Atmospheric Radiation Measurement Climate Research Facility US Department of Energy

kazrarscl > Active Remote Sensing of CLouds (ARSCL) product using Ka-band ARM Zenith RadarsVAP Type(s) > Baseline • Evaluation

KAZRARSCL is a core ARM VAP which provides time vs. height information on lowest cloud base and cloud boundaries for up to 10 cloud layers.  In addition, it includes best-estimate cloud radar reflectivities corrected for gaseous attenuation, dealiased mean Doppler velocities, and a cloud (hydrometeor) mask, after flagging and removing vegetative and insect clutter returns.  The VAP merges cloud radar moments with collocated laser ceilometer, micropulse lidar, microwave radiometer, radiosonde and surface precipitation measurements to mitigate known deficiencies in single-instrument cloud sampling.  KAZRARSCL cloud properties are available at high temporal (4 s) and vertical (30 m) resolution at fixed and ARM Mobile Facility deployments, within approximately 2 months of data collection.

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KAZRARSCL is released in two stages, an early ‘.c0’ data level version (noncalibrated radar reflectivity factor Z) followed by a calibrated ‘.c1’ version, which replaces the ‘.c0’ version.  The ‘.c1’ files undergo radar mentor calibration to align radar Z measurements to operating conditions. Note that neither data level guarantees absolute calibration for quantitative uses of Z and both formats are suitable for relative ARSCL cloud property applications.

KAZRARSCL is a frequent selection among ARM users to inform on column (time-height) cloud properties (e.g. cloud base, thickness) or cloud frequency of occurrence.  The VAP also provides a convenient way to access consistently-gridded best-estimate cloud radar moments.

At fixed ARM sites, it provides an extended time record of observations, with data available since 2011. KAZRARSCL cloud base is determined using a combination of ceilometer and micropulse lidar, and is unaffected by subcloud attenuation in rain/drizzle. KAZRARSCL sensitivity to high altitude clouds and estimates of the cloud (echo) top or thickness may be suboptimal in multi-layer cloud or rainy conditions. For shallow cloud KAZRARSCL applications, there are ambiguities when identifying mixed cloud and insect echoes.  KAZRARSCL includes meteorological (cloud) and non-meteorological (e.g., biological/insect) flags to focus user attention on this potential issue. For additional information on KAZRARSCL, radar reflectivity factor Z measurement uncertainty and comparisons against standard references, please contact ARM Engineering or the ARM Translators.


The data set provides cloud boundaries and best-estimate radar moments.  These can be used to improve our understanding of cloud processes and in turn lead to improvements in climate and earth system models.


  • Fixed
  • AMF1
  • AMF2
  • AMF3

Data Details

Developed By Karen Johnson | Scott Giangrande
Contact Karen Johnson
Resource(s) Data Directory
Data format netCDF
Site ENA
Content time range 18 January 2011 - 30 September 2022
Attribute accuracy No formal attribute accuracy tests were conducted
Positional accuracy No formal positional accuracy tests were conducted
Data Consistency and Completeness Data set is considered complete for the information presented, as described in the abstract.Users are advised to read the rest of the metadata record carefully for additional details.
Access Restriction No access constraints are associated with this data.
Use Restriction No use constraints are associated with this data.
File naming convention Standard ARM naming convention: sss arsclkazr1kollias FF . dl . yyyymmdd . hhmmss .nc and sss arsclkazrbnd1kollias FF . dl . yyyymmdd . hhmmss .nc
Directory Organization no sub-directories


Zhang D, J Comstock, H Xie, and Z Wang. 2022. "Polar Aerosol Vertical Structures and Characteristics Observed with a High Spectral Resolution Lidar at the ARM NSA Observatory." Remote Sensing, 14(18), 10.3390/rs14184638.

Borque P, A Varble, and J Hardin. 2022. "Peak Rain Rate Sensitivity to Observed Cloud Condensation Nuclei and Turbulence in Continental Warm Shallow Clouds During CACTI." Journal of Geophysical Research: Atmospheres, , e2022JD036864, 10.1029/2022JD036864. ACCEPTED.

Wang M, K Balmes, T Thorsen, D Willick, and Q FU. 2022. "An Investigation of the Ice Cloud Detection Sensitivity of Cloud Radars Using the Raman Lidar at the ARM SGP Site." Remote Sensing, 14(14), 3466, 10.3390/rs14143466.

Daub B and N Lareau. 2022. "Observed Covariations in Boundary Layer and Cumulus Cloud Layer Processes." Journal of Applied Meteorology and Climatology, 61(10), 10.1175/JAMC-D-21-0213.1.

Van Weverberg K and C Morcrette. 2022. "Sensitivity of Cloud‐Radiative Effects to Cloud Fraction Parametrizations in Tropical, Mid‐Latitude and Arctic Kilometre‐Scale Simulations." Quarterly Journal of the Royal Meteorological Society, 148(746), 10.1002/qj.4325.

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Scott Giangrande
Brookhaven National Laboratory

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