2021
DOI: 10.3329/dujees.v9i2.55089
|View full text |Cite
|
Sign up to set email alerts
|

Assessing Atmospheric Instability over the Bay of Bengal during October and November Months between 2007 – 2018

Abstract: An attempt has been made in this research to delineate a pattern for atmospheric instability during the months of October and November from 2007 to 2018. The results show an alarming trend of increasing instability throughout the study period. The average temperature at 2-meters height around the Bay of Bengal has changed significantly over time. Most notably, the gap between monthly average highest and monthly average lowest temperatures (at 2-meters height) is more or less increasing from 2007 to 2018 – rang… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(2 citation statements)
references
References 42 publications
0
2
0
Order By: Relevance
“…Bay of Bengal has this tendency to have some increase during the pre-monsoon months (Shuvo and Sultana, 2022). This increase in temperature can run through the monsoon season and can last up to postmonsoon as well (Shuvo and Awal, 2021;Shuvo, 2021).…”
Section: Analysis Of Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Bay of Bengal has this tendency to have some increase during the pre-monsoon months (Shuvo and Sultana, 2022). This increase in temperature can run through the monsoon season and can last up to postmonsoon as well (Shuvo and Awal, 2021;Shuvo, 2021).…”
Section: Analysis Of Resultsmentioning
confidence: 99%
“…But, the choice of NCEP/NCAR FNL dataset has been made after careful consideration. The FNL dataset has been extensively used in predicting extreme weather events (Rabbani and Shuvo, 2021;Ferdaus et al, 2021;Islam et al, 2021;Sarker et al, 2021;Shuvo and Awal, 2021; around the world with much success. Therefore, the researchers have decided to use the NCEP/NCAR FNL data for simulating heatwave events.…”
Section: Data Used In This Researchmentioning
confidence: 99%