Modifications to the Effective Sample Area in Data Acquired by 2-Dimensional Video Disdrometers

2021 ◽  
Author(s):  
Michael L. Larsen ◽  
Christopher K. Blouin
Keyword(s):  
Careful Analysis ◽  
Equivalent Diameter ◽  
Sampling Area ◽  
Fall Velocity ◽  
Sample Area ◽  
Fixed Sample ◽  
Data Record ◽  
Ground Validation ◽  
Time Fall ◽  
Effective Sampling Area

<p>The 2-Dimensional Video Disdrometer (manufactured by Joanneum Research) is an instrument widely used for ground validation and precipitation microphysics studies. This instrument is capable of reporting back multiple properties of each detected hydrometeor; fields in the data record include arrival time, fall velocity, oblateness, mass-weighted equivalent diameter, detection position, and estimated detector sample area for each detected drop.</p><p>The last of these variables is necessary for using the data record to reliably estimate the instantaneous rain rate and total accumulations; it varies from detected drop to detected drop because a detected hydrometer must be fully enclosed within a fixed sample area to be successfully characterized by the instrument; this means that larger droplets have a smaller region that their centers can fall through and still be accurately measured. Careful analysis reveals that improvements can be made to the manufacturer’s calculation of this drop-dependent effective sample area.</p><p>These improvements are related to four key observations. (1) Due to the optical geometry of the instrument, not every pixel comprising the detection area has the same size. (2) The manufacturer’s algorithm makes some sub-optimal corrections for accounting for the detection area boundary. (3) The assumed extent of the full detection area field-of-view has been found to be slightly inaccurate. (4) There is a recently found anomaly that intermittently renders part of the detection area insensitive to reliable drop detection.</p><p>Here, we present a review of these observations, outline the structure of a simple post-processing algorithm developed to adjust the effective sampling area for each drop, and present results quantifying the overall impact on precipitation accumulations for a data record incorporating over 200 million detected raindrops.</p>

scholarly journals Error in the Sampling Area of an Optical Disdrometer: Consequences in Computing Rain Variables

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
R. Fraile ◽  
A. Castro ◽  
M. Fernández-Raga ◽  
C. Palencia ◽  
A. I. Calvo
Keyword(s):  
Rainfall Intensity ◽  
Rain Event ◽  
Rain Intensity ◽  
Sampling Area ◽  
The Real ◽  
Efficient Sampling ◽  
Real Value ◽  
Effective Sampling Area ◽  
Reflectivity Factor

The aim of this study is to improve the estimation of the characteristic uncertainties of optic disdrometers in an attempt to calculate the efficient sampling area according to the size of the drop and to study how this influences the computation of other parameters, taking into account that the real sampling area is always smaller than the nominal area. For large raindrops (a little over 6 mm), the effective sampling area may be half the area indicated by the manufacturer. The error committed in the sampling area is propagated to all the variables depending on this surface, such as the rain intensity and the reflectivity factor. Both variables tend to underestimate the real value if the sampling area is not corrected. For example, the rainfall intensity errors may be up to 50% for large drops, those slightly larger than 6 mm. The same occurs with reflectivity values, which may be up to twice the reflectivity calculated using the uncorrected constant sampling area. TheZ-Rrelationships appear to have little dependence on the sampling area, because both variables depend on it the same way. These results were obtained by studying one particular rain event that occurred on April 16, 2006.

Estimating population density of the Formosan subterranean termite, Coptotermes formosanus(Isoptera: Rhinotermitidae) using the effective sampling area of in-ground monitoring stations

2004 ◽  
Vol 94 (1) ◽  
pp. 47-53 ◽  
Author(s):  
H. Puche ◽  
N.-Y. Su
Keyword(s):  
Population Density ◽  
Coptotermes Formosanus ◽  
Subterranean Termite ◽  
Broward County ◽  
Sampling Area ◽  
Release Point ◽  
Factors Influencing ◽  
Average Proportion ◽  
Ground Monitoring ◽  
Effective Sampling Area

AbstractThe effective sampling area of a monitoring station, α, was calculated for several Coptotermes formosanus Shiraki colonies in Broward County, Florida, USA. A simple mark–recapture protocol provided data on termite station catch within a foraging range of a colony. Average recapture probability was 0.005 close to the releae point (< 5 m) and declined to 0.0008 at a distance of 51 to 60 m. The relation between the log % termites recaptured was fitted with log distance, to determine P(x), the average proportion of captured termites that started at distance x from the release point. The effective sampling area was estimated by using P(x) and the equation, α 2 π∫{ x P(x)} dx. Integrating this equation, an average estimate α that ranged from 0.607 to 14.5 m2 was obtained. Factors influencing the variation of α among the colonies are discussed. The effective sampling area estimated should be taken as a reliable estimator that translates subterranean termite catches into termite population density.

Repetitive rates of harp seal underwater vocalizations

1987 ◽  
Vol 65 (8) ◽  
pp. 2119-2120 ◽  
Author(s):  
J. M. Terhune ◽  
G. MacGowan ◽  
L. Underhill ◽  
K. Ronald
Keyword(s):  
Harp Seal ◽  
Level Control ◽  
Sampling Area ◽  
Significant Relationships ◽  
Phoca Groenlandica ◽  
Breeding Herd ◽  
Sound Pulses ◽  
Effective Sampling Area ◽  
Automatic Level

Underwater recordings of harp seal (Phoca groenlandica) vocalizations, obtained within the breeding herd during March, were examined with respect to calling rate and repetition of calls. Vocalizations typically overlapped one another. Calling rates ranged from 32 to 88 calls/min. Repetition rates averaged between 1.9 and 4.7 sound pulses/call (maximum repetition 24 times). Approximately 30% of the calls were not repeated and 40% were repeated twice. We found no significant relationships between calling rates and repetition rates. There were no variations in these factors throughout the day or month. An automatic level control on the recorder and the overlapping of the calls may have compromised the counts by altering the effective sampling area. The use of vocalization indexes in association with population estimations may be possible only when calls do not overlap.

scholarly journals Effective sampling area is a major driver of power to detect long‐term trends in multispecies occupancy monitoring

Ecosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
Author(s):  
Jody M. Tucker ◽  
Katie M. Moriarty ◽  
Martha M. Ellis ◽  
Jessie D. Golding
Keyword(s):  
Sampling Area ◽  
Occupancy Monitoring ◽  
Long Term Trends ◽  
Effective Sampling Area

scholarly journals Articulating and Stationary PARSIVEL Disdrometer Measurements in Conditions with Strong Winds and Heavy Rainfall

2013 ◽  
Vol 30 (9) ◽  
pp. 2063-2080 ◽  
Author(s):  
Katja Friedrich ◽  
Stephanie Higgins ◽  
Forrest J. Masters ◽  
Carlos R. Lopez
Keyword(s):  
Particle Size ◽  
Quality Control ◽  
Wind Speed ◽  
Number Concentration ◽  
High Wind ◽  
Sampling Area ◽  
Fall Velocity ◽  
Wind Speeds ◽  
Strong Winds

Abstract The influence of strong winds on the quality of optical Particle Size Velocity (PARSIVEL) disdrometer measurements is examined with data from Hurricane Ike in 2008 and from convective thunderstorms observed during the second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2) in 2010. This study investigates an artifact in particle size distribution (PSD) measurements that has been observed independently by six stationary PARSIVEL disdrometers. The artifact is characterized by a large number concentration of raindrops with large diameters (&gt;5 mm) and unrealistic fall velocities (&lt;1 m s−1). It is correlated with high wind speeds and is consistently observed by stationary disdrometers but is not observed by articulating disdrometers (instruments whose sampling area is rotated into the wind). The effects of strong winds are further examined with a tilting experiment, in which drops are dripped through the PARSIVEL sampling area while the instrument is tilted at various angles, suggesting that the artifact is caused by particles moving at an angle through the sampling area. Most of the time, this effect occurs when wind speed exceeds 20 m s−1, although it was also observed when wind speed was as low as 10 m s−1. An alternative quality control is tested in which raindrops are removed when their diameters exceed 8 mm and they divert from the fall velocity–diameter relationship. While the quality control does provide more realistic reflectivity values for the stationary disdrometers in strong winds, the number concentration is reduced compared to the observations with an articulating disdrometer.

Development of an Oropharyngeal Swab Assembly

2020 ◽  
Author(s):  
Chengyang Peng ◽  
Tao Shen
Keyword(s):  
Clinical Specimen ◽  
Disease Diagnosis ◽  
Direct Visualization ◽  
Sampling Area ◽  
Specimen Collection ◽  
Training Requirement ◽  
Oropharyngeal Swab ◽  
Effective Sampling Area ◽  
Swab Specimen

Abstract Oropharyngeal (OP) swabbing is a clinical specimen collection method to diagnose the presence of viral infection in the respiratory tract. During the Covid-19 pandemic, OP swab sampling plays an important role in the disease diagnosis. With its advantages in direct visualization of the swab site and less training requirement on medical professionals, OP swab is massively used for COVID-19 specimen collection in many countries. However, patients may demonstrate less tolerance for the OP swabbing by gagging or closing their mouths, which puts the swab tip in contact with the oral palate or tongue and results in defective sampling. Gagging and other involuntary reactions increase the risk to medical workers who are in direct contact with the patients. To solve these issues, this research presents a novel OP swab assembly which can assist adult patients to collect OP swab specimen by themselves or facilitate adults to collect specimens for their children or disable family members. The OP swab assembly has features to mitigate discomforts in the swab procedures as so to reduce involuntary reactions, minimizing specimen contamination. It also has features to keep the mouth open and constrain the motion of the swab tip in the effective sampling area, furtherly ensuring the high quality of the specimen. Experiments were conducted on a standard adult human skull mannequin by using the presented OP swab assembly. The results demonstrated the feasibility and effectiveness of self-collection for OP swabs using the presented assembly and method.

Analysis of Dark-Field Images of Disordered Materials

1972 ◽  
Vol 30 ◽  
pp. 560-561
Author(s):  
J. M. Cowley
Keyword(s):  
Amorphous Materials ◽  
Careful Analysis ◽  
Dark Field ◽  
Minimum Diameter ◽  
Statistical Fluctuations ◽  
Bright Spots ◽  
Sufficient Detail ◽  
Random Arrangement ◽  
Diffraction Patterns ◽  
Imaging Conditions

Recently a number of authors have reported detail in dark-field images obtained from diffuse-scattering regions of electron diffraction patterns. Bright spots in images from short-range order diffuse peaks of disordered binary alloys have been interpreted as evidence for the existence of microdomains of ordered lattice or of segragated clusters of one component. Spotty contrast in dark field images of near-amorphous materials has been interpreted as evidence for the existense of microcrystals. Without a careful analysis of the imaging conditions such conclusions may be invalid. Usually the conditions of the experiment have not been specified in sufficient detail to allow evaluation of the conclusions.Elementary considerations show that even for a completely random arrangement of atoms the statistical fluctuations of density will give a spotty contrast with spots of minimum diameter determined by the dark field aperture size and other factors influencing the minimum resolvable distance under darkfield imaging conditions, including fluctuations and drift over long exposure times (resolution usually 10Å or more).

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