A conventional method to define short-term climate anomalies for atmospheric and oceanic variables,recommen-ded by the World Meteorological Organization(WMO),is the departure from a 30-yr climatological mean in the pre-ceding three decades.Such a method,however,introduces spurious errors such as sudden jumps and artificial trends.A new method,named a trend correctional method,is introduced to eliminate the errors.To demonstrate the capabil-ity of this new method,we examine a set of idealized cases first by superposing a“true”interannual or interdecadal signal onto a linear or a nonlinear trend.Comparing to the conventional method,the trend correctional method is able to retain,to a large extent,the“true”anomaly signals.Next,we examined real-time indices.The anomaly time series derived based on the trend correctional method show a better agreement with the observed anomaly series.The root-mean-square error is greatly improved,comparing to that calculated based on the conventional method.Therefore,the results from both the idealized and real cases demonstrate that the new method has a clear advantage to the con-ventional method in deriving true climate anomalies,in particular under the ongoing global warming circumstance.