scholarly journals VARIABILITY OF SEA SURFACE TEMPERATURE IN THE HEATING PERIOD AT THE COASTAL AREA OF THE NORTHEAST JAPAN

2000 ◽  
Vol 44 ◽  
pp. 927-932 ◽  
Author(s):  
Cham-Su YANG
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Coastal Area ◽  
Sea Surface ◽  
Heating Period

scholarly journals Sea surface temperature trend analysis by Mann-Kendall test and sen’s slope estimator: a study of the Hai Phong coastal area (Vietnam) for the period 1995-2020

2022 ◽  
Author(s):  
Vinh Vu Duy ◽  
Sylvain Ouillon ◽  
Hai Nguyen Minh
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Coastal Area ◽  
Kendall Test ◽  
Sea Surface ◽  
Intrinsic Mode Functions ◽  
Sen’S Slope ◽  
Enso Events ◽  
Mann Kendall Test ◽  
The Impact

Based on the Mann-Kendall test and Sen’s slope method, this study investigates the monthly, seasonal, and annual sea surface temperature (SST) trends in the coastal area of Hai Phong (West of Tonkin Gulf) based on the measurements at Hon Dau Station from 1995 to 2020. The results show a sea surface warming trend of 0.02°C/year for the period 1995-2020 (significant level α = 0.1) and of 0.093°C/year for the period 2008-2020 (significant level α = 0.05). The monthly SSTs in June and September increased by 0.027°C/year and 0.036°C/year, respectively, for the period 1995-2020, and by 0.080°C/year and 0.047°C/year, respectively, for the period 2008-2020. SST trends in winter, summer, and other months were either different for the two periods or not significant enough. This may be due to the impact of ENSO, which caused interannual SST variability in the Hai Phong coastal with two intrinsic mode functions (IMF) signals a period of ~2 (IMF3) and ~5.2 years cycle (IMF4). A combination of these signals had a maximum correlation of 0.22 with ONI (Oceanic Niño Index) delayed by 8 months. ENSO events took ~8 months to affect SST at Hai Phong coastal area for 1995-2020 and caused a variation of SST within 1.2°C.

scholarly journals Prakiraan Kesuburan Perairan Bali Dari Citra Satelit [Forecast Fertility Bali Waters From Satellite Imagery]

2019 ◽  
Vol 4 (1) ◽  
pp. 81
Author(s):  
Sony Angga Satrya, Abdul Manan
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Coastal Area ◽  
Satellite Image ◽  
Image Data ◽  
Pearl Oyster ◽  
Sea Surface ◽  
Oyster Culture ◽  
Sensing Technology ◽  
Terra Modis

Abstract Aplication Ocean Remote Sensing technology to many use for field fisheries, once use this technology in forecast fertility water. The aim of this study was to determine the feasibility of Bali coastal area for cage of pearl oyster culture. The method used is a descriptive method of data collection. Satellite image processing activities Aqua/Terra Modis starting with the collection of satellite image data from the database NASA via OceanColor Web site, the selection of a clean image data, and than download of satellite images. The first stages of image data processing are used software ENVI 4.7, with procedures are coloring the image, limiting the minimum and maximum temperatures and sea surface chlorophyll-a, and classifiying of the image based on the value of sea surface temperature. Sea surface temperature parameter determine the location of the cage of pearl oysters (Pinctada maxima) culture. Suitability of the location of the cage of pearl oyster culture on Bali coastal area, at coordinates 8° 33' 00.97 " - 8° 42' 05.30" South Latitude and 115° 18' 03.40 " - 115° 39 ' 03.21" East Longitude. Based on geographical, that the location in the southeastern Bali coastal area and on the northern area of Nusa Pennida island.

scholarly journals A METHOD OF WATER DEPTH INVERSION IN COASTAL AREA CONSIDERING TEMPERATURE INFORMATION

2021 ◽  
Vol V-3-2021 ◽  
pp. 23-28
Author(s):  
Y. Liu ◽  
X. Gao ◽  
G. Wang ◽  
T. Zhang ◽  
J. Wang
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Water Depth ◽  
Coastal Area ◽  
Research Area ◽  
Sea Surface ◽  
Nonlinear Inversion ◽  
Depth Data ◽  
Important Means ◽  
Measured Water

Abstract. The remote sensing method for water depth inversion is fast, flexible, and low in cost, which has become an important means of method for water depth detection. This paper takes the coastal area where is around Gulangyu Island as the research area. Based on the spectral reflectance, sea surface temperature (SST) and measured water depth data, a nonlinear inversion model of water depth is established by using BP neural network. Combined with the tide data, the water depth and underwater topography in coastal area is obtained. The average relative error is 0.27. The root mean square error is 1.92. The results show that the participation of sea surface temperature in the model construction can improve the inversion error of offshore water depth to a certain extent, and can help improve the accuracy of the model.

scholarly journals Investigating Sea Surface Temperature and Coral Bleaching in the Coastal Area of Khanh Hoa Province

2022 ◽  
Vol 964 (1) ◽  
pp. 012004
Author(s):  
Tran Thi Van ◽  
Nguyen Trinh Duc Hieu ◽  
Nguyen Huu Huan ◽  
Nguyen Phuong Lien
Keyword(s):  
Heat Stress ◽  
Coral Reefs ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Coral Bleaching ◽  
Coastal Area ◽  
Hot Spot ◽  
Southwest Monsoon ◽  
Sea Surface ◽  
Two Parameters

Abstract Khanh Hoa Coastal area is considered the area with the most diverse coral reefs in the west of the East Sea. With the trend of increasing global temperature, the coral reefs here are affected, including the phenomenon of bleaching. This paper uses a Multi-scale Ultra-high Resolution Sea Surface Temperature (MUR SST) data source to evaluate the possible relationship between sea surface temperature and coral bleaching in the period 2010-2019 in Khanh Hoa coastal area is based on two parameters: Hot Spot (HS) and Degree Heating Months (DHM). Research results show that in the past 10 years, corals in Khanh Hoa coastal area may experience heat stress in 6 years, including 2010, 2013 and the years from 2016 to 2019. The phenomenon of heat stress starts to occur in May of each year, and the level of heat stress in 2010 was stronger than in other years. Within 6 years, there have been heat stress, coral bleaching events due to temperature only occurred in 2010; while in 2013, 2016, 2017, 2018 and 2019, corals suffered from heat stress in the watch level, meaning an increase in temperature is not yet capable of causing coral bleaching. The cause of coral bleaching in 2010 was the combined effect of the increase in sea surface temperature and the suppression of upwelling during the southwest monsoon.

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