High resolution low-level liquid scintillation β-spectrometer

Small sample 14C dating is tested using conventional as well as high-resolution low-level liquid scintillation (LS) spectrometers. Contrasted are the results obtained dating ∼25, 125 and 250mg of elemental carbon in standard size counting vials (3mL) and 0.3mL teflon and quartz vials. It is demonstrated that the improved performance of the 0.3mL counting vials enables just adequate resolution of 25mg and very good resolution of 100mg carbon samples both at Modern and Old age limits when the determination is made in a high-resolution low-level LS spectrometer.

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Determination of low-level biogenic gasoline, jet fuel, and diesel in blends using the direct liquid scintillation counting method for 14C content

Fuel ◽

10.1016/j.fuel.2020.120084 ◽

2021 ◽

Vol 291 ◽

pp. 120084

Author(s):

Charles G. Doll ◽

Andrew E. Plymale ◽

Alan Cooper ◽

Igor Kutnyakov ◽

Marie Swita ◽

...

Keyword(s):

Liquid Scintillation Counting ◽

Liquid Scintillation ◽

Jet Fuel ◽

Scintillation Counting ◽

Counting Method ◽

Low Level

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The Impact of Forcing Datasets on the High-Resolution Simulation of Tropical Storm Ivan (2004) in the Southern Appalachians

Monthly Weather Review ◽

10.1175/mwr-d-11-00345.1 ◽

2012 ◽

Vol 140 (10) ◽

pp. 3300-3326 ◽

Cited By ~ 15

Author(s):

Xiaoming Sun ◽

Ana P. Barros

Keyword(s):

High Resolution ◽

Global Analysis ◽

Surface Wind ◽

Tropical Storm ◽

Southern Appalachians ◽

Low Level ◽

Simulated Precipitation ◽

Forced Simulation ◽

The Impact ◽

Resolution Simulation

Abstract The influence of large-scale forcing on the high-resolution simulation of Tropical Storm Ivan (2004) in the southern Appalachians was investigated using the Weather Research and Forecasting model (WRF). Two forcing datasets were employed: the North American Regional Reanalysis (NARR; 32 km × 32 km) and the NCEP Final Operational Global Analysis (NCEP FNL; 1° × 1°). Simulated fields were evaluated against rain gauge, radar, and satellite data; sounding observations; and the best track from the National Hurricane Center (NHC). Overall, the NCEP FNL forced simulation (WRF_FNL) captures storm structure and evolution more accurately than the NARR forced simulation (WRF_NARR), benefiting from the hurricane initialization scheme in the NCEP FNL. Further, the performance of WRF_NARR is also negatively affected by a previously documented low-level warm bias in NARR. These factors lead to excessive precipitation in the Piedmont region, delayed rainfall in Alabama, as well as spatially displaced and unrealistically extreme rainbands during its passage over the southern Appalachians. Spatial filtering of the simulated precipitation fields confirms that the storm characteristics inherited from the forcing are critical to capture the storm’s impact at local places. Compared with the NHC observations, the storm is weaker in both NARR and NCEP FNL (up to Δp ~ 5 hPa), yet it is persistently deeper in all WRF simulations forced by either dataset. The surface wind fields are largely overestimated. This is attributed to the underestimation of surface roughness length over land, leading to underestimation of surface drag, reducing low-level convergence, and weakening the dissipation of the simulated cyclone.

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Examining Terrain Effects on an Upstate New York Tornado Event Utilizing a High-Resolution Model Simulation

Weather and Forecasting ◽

10.1175/waf-d-21-0018.1 ◽

2021 ◽

Author(s):

Luke J. LeBel ◽

Brian H. Tang ◽

Ross A. Lazear

Keyword(s):

New York ◽

High Resolution ◽

Wind Shear ◽

Model Simulation ◽

Wrf Model ◽

Severe Weather ◽

Streamwise Vorticity ◽

Low Level ◽

Severe Convection ◽

The Impact

AbstractThe complex terrain at the intersection of the Mohawk and Hudson valleys of New York has an impact on the development and evolution of severe convection in the region. Specifically, previous research has concluded that terrain-channeled flow in the Mohawk and Hudson valleys likely contributes to increased low-level wind shear and instability in the valleys during severe weather events such as the historic 31 May 1998 event that produced a strong (F3) tornado in Mechanicville, New York.The goal of this study is to further examine the impact of terrain channeling on severe convection by analyzing a high-resolution WRF model simulation of the 31 May 1998 event. Results from the simulation suggest that terrain-channeled flow resulted in the localized formation of an enhanced low-level moisture gradient, resembling a dryline, at the intersection of the Mohawk and Hudson valleys. East of this boundary, the environment was characterized by stronger low-level wind shear and greater low-level moisture and instability, increasing tornadogenesis potential. A simulated supercell intensified after crossing the boundary, as the larger instability and streamwise vorticity of the low-level inflow was ingested into the supercell updraft. These results suggest that terrain can have a key role in producing mesoscale inhomogeneities that impact the evolution of severe convection. Recognition of these terrain-induced boundaries may help in anticipating where the risk of severe weather may be locally enhanced.

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The South Georgia Wave Experiment: A Means for Improved Analysis of Gravity Waves and Low-Level Wind Impacts Generated from Mountainous Islands

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-16-0151.1 ◽

2018 ◽

Vol 99 (5) ◽

pp. 1027-1040 ◽

Cited By ~ 7

Author(s):

D. R. Jackson ◽

A. Gadian ◽

N. P. Hindley ◽

L. Hoffmann ◽

J. Hughes ◽

...

Keyword(s):

High Resolution ◽

Gravity Waves ◽

Numerical Models ◽

Small Island ◽

Small Scale ◽

The South ◽

South Georgia ◽

Low Level ◽

Wave Experiment ◽

Realistic Representation

AbstractGravity waves (GWs) play an important role in many atmospheric processes. However, the observation-based understanding of GWs is limited, and representing them in numerical models is difficult. Recent studies show that small islands can be intense sources of GWs, with climatologically significant effects on the atmospheric circulation. South Georgia, in the South Atlantic, is a notable source of such “small island” waves. GWs are usually too small scale to be resolved by current models, so their effects are represented approximately using resolved model fields (parameterization). However, the small-island waves are not well represented by such parameterizations, and the explicit representation of GWs in very-high-resolution models is still in its infancy. Steep islands such as South Georgia are also known to generate low-level wakes, affecting the flow hundreds of kilometers downwind. These wakes are also poorly represented in models.We present results from the South Georgia Wave Experiment (SG-WEX) for 5 July 2015. Analysis of GWs from satellite observations is augmented by radiosonde observations made from South Georgia. Simulations were also made using high-resolution configurations of the Met Office Unified Model (UM). Comparison with observations indicates that the UM performs well for this case, with realistic representation of GW patterns and low-level wakes. Examination of a longer simulation period suggests that the wakes generally are well represented by the model. The realism of these simulations suggests they can be used to develop parameterizations for use at coarser model resolutions.

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Determination of radiostrontium in milk samples by ultra-low-level liquid scintillation counting: a validated approach

Food Additives & Contaminants Part A ◽

10.1080/19440049.2014.968883 ◽

2014 ◽

Vol 31 (12) ◽

pp. 2014-2021 ◽

Cited By ~ 4

Author(s):

Daniela dell’Oro ◽

Marco Iammarino ◽

Nicola Bortone ◽

Michele Mangiacotti ◽

Antonio Eugenio Chiaravalle

Keyword(s):

Liquid Scintillation Counting ◽

Liquid Scintillation ◽

Scintillation Counting ◽

Low Level ◽

Milk Samples

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Building Extraction in Very High Resolution Imagery by Dense-Attention Networks

Remote Sensing ◽

10.3390/rs10111768 ◽

2018 ◽

Vol 10 (11) ◽

pp. 1768 ◽

Cited By ~ 24

Author(s):

Hui Yang ◽

Penghai Wu ◽

Xuedong Yao ◽

Yanlan Wu ◽

Biao Wang ◽

...

Keyword(s):

Deep Learning ◽

High Resolution ◽

Building Extraction ◽

Learning Networks ◽

Feature Maps ◽

Low Level ◽

High Resolution Imagery ◽

Very High Resolution Imagery ◽

High Level ◽

Very High

Building extraction from very high resolution (VHR) imagery plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications. Compared with the traditional building extraction approaches, deep learning networks have recently shown outstanding performance in this task by using both high-level and low-level feature maps. However, it is difficult to utilize different level features rationally with the present deep learning networks. To tackle this problem, a novel network based on DenseNets and the attention mechanism was proposed, called the dense-attention network (DAN). The DAN contains an encoder part and a decoder part which are separately composed of lightweight DenseNets and a spatial attention fusion module. The proposed encoder–decoder architecture can strengthen feature propagation and effectively bring higher-level feature information to suppress the low-level feature and noises. Experimental results based on public international society for photogrammetry and remote sensing (ISPRS) datasets with only red–green–blue (RGB) images demonstrated that the proposed DAN achieved a higher score (96.16% overall accuracy (OA), 92.56% F1 score, 90.56% mean intersection over union (MIOU), less training and response time and higher-quality value) when compared with other deep learning methods.

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