Zhu Weijun

Causes of the Intraseasonal SST Variability in the Tropical Indian Ocean

Abstract Satellite observations reveal a much stronger intraseasonal sea surface temperature (SST) variability in the southern Indian Ocean along 5-10°S in boreal winter than in boreal summer. The cause of this seasonal dependence is studied using a 2½-layer ocean model forced by ERA-40 reanalysis products during 1987–2001. The simulated winter-summer asymmetry of the SST variability is consistent with the observed. A mixed-layer heat budget is analyzed. Mean surface westerlies along the ITCZ (5-10°S) in December-January-February (DJF) leads to an increased (decreased) evaporation in the westerly (easterly) phase of the intraseasonal oscillation (ISO), during which convection is also enhanced (suppressed). Thus the anomalous shortwave radiation, latent heat flux and entrainment effects are all in phase and produce strong SST signals. During June-July-August (JJA), mean easterlies prevail south of the equator. Anomalies of the shortwave radiation tend to be out of phase to those of the latent heat flux and ocean entrainment. This mutual cancellation leads to a weak SST response in boreal summer. The resultant SST tendency is further diminished by a deeper mixed layer in JJA compared to that in DJF. The strong intraseasonal SST response in boreal winter may exert a delayed feedback to the subsequent opposite phase of ISO, implying a two-way air-sea interaction scenario on the intraseasonal timescale.

Non-linear dynamic model retrieval of subtropical high based on empirical orthogonal function and genetic algorithm

Aiming at the difficulty of accurately constructing the dynamic model of subtropical high, based on the potential height field time series over 500 hPa layer of T106 numerical forecast products, by using EOF (empirical orthogonal function) temporal-spatial separation technique, the disassembled EOF time coefficients series were regarded as dynamical model variables, and dynamic system retrieval idea as well as genetic algorithm were introduced to make dynamical model parameters optimization search, then, a reasonable non-linear dynamic model of EOF time-coefficients was established. By dynamic model integral and EOF temporal-spatial components assembly, a mid-/long-term forecast of subtropical high was carried out. The experimental results show that the forecast results of dynamic model are superior to that of general numerical model forecast results. A new modeling idea and forecast technique is presented for diagnosing and forecasting such complicated weathers as subtropical high.