Underwater optical environment in the Upper Gulf of Thailand

Because the composition of coastal water is full of variety by each region, relationship between chlorophyll-a (chl.a) concentration as a indicator of primary productivity derived by satellite ocean color data and in situ data of chl.a may not be same always. Those relations or algorithms should be verified at each coastal water for managing coastal environment. Coastal ocean color algorithms should be built up at each coastal water or at least should be verified by wide range field data for practical application at each region. Intensive research cruises were conducted at the Upper Gulf of Thailand. Optical survey using PRR (Profiling Reflectance Radiometer) showed the character of the Upper Gulf water. Under water optical algorithms for that water were suggested by these survey data. Optical depths in the Gulf of Thailand were also measured to know the compensation depth for primary production. Although the transparency measured by Secchi disk is not so large and surface water looks very turbid, the light energies are reaching to near bottom at almost all stations of the upper Gulf. It suggests that the turbidity of this water were mainly composed of scattering material like as clay mineral rather than absorbing material like as phytoplankton pigment or CDOM

MODIS-derived green Noctiluca blooms in the upper Gulf of Thailand: Algorithm development and seasonal variation mapping

In recent decades, red tides of non-toxic harmful algal blooms have frequently occurred in monsoon-influenced tropical areas, particularly the green form of Noctiluca scintillans (hereafter green Noctiluca). However, our understanding of the mechanism of red tide formation is hindered by spatial and temporal constraints of field data. In this study, we used moderate resolution imaging spectroradiometer (MODIS) ocean color data along with a locally developed algal-bloom classification algorithm to investigate the seasonal variability of dominant red tides across the upper Gulf of Thailand (uGoT). During our July 2018 observation, a super green Noctiluca bloom with extraordinarily high chl-a (>1,469 mg m-3) displayed a distinct spectral reflectance characteristic among red tides in blue-to-green and red-to-near infrared wavelengths. According to the distinctive in situ hyperspectral characteristics of uGoT algal blooms, we developed a classification algorithm for MODIS normalized at 488, 531, and 667 nm, which successfully discriminated green Noctiluca in three levels of blooms, namely, super (100%), strong (>80%), and weak (>40%), from other algal blooms (i.e., dinoflagellates, diatoms, cyanobacteria, and mixed red tide species) as well as non-bloom oceanic and coastal waters using MODIS data, as confirmed by uGoT red tide reports. Monthly MODIS-based discrimination composites from 2003 to 2021 revealed seasonal variability in the surface distribution and bloom frequency of green Noctiluca and other red tides according to the Asian monsoon seasons: the southwest monsoon (May–September) and the northeast monsoon (October–January of the following year). Green Noctiluca blooms occurred farther from the shore and estuaries than other red tides (dinoflagellates and cyanobacteria), and were much more frequent than other red tides between the Tha Chin and Chao Phraya River mouths during the non-monsoon period (February to April). The frequency and distribution of green Noctiluca blooms, as well as other algal blooms, varied with the monsoon season. By comparing MODIS-derived algal blooms to monsoon-induced factors (i.e., sea surface winds, precipitation, and river discharge), we present an unprecedented overview of the spatial and temporal dynamics of red tides throughout the uGoT under Asian monsoon conditions. This research contributes to our understanding of the impact of climate change on phytoplankton dynamics

Meris imageries to investigate surface chlorophyll in the upper gulf of Thailand

Medium Resolution Imaging Spectrometer Instrument (MERIS) Level 2 data were used to investigate the seasonal patterns of surface chlorophyll-a (chl-a) distribution related to eutrophic conditions in the upper Gulf of Thailand (UGoT). Initial overestimation of chl-a using MERIS Rrs was reduced when Rrs ratios were used. A local in-water algorithm, named Chula algorithm, was embedded into MERIS data due to higher accuracy in chl-a prediction, compared to standard MERIS chl-a products. Subsequent MERIS-derived chl-a maps revealed that during the northeast monsoon, high chl-a water moves westward, while during the southwest monsoon, it accumulates in the northeast corner of UGoT. These seasonal patterns of movement agree well with previous investigations on seasonal circulation and red tides in UGoT. Compared to other satellite data having larger spatial resolutions, MERIS chl-a images provide more details on chl-a distribution which may be useful for oceanographic studies in such a small coastal area as UGoT

Meris imageries to investigate surface chlorophyll in the upper gulf of Thailand

Medium Resolution Imaging Spectrometer Instrument (MERIS) Level 2 data were used to investigate the seasonal patterns of surface chlorophyll-a (chl-a) distribution related to eutrophic conditions in the upper Gulf of Thailand (UGoT). Initial overestimation of chl-a using MERIS Rrs was reduced when Rrs ratios were used. A local in-water algorithm, named Chula algorithm, was embedded into MERIS data due to higher accuracy in chl-a prediction, compared to standard MERIS chl-a products. Subsequent MERIS-derived chl-a maps revealed that during the northeast monsoon, high chl-a water moves westward, while during the southwest monsoon, it accumulates in the northeast corner of UGoT. These seasonal patterns of movement agree well with previous investigations on seasonal circulation and red tides in UGoT. Compared to other satellite data having larger spatial resolutions, MERIS chl-a images provide more details on chl-a distribution which may be useful for oceanographic studies in such a small coastal area as UGoT