Sensitivity of Dynamical Intraseasonal Prediction Skills to Different Initial Conditions

AbstractPredictability of intraseasonal oscillation (ISO) relies on both initial conditions and lower boundary conditions (or atmosphere–ocean interaction). The atmospheric reanalysis datasets are commonly used as initial conditions. Here, the biases of three reanalysis datasets [the NCEP reanalysis 1 and 2 (NCEP-R1 and -R2) and the ECMWF Re-Analysis Interim (ERA-Interim)] in describing ISO were briefly revealed and the impacts of these biases as initial conditions on ISO prediction skills were assessed. A signal-recovery method is proposed to improve ISO prediction.Although all three reanalyses underestimate the intensity of the equatorial eastward-propagating ISO, the overall quality of the ERA-Interim is better than the NCEP-R1 and -R2. When these reanalyses are used as initial conditions in the ECHAM4-University of Hawaii hybrid coupled model (UH-HCM), skillful ISO prediction reaches only about 1 week for both the 850-hPa zonal winds (U850) and rainfall over Southeast Asia and the global tropics. An e...

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