DOI: 10.5061/dryad.0cfxpnw7f
title: Dust devil detection microbarometer and weather – Summer 2018 data

description: 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, all deployed in the Mojave Desert in
 Nevada. There are a total of 16 infrasound stations as part of this
 dataset. Specifically, we include 7 Hyperion stations that recorded data
 over the months of June & July 2018 that can be used to detect
 dust devils. We also include 16 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.
description: This is raw data recorded by the Hyperion microbarometer sensors
 and by a nearby weather sensor. 
description: Data are CSV and miniSEED. There are multiple programs to open
 miniSEED files, including python's obspy package.
description: # Dust Devil Detection Microbarometer and Weather Summer 2018 Data --- 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:
 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
 (). * 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: 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 :