A radar data quality control (QC) system is being developed for the real-time, continuously updateable NOWCAST system at the Naval Research Laboratory (NRL-NOWCAST) in Monterey, California. NRL has developed its own new radar QC algorithms, and is also working with the MIT Lincoln Laboratory (MIT LL), the National Center for Atmospheric Research (NCAR), the National Severe Storms Laboratory and the Cooperative Institute for Mesoscale Meteorological Studies at the University of Oklahoma (NSSL-OU) to obtain, adapt, integrate, test and install various types of recently-developed radar QC algorithms for use with NRL-NOWCAST. These algorithms work with volume scans of full-resolution Doppler radar data. Radar data QC can be divided into two categories: echo classification (EC) and calibration. New EC algorithms have recently demonstrated substantial success at separating the radar echoes of precipitation from other echo types, such as noise, normal propagation (NP) and anomalous propagation (AP) ground clutter, sea clutter, insects/clear-air, birds, second-trip echoes, and constant power function (CPF) artifacts. Radar data calibration methods assess the accuracy of both the data values and data coordinates. One calibration issue is aliased radial velocity data from precipitation and insect/clear-air returns, which if correctly de-aliased, afford the opportunity to estimate winds. Another calibration issue of concern to NRL is the processing of radar data from mobile platforms, such as US Navy ships. This processing requires corrections to the radial velocity data and the data-coordinates for the motion of the platform, as well as corrections for the altitude of the data coordinates due to the AP of the radar beam that frequently occurs within surface and evaporation ducts of the marine atmosphere. The goal of this work is to test the performance of the most current and promising radar data QC algorithms on archived data sets, both from ground- and sea-based radars, in order to determine the optimal combination for future real-time use within NRL-NOWCAST. NRL-NOWCAST currently ingests full-resolution Doppler radar data from both the Weather Surveillance Radar-1988 Doppler (WSR-88D) network and the US Department of Defense (DoD) Supplemental Weather Radar (SWR) at the Naval Air Station (NAS) in Fallon, NV. Various products are then created from these data for NRL-NOWCAST display. The radar data are also ingested into the COAMPS-0S (R) (Geiszler et al. 2004) data assimilation system at NRL. Figure 1 shows a flow chart that summarizes the processing stages and uses of radar data at NRL. Figure 2 shows an example of the NRL-NOWCAST demonstration site currently set up at Fallon, where the specific products displayed are only a few from a large list that may be chosen by the forecasters at the NAS. This paper presents a brief overview of the concepts behind the various EC and radial velocity de-aliasing algorithms under consideration. Test results from an NRL algorithm-testing platform will also be presented along with some previously published test results from the authors. Additional test results from the platform will be presented at the conference. Methods to address data-value and data coordinate calibration problems associated with Doppler radars onboard US Navy ships are currently being studied; a discussion on future work in this area will be outlined.