An Improved Method for Defining Short-Term Climate Anomalies

Abstract

A conventional method to define short-term climate anomalies for atmospheric and oceanic variables, recommended by the World Meteorological Organization (WMO), is the departure from a 30-yr climatological mean in the preceding 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 capability 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 conventional method in deriving true climate anomalies, in particular under the ongoing global warming circumstance.