Sea Surface Temperature and Net Heat Flux Variation in the Gulf of Thailand using Buoy, Meteorological and Remote Sensing Data

The COVID 19 related social distancing is hypothesized can affect the environmental quality including the air and water quality. Correspondingly, this study aims to study how the reduction of activities of people living near the rivers and the coastal areas due to social distancing may decrease the discharges of materials and nutrients to the water body. The chlorophyll-a was used as bio indicators of nutrient contents related to the anthropogenic activities in the coast. The study was conducted in the Jakarta coast considering that this coast was surrounded by populated cities with total population equal to 16 million people. The chlorophyll-a was measured in mg/m3 and monitored using remote sensing data from January to April 2020 representing the period before and after the implementation of social distancing. The determinant environmental factor measured was sea surface temperature (0C). The study considered that there were reductions of levels and areas of chlorophyll-a in the coast. The chlorophyll-a levels were reduced from January to April (p<0.05). The chlorophyll-a levels for January, February, March, and April were 7.36 mg/m3 (95%CI: 6.34-8.37), 7.90 mg/m3 (95%CI: 7.32-8.47), 6.52 mg/m3 (95%CI: 5.37-7.66), and 4.21 mg/m3 (95%CI: 3.34-5.07) respectively. However, the differences of chlorophyll-a were not influenced by the sea surface temperature factor (p>0.05). Based on remote sensing data in January and February, the sizes of coastal areas with chlorophyll-a levels >7.00 mg/m3 were larger than areas observed in March and April. Contrarily, the coastal area sizes with low chlorophyll-a levels <5.00 mg/m3 were increasing in April. To conclude the dynamic of anthropogenic activities in coastal setting is responsible and associated with the water quality and nutrient contents as indicated by chlorophyll-a levels.

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Removing Striping Noise from Cloudy Level 2 Sea Surface Temperature and Ocean Color Datasets

10.20944/preprints201610.0002.v1 ◽

2016 ◽

Author(s):

Brahim Boussidi ◽

Ronan Fablet ◽

Bertrand Chapron

Keyword(s):

Remote Sensing ◽

Wavelet Transform ◽

Surface Temperature ◽

Sea Surface Temperature ◽

Ocean Color ◽

Remote Sensing Data ◽

Sea Surface ◽

Discrete Wavelet ◽

Sensing Data ◽

Fourier Filtering

This paper introduces a new destriping algorithm for remote sensing data. The method is based on combined Haar Stationary Wavelet transform and Fourier filtering. State-of-the-Art methods based on the discrete wavelet transform (DWT) may not always be effective and may cause different artifacts. Our contribution is three-fold: i) we propose to use the Undecimated Wavelet transform (UWT) to avoid as much as possible shortcomings of the classical DWT; ii) we combine a spectral filtering and UWT using the simplest possible wavelet, the Haar basis, for a computational efficiency; iii) we handle 2D fields with missing data, as commonly observed in ocean remote sensing data due to atmospheric conditions (e.g., cloud contamination). The performances of the proposed filter are tested and validated on the suppression of horizontal strip artifacts in cloudy L2 Sea Surface Temperature (SST) and ocean color snapshots.

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A split-window method to retrieving sea surface temperature from landsat 8 thermal infrared remote sensing data in offshore waters

Estuarine Coastal and Shelf Science ◽

10.1016/j.ecss.2020.106626 ◽

2020 ◽

Vol 236 ◽

pp. 106626 ◽

Cited By ~ 2

Author(s):

Jiaoqi Fu ◽

Chao Chen ◽

Biyun Guo ◽

Yanli Chu ◽

Hong Zheng

Keyword(s):

Remote Sensing ◽

Surface Temperature ◽

Sea Surface Temperature ◽

Remote Sensing Data ◽

Sea Surface ◽

Landsat 8 ◽

Thermal Infrared Remote Sensing ◽

Sensing Data ◽

Window Method ◽

Infrared Remote Sensing

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North Pacific subtropical sea surface temperature frontogenesis and its connection with the atmosphere above

10.5194/esd-2018-52 ◽

2018 ◽

Author(s):

Leying Zhang ◽

Haiming Xu ◽

Jing Ma ◽

Ning Shi ◽

Jiechun Deng

Keyword(s):

Heat Flux ◽

Surface Temperature ◽

Sea Surface Temperature ◽

North Pacific ◽

Ocean Currents ◽

Sea Surface ◽

Aleutian Low ◽

The North ◽

Net Heat Flux ◽

Temperature Advection

Abstract. The frontogenesis of the North Pacific subtropical sea surface temperature front (NPSTF) occurring from October to the following February is examined quantitatively based on the mixed-layer energy budget equation, with a focus on its connection with the atmosphere above. Diagnosis results show that the net heat flux dominates the frontogenesis from October to December, while the meridional temperature advection in the ocean contributes equally as or even more than the net heat flux in January and February. The atmosphere is critical to the frontogenesis of the NPSTF, including the direct effect of the net heat flux and the indirect effect through the Aleutian low. Further analyses demonstrate that the latent heat flux (the shortwave radiation) dominates the net heat flux in October (from November to February). The meridional temperature advection in the ocean is mostly owing to the meridional Ekman convergence, which is related to the Aleutian low. Climatologically, the strengthening and southward migration of the Aleutian low from October to the following February are characterized by the acceleration and southward shift of the westerly wind to the south, respectively, which can drive southward ocean currents. Correspondingly, the southward ocean currents give the colder meridional advection to the north of the NPSTF in January and February, favoring the frontogenesis. In addition, the Aleutian low plays a role in transforming the dominant effect of the net heat flux to the joint effect of the meridional temperature advection and the net heat flux in January. CESM1.0.3 model with a slab ocean model further confirms the important influence of the atmosphere on the frontogenesis and on the meridional temperature advection.

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