The dataset consists of continuous recorded data from Hyperion microbarometer sensors, with a sampling rate of 500 Hz, and a weather sensor, sampling once per 15 minutes, deployed in Nevada. There are a total of 15 infrasound stations as part of this dataset. Specifically, we include 6 Hyperion stations that recorded data over the months of June & July 2018 that can be used to detect dust devils. We also include 15 stations that recorded data over July 4-9, 2018, which can be used to characterize background noise levels. The weather station data covers June & July of 2018. A full list of the locations of each sensor is provided in the following section and in the included Metadata.csv file.

The Hyperion data (6 stations) over June 1 July 31, 2018 is a total size of ~24 GB.
The Hyperion data (16 stations) over July 4-9, 2018 is a total size of ~5.5 GB.
The weather station data is a total size of 325 KB.

We acknowledge compilation of this data is financially supported through the NASA Solar System Workings program.

Description of the data and file structure

Weather data

Contained in a CSV file: WeatherStation_Data.csv
Note that if a measurement point was not collected, this will be denoted with the value -99.
The columns of the weather data file include the following information:
* Station - station identifier
* Date (YRMODY) - date of collection, formatted YRMODY, for example June 1, 2018 is formatted 180601
* Time - local time (15 minute increments) of collection, formatted HR:MN, for example 1:30pm is formatted 13:30
* Wind_Direction - azimuthal direction of wind (in degrees)
* Average_Wind_Speed (m/s) - average speed of wind (m/s) collected over the 15-minute time period
* Max_Wind_Speed (m/s) - maximum speed of wind (m/s) collected over the 15-minute time period
* Min_Wind_Speed (m/s) - minimum speed of wind (m/s) collected over the 15-minute time period
* Humidity - Mean relative humidity (%) collected over the 15-minute time period
* Temperature (ºC)- average temperature (degrees Celsius) collected over the 15-minute time period
* Pressure (hPa) - average pressure (hPa) collected over the 15-minute time period
* Voltage - Average battery voltage of sensor (in Volts) over the 15-minute time period
* Precipitation - inches of precipitation over the 15-minute period
* Sigma_Theta - standard deviation of wind direction (degrees) over the 15-minute period

Microbarometer data

Microbarometer infrasound data are included as miniseed files within each station's directory, which are included as zipped files for ease of access.
Microbarometer infrasound data miniseed files are formatted as:
data_sta/sta.chan.year.jday.00.00.00
Note that the sta corresponds to the station, chan to the channel (CDF), and jday to the Julian Day.

More information regarding miniseed file structure is available: http://ds.iris.edu/ds/nodes/dmc/data/formats/miniseed/
An example of reading in a miniseed file with python is provided in the Code/Software section below.

Microbarometer Metadata

Microbarometer metadata for each station is included in Metadata.csv (note that NA corresponds to Not-Applicable).
For each station the following information is provided in each column:
* Station - Station identification (e.g., D10M0 for an infrasound sensor and 09 for a weather sensor)
* Channel - Channel identification following waveform data standards for infrasound (CDF) and denoted 'Weather' for the weather sensor. CDF corresponds to a C: 250-1000 Hz sample rate, D: pressure sensor, and F: infrasound orientation (omnidirectional), as denoted in the Standard for Exchange of Earthquake Data Appendix A (https://www.fdsn.org/pdf/SEEDManual_V2.4.pdf).
* Gain: Gain on the signal (1 indicates no effective change in signal amplitude applied).
* Bitweight (Volts/Counts): Scalar correction required to be applied to the raw waveform infrasound data, which is recorded in counts.
* Volts to Pascals (Volts/Pa): Scalar correction required to be applied to the raw waveform infrasound data, which is recorded in counts. To obtain SI units of pressure for the dataset, the raw data (counts) would be scaled by Bitweight/Volts to Pascals for each sensor.
* Lat: Station latitude location in degrees.
* Lon: Station longitude location in degrees.
* Elev: Station elevation (from Mean Sea Level).
* RedNoise: Timeframe over which red noise of the data was estimated for this station.
* Detections: Timeframe over which detections of dust devils was performed for this station.

Sharing/Access information

A subset of this data is available via IRIS: https://ds.iris.edu/mda/21-020/ that captured the Dry Alluvium Geology experiment 1 to study the generation and propagation of seismic waves from underground explosions.

Code/Software

Example python code to read in a miniseed file:

import obspy
sta='D10M0'
jday='152'
quickfile=sta+'.CDF.2018.'+jday+'.00.00.00'
st=obspy.read('data_'+sta+'/'+quickfile)

Obspy also offers python tools to plot and view file metadata:
st.plot()
print(st[0].stats)

More information on obspy functions is available : https://docs.obspy.org/