Potential Predictability of Summer Mean Precipitation in a Dynamical Seasonal Prediction System with Systematic Error Correction

Abstract

Potential predictability of summer mean precipitation over the globe is investigated using data obtained from seasonal prediction experiments for 21 yr from 1979 to 1999 using the Korea Meteorological Administration–Seoul National University (KMA–SNU) seasonal prediction system. This experiment is a part of the Climate Variability and Predictability Program (CLIVAR) Seasonal Model Intercomparison Project II (SMIP II). The observed SSTs are used for the external boundary condition of the model integration; thus, the present study assesses the upper limit of predictability of the seasonal prediction system. The analysis shows that the tropical precipitation is largely controlled by the given SST condition and is thus predictable, particularly in the ENSO region. But the extratropical precipitation is less predictable due to the large contribution of the internal atmospheric processes to the seasonal mean. The systematic error of the ensemble mean prediction is particularly large in the subtropical ... Abstract Potential predictability of summer mean precipitation over the globe is investigated using data obtained from seasonal prediction experiments for 21 yr from 1979 to 1999 using the Korea Meteorological Administration–Seoul National University (KMA–SNU) seasonal prediction system. This experiment is a part of the Climate Variability and Predictability Program (CLIVAR) Seasonal Model Intercomparison Project II (SMIP II). The observed SSTs are used for the external boundary condition of the model integration; thus, the present study assesses the upper limit of predictability of the seasonal prediction system. The analysis shows that the tropical precipitation is largely controlled by the given SST condition and is thus predictable, particularly in the ENSO region. But the extratropical precipitation is less predictable due to the large contribution of the internal atmospheric processes to the seasonal mean. The systematic error of the ensemble mean prediction is particularly large in the subtropical ...