196,071 research outputs found
Early-stage aeolian protodunes: bedform development and sand transport dynamics
No full textEarly-stage aeolian bedforms, or protodunes, are elemental in the continuum of dune development and act as essential precursors to mature dunes. Despite this, we know very little about the processes and feedback mechanisms that shape these nascent bedforms. Whilst theory and conceptual models have offered some explanation for protodune existence and development, until now, we have lacked the technical capability to measure such small bedforms in aeolian settings. Here, we employ terrestrial laser scanning to measure morphological change at the high frequency and spatial resolution required to gain new insights into protodune behaviour. On a 0.06 m high protodune, we observe vertical growth of the crest by 0.005 m in two hours. Our direct measurements of sand transport on the protodune account for such growth, with a reduction in time-averaged sediment flux of 18% observed over the crestal region. Detailed measurements of form also establish key points of morphological change on the protodune. The position on the stoss slope where erosion switches to deposition is found at a point 0.07 m upwind of the crest. This finding supports recent models that explain vertical dune growth through an upwind shift of this switching point. Observations also show characteristic changes in the asymmetric cross section of the protodune. Flow-form feedbacks result in a steepening of the lee slope and a decline in lower stoss slope steepness (by 3°), constituting a reshaping of protodune form towards more mature dune morphology. The approaches and findings applied here, a) demonstrate an ability to quantify processes at requisite spatial and temporal scales for monitoring early-stage dune evolution, b) highlight the crucial role of form-flow feedbacks in enabling early-stage bedform growth, alluding to a fluctuation in feedbacks that require better representation in dune models, and c) provide a new stimulus for advancing understanding of aeolian bedforms
Understanding dust sources through remote sensing: Making a case for CubeSats
No full textAbstract: Dust sources have been revealed through remote sensing, first regionally by ~1° resolution sensors (TOMS), then at sub-basin scale by moderate-resolution sensors (MODIS). Sensors with higher spatial resolution until recently were poorly temporally-resolved, precluding their use for systematic investigations of sources. Now, “CubeSat” constellations with high-temporal-and-spatial-resolution sensors such as PlanetScope offer ~3 m resolution and daily (to sub-daily) temporal resolution. We illustrate the spatio-temporal dust plume observation capabilities of CubeSat data through a dust event case study, Bolson de los Muertos playa, Chihuahuan Desert, Mexico. For the event, PlanetScope showed numerous discrete point sources, revealing variability of surface erodibility and emission over ~8% of a focus area at time of capture. The unprecedented detail of PlanetScope imagery revealed plume development where outer-playa sands and fluvial-deltaic inputs contact lacustrine silts/clays, consistent with field-studies. PlanetScope's high fidelity improves spatial quantification and temporal constraint of source activity, and we assess the spatio-temporal capabilities of CubeSat in context with other dust observation remote sensing systems. Compared to previous satellite technologies, CubeSats bring better potential to link remote sensing to field observations of emission. This leap forward in the remote sensing of dust sources calls for the systematic analysis of CubeSat imagery in source areas
Coupling leeside grainfall to avalanche characteristics in aeolian dune dynamics
No full textAvalanche (grainflow) processes are fundamental drivers of dune morphodynamics and are typically initiated by grainfall accumulations. In sedimentary systems, however, the dynamism between grainfall and grainflow remains unspecified because simple measurements are hampered by the inherent instability of lee slopes. Here, for the first time, terrestrial laser scanning is used to quantify key aspects of the grainfall process on the lee (slip face) of a barchan sand dune. We determine grainfall zone extent and flux and show their variability under differing wind speeds. The increase in the downwind distance from the brink of peak grainfall under stronger winds provides a mechanism that explains the competence of large avalanches to descend the entire lee slope. These findings highlight important interactions between wind speed, grainfall, and subsequent grainflow that influence dune migration rates and are important for correct interpretation of dune stratigraphy
Surface and Meteorological Data at Huab River Valley, Skeleton Coast National Park, Namibia in September 2019
No full textWind, sediment transport and surface/saltation data collected at Huab River Valley during a field campaign in September 2019 to investigate saltation on gravel and sand surfaces. Surface/saltation data: This is terrestrial laser scanned (TLS) data collected over sand and gravel surfaces during multiple days when saltation was active, on a surface approximately 8 m from the TLS, perpendicular to the wind direction. The data is raw point cloud format in text columns of x, y and z coordinate data. Files are named *_^_scan&amp; where * is the date that the data was collected in yymmdd format, ^ is surface type (sand or gravel) and &amp; is the scan number. Each data set uses the same coordinate system. Data can be viewed in any spatial software. Wind and sediment data were collected from a fixed point on each surface, directly downwind of the TLS data. The data is in csv file format with column titles and can be viewed in any text or database software. Data include hot wire measurements at different heights, Wenglor counts, sensit counts and 3D sonic measurements on some days. Sonic data is at 10 Hz, hotwire data at 10 second intervals, transport data is given within both datasets.</span
Data used in 'Local Wind Regime Induced by Giant Linear Dunes: Comparison of ERA5-Land Reanalysis with Surface Measurements.'
No full textThis repository contains the data used in: Gadal, C., Delorme, P., Narteau, C. et al. Local Wind Regime Induced by Giant Linear Dunes: Comparison of ERA5-Land Reanalysis with Surface Measurements. Boundary-Layer Meteorol 185, 309–332 (2022). https://doi.org/10.1007/s10546-022-00733-6 where wind data measured at 4 different places in and across the Namib Sand Sea are compared to the data from the ERA5/ERA5Land climate reanalyses. The use this data, one should first look at the GitHub repository https://github.com/Cgadal/GiantDunes and at the corresponding documentation https://cgadal.github.io/GiantDunes/. The description sometimes refers to scripts used in https://github.com/Cgadal/GiantDunes/tree/master/Processing. The two folders 'raw_data' and 'processed_data' contain the input raw_data, and the output data after processing used to make the paper figures, respectively. In each of them, '.npy' files contain Python dictionaries with different variables in them. They can be loaded using the Python library numpy as data = np.load('file.npy', allow_pickle=True).item(); and the different keys (variables) can be printed with data.keys() or data[station].keys() if data.keys() return the different stations. Unless specified otherwise below, note that all variables are given in the International System of Units (SI), and wind direction is given anticlockwise, with the 0 being a wind blowing from the West to the East. raw_data: DEM: contains the Digital Elevation Models of the two stations from the SRTM30, downloaded from here: https://dwtkns.com/srtm30m/ ERA5: hourly data from the ER5 climate reanalysis, on surface (_BLH) and pressure levels (_levels). Downloaded from https://cds.climate.copernicus.eu/ ERA5Land: hourly data from the ER5Land climate reanalysis Downloaded from https://cds.climate.copernicus.eu/ KML_points: kml points of the measurement station. It can be opened directly in GoogleEarth. measured_wind_data: contains the measured in situ data. The windspeed is measured using Vector Instruments A100-LK cup anemometers, the wind direction using Vector Instruments W200-P wind vane and the time using Campbell Instruments CR10X and CR1000X dataloggers. processed_data: 'Data_preprocessed.npy': preprocessed_data, output of 1_data_preprocessing_plot.py 'Data_DEM.npy': properties of the processed DEM, the output of 2_DEM_analysis_plot.py 'Data_calib_roughness.npy': data from the calibration of the hydrodynamic roughnesses, the output of 3_roughness_calibration_plot.py 'Data_final.npy': file containing all computed quantities 'time_series_hydro_coeffs.npy': file containing the time series of the calculated hydrodynamic coefficients by '5_norun_hydro_coeff_time_series.npy'. Depending on the loaded data file, main dictionary keys can be: 'lat': latitude, in degree 'lon': longitude, in degree 'time': time vector, in datetime objects (https://docs.python.org/3/library/datetime.html) 'DEM': elevation data array in [m], with dimensions matching 'lat' and 'lon' vectors 'z_mes', 'z_insitu', 'z_ERA5LAND': height of the corresponding velocity 'direction': measured wind direction, in [degrees] 'velocity': measured wind velocity, in [m/s] 'orientaion': dune pattern orientation, [deg] 'wavelength': dune pattern wavelength, [km] 'z0_insitu': chosen hydrodynamic roughness for the considered station. 'U_insitu', 'Orientation_insitu': hourly averaged measured wind velocities and direction 'U_era', 'Orientation_era': hourly 10m wind data from the ERA5Land data set 'Boundary layer height', 'blh': boundary layer height from the hourly ERA5 dataset 'Pressure levels', 'levels': Pressure levels from the pressure levels ERA5 dataset 'Temperature', 't': Temperature from the pressure levels ERA5 dataset 'Specific humidity', 'q': Specific humidity from the pressure levels ERA5 dataset 'Geopotential', 'z': Geopotential from the pressure levels ERA5 dataset 'Virtual_potential_temperature': Virtual potential temperature calculated from the pressure levels ERA5 dataset 'Potential_temperature': Potential temperature calculated from the pressure levels ERA5 dataset 'Density': Density calculated from the pressure levels ERA5 dataset 'height': Vertical coordinates calculated from the pressure levels ERA5 dataset 'theta_ground': Averaged virtual potential temperature within the ABL. 'delta_theta': Virtual potential temperature at the ABL. 'gradient_free_atm': Virtual potential temperature gradient in the FA. 'Froude': time series of the Froude number U/((delta_theta/theta_ground)*g*BLH) 'kH': time series of the number 'kH' 'kLB': time series of the internal Froude number kU/N Other keys are not relevant and are stored for verification purposes. For more details, please contact Cyril Gadal (see authors), and look at the following GitHub repository: https://github.com/Cgadal/GiantDunes, where all the codes are present.</span
Surface and Meteorological Data at Medano Creek, Great Sand Dunes National Park, Colorado, USA on 15th April 2019
No full textWind and surface morphological data collected at Medano Creek on the 15th April 2019 to investigate protodune initiation. Surface morphological data: This is terrestrial laser scanned (TLS) data collected of the creek sand surface using three different co-located Leica TLS (C10, P20 and P50). The data is raw point cloud format in text columns of x, y and z coordinate data. It has been orientation into the same local coordinate system. Each data set uses the same coordinate system. Data can be viewed in any spatial software. Data is labelled using C10, P20 or P50, followed by the scan number. Scan times are indicated in a separate file. Wind data were collected from a fixed point next to the TLS instruments using a Gill 3D sonic anemometer. The data is in csv file format with column titles and can be viewed in any text or database software.</span
Dr. Duane M. Jackson, Morehouse College, July 2011
No full textThis video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer
Surface and Meteorological Data of Saltation and Ripple Dynamics at Huab Dune Field, Skeleton Coast National Park, Namibia 2014, 2016 and 2018
No full textThis dataset includes raw point cloud data from repeat terrestrial laser scans (TLS) of rippled surfaces on barchan and dome dunes within the Huab Dune Field, Skeleton Coast National Park, Namibia. This raw data can be used to extract saltation height dynamics as well as 3D ripple data including celerity. As well as the TLS data, additional measurements of the wind speed through a CSAT 3D sonic anemometer or cup anemometer and sediment transport using a Sensit and Wenglor gate sensor.</span
"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States" By M. Carey.
No full text"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States: containing bried sketches of the moral and political character of those states.
By M. Carey, member of the American philosophical, and of the American Antiquarian Society, and author of The Olive Branch, Cindiciae Hibernicae, essays on banking, on political economy, and on internal improvement.
To which are now added the English editor's comments on the subject; together with Important Advice to Emigrants, and Cautions Against Impositions Practiced in the Outports
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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