A look at profiler performance

Since about 1974, Doppler radars operating in UHF and VHF ranges have been used increasingly to study atmospheric winds. Historically, large systems capable of obtaining data from high altitudes have focused attention on the mesosphere and stratosphere, rather than on the troposphere wherein abides most of the weather considered by most meteorologists. Research address some questions the meteorologist must logically ask first, viz., what is the actual performance capability of these systems, how accurate is the wind data of interest to meteorologists, and from what altitudes in the troposphere are the data reliably obtained

Analysis of airborne Doppler lidar, Doppler radar and tall tower measurements of atmospheric flows in quiescent and stormy weather

The first experiment to combine airborne Doppler Lidar and ground-based dual Doppler Radar measurements of wind to detail the lower tropospheric flows in quiescent and stormy weather was conducted in central Oklahoma during four days in June-July 1981. Data from these unique remote sensing instruments, coupled with data from conventional in-situ facilities, i.e., 500-m meteorological tower, rawinsonde, and surface based sensors, were analyzed to enhance understanding of wind, waves and turbulence. The purposes of the study were to: (1) compare winds mapped by ground-based dual Doppler radars, airborne Doppler lidar, and anemometers on a tower; (2) compare measured atmospheric boundary layer flow with flows predicted by theoretical models; (3) investigate the kinematic structure of air mass boundaries that precede the development of severe storms; and (4) study the kinematic structure of thunderstorm phenomena (downdrafts, gust fronts, etc.) that produce wind shear and turbulence hazardous to aircraft operations. The report consists of three parts: Part 1, Intercomparison of Wind Data from Airborne Lidar, Ground-Based Radars and Instrumented 444 m Tower; Part 2, The Structure of the Convective Atmospheric Boundary Layer as Revealed by Lidar and Doppler Radars; and Part 3, Doppler Lidar Observations in Thunderstorm Environments

Supervised Domain Adaptation using Graph Embedding

Getting deep convolutional neural networks to perform well requires a large amount of training data. When the available labelled data is small, it is often beneficial to use transfer learning to leverage a related larger dataset (source) in order to improve the performance on the small dataset (target). Among the transfer learning approaches, domain adaptation methods assume that distributions between the two domains are shifted and attempt to realign them. In this paper, we consider the domain adaptation problem from the perspective of dimensionality reduction and propose a generic framework based on graph embedding. Instead of solving the generalised eigenvalue problem, we formulate the graph-preserving criterion as a loss in the neural network and learn a domain-invariant feature transformation in an end-to-end fashion. We show that the proposed approach leads to a powerful Domain Adaptation framework; a simple LDA-inspired instantiation of the framework leads to state-of-the-art performance on two of the most widely used Domain Adaptation benchmarks, Office31 and MNIST to USPS datasets.Comment: 7 pages, 3 figures, 3 table

Environmental heterogeneity has a weak effect on diversity during community assembly in tallgrass prairie

Citation: Baer, S. G., Blair, J. M., & Collins, S. L. (2016). Environmental heterogeneity has a weak effect on diversity during community assembly in tallgrass prairie. Ecological Monographs, 86(1), 94-106. doi:10.1890/15-0888.1Understanding what constrains the persistence of species in communities is at the heart of community assembly theory and its application to conserving and enhancing biodiversity. The "environmental heterogeneity hypothesis" predicts greater species coexistence in habitats with greater resource variability. In the context of community assembly, environmental heterogeneity may influence the variety and strength of abiotic conditions and competitive interactions (environmental filters) to affect the relative abundance of species and biodiversity. We manipulated key resources that influence plant diversity in tallgrass prairie (i.e., soil depth and nitrogen availability) to increase environmental heterogeneity prior to sowing native prairie species into a former agricultural field. We compared variability in nutrient availability, aboveground annual net primary productivity (ANPP), and the composition of species between replicate plots containing soil heterogeneity manipulations and plots with no resource manipulations (n = 4 per treatment) during the first 15 yr of community assembly as a test of the "environmental heterogeneity hypothesis." The manipulations increased environmental heterogeneity, measured as the coefficient of variation in NO3-N availability and ANPP. Plant diversity, however, was similar and decayed exponentially and indiscriminately over time between the heterogeneity treatments. Species richness declined linearly over time in both heterogeneity treatments, but richness was higher in the more heterogeneous soil 2 yr following a second propagule addition 8 yr after the initial sowing. As a result, there was a lower rate of species loss over time in the more heterogeneous soil (0.60 species yr(-1)) relative to the control soil (0.96 species yr(-1)). Communities in each treatment exhibited strong convergence over time resulting from a shift in dominant species across all treatments and a gradual increase in the clonal C-4 grass, Andropogon gerardii. We attribute the weak effect of heterogeneity on diversity to increasing dominance of a clonal species, which decreased the scale of soil treatments relative to plant size, dispersal limitation, and absence of a key driver (grazing) known to increase plant diversity under a frequent fire regime. Thus, steering community assembly to attain high biodiversity may depend more on manipulating processes that reduce dominance and facilitate the arrival of new species than promoting environmental heterogeneity

Characterization and cooled storage of semen from corn snakes (Elaphe guttata)

The phylogenetic order Squamata has many representatives that could benefit from the use of semen preservation as a tool for assisting conservation. To date, few studies have been made evaluating the potential for collecting and preserving semen from snakes. The objectives of this study were to characterize semen parameters of the corn snake (Elaphe guttata), including appearance, volume, concentration, sperm motility, and sperm morphology, and to determine the longevity of corn snake sperm motility stored at 4 degrees C. Single semen samples were collected from 22 adult corn snakes. The appearance of the corn snake semen was generally cloudy, and the color was white to tan. Corn snake spermatozoa initially exhibited a median motility of 92.5%. Corn snakes were found to produce small-volume ejaculates (median 0.01 ml). However, the overall concentration of the snake ejaculate was high (chi = 852 x 10(6) +/- 585 x 10(6) spermatozoa/ml). Morphologically, a mean of 75.7 +/- 9.3% of the sperm cells in an ejaculate were normal. Snake ejaculate with a white appearance had significantly higher sperm concentrations (chi = 1,859 x 10(6) +/- 1,008 x 106 sperm cells/ml; F = 15.74, P = 0.001) than tan ejaculates (chi = 601 x 10(6) +/- 439 x 106 sperm cells/ml). Sperm motility decreased significantly in samples that were stored at 4 degrees C for greater than 48 hr in a refrigerator or Equitainer I. This is the first study to characterize semen volume, appearance, and concentration; sperm motility; and sperm morphology in captive corn snakes. The information derived from this study can be used to develop a model for a collection, cooled storage, and shipping program for semen from endangered or threatened captive and wild snakes