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 pre...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 rootmean-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.展开更多
基金Supported by the National Natural Science Foundation of China(42088101)NOAA of US(NA18OAR4310298)National Science Foundation of US(AGS-2006553)。
文摘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 rootmean-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.
