This poster will focus on the KAZR data quality, calibrations, and corrections. We use an intermode cross comparison to determine relative offsets, before a comparison with nearby disdrometers to establish a baseline. This is then evaluated against the nearby CSU X-band radar.
This process results in a calibrated dataset available on ARM Data Discovery and will include corrected reflectivity, meteorological echo masks, and a data quality flag to denote time periods when there were data quality issues, often accompanied by individual data quality reports. This dataset is then used in ARM value added products, such as the Active Remote Sensing of CLouds (ARSCL) product.
This work will show the combination of multiple techniques and cross comparisons with external instrumentation used to calibrate and improve radar data quality, which allows for a much more trustworthy dataset for scientific analysis.

