NSFGEO-NERC: The Origin of Aeolian Dunes (TOAD)
Lead Research Organisation:
University of Southampton
Department Name: Sch of Geography & Environmental Sci
Abstract
Aeolian (wind-blown) sand dunes occupy 10% of the Earth's surface, both in vast desert sand seas and as important natural defences against flooding along coasts. While the environmental conditions that influence the shape, movement and patterns of fully grown dunes have been extensively studied, arguably the most enduring deficiency in our understanding of these landforms is also the most profound: how do wind-blown dunes initiate?
Initiation is central to understanding dunes as major geological units, including the response of these landscapes to climatic drivers, environmental change and societal impact. The significance of dune initiation for the wider understanding of wind-blown sandy systems and their contexts, for which the discovery of extra-terrestrial dune fields has added a recent impetus, ensures that the question of initiation has remained prominent throughout the history of desert research. Despite this, existing ideas proposed to explain processes of dune origin have remained largely descriptive and uncorroborated. The persistence of the question regarding dune initiation is not due to an absence of appreciation of its importance but, rather, a lack of the means to tackle this fundamental issue.
The critical obstacle to a fully developed understanding of dune initiation is that, until now, measurement of the necessary variables, at the ultra-high spatial and temporal resolutions required to detect small-scale variations in surface conditions and wind-blown sand transport, has been impossible. Recent technological advances in the geosciences both inspire and underpin this proposal, as they now provide the opportunity to meet the demanding requirements of process measurement.
Surmounting the abiding problem of dune initiation requires novel approaches in research design and our proposal tackles the issues of measurement at small scales by forging complementary links between fieldwork and physical modelling, as well as an ability to widen the application of detailed process findings through computer modelling. Specifically, this proposal will for the first time examine the key inter-relationships between airflow, surface properties, changes in sand transport and bedform shape that lie behind a meaningful understanding of how nascent dunes emerge. Full measurement of controlling processes and bedform development will be achieved through field monitoring of surface properties and bedform change at extremely high resolution. A key novelty of the fieldwork is that it will be carried out at three carefully chosen locations of known dune development, with each location representing the 'type site' for three different drivers of dune initiation; surface roughness, surface moisture and sand bed instability.
The fieldwork will inform experiments undertaken in a bespoke laboratory flume that is designed to enable accurate characterisation of flow very close to the 3D surface of modelled dunes using state-of-the-art imaging techniques. Our field and laboratory dataset will be used to drive a computer model that we will then run to test the sensitivity of dune initiation and growth to different controls in a range of environmental conditions in deserts, coasts and on other planets.
Our proposal is built on a new capability to make field observations at the requisite exceptional levels of detail, augmented by closely coupled state-of-the-art laboratory flow simulations, plus the development and application of evidence-based modelling to examine drivers of dune initiation. In concert, this approach represents an unprecedented opportunity to overcome a truly enduring plateau for understanding the origins of one of the major terrestrial landform systems.
Initiation is central to understanding dunes as major geological units, including the response of these landscapes to climatic drivers, environmental change and societal impact. The significance of dune initiation for the wider understanding of wind-blown sandy systems and their contexts, for which the discovery of extra-terrestrial dune fields has added a recent impetus, ensures that the question of initiation has remained prominent throughout the history of desert research. Despite this, existing ideas proposed to explain processes of dune origin have remained largely descriptive and uncorroborated. The persistence of the question regarding dune initiation is not due to an absence of appreciation of its importance but, rather, a lack of the means to tackle this fundamental issue.
The critical obstacle to a fully developed understanding of dune initiation is that, until now, measurement of the necessary variables, at the ultra-high spatial and temporal resolutions required to detect small-scale variations in surface conditions and wind-blown sand transport, has been impossible. Recent technological advances in the geosciences both inspire and underpin this proposal, as they now provide the opportunity to meet the demanding requirements of process measurement.
Surmounting the abiding problem of dune initiation requires novel approaches in research design and our proposal tackles the issues of measurement at small scales by forging complementary links between fieldwork and physical modelling, as well as an ability to widen the application of detailed process findings through computer modelling. Specifically, this proposal will for the first time examine the key inter-relationships between airflow, surface properties, changes in sand transport and bedform shape that lie behind a meaningful understanding of how nascent dunes emerge. Full measurement of controlling processes and bedform development will be achieved through field monitoring of surface properties and bedform change at extremely high resolution. A key novelty of the fieldwork is that it will be carried out at three carefully chosen locations of known dune development, with each location representing the 'type site' for three different drivers of dune initiation; surface roughness, surface moisture and sand bed instability.
The fieldwork will inform experiments undertaken in a bespoke laboratory flume that is designed to enable accurate characterisation of flow very close to the 3D surface of modelled dunes using state-of-the-art imaging techniques. Our field and laboratory dataset will be used to drive a computer model that we will then run to test the sensitivity of dune initiation and growth to different controls in a range of environmental conditions in deserts, coasts and on other planets.
Our proposal is built on a new capability to make field observations at the requisite exceptional levels of detail, augmented by closely coupled state-of-the-art laboratory flow simulations, plus the development and application of evidence-based modelling to examine drivers of dune initiation. In concert, this approach represents an unprecedented opportunity to overcome a truly enduring plateau for understanding the origins of one of the major terrestrial landform systems.
Planned Impact
This research will generate impact through our project partners in terms of societal, economic, industry and public education.
1) UK school students will benefit from enhanced educational materials developed in collaboration with our project partner The Royal Geographical Society (with IBG). Over 250,000 students take Geography at GCSE level (14-16 year old) in the UK and as many as 55,000 go on to take it at AS or A-Level (17-18 year old) and the number is increasing with an upward trajectory of 17-20% in the last three years. The new A-Level curriculum now includes a deserts module, indicating the relevance and importance of these environments in a changing planet and in the eyes of the general public through education policy. As this topic is new for UK Geography, there is an urgent need to provide materials to teachers.
2) National Park visitors will benefit from information displays, signage boards and fliers that we will develop with our project partners Great Sand Dunes National Park and Gobabeb Research and Training Centre, Namibia. These materials will inform visitors about desert landscapes, dune processes and climate change impact. Approximately 300,000 and 70,000 people visit Great Sand Dunes and Namib-Naukluft National Parks annually. The Namib Sand Sea, within which Gobabeb is situated, has recently been designated as a UNESCO World Heritage Site, so it is particularly important that with an anticipated increase in international visitors we disseminate our research on the very processes that enabled this landscape to develop.
3) Scientists and practitioners, both local and international will benefit from the outcomes of our findings and the potential for their broader application in land management, planetary and climate change scenarios at the dedicated impact workshop that we will hold towards the end of our grant. It will coincide with the biennial ICAR conference, the premier gathering of aeolian scientists that typically attracts ~200 international scientists, along with other interested stakeholders and industrial researchers. Items of broader interest for discussion include modelling of dune encroachment on transport routes and arable land, and dune development for coastal protection.
4) University students in Namibia and the US will benefit from the opportunity to engage with our field campaigns through project partner involvement. Particularly in Namibia there is a lack of students continuing past undergraduate level, and this exposure to an international research project should inspire them to study further. The UK investigators have positive experience of this as part of recent National Geographic funded research. Aeolian dunes are also present on other planetary bodies, and through PP Diniega, an undergraduate or MSc student will be able to develop skills and gain valuable work experience at the Jet Propulsion Lab through an inventory of early-stage bedform development on Mars.
5) Through our project partner Shell International, we will engage with the hydrocarbons industry and ensure that our scientific findings have industrial applications, particularly by improving our understanding of the ancient dune systems which contain offshore oil reserves.
6) More broadly, the general public will benefit from educational materials publicised on our webpage and twitter feed, as well as at Engineering Open House which is held at the University of Illinois and attended by >20,000 people each year. Here we will display exhibits detailing the linkage of our field, laboratory and numerical experiments, and the societal, industrial, environmental and academic application of these results in desert, coastal and planetary systems.
1) UK school students will benefit from enhanced educational materials developed in collaboration with our project partner The Royal Geographical Society (with IBG). Over 250,000 students take Geography at GCSE level (14-16 year old) in the UK and as many as 55,000 go on to take it at AS or A-Level (17-18 year old) and the number is increasing with an upward trajectory of 17-20% in the last three years. The new A-Level curriculum now includes a deserts module, indicating the relevance and importance of these environments in a changing planet and in the eyes of the general public through education policy. As this topic is new for UK Geography, there is an urgent need to provide materials to teachers.
2) National Park visitors will benefit from information displays, signage boards and fliers that we will develop with our project partners Great Sand Dunes National Park and Gobabeb Research and Training Centre, Namibia. These materials will inform visitors about desert landscapes, dune processes and climate change impact. Approximately 300,000 and 70,000 people visit Great Sand Dunes and Namib-Naukluft National Parks annually. The Namib Sand Sea, within which Gobabeb is situated, has recently been designated as a UNESCO World Heritage Site, so it is particularly important that with an anticipated increase in international visitors we disseminate our research on the very processes that enabled this landscape to develop.
3) Scientists and practitioners, both local and international will benefit from the outcomes of our findings and the potential for their broader application in land management, planetary and climate change scenarios at the dedicated impact workshop that we will hold towards the end of our grant. It will coincide with the biennial ICAR conference, the premier gathering of aeolian scientists that typically attracts ~200 international scientists, along with other interested stakeholders and industrial researchers. Items of broader interest for discussion include modelling of dune encroachment on transport routes and arable land, and dune development for coastal protection.
4) University students in Namibia and the US will benefit from the opportunity to engage with our field campaigns through project partner involvement. Particularly in Namibia there is a lack of students continuing past undergraduate level, and this exposure to an international research project should inspire them to study further. The UK investigators have positive experience of this as part of recent National Geographic funded research. Aeolian dunes are also present on other planetary bodies, and through PP Diniega, an undergraduate or MSc student will be able to develop skills and gain valuable work experience at the Jet Propulsion Lab through an inventory of early-stage bedform development on Mars.
5) Through our project partner Shell International, we will engage with the hydrocarbons industry and ensure that our scientific findings have industrial applications, particularly by improving our understanding of the ancient dune systems which contain offshore oil reserves.
6) More broadly, the general public will benefit from educational materials publicised on our webpage and twitter feed, as well as at Engineering Open House which is held at the University of Illinois and attended by >20,000 people each year. Here we will display exhibits detailing the linkage of our field, laboratory and numerical experiments, and the societal, industrial, environmental and academic application of these results in desert, coastal and planetary systems.
Organisations
- University of Southampton (Lead Research Organisation)
- Desert Research Institute (Project Partner)
- Shell Global Solutions International BV (Project Partner)
- University of Notre Dame Indiana (Project Partner)
- NASA (Project Partner)
- University of Namibia (Project Partner)
- Uni of Illinois at Urbana Champaign (Project Partner)
- Gobabeb – Namib Research Institute (Project Partner)
- CNRS (Project Partner)
- Royal Geographical Society (Project Partner)
- National Parks Service (NPS) (Project Partner)
- University of Texas at Austin (Project Partner)
- University of Texas at Dallas (Project Partner)
Publications
Bristow N
(2022)
Topographic perturbation of turbulent boundary layers by low-angle, early-stage aeolian dunes
in Earth Surface Processes and Landforms
Delorme P
(2023)
Field Evidence for the Initiation of Isolated Aeolian Sand Patches
in Geophysical Research Letters
Delorme P
(2020)
Dune Initiation in a Bimodal Wind Regime
in Journal of Geophysical Research: Earth Surface
Gadal C
(2022)
Local Wind Regime Induced by Giant Linear Dunes: Comparison of ERA5-Land Reanalysis with Surface Measurements
in Boundary-Layer Meteorology
| Title | Data used in 'Local Wind Regime Induced by Giant Linear Dunes: Comparison of ERA5-Land Reanalysis with Surface Measurements.' |
| Description | This 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. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | Improve our understanding of dune dynamics |
| URL | https://zenodo.org/doi/10.5281/zenodo.6343137 |
| Title | Data used in 'Local Wind Regime Induced by Giant Linear Dunes: Comparison of ERA5-Land Reanalysis with Surface Measurements.' |
| Description | This 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. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | Improve our understanding of dune dynamics |
| URL | https://zenodo.org/doi/10.5281/zenodo.7198452 |
| Title | Data used in 'Local wind regime induced by giant linear dunes: comparison of ERA5-Land re-analysis with surface measurements' |
| Description | This repository contains the data used in the paper ,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 following GitHub repository: https://github.com/Cgadal/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 procesing used to make the paper figures, respectively. In each of them, '.npy' files contain python dictionaries with different variables in it. 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. Note that, unless specified otherwise below, all variables are given in International System of Units (SI), and wind direction are given anticlockwise, with the 0 being a wind blowing from the West to the East. raw_data: - DEM: contain 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. Can be opened directly in GoogleEarth. - measured_wind_data: contain 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, output of 2_DEM_analysis_plot.py - 'Data_calib_roughness.npy': data from the calibration of the hydrodynamic roughnesses, 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 dictionnary 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 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. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | Improve our understanding of dune dynamics |
| URL | https://zenodo.org/record/6343138 |
| Title | Surface and Meteorological Data at Huab River Valley, Skeleton Coast National Park, Namibia in September 2019 |
| Description | Wind, 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& where * is the date that the data was collected in yymmdd format, ^ is surface type (sand or gravel) and & 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. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | Unique dataset |
| URL | https://www2.bgs.ac.uk/nationalgeosciencedatacentre/citedData/catalogue/99e4446f-c43a-492d-83c9-e896... |
| Title | Surface and Meteorological Data at Medano Creek, Great Sand Dunes National Park, Colorado, USA on 15th April 2019 |
| Description | Wind 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. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | Unique dataset |
| URL | https://www2.bgs.ac.uk/nationalgeosciencedatacentre/citedData/catalogue/46e9ff95-27ca-4d3b-b587-fc9c... |
| Title | Surface and Meteorological Data at Sand Creek, Great Sand Dunes National Park, Colorado, USA in March and April 2019 |
| Description | Wind, sediment transport and surface morphological data collected at Sand Creek during a month long field campaign in March and April 2019 to investigate protodune development under bimodal winds. Data is used in the accepted paper 'Dune initiation in a bimodal wind regime', Journal of Geophysical Research: Earth Surface, by Delorme, P., Wiggs, G.F.S., Baddock, M.C., Claudin, P., Nield, J.M. and Valdez, A. (accepted 18th September 2020, article reference number 2020JF005757R; https://repository.lboro.ac.uk/articles/Dune_initiation_in_a_bimodal_wind_regime/12973817) Surface morphological data: This is terrestrial laser scanned (TLS) data collected of the creek sand surface during multiple visits. The data is raw point cloud format in text columns of x, y and z coordinate data. It has been orientation in local format (the origin is located at 13UTM 443152, 4184478). *_full_lowres cover the whole creek surface and the banks on either side. * is the date that the data was collected in yymmdd format. All other data is high resolution section of the actual creek surface within the channel. 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 the eastern edge of the creek channel. The data is in csv file format with column titles and can be viewed in any text or database software. See Delorme et al. (accepted) for more details. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | Improve our understanding of protodune dynamics |
| URL | https://www2.bgs.ac.uk/nationalgeosciencedatacentre/citedData/catalogue/46af71db-1caa-4c88-bd6a-c972... |
| Title | Surface and Meteorological Data of Protodune Dynamics at Brancaster Beach, UK on 12th August 2016 |
| Description | Protodune data from 2016 and grain size from 2019 |
| Type Of Material | Database/Collection of data |
| Year Produced | 2023 |
| Provided To Others? | Yes |
| Impact | Unique dataset |
| URL | https://www2.bgs.ac.uk/nationalgeosciencedatacentre/citedData/catalogue/26eacb3a-982b-4d5c-bb48-9bc4... |
| Title | Surface and Meteorological Data of Protodune Dynamics at Helga's Interdune Area, Gobabeb, Namib Desert, Namibia on 13th September 2022 |
| Description | Data on protodune initiation and development |
| Type Of Material | Database/Collection of data |
| Year Produced | 2023 |
| Provided To Others? | Yes |
| Impact | First dataset of its kind |
| URL | https://www2.bgs.ac.uk/nationalgeosciencedatacentre/citedData/catalogue/10203f53-7471-4b8e-8177-74ae... |
| Title | Surface and Meteorological Data of Protodune Dynamics at Helga's Interdune Area, Gobabeb, Namib Desert, Namibia, 12th September 2023 |
| Description | This dataset includes raw point cloud data from repeat terrestrial laser scans (TLS) for early-stage protodunes migrating and eroding on a gravel surface in the Helga's Interdune Area, Gobabeb, Namib Desert, Namibia. As well as the TLS data, additional nearby measurements of the wind speed through a CSAT 3D sonic anemometer and sediment transport using a Sensit along with sediment trap data downwind of the focus protodune. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2025 |
| Provided To Others? | Yes |
| Impact | Improve our understanding of protodune dynamics |
| URL | https://www2.bgs.ac.uk/nationalgeosciencedatacentre/citedData/catalogue/786969f7-ff58-42d3-9175-3f79... |
| Title | Surface and Meteorological Data of Protodune Dynamics at Medano Creek Area, Great Sand Dunes National Park, Colorado, USA on 3rd April 2023 |
| Description | This dataset includes raw point cloud data from repeat terrestrial laser scans (TLS) for early-stage protodunes developing on a moist sandy surface in the Medano Creek area at Great Sand Dunes National Park, Colorado, USA under very strong winds. As well as the TLS data, additional nearby measurements of the wind speed through a CSAT 3D sonic anemometer and sediment transport using a Sensit and Wenglor fork sensors. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2025 |
| Provided To Others? | Yes |
| Impact | Improve our understanding of protodune dynamics |
| URL | https://www2.bgs.ac.uk/nationalgeosciencedatacentre/citedData/catalogue/95fb2393-954a-4217-86aa-cb10... |
| Title | Surface and Meteorological Data of Ripple and Saltation Dynamics at Medano Creek Area, Great Sand Dunes National Park, Colorado, USA on 5-11th April 2022 |
| Description | Dataset of ripples and saltation |
| Type Of Material | Database/Collection of data |
| Year Produced | 2023 |
| Provided To Others? | Yes |
| Impact | Unique dataset |
| URL | https://www2.bgs.ac.uk/nationalgeosciencedatacentre/citedData/catalogue/738dc233-3bd7-4174-aa98-8c33... |
| Description | CLIMATE+ School Talk |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Schools |
| Results and Impact | A CLIMATE+ Deserts Talk to Secondary School Geography Students, hosted by Lancing School, and part of a broader CLIMATE+ series. I gave a talk on fieldwork and teh TOAD project. It was supposed to be live in the field in Colorado, but, due to Covid-19 fieldwork was not possible and so the talk was given from home instead. It was well recieved with students asking questions on the online chat. |
| Year(s) Of Engagement Activity | 2020 |
| URL | https://climateplus147581778.wordpress.com/ |
| Description | Department seminar |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Undergraduate students |
| Results and Impact | Invited department seminar entitled 'Harnessing the noise from ground-based lidar data to investigate process-form feedbacks in dynamic desert landscapes'. Given at Texas A&M University, Department of Geology and Geophysics, USA, Halbouty Invited Seminar, 8th February 2019. |
| Year(s) Of Engagement Activity | 2018 |
| Description | ISAR Virtuaeolian Seminar |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Co-gave a International Society of Aeolian Research Virtuaeolian Online Seminar entitled ''Intersection of Field and Lab Measurement. Where's it at?' with Prof Cheryl Mckenna Neuman from Trent University, Canada. This was both attended live but is also now available to watch (25 people have viewed it), and on the society website. |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://youtu.be/RRH4Elr_yms?si=45xlIxYthGF4LbYp |
| Description | International Conference on Aeolian Research |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Two talks were given during the conference to an aeolian research audience. |
| Year(s) Of Engagement Activity | 2023 |
| URL | https://www.icarxi.com/ |
| Description | Interview for CrowdScience Radio Programme |
| Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | Interviewed for CrowdScience episode 'Where does the sand in a desert come from?' This was broadcast on BBC World Service around the world and also available online as a podcast. It was also highlighted in 'Pick of the World' as one of the top BBC World Service Programmes engaging with listeners that week (https://www.bbc.co.uk/programmes/w3ct41y1). |
| Year(s) Of Engagement Activity | 2023 |
| URL | https://www.bbc.co.uk/programmes/w3ct3j84 |
| Description | Pint of Science talk |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Public/other audiences |
| Results and Impact | Science talk to general public as part of the Pint of Science series. Talk entitled What is a dune before it becomes a dune?. The pub was full (approximately 60 people), and some interesting questions were asked. |
| Year(s) Of Engagement Activity | 2024 |
| Description | Project partner invited seminar |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Study participants or study members |
| Results and Impact | Invited seminar presentation entitled 'The precursor to TOAD: protodune dynamics'. Given at Gobabeb Research and Training Centre, Namibia, 15th August 2018. |
| Year(s) Of Engagement Activity | 2018 |
| Description | Public lecture |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | Public lecture entitled 'Dune initiation and migration dynamics on the Skeleton Coast: insights from a Terrestrial Laser Scanner (TLS)'. Given at the Geological Society of Namibia, Windhoek, Namibia, 20th August 2018. |
| Year(s) Of Engagement Activity | 2018 |
| Description | Windy Day conference poster presentation |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Other audiences |
| Results and Impact | Poster presented at annual UK Windy Day conference: Delorme, P.M.T., Nield, J.M., Baddock, M.C., Wiggs, G.F.S., Best, J., Christensen, K. (2018) The Origin of Aeolian Dunes - TOAD, Windy Day, UCL, UK, October 2018. |
| Year(s) Of Engagement Activity | 2018 |