Sun Zhaobo

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.

A Note on the Role of Meridional Wind Stress Anomalies and Heat Flux in ENSO Simulations

Four comparative experiments and some supplementary experiments were conducted to examine the role of meridional wind stress anomalies and heat flux variability in ENSO simulations by using a highresolution Ocean General Circulation Model (OGCM). The results indicate that changes in the direction and magnitude of meridional wind stress anomalies have little influence on ENSO simulations until meridional wind stress anomalies are unrealistically enlarged by a factor of 5.0. However, evidence of an impact on ENSO simulations due to heat flux variability was found. The simulated Niño-3 index without the effect of heat flux anomalies tended to be around 1.0° lower than the observed, as well as the control run, during the peak months of ENSO events.

A modeling study of the effects of anomalous snow cover over the Tibetan Plateau upon the South Asian summer monsoon

The effect of anomalous snow cover over the Tibetan Plateau upon the South Asian summer monsoon is investigated by numerical simulations using the NCAR regional climate model (RegCM2) into which gravity wave drag has been introduced. The simulations adopt relatively realistic snow mass forcings based on Scanning Multi-channel Microwave Radiometer (SMMR) pentad snow depth data. The physical mechanism and spatial structure of the sensitivity of the South Asian early summer monsoon to snow cover anomaly over the Tibetan Plateau are revealed. The main results are summarized as follows. The heavier than normal snow cover over the Plateau can obviously reduce the shortwave radiation absorbed by surface through the albedo effect, which is compensated by weaker upward sensible heat flux associated with colder surface temperature, whereas the effects of snow melting and evaporation are relatively smaller. The anomalies of surface heat fluxes can last until June and become unobvious in July. The decrease of the Plateau surface temperature caused by heavier snow cover reaches its maximum value from late April to early May. The atmospheric cooling in the mid-upper troposphere over the Plateau and its surrounding areas is most obvious in May and can keep a fairly strong intensity in June. In contrast, there is warming to the south of the Plateau in the mid-lower troposphere from April to June with a maximum value in May. The heavier snow cover over the Plateau can reduce the intensity of the South Asian summer monsoon and rainfall to some extent, but this influence is only obvious in early summer and almost disappears in later stages.

A New Multidimensional Time Series Forecasting Method Based on the EOF Iteration Scheme

In this paper a new mnultidimensional time series forecasting scheme based on the empirical orthogonal function (EOF) stepwise iteration process is introduced. The scheme is tested in a series of forecast experiments of Nino3 SST anomalies and Tahiti-Darwin SO index. The results show that the scheme is feasible and ENSO predictable.

A Method for Improving Simulation of PNA Teleconnection Interannual Variation in a Climate Model

Abstract The climate modeling community has been challenged to develop a method for improving the simulation of the Pacific-North America (PNA) teleconnection pattern in climate models. The accuracy of PNA teleconnection simulation is significantly improved by considering mesoscale convection contributions to sea surface fluxes. The variation in the PNA over the past 22 years was simulated by the Grid Atmospheric Model of IAP LASG version 1.0 (GAMIL1.0), which was guided by observational SST from January 1979 to December 2000. Results show that heating in the tropical central-eastern Pacific is simulated more realistically, and sea surface latent heat flux and precipitation anomalies are more similar to the reanalysis data when mesoscale enhancement is considered during the parameterization scheme of sea surface turbulent fluxes in GAMIL1.0. Realistic heating in the tropical central-eastern Pacific in turn significantly improves the simulation of interannual variation and spatial patterns of PNA.