scholarly journals Theoretical framework for estimating snow distribution through point measurements

2015 ◽  
Vol 9 (1) ◽  
pp. 1-44
Author(s):  
E. Trujillo ◽  
M. Lehning
Keyword(s):  
Snow Depth ◽  
Survey Design ◽  
Spatial Location ◽  
Theoretical Framework ◽  
Statistical Properties ◽  
Spatial Covariance ◽  
Sample Mean ◽  
Snow Properties ◽  
Survey Designs

Abstract. In recent years, marked improvements in our knowledge of the statistical properties of the spatial distribution of snow properties have been achieved thanks to improvements in measuring technologies (e.g. LIDAR, TLS, and GPR). Despite of this, objective and quantitative frameworks for the evaluation of errors and extrapolations in snow measurements have been lacking. Here, we present a theoretical framework for quantitative evaluations of the uncertainty of point measurements of snow depth when used to represent the average depth over a profile section or an area. The error is defined as the expected value of the squared difference between the real mean of the profile/field and the sample mean from a limited number of measurements. The model is tested for one and two dimensional survey designs that range from a single measurement to an increasing number of regularly-spaced measurements. Using high-resolution (~1 m) LIDAR snow depths at two locations in Colorado, we show that the sample errors follow the theoretical behavior. Furthermore, we show how the determination of the spatial location of the measurements can be reduced to an optimization problem for the case of the predefined number of measurements, or to the designation of an acceptable uncertainty level to determine the total number of regularly-spaced measurements required to achieve such error. On this basis, a series of figures are presented that can be used to aid in the determination of the survey design under the conditions described, and under the assumption of prior knowledge of the spatial covariance/correlation properties. With this methodology, better objective survey designs can be accomplished, tailored to the specific applications for which the measurements are going to be used. The theoretical framework can be extended to other spatially distributed snow variables (e.g. SWE) whose statistical properties are comparable to those of snow depth.

scholarly journals Theoretical analysis of errors when estimating snow distribution through point measurements

2015 ◽  
Vol 9 (3) ◽  
pp. 1249-1264 ◽  
Author(s):  
E. Trujillo ◽  
M. Lehning
Keyword(s):  
Snow Depth ◽  
Laser Scanning ◽  
Snow Water Equivalent ◽  
Survey Design ◽  
Spatial Location ◽  
Theoretical Framework ◽  
Statistical Properties ◽  
Spatial Covariance ◽  
Sample Mean ◽  
Survey Designs

Abstract. In recent years, marked improvements in our knowledge of the statistical properties of the spatial distribution of snow properties have been achieved thanks to improvements in measuring technologies (e.g., LIDAR, terrestrial laser scanning (TLS), and ground-penetrating radar (GPR)). Despite this, objective and quantitative frameworks for the evaluation of errors in snow measurements have been lacking. Here, we present a theoretical framework for quantitative evaluations of the uncertainty in average snow depth derived from point measurements over a profile section or an area. The error is defined as the expected value of the squared difference between the real mean of the profile/field and the sample mean from a limited number of measurements. The model is tested for one- and two-dimensional survey designs that range from a single measurement to an increasing number of regularly spaced measurements. Using high-resolution (~ 1 m) LIDAR snow depths at two locations in Colorado, we show that the sample errors follow the theoretical behavior. Furthermore, we show how the determination of the spatial location of the measurements can be reduced to an optimization problem for the case of the predefined number of measurements, or to the designation of an acceptable uncertainty level to determine the total number of regularly spaced measurements required to achieve such an error. On this basis, a series of figures are presented as an aid for snow survey design under the conditions described, and under the assumption of prior knowledge of the spatial covariance/correlation properties. With this methodology, better objective survey designs can be accomplished that are tailored to the specific applications for which the measurements are going to be used. The theoretical framework can be extended to other spatially distributed snow variables (e.g., SWE – snow water equivalent) whose statistical properties are comparable to those of snow depth.

scholarly journals Biofilm Localization in the Vertical Wall of Shaking 96-Well Plates

Scientifica ◽  
2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Luciana C. Gomes ◽  
Joana M. R. Moreira ◽  
Manuel Simões ◽  
Luís F. Melo ◽  
Filipe J. Mergulhão
Keyword(s):  
Low Cost ◽  
Vertical Wall ◽  
Spatial Location ◽  
Strain Rates ◽  
Microtiter Plates ◽  
Equipment Availability ◽  
Cell Accumulation ◽  
Electron Microscopes ◽  
Air Liquid Interface

Microtiter plates with 96 wells are being increasingly used for biofilm studies due to their high throughput, low cost, easy handling, and easy application of several analytical methods to evaluate different biofilm parameters. These methods provide bulk information about the biofilm formed in each well but lack in detail, namely, regarding the spatial location of the biofilms. This location can be obtained by microscopy observation using optical and electron microscopes, but these techniques have lower throughput and higher cost and are subjected to equipment availability. This work describes a differential crystal violet (CV) staining method that enabled the determination of the spatial location ofEscherichia colibiofilms formed in the vertical wall of shaking 96-well plates. It was shown that the biofilms were unevenly distributed on the wall with denser cell accumulation near the air-liquid interface. The results were corroborated by scanning electron microscopy and a correlation was found between biofilm accumulation and the wall shear strain rates determined by computational fluid dynamics. The developed method is quicker and less expensive and has a higher throughput than the existing methods available for spatial location of biofilms in microtiter plates.

Experimental Determination of Statistical Properties of Two-Phase Turbulent Motion

1960 ◽  
Vol 82 (3) ◽  
pp. 609-621 ◽  
Author(s):  
S. L. Soo ◽  
H. K. Ihrig ◽  
A. F. El Kouh
Keyword(s):  
Gas Phase ◽  
Tracer Diffusion ◽  
Statistical Properties ◽  
Solid Particles ◽  
Turbulent Motion ◽  
Two Phase ◽  
Gaseous State ◽  
Diffusion Technique ◽  
And Diffusion

Experimental methods for the determination of certain statistical properties of turbulent conveyance and diffusion of solid particles in a gaseous state are presented. Methods include a tracer-diffusion technique for the determination of gas-phase turbulent motion and a photo-optical technique for the determination of motion of solid particles. Results are discussed and compared with previous analytical results.

Spatiotemporal modelling for the annual egg production method of stock assessment using generalized additive models

1998 ◽  
Vol 55 (12) ◽  
pp. 2608-2621 ◽  
Author(s):  
N H Augustin ◽  
D L Borchers ◽  
E D Clarke ◽  
S T Buckland ◽  
M Walsh
Keyword(s):  
Environmental Variables ◽  
Egg Production ◽  
Survey Design ◽  
Stock Assessment ◽  
Generalized Additive Models ◽  
Production Method ◽  
Additive Models ◽  
Atlantic Mackerel ◽  
Egg Density ◽  
Survey Designs

Generalized additive models (GAMs) are used to model the spatiotemporal distribution of egg density as a function of locational and environmental variables. The main aim of using GAMs is to improve precision of egg abundance estimates needed for the annual egg production method. The application of GAMs requires a survey design with good coverage in space and time. If the only results available are from less optimal survey designs, they can be improved by using historical data for spawning boundaries. The method is applied to plankton egg survey data of Atlantic mackerel (Scomber scombrus) in 1995. The GAM-based method improves the precision of estimates substantially and is also useful in explaining complex space-time trends using environmental variables.

Critical snow density threshold for Dall’s sheep (Ovis dalli dalli)

2018 ◽  
Vol 96 (10) ◽  
pp. 1170-1177 ◽  
Author(s):  
Kelly J. Sivy ◽  
Anne W. Nolin ◽  
Christopher L. Cosgrove ◽  
Laura R. Prugh
Keyword(s):  
Snow Depth ◽  
Animal Movement ◽  
Population Declines ◽  
Snow Density ◽  
Energetic Costs ◽  
Snow Properties ◽  
Ovis Dalli ◽  
Snow Conditions ◽  
Dall’S Sheep ◽  
Density Threshold

Snow cover can significantly impact animal movement and energetics, yet few studies have investigated the link between physical properties of snow and energetic costs. Quantification of thresholds in snow properties that influence animal movement are needed to help address this knowledge gap. Recent population declines of Dall’s sheep (Ovis dalli dalli Nelson, 1884) could be due in part to changing snow conditions. We examined the effect of snow density, snow depth, and snow hardness on sinking depths of Dall’s sheep tracks encountered in Wrangell–St. Elias National Park and Preserve, Alaska. Snow depth was a poor predictor of sinking depths of sheep tracks (R2 = 0.02, p = 0.38), as was mean weighted hardness (R2 = 0.09, p = 0.07). Across competing models, top layer snow density (0–10 cm) and sheep age class were the best predictors of track sink depths (R2 = 0.58). Track sink depth decreased with increasing snow density, and the snowpack supported the mass of a sheep above a density threshold of 329 ± 18 kg/m3 (mean ± SE). This threshold could aid interpretation of winter movement and energetic costs by animals, thus improving our ability to predict consequences of changing snowpack conditions on wildlife.

scholarly journals Language recognition methods and Voynich Manuscript analysis

2021 ◽  
Author(s):  
Yurii Nikolaevich Orlov
Keyword(s):  
Internal Structure ◽  
Statistical Properties ◽  
Language Recognition ◽  
European Literature ◽  
Logarithmic Dependence

The statistical properties of letters frequencies in European literature texts are investigated. The determination of logarithmic dependence of letters sequence for one-languge and two-language texts are examined. The pare of languages are suggested for Voynich Manuscript. The internal structure of Manuscript is considered. The spectral portraits of two-letters distribution are constructed.

scholarly journals Validation of modeled snow properties in Afghanistan, Pakistan, and Tajikistan

2019 ◽  
Author(s):  
Edward H. Bair ◽  
Karl Rittger ◽  
Jawairia A. Ahmad ◽  
Doug Chabot
Keyword(s):  
Snow Depth ◽  
Snow Water Equivalent ◽  
Median Number ◽  
In Situ Measurements ◽  
Snow Properties ◽  
Wide Range ◽  
Spatial Estimates ◽  
Snow Water ◽  
Critical Layers

Abstract. Ice and snowmelt feed the Indus and Amu Darya rivers, yet there are limited in situ measurements of these resources. Previous work in the region has shown promise using snow water equivalent (SWE) reconstruction, which requires no in situ measurements, but validation has been a problem until recently when we were provided with daily manual snow depth measurements from Afghanistan, Tajikistan, and Pakistan by the Aga Khan Agency for Habitat (AKAH). For each station, accumulated precipitation and SWE were derived from snow depth using the SNOWPACK model. High-resolution (500 m) reconstructed SWE estimates from the ParBal model were then compared to the modeled SWE at the stations. The Alpine3D model was then used to create spatial estimates at 25 km to compare with estimates from other snow models. Additionally, the coupled SNOWPACK and Alpine3D system has the advantage of simulating snow profiles, which provide stability information. Following previous work, the median number of critical layers and percentage of facets across all of the pixels containing the AKAH stations was computed. For SWE at the point scale, the reconstructed estimates showed a bias of −42 mm (−19 %) at the peak. For the coarser spatial SWE estimates, the various models showed a wide range, with reconstruction being on the lower end. For stratigraphy, a heavily faceted snowpack is observed in both years, but 2018, a dry year, according to most of the models, showed more critical layers that persisted for a longer period.

Workspace Cusp Locations, and Simplified Workspace Boundary Equations for General RRR Regional Structures of Manipulators

1996 ◽  
Author(s):  
Peregrine E. J. Riley ◽  
Louis E. Torfason
Keyword(s):  
Complex Geometry ◽  
Spatial Location ◽  
Polynomial Equation ◽  
Toroidal Surface ◽  
General Complex ◽  
Cusp Points ◽  
Joint Variable ◽  
Boundary Equations ◽  
Workspace Boundary

Abstract General, complex geometry forms of RRR regional structures are often avoided due to the presence of inner boundaries within the workspace which tend to complicate robot guidance. Despite the added complexity, certain RRR geometries may have useful applications as they contain large workspace regions where four alternate configurations may be used to reach a given spatial location. Cusp points often appear on the workspace boundaries of general RRR regional structures, and determining their precise location may be useful for both design and guidance purposes. A twelfth degree polynomial equation in the outer joint variable is derived which defines the location of non-trivial cusps in the workspace. A new closed form workspace boundary equation is derived in the outer joint variable and x coordinate of the toroidal surface generated by rotation of the two outer revolutes. If the outer joint variable is incremented, a quadratic in x is formed at each step which enables a very efficient determination of the workspace boundaries while also providing the coordinates of the boundary on the toroidal surface.

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