Identification of Optimal Satellite Compositing Length Using GLOBE Budburst Measurements

Phenology, the study of recurring biological cycles and their connection to climate, is a critical and growing field of global change research. In particular, scientists now recognize that regular satellite monitoring of the timing and length of the terrestrial growing season is a valuable metric of biospheric responses to short- and long-term climate variability. While many methodologies exist with which to detect growing season dynamics, most have a poorly understood relationship to actual ground vegetation conditions. GLOBE schools, through participation in the budburst protocols, are helping to bridge this gap between satellite observations and ground conditions. In this research we show how GLOBE budburst data can be used to select the optimal satellite compositing length (a technique used to reduce cloud, snow, and atmospheric contamination). One- and two-week compositing lengths produced similar results, both of which were superior to monthly compositing. The longer compositing length, contrary to popular remote sensing lore, tended to predict an earlier initiation of growth due to removal of inflection points in the satellite greenness time series. Overall, the GLOBE budburst data were extremely useful but also contained several troubling artifacts probably relating to infrequent observation, errors in date reporting, and use of exotic species

Fluctuating volume-current formulation of electromagnetic fluctuations in inhomogeneous media: incandecence and luminescence in arbitrary geometries

We describe a fluctuating volume--current formulation of electromagnetic fluctuations that extends our recent work on heat exchange and Casimir interactions between arbitrarily shaped homogeneous bodies [Phys. Rev. B. 88, 054305] to situations involving incandescence and luminescence problems, including thermal radiation, heat transfer, Casimir forces, spontaneous emission, fluorescence, and Raman scattering, in inhomogeneous media. Unlike previous scattering formulations based on field and/or surface unknowns, our work exploits powerful techniques from the volume--integral equation (VIE) method, in which electromagnetic scattering is described in terms of volumetric, current unknowns throughout the bodies. The resulting trace formulas (boxed equations) involve products of well-studied VIE matrices and describe power and momentum transfer between objects with spatially varying material properties and fluctuation characteristics. We demonstrate that thanks to the low-rank properties of the associatedmatrices, these formulas are susceptible to fast-trace computations based on iterative methods, making practical calculations tractable. We apply our techniques to study thermal radiation, heat transfer, and fluorescence in complicated geometries, checking our method against established techniques best suited for homogeneous bodies as well as applying it to obtain predictions of radiation from complex bodies with spatially varying permittivities and/or temperature profiles

BIOME-BGC simulations of stand hydrologic process for BOREAS

BIOME-BGC is a general ecosystem model designed to simulate hydrologic and biogeochemical processes across multiple scales. The objectives of this investigation were to compare BIOME-BGC estimates of hydrologic processes with observed data for different boreal forest stands and investigate factors that control simulated water fluxes. Model results explained 62 and 98% of the respective variances in observed daily evapotranspiration and soil water; simulations of the onset of spring thaw and the dates of snowpack disappearance and accumulation also generally tracked observations. Differences between observed and simulated evapotranspiration were attributed to model assumptions of constant, growing season, overstory leaf areas that did not account for phenological changes and understory effects on stand daily water fluxes. Vapor pressure deficit and solar radiation accounted for 58–74% of the variances in simulated daily evapotranspiration during the growing season, though low air temperature and photosynthetic light levels were found to be the major limiting factors regulating simulated canopy conductances to water vapor. Humidity and soil moisture were generally not low enough to induce physiological water stress in black spruce stands, though low soil water potentials resulted in approximate 34% reductions in simulated mean daily canopy conductances for aspen and jack pine stands. The sensitivity of evapotranspiration simulations to leaf area (LAI) was less than expected because of opposing responses of transpiration and evaporation to LAI. The results of this investigation identify several components within boreal forest stands that are sensitive to climate change

A continental phenology model for monitoring vegetation responses to interannual climatic variability

Regional phenology is important in ecosystem simulation models and coupled biosphere/atmosphere models. In the continental United States, the timing of the onset of greenness in the spring (leaf expansion, grass green-up) and offset of greenness in the fall (leaf abscission, cessation of height growth, grass brown-off) are strongly influenced by meteorological and climatological conditions. We developed predictive phenology models based on traditional phenology research using commonly available meteorological and climatological data. Predictions were compared with satellite phenology observations at numerous 20 km × 20 km contiguous landcover sites. Onset mean absolute error was 7.2 days in the deciduous broadleaf forest (DBF) biome and 6.1 days in the grassland biome. Offset mean absolute error was 5.3 days in the DBF biome and 6.3 days in the grassland biome. Maximum expected errors at a 95% probability level ranged from 10 to 14 days. Onset was strongly associated with temperature summations in both grassland and DBF biomes; DBF offset was best predicted with a photoperiod function, while grassland offset required a combination of precipitation and temperature controls. A long-term regional test of the DBF onset model captured field-measured interannual variability trends in lilac phenology. Continental application of the phenology models for 1990–1992 revealed extensive interannual variability in onset and offset. Median continental growing season length ranged from a low of 129 days in 1991 to a high of 146 days in 1992. Potential uses of the models include regulation of the timing and length of the growing season in large-scale biogeochemical models and monitoring vegetation response to interannual climatic variability

Real-Time Detection of Optical Transients with RAPTOR

Fast variability of optical objects is an interesting though poorly explored subject in modern astronomy. Real-time data processing and identification of transient celestial events in the images is very important for such study as it allows rapid follow-up with more sensitive instruments. We discuss an approach which we have developed for the RAPTOR project, a pioneering closed-loop system combining real-time transient detection with rapid follow-up. RAPTOR's data processing pipeline is able to identify and localize an optical transient within seconds after the observation. The testing we performed so far have been confirming the effectiveness of our method for the optical transient detection. The software pipeline we have developed for RAPTOR can easily be applied to the data from other experiments.Comment: 10 pages, 7 figures, to appear in SPIE proceedings vol. 484

Spectral Function for the S=1 Heisenberg Antiferromagetic Chain

We study the spectral function, $S(k,\omega)$ for the spin-1, one dimensional antiferromagnetic chain using a time-dependent density matrix renormalizaton group (DMRG) numerical method. We develop methods for extrapolating the time dependent correlation functions to larger times in order to enhance the frequency resolution. The resulting spectral functions are impressively precise and accurate. Our results confirm many qualitative expectations from non-linear $\sigma$ model methods and test them quantitatively. The critical wave-vector at which the single particle excitation emerges from the 2-particle continuum is estimated to be $0.23\pi-0.24\pi$.Comment: 12 pages, 19 fig

Parameterization and Sensitivity Analysis of the BIOME-BGC Terrestrial Ecosystem model: Net Primary Production Controls

Ecosystem simulation models use descriptive input parameters to establish the physiology, biochemistry, structure, and allocation patterns of vegetation functional types, or biomes. For single-stand simulations it is possible to measure required data, but as spatial resolution increases, so too does data unavailability. Generalized biome parameterizations are then required. Undocumented parameter selection and unknown model sensitivity to parameter variation for larger-resolution simulations are currently the major limitations to global and regional modeling. The authors present documented input parameters for a process-based ecosystem simulation model, BIOME–BGC, for major natural temperate biomes. Parameter groups include the following: turnover and mortality; allocation; carbon to nitrogen ratios (C:N); the percent of plant material in labile, cellulose, and lignin pools; leaf morphology; leaf conductance rates and limitations; canopy water interception and light extinction; and the percent of leaf nitrogen in Rubisco (ribulose bisphosphate-1,5-carboxylase/oxygenase) (PLNR). Using climatic and site description data from the Vegetation/Ecosystem Modeling and Analysis Project, the sensitivity of predicted annual net primary production (NPP) to variations in parameter level of ± 20% of the mean value was tested. For parameters exhibiting a strong control on NPP, a factorial analysis was conducted to test for interaction effects. All biomes were affected by variation in leaf and fine root C:N. Woody biomes were additionally strongly controlled by PLNR, maximum stomatal conductance, and specific leaf area while nonwoody biomes were sensitive to fire mortality and litter quality. None of the critical parameters demonstrated strong interaction effects. An alternative parameterization scheme is presented to better represent the spatial variability in several of these critical parameters. Patterns of general ecological function drawn from the sensitivity analysis are discussed

3-PG Productivity Modeling of Regenerating Amazon Forests: Climate Sensitivity and Comparison with MODIS-Derived NPP

Potential forest growth predicted by the Physiological Principles in Predicting Growth (3-PG) model was compared for forest and deforested areas in the Legal Amazon to assess potential differing regeneration associated with climate. Historical deforestation and regeneration have occurred in environmentally marginal areas that influence regional carbon sequestration estimates. Effects of El Niño–induced drought further reduce simulated production by decreasing soil water availability in areas with shallow soils and high transpiration potential. The model was calibrated through comparison of literature biomass and with satellite-based estimates. Net primary productivity (NPP) for mature Amazonian forests from the 3-PG model was positively correlated (r 2 = 0.77) with a Moderate Resolution Imaging Spectroradiometer (MODIS)-derived algorithm, though with some bias. Annual total NPP for the study area using a 1961–90 average climatology was 4.6 Pg C yr−1, which decreased to 4.2 Pg C yr−1 when simulated with climate from the severe 1997/98 El Niño event. From a regional analysis, results showed that biomass accumulation is almost entirely controlled by the availability of soil water. Also, areas currently forested in the eastern Amazon are more sensitive to extreme El Niño–induced drought than southern areas with the greatest deforestation extent

A Group-Based Yule Model for Bipartite Author-Paper Networks

This paper presents a novel model for author-paper networks, which is based on the assumption that authors are organized into groups and that, for each research topic, the number of papers published by a group is based on a success-breeds-success model. Collaboration between groups is modeled as random invitations from a group to an outside member. To analyze the model, a number of different metrics that can be obtained in author-paper networks were extracted. A simulation example shows that this model can effectively mimic the behavior of a real-world author-paper network, extracted from a collection of 900 journal papers in the field of complex networks.Comment: 13 pages (preprint format), 7 figure