scholarly journals Probing near-surface atmospheric turbulence with lidar measurements and high-resolution hydrodynamic models

2001 ◽  
Author(s):  
Chih-Yue J. Kao ◽  
D. I. Cooper ◽  
J. M. Reisner ◽  
William E. Eichinger ◽  
Michael Ghil
Keyword(s):  
High Resolution ◽  
Atmospheric Turbulence ◽  
Hydrodynamic Models ◽  
Near Surface ◽  
Lidar Measurements

scholarly journals Probing near-surface atmospheric turbulence with high-resolution lidar measurements and models

2002 ◽  
Vol 107 (D10) ◽  
pp. ACL 7-1-ACL 7-9 ◽  
Author(s):  
C.-Y. J. Kao ◽  
D. I. Cooper ◽  
J. M. Reisner ◽  
W. E. Eichinger ◽  
M. Ghil
Keyword(s):  
High Resolution ◽  
Atmospheric Turbulence ◽  
Near Surface ◽  
Lidar Measurements

scholarly journals Geophysical investigations for stability and safety mitigation of regional crude-oil pipeline near abandoned coal mines

2021 ◽  
Vol 18 (1) ◽  
pp. 145-162
Author(s):  
B Butchibabu ◽  
Prosanta Kumar Khan ◽  
P C Jha
Keyword(s):  
High Resolution ◽  
Crude Oil ◽  
Seismic Refraction ◽  
High Resolution Imaging ◽  
Weak Zone ◽  
Near Surface ◽  
Oil Pipeline ◽  
Refraction Tomography ◽  
Geophysical Investigations ◽  
Resolution Imaging

Abstract This study aims for the protection of a crude-oil pipeline, buried at a shallow depth, against a probable environmental hazard and pilferage. Both surface and borehole geophysical techniques such as electrical resistivity tomography (ERT), ground penetrating radar (GPR), surface seismic refraction tomography (SRT), cross-hole seismic tomography (CST) and cross-hole seismic profiling (CSP) were used to map the vulnerable zones. Data were acquired using ERT, GPR and SRT along the pipeline for a length of 750 m, and across the pipeline for a length of 4096 m (over 16 profiles of ERT and SRT with a separation of 50 m) for high-resolution imaging of the near-surface features. Borehole techniques, based on six CSP and three CST, were carried out at potentially vulnerable locations up to a depth of 30 m to complement the surface mapping with high-resolution imaging of deeper features. The ERT results revealed the presence of voids or cavities below the pipeline. A major weak zone was identified at the central part of the study area extending significantly deep into the subsurface. CSP and CST results also confirmed the presence of weak zones below the pipeline. The integrated geophysical investigations helped to detect the old workings and a deformation zone in the overburden. These features near the pipeline produced instability leading to deformation in the overburden, and led to subsidence in close vicinity of the concerned area. The area for imminent subsidence, proposed based on the results of the present comprehensive geophysical investigations, was found critical for the pipeline.

Developing High-Resolution Channel to Basin-Scale Unstructured Grid Hydrodynamic Models for Tide/Storm Predictions in the US East and Gulf of Mexico Coasts

2020 ◽  
Author(s):  
María Teresa Contreras Vargas ◽  
Joannes Westerink ◽  
Damrongsak Wirasaet ◽  
William Pringle ◽  
Edward Myers ◽  
...  
Keyword(s):  
High Resolution ◽  
Gulf Of Mexico ◽  
Unstructured Grid ◽  
Hydrodynamic Models ◽  
Basin Scale ◽  
The Us

scholarly journals High Resolution Transmission Electron Microscopy of Metallic Film/Laser-Irradiated Alumina Couples.

1994 ◽  
Vol 357 ◽  
Author(s):  
A. J. Pedraza ◽  
Siqi Cao ◽  
L. F. Allard ◽  
D. H. Lowndes
Keyword(s):  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
High Resolution ◽  
Copper Film ◽  
Interfacial Structure ◽  
Diffuse Interface ◽  
Cross Sectional ◽  
Polycrystalline Alumina ◽  
Near Surface ◽  
Transmission Electron

AbstractA near-surface thin layer is melted when single crystal alumina (sapphire) is pulsed laserirradiated in an Ar-4%H2 atmosphere. γ-alumina grows epitaxially from the (0001) face of axalumina (sapphire) during the rapid solidification of this layer that occurs once the laser pulse is over. Cross sectional high resolution transmission electron microscopy (HRTEM) reveals that the interface between unmelted sapphire and γ-alumina is atomistically flat with steps of one to a few close-packed oxygen layers; however, pronounced lattice distortions exist in the resolidified γ-alumina. HRTEM also is used to study the metal-ceramic interface of a copper film deposited on a laser-irradiated alumina substrate. The observed changes of the interfacial structure relative to that of unexposed substrates are correlated with the strong enhancement of film-substrate bonding promoted by laser irradiation. HRTEM shows that a thin amorphous film is produced after irradiation of 99.6% polycrystalline alumina. Formation of a diffuse interface and atomic rearrangements that can take place in metastable phases contribute to enhance the bonding strength of copper to laser-irradiated alumina.

Machine learning analyses of remote sensing measurements establish strong relationships between vegetation and snow depth in the boreal forest of Interior Alaska

2021 ◽  
Author(s):  
Thomas Douglas ◽  
Caiyun Zhang
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Snow Depth ◽  
Spatial Scales ◽  
Critical Role ◽  
Winter Season ◽  
Thermal Conditions ◽  
Near Surface ◽  
Lidar Measurements ◽  
Remote Sensing Methods

The seasonal snowpack plays a critical role in Arctic and boreal hydrologic and ecologic processes. Though snow depth can be different from one season to another there are repeated relationships between ecotype and snowpack depth. Alterations to the seasonal snowpack, which plays a critical role in regulating wintertime soil thermal conditions, have major ramifications for near-surface permafrost. Therefore, relationships between vegetation and snowpack depth are critical for identifying how present and projected future changes in winter season processes or land cover will affect permafrost. Vegetation and snow cover areal extent can be assessed rapidly over large spatial scales with remote sensing methods, however, measuring snow depth remotely has proven difficult. This makes snow depth–vegetation relationships a potential means of assessing snowpack characteristics. In this study, we combined airborne hyperspectral and LiDAR data with machine learning methods to characterize relationships between ecotype and the end of winter snowpack depth. Our results show hyperspectral measurements account for two thirds or more of the variance in the relationship between ecotype and snow depth. An ensemble analysis of model outputs using hyperspectral and LiDAR measurements yields the strongest relationships between ecotype and snow depth. Our results can be applied across the boreal biome to model the coupling effects between vegetation and snowpack depth.

Climate change in the High Mountain Asia simulated with CMIP6 models

2021 ◽  
Author(s):  
Mickaël Lalande ◽  
Martin Ménégoz ◽  
Gerhard Krinner
Keyword(s):  
High Resolution ◽  
Snow Cover ◽  
Climate Models ◽  
Global Climate Models ◽  
Cold Bias ◽  
High Mountain ◽  
The Tibetan Plateau ◽  
Near Surface ◽  
Model Biases ◽  
Snow Cover Extent

<p>The High Mountains of Asia (HMA) region and the Tibetan Plateau (TP), with an average altitude of 4000 m, are hosting the third largest reservoir of glaciers and snow after the two polar ice caps, and are at the origin of strong orographic precipitation. Climate studies over HMA are related to serious challenges concerning the exposure of human infrastructures to natural hazards and the water resources for agriculture, drinking water, and hydroelectricity to whom several hundred million inhabitants of the Indian subcontinent are depending. However, climate variables such as temperature, precipitation, and snow cover are poorly described by global climate models because their coarse resolution is not adapted to the rugged topography of this region. Since the first CMIP exercises, a cold model bias has been identified in this region, however, its attribution is not obvious and may be different from one model to another. Our study focuses on a multi-model comparison of the CMIP6 simulations used to investigate the climate variability in this area to answer the next questions: (1) are the biases in HMA reduced in the new generation of climate models? (2) Do the model biases impact the simulated climate trends? (3) What are the links between the model biases in temperature, precipitation, and snow cover extent? (4) Which climate trajectories can be projected in this area until 2100? An analysis of 27 models over 1979-2014 still show a cold bias in near-surface air temperature over the HMA and TP reaching an annual value of -2.0 °C (± 3.2 °C), associated with an over-extended relative snow cover extent of 53 % (± 62 %), and a relative excess of precipitation of 139 % (± 38 %), knowing that the precipitation biases are uncertain because of the undercatch of solid precipitation in observations. Model biases and trends do not show any clear links, suggesting that biased models should not be excluded in trend and projections analysis, although non-linear effects related to lagged snow cover feedbacks could be expected. On average over 2081-2100 with respect to 1995-2014, for the scenarios SSP126, SSP245, SSP370, and SSP585, the 9 available models shows respectively an increase in annual temperature of 1.9 °C (± 0.5 °C), 3.4 °C (± 0.7 °C), 5.2 °C (± 1.2 °C), and 6.6 °C (± 1.5 °C); a relative decrease in the snow cover extent of 10 % (± 4.1 %), 19 % (± 5 %), 29 % (± 8 %), and 35 % (± 9 %); and an increase in total precipitation of 9 % (± 5 %), 13 % (± 7 %), 19 % (± 11 %), and 27 % (± 13 %). Further analyses will be considered to investigate potential links between the biases at the surface and those at higher tropospheric levels as well as with the topography. The models based on high resolution do not perform better than the coarse-gridded ones, suggesting that the race to high resolution should be considered as a second priority after the developments of more realistic physical parameterizations.</p>

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