King Air Users Information
Frequently asked questions
Requesting Support - Data -
Instruments & Measurements
- How do I request the Uwyo King Air?
Please see our page on Requesting Support
- Is the Wyoming Cloud Radar (WCR) available for request on other aircraft?
Yes, the WCR is a separate facility instrument that can be requested along with the UWyo
King Air facility, the NCAR C-130 facility, or as a standalone instrument.
Please see the WCR page for more information.
- Is the Wyoming Cloud Lidar (WCL) available for request on other aircraft?
Yes, the WCL is a separate facility instrument that can be requested along with the UWyo
King Air facility or the NCAR C-130 facility.
Please see the WCL page for more information.
- How do I request WCR data?
Please see the WCR request page.
Instrument and Measurement (variables)
- Is there software available for viewing King Air data files?
Our netCDF files contain all processed data. The file formats follow
NCAR-RAF/nimbus conventions. EOL has several software packages
for viewing these files--
visit the EOL page to learn more or download.
'ncplot' can be used to plot time series of all 1D variables within
the netcdf files.
'ncpp' can be used to plot particle spectra for 2D variables in the
'xpms2d' can be used to display images from OAP probes (such as the
2DC, 2DP, and CIP).
All of these programs run only under Linux or MacOSx.
Aeros is a realtime and post-analysis display package that can run under
Linux, Mac, and Windows. It can provide visualization for time series,
particle spectra, flight tracks.
AWOT is a Python
package that reads in multiple NetCDF formats and can
be customized to the data file variable names. It allows visualization
of flight track and time series data.
For more in-depth analysis, most folks here use Python, IDL, or MATLAB.
Examples can be found at the
One could just as easily use C, FORTRAN, etc --- anything with
build-in netcdf libraries.
- We have the option of using reverse-flow temperature or the Rosemont
temperature. Do you have any information on which is more accurate in
the OWLeS setting? Or is there some other temperature sensor we've
missed which you think would work better"?
Reverse Flow temperature is always preferable. In terms of accuracy
(outside of clouds) reverse flow (RFT) and Rosemount is about the same.
RFT provides better temporal response at all times. In cloud, RFT is
less susceptible to wetting (although wetting does occur under various
conditions). Most recent reference for RFT wetting and corrections that
can be applied is Wang and Geerts (2009) in JAOTech. This provides
references to earlier work with the RFT and discusses ranges of
temperature over which one must consider wetting in cloud.
- Air pressure is measured by the Weston Digital instrument and by the
Rosemont probes - again, do you know which would you suggest using?
Rosemount HADS modules provide the best pressure measurement (ps_hads_a
is the the static pressure used in calculations). Overall accuracy of
static pressure measurement *tends* to be more a function of our ability
to compute the static deficit than the ability of the instrument to
measure pressure. Discussion of this correction that is done and applied
to the UWKA static pressure measurements is given in Rodi and Leon (2012)
in Atmos. Meas. Tech.
- Mixing ratio is measured by the LICOR instrument, denoted on the in
situ files as 'variable #26, h2omx, sps25time, H2O mixing ratio, LICOR'.
It is also measured by another instrument: denoted as 'variable #16,
mr, sps25time, Mixing Ratio'. Do you know which of these is the better
one to use?
Incidentally, do you know which instrument measures the variable-16
There are two instruments that provide measures of water vapor--chilled
mirror and Licor6262. The Chilled mirror inherently measures the dewpoint
(and there exists some ambiguity of what measure is actually provides at
temperatures below zero - dewpoint or frostpoint). It is *slow* response
(10s of seconds at cold T's; a few seconds at warmer T's). The Licor6262
responds to the number of h2o molecules in a volume of air so is most
closely related to mixing ratio and it is a much faster response device
(<1 s). Its accuracy is partly a function of the number of vapor molecules
(as # of molecules decreases, SNR goes down). At low dewpoints, -20 or
lower, it is quite noisy. The variable 'h2omx' comes from the licor.
The variable 'mr' comes from the chilled mirror. Which to use depends on
the environment and how you want to use the data. In terms of absolute
accuracy, over long enough averaging, the chilled mirror tends to be more
accurate while the Licor instrument is prone to some drift. If looking at
fluxes, then the Licor is by far your best bet.
- Latitude and Longitude are measured by the Honeywell, Ashtec, and
Applanix instruments. Do you know which is most appropriate for OWLeS?
We've had an explosion of these variables recently. Until recently
(before OwLES) we provided a measure of latitude and longitude that
combined GPS measures from the Ashtec with high frequency measures from
the Honeywell. Prior to OwLES we added the Applanix which is a combined
GPS/INS instrument that provides the complimentary filtered measures both
'on the fly' and through post processing utilizing superior GPS corrections.
To make a long story not-so-short, currently the best measure is 'AVlat',
'AVlon'. Variables that start with 'av' indicate real-time applanix
variables; those with 'AV' are post-processed applanix variables.
Generally, all aircraft position variables are best to use the post-processed
applanix variables (including roll, pitch, heading, etc).
NOTE that for latitude and longitude we provide are best estimate for
that project in the variables 'LAT' & 'LON' (and 'LATC' & LONC') to be
consistent with variables definitions used in NCAR software packages. For
the OWLES data set these variables will be identical to AVlat and AVlon.
- Altitude is measured many different ways: pressure altitude,
hypsometric altitude, radar altitude, Honeywell, the Ashtec GPS (real-time
or post-processed by the looks of it), and Applanix instrument (various
options: ellipsoid, real-time, orthometric). Do you have a preference for
one of these variables? In particular a good pressure altitude and a good
absolute altitude would both be of use.
This really depends on what you are trying to do with altitude. When I am
plotting a sounding, for instance, I typically use a gps altitude. I tend to
not like pressure altitude for most applications, but at times it is the
- In terms of winds, we have most often been using the Applanix
post-processed data (AVuwind, etc. in the in situ files). We're aware that
the Honeywell instrument also measured horizontal velocity. There is also an
option of using real-time or post-processed data (we've usually opted for the
post-processed data when available). Which set of winds do you suggest we use?
Right on for your choice of winds--post processed applanix is our current best estimate.
- We also have a question about plane-diagnostics measurements.
We're aware of independent measurements by the Honeywell instrument and the
Applanix instrument of pitch angle, roll angle, pitch angle rate, roll angle
rate, yaw angle rate (or body-axes rates). Is the set of plane diagnostics
by one of the instruments preferable to that from the other?
See answer for #4.
- We are looking at data processed from the OAPs (CIP, 2DC, 2DP) and
notice that for 3 different variables - mass0_..., mass1_..., mass2_..., the
mass varies wildly. The data were collected in all liquid clouds with
reasonably high cloud liquid water contents. Can you explain why the
difference in the 3 calculations and suggest which might provide the best
The difference in the variables is based on the difference in techniques for
sizing particles/images. The 0 method uses the x-direction (along flight)
which corresponds to the direction the probe is moving The 1 method uses the
y-direction (across flight) which corresponds to the direction along the diode
array The 2 method uses the max of the 0 & 1 method.
For all water particles, the size of any individual particle should be the
same for 0 and 1 (and hence 2) assuming that the center of the particle is
within the diode array (because the particles are spheres...). However, we
also must consider artifacts. In high cloud water content clouds, the OAPs
will produce a lot of artifact images -- 'streakers'. These result from water
building up on the tips and 'streaking' through the sample volume, resulting
in long, thin images. These images have large sizes in the x-direction and
small sizes in the y-direction. Thus, the result is a significant mass for
method 1 and 3, and considerably less for method 2. In a perfect world we
would identify all of these as artifacts and then not be included in our
calculations, but there is always a trade-off between identifying ALL
artifacts and throwing out some real particles. Most are identified, but not all...
Since you are looking at mass, it doesn't take many very large 0 and 2
particles to contribute to a lot of mass.