scholarly journals NGHIÊN CỨU XU THẾ BIẾN ĐỘNG TRƯỜNG NHIỆT ĐỘ BỀ MẶT BIỂN VÀ ẢNH HƯỞNG CỦA ENSO ĐẾN VÙNG BIỂN TÂY NAM VIỆT NAM SỬ DỤNG DỮ LIỆU VIỄN THÁM VÀ GIS

2020 ◽  
Vol 20 (2) ◽  
pp. 129-141
Author(s):  
Tran Anh Tuan ◽  
Vu Hai Dang ◽  
Pham Viet Hong ◽  
Do Ngoc Thuc ◽  
Nguyen Thuy Linh ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Monsoon Season ◽  
Linear Regression Analysis ◽  
Southwest Monsoon ◽  
Sea Surface ◽  
Northeast Monsoon ◽  
Temperature Trends ◽  
Sea Surface Temperature Anomalies ◽  
Southwest Monsoon Season

In this article, the sea surface temperature trends and the influence of ENSO on the southwest sea of Vietnam were analyzed using the continuous satellite-acquired data sequence of SST in the period of 2002–2018. GIS and average statistical methods were applied to calculate the average monthly and seasonal sea surface temperature, the seasonal sea surface temperature anomalies for each year and for the whole study period. Subsequently, the changing trends of sea surface temperature in the northeast and southwest monsoon seasons were estimated using linear regression analysis. Research results indicated that the sea surface temperature changed significantly throughout the calendar year, in which the maximum and minimum sea surface temperature are 31oC in May and 26oC in January respectively. Sea surface temperature trends range from 0oC/year to 0.05oC/year during the Northeast monsoon season and from 0.025oC/year to 0.055oC/year during the southwest monsoon season. Results based on the Oceanic Niño Index (ONI) analysis also show that the sea surface temperature in the study area and adjacent areas is strongly influenced and significantly fluctuates during El Niño and La Niña episodes.

scholarly journals Relationship between Lightning Activity over Peninsular India and Sea Surface Temperature

2010 ◽  
Vol 49 (4) ◽  
pp. 828-835 ◽  
Author(s):  
M. I. R. Tinmaker ◽  
Kaushar Ali ◽  
G. Beig
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Monsoon Season ◽  
Lightning Activity ◽  
Sea Surface ◽  
Lightning Flash ◽  
Northeast Monsoon ◽  
Monsoon Period ◽  
Peninsular India ◽  
Seasonal Time Scale

Abstract This paper presents a study of spatiotemporal variation of lightning activity over Peninsular India (8°–22°N, 72°–88°E) by using monthly satellite-based lightning flash grid (1° × 1°) data for a period of 10 yr (1998–2007). The data are examined in terms of spatial, annual, and seasonal distribution of the lightning activity. It is found that lightning activity is higher over south Peninsular India and eastern India. On a seasonal time scale, the lightning activity shows two maxima—first in the month of May and then in the month of September. The lightning activity in the monsoon period is noticed to be considerable because of the occurrence of the low-level jet and increase in the monsoon break period. During the postmonsoon, the activity is mainly due to the presence of the convective nature of the disturbed weather during the northeast monsoon season over most parts of the east coast of south Peninsular India. The relationship between lightning activity over Peninsular India and sea surface temperature in the bordering seas (Arabian Sea and Bay of Bengal) is also examined. The results disclose a significant link between them.

scholarly journals Satellite derived sea surface temperature variability in the Bay of Bengal

MAUSAM ◽  
2021 ◽  
Vol 63 (1) ◽  
pp. 71-76
Author(s):  
O.P. SINGH
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Bay Of Bengal ◽  
Monsoon Season ◽  
Southwest Monsoon ◽  
Sea Surface ◽  
Sst Variability ◽  
Different Seasons ◽  
Recent Trends ◽  
Monsoon Depressions

Bay of Bengal is associated with disturbances like tropical cyclones and monsoon depressions during pre and post monsoon and southwest monsoon seasons respectively. The Sea Surface Temperature (SST) variability over the Bay of Bengal plays an important role in the genesis of these disturbances. Satellite based SST climatologies, though based on shorter duration of data, have enabled study of interannual variabilities of SST over the smaller regions of Bay of Bengal which are associated with different types of weather disturbances in different seasons. Interannual variabilities and recent trends in SSTs over different regions of Bay of Bengal have been presented using a reliable satellite based climatological data for the 14 year period from 1985-1998.The annual SST over the Bay of Bengal has risen at the rate of about 0.2°C /decade during the period from 1985-1998. Maximum rising trend of 0.71°C/decade has been found over south Bay of Bengal during June. Frequency of monsoon depressions has decreased considerably in recent years in spite of increasing SST trends over Bay of Bengal in southwest monsoon season.

Copepod and monogenean infection of fish under sea surface temperature anomalies

2021 ◽  
pp. 102098
Author(s):  
F. Neptalí Morales-Serna ◽  
Lorenia Olivas-Padilla ◽  
Emigdio Marín-Enriquez ◽  
Juan M. Osuna-Cabanillas ◽  
Hugo Aguirre-Villaseñor ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Temperature Anomalies ◽  
Sea Surface Temperature Anomalies ◽  
Monogenean Infection

scholarly journals A Process-Oriented Approach to Identify Evolutions of Sea Surface Temperature Anomalies with a Time-Series of a Raster Dataset

2021 ◽  
Vol 10 (8) ◽  
pp. 500
Author(s):  
Lianwei Li ◽  
Yangfeng Xu ◽  
Cunjin Xue ◽  
Yuxuan Fu ◽  
Yuanyu Zhang
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Global Climate ◽  
Sea Surface ◽  
Temperature Anomalies ◽  
Global Climate Changes ◽  
Space And Time ◽  
Novel Approach ◽  
Sea Surface Temperature Anomalies

It is important to consider where, when, and how the evolution of sea surface temperature anomalies (SSTA) plays significant roles in regional or global climate changes. In the comparison of where and when, there is a great challenge in clearly describing how SSTA evolves in space and time. In light of the evolution from generation, through development, and to the dissipation of SSTA, this paper proposes a novel approach to identifying an evolution of SSTA in space and time from a time-series of a raster dataset. This method, called PoAIES, includes three key steps. Firstly, a cluster-based method is enhanced to explore spatiotemporal clusters of SSTA, and each cluster of SSTA at a time snapshot is taken as a snapshot object of SSTA. Secondly, the spatiotemporal topologies of snapshot objects of SSTA at successive time snapshots are used to link snapshot objects of SSTA into an evolution object of SSTA, which is called a process object. Here, a linking threshold is automatically determined according to the overlapped areas of the snapshot objects, and only those snapshot objects that meet the specified linking threshold are linked together into a process object. Thirdly, we use a graph-based model to represent a process object of SSTA. A node represents a snapshot object of SSTA, and an edge represents an evolution between two snapshot objects. Using a number of child nodes from an edge’s parent node and a number of parent nodes from the edge’s child node, a type of edge (an evolution relationship) is identified, which shows its development, splitting, merging, or splitting/merging. Finally, an experiment on a simulated dataset is used to demonstrate the effectiveness and the advantages of PoAIES, and a real dataset of satellite-SSTA is used to verify the rationality of PoAIES with the help of ENSO’s relevant knowledge, which may provide new references for global change research.

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