size, energy thresholding,noise characteristics and sampling geometry. Applying scaling factors to either the ground or canopyportions of waveforms has successfully circumvented this issue, but not at large scales. This studydevelops a method to scale spaceborne altimeter waveforms by identifying which remotely-sensedvegetation, terrain and environmental attributes are best suited to predicting scaling factors basedon an independent measure of importance. The most important attributes were identified as: soilphosphorus and nitrogen contents, vegetation height, MODIS vegetation continuous fields productand terrain slope. Unscaled and scaled estimates of GF are compared to corresponding ALS datafor all available data and an optimized subset, where the latter produced most encouraging results(R2 = 0.89, RMSE = 0.10). This methodology shows potential for successfully refining estimates ofGF at large scales and identifies the most suitable attributes for deriving appropriate scaling factors.Large-scale active sensor estimates of GF can establish a baseline from which future monitoringinvestigations can be initiated via upcoming Earth Observation missions

OzFlux data: Network integration from collection to curation

© Author(s) 2017. Measurement of the exchange of energy and mass between the surface and the atmospheric boundary-layer by the eddy covariance technique has undergone great change in the last 2 decades. Early studies of these exchanges were confined to brief field campaigns in carefully controlled conditions followed by months of data analysis. Current practice is to run tower-based eddy covariance systems continuously over several years due to the need for continuous monitoring as part of a global effort to develop local-, regional-, continental-and global-scale budgets of carbon, water and energy. Efficient methods of processing the increased quantities of data are needed to maximise the time available for analysis and interpretation. Standardised methods are needed to remove differences in data processing as possible contributors to observed spatial variability. Furthermore, public availability of these data sets assists with undertaking global research efforts. The OzFlux data path has been developed (i) to provide a standard set of quality control and post-processing tools across the network, thereby facilitating inter-site integration and spatial comparisons; (ii) to increase the time available to researchers for analysis and interpretation by reducing the time spent collecting and processing data; (iii) to propagate both data and metadata to the final product; and (iv) to facilitate the use of the OzFlux data by adopting a standard file format and making the data available from web-based portals. Discovery of the OzFlux data set is facilitated through incorporation in FLUXNET data syntheses and the publication of collection metadata via the RIF-CS format. This paper serves two purposes. The first is to describe the data sets, along with their quality control and post-processing, for the other papers of this Special Issue. The second is to provide an example of one solution to the data collection and curation challenges that are encountered by similar flux tower networks worldwide

Behavior of multitemporal and multisensor passive microwave indices in Southern Hemisphere ecosystems

©2014. American Geophysical Union. All Rights Reserved. This study focused on the time series analysis of passive microwave and optical satellite data collected from six Southern Hemisphere ecosystems in Australia and Argentina. The selected ecosystems represent a wide range of land cover types, including deciduous open forest, temperate forest, tropical and semiarid savannas, and grasslands. We used two microwave indices, the frequency index (FI) and polarization index (PI), to assess the relative contributions of soil and vegetation properties (moisture and structure) to the observations. Optical-based satellite vegetation products from the Moderate Resolution Imaging Spectroradiometer were also included to aid in the analysis. We studied the X and Ka bands of the Advanced Microwave Scanning Radiometer-EOS and Wind Satellite, resulting in up to four observations per day (1:30, 6:00, 13:30, and 18:00-h). Both the seasonal and hourly variations of each of the indices were examined. Environmental drivers (precipitation and temperature) and eddy covariance measurements (gross ecosystem productivity and latent energy) were also analyzed. It was found that in moderately dense forests, FI was dependent on canopy properties (leaf area index and vegetation moisture). In tropical woody savannas, a significant regression (R2) was found between FI and PI with precipitation (R2->-0.5) and soil moisture (R2->-0.6). In the areas of semiarid savanna and grassland ecosystems, FI variations found to be significantly related to soil moisture (R2->-0.7) and evapotranspiration (R2->-0.5), while PI varied with vegetation phenology. Significant differences (p-<-0.01) were found among FI values calculated at the four local times. Key Points Passive microwave indices can be used to estimate vegetation moisture Microwave observations were supported by flux data Passive microwave indices could be used to estimate evapotranspiratio

Intrinsic climate dependency of ecosystem light and water-use-efficiencies across Australian biomes

© 2014 IOP Publishing Ltd. The sensitivity of ecosystem gross primary production (GPP) to availability of water and photosynthetically active radiation (PAR) differs among biomes. Here we investigated variations of ecosystem light-use-efficiency (eLUE: GPP/PAR) and water-use-efficiency (eWUE: GPP/evapotranspiration) among seven Australian eddy covariance sites with differing annual precipitation, species composition and temperature. Changes to both eLUE and eWUE were primarily correlated with atmospheric vapor pressure deficit (VPD) at multiple temporal scales across biomes, with minor additional correlations observed with soil moisture and temperature. The effects of leaf area index on eLUE and eWUE were also relatively weak compared to VPD, indicating an intrinsic dependency of eLUE and eWUE on climate. Additionally, eLUE and eWUE were statistically different for biomes between summer and winter, except eWUE for savannas and the grassland. These findings will improve our understanding of how light- and water-use traits in Australian ecosystems may respond to climate change

MODIS vegetation products as proxies of photosynthetic potential along a gradient of meteorologically and biologically driven ecosystem productivity

© 2016 Author(s). A direct relationship between gross ecosystem productivity (GEP) estimated by the eddy covariance (EC) method and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices (VIs) has been observed in many temperate and tropical ecosystems. However, in Australian evergreen forests, and particularly sclerophyll and temperate woodlands, MODIS VIs do not capture seasonality of GEP. In this study, we re-evaluate the connection between satellite and flux tower data at four contrasting Australian ecosystems, through comparisons of GEP and four measures of photosynthetic potential, derived via parameterization of the light response curve: ecosystem light use efficiency (LUE), photosynthetic capacity (Pc), GEP at saturation (GEPsat), and quantum yield (α) with MODIS vegetation satellite products, including VIs, gross primary productivity (GPPMOD) leaf area index (LAIMOD), and fraction of photosynthetic active radiation (fPARMOD). We found that satellite-derived biophysical products constitute a measurement of ecosystem structure (e.g. leaf area index-quantity of leaves) and function (e.g. leaf level photosynthetic assimilation capacity-quality of leaves), rather than GEP. Our results show that in primarily meteorological-driven (e.g. photosynthetic active radiation, air temperature, and/or precipitation) and relatively aseasonal ecosystems (e.g. evergreen wet sclerophyll forests), there were no statistically significant relationships between GEP and satellite-derived measures of greenness. In contrast, for phenology-driven ecosystems (e.g. tropical savannas), changes in the vegetation status drove GEP, and tower-based measurements of photosynthetic activity were best represented by VIs. We observed the highest correlations between MODIS products and GEP in locations where key meteorological variables and vegetation phenology were synchronous (e.g. semi-arid Acacia woodlands) and low correlation at locations where they were asynchronous (e.g. Mediterranean ecosystems). However, we found a statistical significant relationship between the seasonal measures of photosynthetic potential (Pc and LUE) and VIs, where each ecosystem aligns along a continuum; we emphasize here that knowledge of the conditions in which flux tower measurements and VIs or other remote sensing products converge greatly advances our understanding of the mechanisms driving the carbon cycle (phenology and climate drivers) and provides an ecological basis for interpretation of satellite-derived measures of greenness