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Data used in 'Local Wind Regime Induced by Giant Linear Dunes: Comparison of ERA5-Land Reanalysis with Surface Measurements.'

Data used in 'Local Wind Regime Induced by Giant Linear Dunes: Comparison of ERA5-Land Reanalysis with Surface Measurements.'
Data used in 'Local Wind Regime Induced by Giant Linear Dunes: Comparison of ERA5-Land Reanalysis with Surface Measurements.'
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.
Zenodo
Claudin, Philippe
bc540459-6b06-4c62-a8ea-2b05b760b3ad
Baddock, Mattew
608a043c-3fa1-421f-bd92-4fce325bfd1f
Nield, Joanna M.
173be2c5-b953-481a-abc4-c095e5e4b790
Delorme, Pauline
d7e1a2d1-82e0-4c82-ae92-75d8ada3e51e
Gadal, Cyril
8762ef3e-0a5b-44d3-837e-fb51d0a646b3
Wiggs, Giles
0b574ec8-fcd5-43b8-8b0b-0c84a01499d4
Narteau, Clément
44f8a32e-3f2a-4ded-98cd-3d467dd83dc0
Claudin, Philippe
bc540459-6b06-4c62-a8ea-2b05b760b3ad
Baddock, Mattew
608a043c-3fa1-421f-bd92-4fce325bfd1f
Nield, Joanna M.
173be2c5-b953-481a-abc4-c095e5e4b790
Delorme, Pauline
d7e1a2d1-82e0-4c82-ae92-75d8ada3e51e
Gadal, Cyril
8762ef3e-0a5b-44d3-837e-fb51d0a646b3
Wiggs, Giles
0b574ec8-fcd5-43b8-8b0b-0c84a01499d4
Narteau, Clément
44f8a32e-3f2a-4ded-98cd-3d467dd83dc0

(2022) Data used in 'Local Wind Regime Induced by Giant Linear Dunes: Comparison of ERA5-Land Reanalysis with Surface Measurements.'. Zenodo doi:10.5281/zenodo.6343137 [Dataset]

Record type: Dataset

Abstract

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.

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Published date: 10 March 2022

Identifiers

Local EPrints ID: 474101
URI: http://eprints.soton.ac.uk/id/eprint/474101
PURE UUID: 1ae89b13-6ba7-4313-bd86-5dbe5f22499b
ORCID for Joanna M. Nield: ORCID iD orcid.org/0000-0002-2657-0525

Catalogue record

Date deposited: 13 Feb 2023 18:09
Last modified: 21 Nov 2023 02:41

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Contributors

Contributor: Philippe Claudin
Contributor: Mattew Baddock
Contributor: Joanna M. Nield ORCID iD
Contributor: Pauline Delorme
Contributor: Cyril Gadal
Contributor: Giles Wiggs
Contributor: Clément Narteau

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