HALO as a Cloud Observatory


Image from Stevens et al (2019)
HALO is configured to function as an airborne cloud observatory with a great variety of remote-sensing instruments on board along with a dropsonde launching system. For greater detail, refer to Stevens et al (2019). The instruments have been listed in the table below.

Name Instrument Quantities measured & derived products Type Detailed description of instrument Campaigns
BAHAMAS
(not shown in image)
Multiple sensors all over the aircraft fuselage such as five hole probe on boom, diode laser, etc. Aircraft state variables, position, three-dimensional turbulent winds, humidity, temperature and pressure In-situ DLR website All
Dropsondes Vaisala RD-94 sondes with AVAPS receiver on HALO (EUREC4A used RD-41) Vertical profiles of:
Temperature
Relative Humidity
Horizontal wind speed and direction

Derived Products:
Divergence
Vorticity
Vertical velocity
Moist static energy
Integrated water vapour (Precipitable water)
In-situ Wang et al (2015) 8-channel receiver for EUREC4A;
4-channel for campaigns earlier
HAMP Cloud Radar Ka-band (35 GHz)
mono-static, pulsed magnetron radar
Vertical profiles of:
Radar reflectivity
Linear Depolarization ratio 1)

Derived products:
Cloud objects
Cloud fraction
Active remote-sensing Ewald et al (2019) All
HAMP Radiometers Microwave radiometers in:
K-band (22- 31 GHz)
V-band (50 - 58 GHz)
W-band (90 GHz)
F-band (119 GHz) and
G-band (183 GHz)
Brightness Temperature

Derived products:
Liquid water path
Rain water path
Water vapour profiling
Water condensate (liquid/ice) path
Temperature profiling
Passive remote-sensing Mech et al (2014) All
SMART Visible and near-infrared (300 to 1000 nm)
2- to 3-nm spectral resolution [full width half maximum (FWHM)]

Shortwave infrared (1000 to 2200 nm)
10- to 15-nm spectral resolution (FWHM)
Downwelling irradiance
Upwelling radiance and irradiance

Derived products:
Cloud fraction
Cloud droplet density
Passive remote-sensing Wendisch et al (2016) NARVAL2, NAWDEX, EUREC4A
specMACS Cameras:
Visible and near-infrared (400 to 1,000 nm)
Shortwave infrared (1,000 to 2,500 nm)
2D polarized (RGGB + polarization Bayer Pattern)
Spectrally resolved line image

Derived products:
Cloud top temperature
Cloud mask (cloud fraction)
3D cloud field along flight path
Passive remote-sensing Ewald et al (2016) NARVAL2, NAWDEX;
Two lens-system with FoV overlap for EUREC4A
WALES High spectral resolution lidar

Multi-wavelength water vapor differential absorption lidar (DIAL)
Four wavelengths near 935 nm

Aerosol channels
532 and 1064 nm with depolarization
Vertical profiles of:
Backscatter
Extinction

Derived products:
Water vapour mixing ratio profiles
Cloud top mask
Aerosol optical depth
Ice water content
Active remote-sensing Wirth et al (2009) All
Velox Thermal Infrared Wavelength Imager Passive Remote-sensing EUREC4A

N.B.: The list of derived products is not an exhaustive list, and most of the listed ones are not from a single instrument, but are estimates of quantities using synergistic measurements from the various instruments on board.

Campaigns and Data

There is a unified dataset, developed by Konow et al (2018), available for all NARVAL campaigns and the NAWDEX campaign together, which integrates the data from the HAMP instruments along with the dropsonde data, over a uniform grid of 30 m resolution in the vertical. The dataset also includes auxiliary data from BAHAMAS. Along with the data, quick looks for all flights have been uploaded to the CERA database as auxiliary data. These datasets are available at:

Using the microwave measurements on board HALO, in combination with the cloud radar and lidar measurements, Jacob et al (2019) have calculated the liquid water path (LWP) and rain water path (RWP), using artificial neural network techniques for the NARVAL1 South and NARVAL2 campaigns. The dataset also includes integrated water vapor (IWV), along with auxiliary data from the radar and lidar. These are also available through the CERA database at:

All WALES data is available through the DLR Institute for Atmospheric Physics in the HALO database at:
German Aerospace Center (2016).

Although the data is not published yet, data from SpecMACS is available at the MACS-LMU server. Please contact Tobias Kölling (LMU) regarding any queries about these data.

Available from the HALO database here


1)
The radar also measures Doppler velocity. However, due to slight fluctuations in the aircraft's altitude, these estimations are not very reliable, as the order of magnitude of measured values is about the same as that of the uncertainty.