King Air Users Information


Frequently asked questions

Requesting Support - Data - Instruments & Measurements

Requesting Support

  1. How do I request the Uwyo King Air?

    Please see our page on Requesting Support

  2. 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.

  3. 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.



Data


  1. How do I request WCR data?

    Please see the WCR request page.

Instrument and Measurement (variables)


  1. Is there software available for viewing King Air data files?

    Our netCDF files contain all processed data. The file formats follow the 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 netCDF files.
    '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 following repository.
    One could just as easily use C, FORTRAN, etc --- anything with build-in netcdf libraries.

  2. 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.

  3. 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.

  4. 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 mixing ratio?


    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.

  5. 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.

  6. 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 appropriate variable.

  7. 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.

  8. 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.

  9. 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 estimate?

    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.