Two bottom-mounted ADCPs were deployed in the coastal waters off the National Museum of Marine Biology and Aquarium at southwestern Taiwan coast from June 5, 2004 to December 20, 2005. The long-term observational dataset of wind, currents, water level and drifters were analyzed here to investigate the mechanism and seasonal variations of tidal and subtidal flows. Diurnal tidal constituent of K dominates the tidal energy in this area. The calculated form ratio is 1.53, indicating that the tide is of the diurnal type. Tidal current direction is consistent with the local coastal line, with the principal axis in the NNE-SSW orientation. The tidal waves of two major constituents¡]K an M ¡^are found to exist in the form of propagating waves in this region, rather than the form of standing waves as was found in the east coast of central Taiwan Strait. The subtidal currents flow toward the south with a speed of about 20-50 cm/s during the winter northeastern monsoon. On the other hand, subtidal flow speed is smaller but still toward the south during the summer southwestern monsoon. Current speed in the surface layer is larger than that in the mid and bottom layers. The persistent southward flow in this region is also found to correlate with the wind stress curl. When the wind stress curl reaches a maximum negative value in winter, an anticyclonic eddy develops and the flow in the study area is toward the south. Analysis of Argos drifter data reveal the existence of anticyclone off the southwestern Taiwan coast. Surface drifters were also deployed in this area, and the trajectories indicate that general flow patterns are toward the south. This finding is consistent with the progressive vector diagram from the moored ADCP current data. To summarize, a persistent southward flow exists in the study region all year round. However, the flow intensifies in winter and decays in summer. The southward flow is also associated with the anticyclonic eddy driven by the negative wind stress curl in winter. The intrusion of Kuroshio water from the Luzon Strait into the northern South China Sea is the possible source of water mass for this phenomenon.

Tropospheric ozone plays an important role in the atmosphere especially towards climate change and air quality. In this study, characteristics of tropospheric ozone over the South African Highveld are investigated using the ozonesonde data collected at Irene weather station (25.9°S, 28.2°E, and 1523 m asl) for the period 1990 to 1993 and 1999 to 2003. It was found that synoptic systems have an effect on the vertical distribution of tropospheric ozone. Ozone stratification appeared during anticyclonic conditions as displayed by a continental high ozone profile. During the ridging high, low ozone concentrations are observed with a strong ozone gradient between 10 and 12 km. Ozone enhancement appeared in the lower altitudes, <4 km, in both the ridging high and the westerly disturbance ozone profiles. Ozone profiles exhibited higher ozone concentrations during the westerly wave conditions. Tropospheric ozone over the South African Highveld region follows a clear annual cycle with lower ozone concentrations observed during autumn and higher ozone concentrations during spring. Summer ozone profiles had high ozone concentrations from the earth’s surface up to 9 km compared to winter ozone profiles. However, winter ozone profiles exhibited higher ozone concentrations than summer ozone profiles and they were characterised by a strong ozone gradient at 12 km. Ozone profiles obtained during the Southern African Fire-Atmosphere Research Initiative conducted in 1992 (SAFARI-92) displayed lower ozone concentrations than ozone profiles from the Southern African Regional Science Initiative conducted during 2000 (SAFARI- 2000). Therefore, it is apparent tropospheric ozone over the South African Highveld has increased over the past decade.

Bio-optical variability of surface waters in Northeastern Gulf of Mexico (NEGOM) was examined using satellite and in situ data. Relatively high chlorophyll-a concentration (chl>=1 mg m-3) and high colored dissolved organic mater (ag443>=0.1 m-1) were generally observed inshore, near major river mouths, and in plumes of Mississippi River water that extended offshore during the three consecutive summer seasons (1998, 1999, and 2000). River discharge dominated chlorophyll-a concentration variability inshore, particularly near major river mouths. Strong interannual variability in chlorophyll-a concentration was observed inshore from Escambia to Tampa Bay region during the winter to spring transition, which was different in 1998 compared to the winter to spring transition in 1999 and 2000. This was related to higher fresh water discharge during the 1997-1998 El Niño-Southern Oscillation event as well as strong upwelling in spring 1998. The Mississippi plume extended >500 km southeast of the Mississippi delta and up to the Florida Keys was observed for the periods extending over 14 weeks between May and September every year of the study. In general, ag443 covaried linearly and inversely with salinity inshore during spring and fall, indicating conservative mixing. The NEGOM salinity-ag443 relationship of fall 1998, i.e., Salinity=36.59-29.86*ag443 (n=8771, r2=0.86; 0.01<=ag443<=0.52, 16 <=S<=36), served as the best predictor of NEGOM salinity based on in situ ag443 observations for spring and fall seasons from all years (<3% mean percentage errors; corresponding to <1.03 psu). This may help estimate salinity from satellite ocean color data, but further testing using data from multiple years is needed to improve such relationship. While river discharge was an important source of colored dissolved organic matter (CDOM), phytoplankton blooms also contributed to CDOM formation in the NEGOM. Using a pigment index of phytoplankton taxonomic groups, the variability in biomass proportion of microphytoplankton explained up to 76% of the variability of the average of normalized phytoplankton absorption coefficients (545, 625, and 673 nm). The clorophyll-specific absorption coefficient, a*ph(440), varies by a factor of 7 (0.02-0.15 m2mg-1). Particle size and pigment composition played important roles in determining a*ph(440) variability. This must be accounted for in chlorophyll-a concentration algorithms based on aph.

The objective of this dissertation is to gain a better understanding of the environmental and climatic effects on the temporal and spatial variability of phytoplankton biomass along the West Florida Shelf. Chapter 1 examines temporal and spatial patterns in chlorophyll concentrations using satellite data collected between 1997 and 2003. Chlorophyll data derived from the SeaWiFS sensor are validated with in-situ data and analyzed. Wind, current, sea surface temperature, river, and rain data are used to better understand the factors responsible for the patterns observed in the satellite data. My question is whether the standard OC4 algorithm is adequate for studying short-term variability of chlorophyll concentrations along the WFS. I will examine temporal and spatial trends using the OC4 and compare them to the Carder semianalytical algorithm which uses remote sensing reflectances at 412nm, 443nm, 490nm,and 555nm to estimate chlorophyll concentrations separately from CDOM estimates. In Chapters 2 and 3 the potential problems due to CDOM and bottom reflectance are examined. In Chapter 2 I analyze the influence of riverine induced CDOM. Water leaving radiances are analyzed in an effort to discriminate true chlorophyll patterns from CDOM contaminated signals. Chapter 3 examines the impact of bottom reflectance on the satellite signal by using the percentage of remote sensing reflectance at a wavelength of 555 to differentiate between optically shallow waters and optically deep waters. Optically shallow waters are defined as those with the percentage of Rrs at 555 due to bottom reflectance greater than or equal to 25 percent, while optically deep waters have percent bottom reflectance less than or equal to 25 percent. These analyses will help assess the validity of the temporal and spatial patterns ofchlorophyll concentration observed with the SeaWiFS data described in Chapter 1.