Subseasonal-to-interdecadal variability of the Australian monsoon over North Queensland

Daily rainfall occurrence and amount at 11 stations over North Queensland are examined for summers 1958– 1998, using a Hidden Markov Model (HMM). Daily rainfall variability is described in terms of the occurrence of five discrete ‘weather states’, identified by the HMM. Three states are characterized respectively by very wet, moderately wet, and dry conditions at most stations; two states have enhanced rainfall along the coast and dry conditions inland. Each HMM rainfall state is associated with a distinct atmospheric circulation regime. The two wet states are accompanied by monsoonal circulation patterns with large-scale ascent, low-level inflow from the north-west, and a phase reversal with height; the dry state is characterized by circulation anomalies of the opposite sense. Two of the states show significant associations with midlatitude synoptic waves. Variability of the monsoon on time-scales from subseasonal to interdecadal is interpreted in terms of changes in the frequency of occurrence of the five HMM rainfall states. Large subseasonal variability is identified in terms of active and break phases, and a highly variable monsoon onset date. The occurrence of the very wet and dry states is somewhat modulated by the Madden–Julian oscillation. On interannual time-scales, there are clear relationships with the El Niño–Southern Oscillation and Indian Ocean sea surface temperatures (SSTs). Interdecadal monsoonal variability is characterized by stronger monsoons during the 1970s, and weaker monsoons plus an increased prevalence of drier states in the later part of the record. Stochastic simulations of daily rainfall occurrence and amount at the 11 stations are generated by introducing predictors based on large-scale precipitation from (a) reanalysis data, (b) an atmospheric general circulation model (GCM) run with observed SST forcing and (c) antecedent June–August Pacific SST anomalies. The reanalysis large-scale precipitation yields relatively accurate station-level simulations of the interannual variability of daily rainfall amount and occurrence, with rainfall intensity less well simulated. At some stations, interannual variations in 10-day dry-spell frequency are also simulated reasonably well. The interannual quality of the simulations is markedly degraded when the GCM simulations are used as inputs, while antecedent Pacific SST inputs yield an anomaly correlation skill comparable to that of the GCM.