Simulation of Seasonal Circulations and Thermohaline Variabilities in the Gulf of Thailand

Based on the Princeton Ocean Model （POM）, the seasonal thermohaline feature and the ocean circulation in the Gulf of Thailand （GOT）, situated between 6°N to 14°N latitude and 99°E to 105°E longitude, were studied numerically with 37 × 97 orthogonal curvilinear grid and 10 vertical sigma levels conforming to a realistic bottom topography. A spin-up phase of the first model run was executed using wind stress calculated from climatological monthly mean wind, restoring-type surface heat and salt, and climatological monthly mean fresh water flux data. In this paper, the temperature and salinity fields taken from Levitus94 data sets and the calculated temperature and salinity from the model run for 12-month mean and for each season are presented where the winter, summer, rainy, and end of the rainy seasons of Thailand are represented by the months January, April, July, and October, respectively. The simulated circulations are also described. The results show that the temperature in the GoT is warmer than the temperature of the other parts connected to the South China Sea （SCS）. At any depth of inflow from SCS into the GoT, the salinity is high, but in the outflow from the GoT at the surface, the salinity is low. The strong circulations are clockwise during summer and the rainy seasons of Thailand, which are the East Asian monsoon periods, northeasterly and southwesterly during summer. They occur near Pattani and Narathiwat provinces during summer and in the central GoT during the rainy seasons. Sensitivity experiments were designed to investigate the effects of wind forcing and open boundary conditions. Wind forcing is shown to be the important factor for generating the circulation in the GoT. The lateral velocity at the open boundaries is of considerable importance to current circulation for the rainy and end of the rainy seasons, with insignificant effect for the winter and summer seasons of Thailand.

Carbon Monoxide Emission and Concentration Models for Chiang Mai Urban Area

An emission inventory containing emissions from traffic and other sources was complied. Based on the analysis, Carbon Monoxide （CO） emissions from traffic play a very important role in CO levels in Chiang Mai area. Analysis showed that CO emissions from traffic during rush hours contributed approximately 90% of total CO emissions. Regional Atmospheric Modeling System （RAMS） was applied to simulate wind fields and temperatures in the Chiang Mai area, and eight ca^es were selected to study annual variations in wind fields and temperatures. Model results can reflect major features of wind fields and diurnal variations in temperatures. For evaluating the model performance, model results were compared with observed wind speed, wind direction and temperature, which were monitored at a meteorological tower. Comparison showed that model results are in good agreement with observations, and the model captured many of the observed features. HYbrid Particle And Concentration Transport model （HYPACT） was used to simulate CO concentration in the Chiang Mai area. Model results generally agree well with observed CO concentrations at the air quality monitoring stations, and can explain observed CO diurnal variations.

A New Lagrangian-Eulerian Coupling Model System

A new Lagrangian—Eulerian coupling model system is developed to study regional air quality. The system consists of mesoscale dynamical meteorological model (MM), Monte—Carlo model (MCM), parameterized model on planetary boundary layer (PBL) turbulent statistics, dry and wet removal model, and Eulerian nonlinear chemical model (ENCM). The physical, chemical and biological processes on air pollutants are considered comprehensively. 3—D distribution laws tor acidic gaseous pollutants (SO2 and NOx) emitted by Thai Mae Moh Power Plant and the secondary pollutants are studied in detail. The results simulated by the coupling model system are in good agreement with observational concentration data. Key words MM - MCM - ENCM - Coupling model system The authors wish to express their thanks to Prof. Zeng Q. C. for his support to this research and to Dr. Han Z. W. and Zhang M. G. for their help in programming and numerical calculation of IAP, Chinese Academy of Sciences. Thanks are also due to NSTD and EGAT in Thailand for supporting this research.