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We describe a simple adaptive quality control procedure that limits the impact of individual observations likely to be inconsistent with the state of the data assimilation system. It smoothly increases the observation error variance depending on the projected +increment, state error variance and so-called K-factor so that the resulting increment does not exceed the estimated state error times K. Because an estimate of the state error is readily available in the Kalman filter (KF), the method isdoi:10.1080/16000870.2017.1318031 fatcat:4jtre72jd5addprdhumzp36exa