Statistical analysis of sea surface temperature for best fit

Srinjoy Nag Chowdhury, Saniya Dhawan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The meeting of the world's top governmental agencies at Paris for the COP21 summit, made it imminently clear that global warming was no longer a distant threat but a real and tangible one. Since then, there has been a noticeable impetus towards developing mechanisms for measuring the current state of different climate change indicators. In this paper, we have presented a statistical estimation of one such climate change indicator which is the sea surface temperature. Sea surface temperature is important because it not only gives us an idea about the sea level rise, the frequency of storms but also about the marine ecosystem as a whole. If we look towards technology which aims at reducing global warming and its effects in entirety, then we will come across renewable energy systems and among them are hydro energy systems. The systems among these which produce energy do so by the thermal & mechanical energy of the seas with thermal producing the bulk of the energy. Thus, it becomes an important task for one to measure and model the sea temperature so as to take effective measures for proper harnessing of hydro energy. In our review, we have used fundamental distribution functions to model the sea surface temperature, and have calculated error using various error detection tests thereby concluding the best fit for sea temperature data.

Original languageEnglish
Title of host publication2016 International Conference on Computation of Power, Energy, Information and Communication, ICCPEIC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages58-62
Number of pages5
ISBN (Electronic)9781509009015
DOIs
Publication statusPublished - 31-08-2016
Externally publishedYes
Event5th International Conference on Computation of Power, Energy Information and Communication, ICCPEIC 2016 - Melmaruvathur, Chennai, India
Duration: 20-04-201621-04-2016

Conference

Conference5th International Conference on Computation of Power, Energy Information and Communication, ICCPEIC 2016
CountryIndia
CityMelmaruvathur, Chennai
Period20-04-1621-04-16

Fingerprint

Sea Surface Temperature
Statistical Analysis
Statistical methods
Energy
Global Warming
Climate Change
Global warming
Climate change
Temperature
Impetus
Statistical Estimation
Aquatic ecosystems
Renewable Energy
Error Detection
Error detection
Sea level
Ecosystem
Distribution functions
Distribution Function
Model

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Control and Optimization

Cite this

Chowdhury, S. N., & Dhawan, S. (2016). Statistical analysis of sea surface temperature for best fit. In 2016 International Conference on Computation of Power, Energy, Information and Communication, ICCPEIC 2016 (pp. 58-62). [7557223] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCPEIC.2016.7557223
Chowdhury, Srinjoy Nag ; Dhawan, Saniya. / Statistical analysis of sea surface temperature for best fit. 2016 International Conference on Computation of Power, Energy, Information and Communication, ICCPEIC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 58-62
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Chowdhury, SN & Dhawan, S 2016, Statistical analysis of sea surface temperature for best fit. in 2016 International Conference on Computation of Power, Energy, Information and Communication, ICCPEIC 2016., 7557223, Institute of Electrical and Electronics Engineers Inc., pp. 58-62, 5th International Conference on Computation of Power, Energy Information and Communication, ICCPEIC 2016, Melmaruvathur, Chennai, India, 20-04-16. https://doi.org/10.1109/ICCPEIC.2016.7557223

Statistical analysis of sea surface temperature for best fit. / Chowdhury, Srinjoy Nag; Dhawan, Saniya.

2016 International Conference on Computation of Power, Energy, Information and Communication, ICCPEIC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 58-62 7557223.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Chowdhury SN, Dhawan S. Statistical analysis of sea surface temperature for best fit. In 2016 International Conference on Computation of Power, Energy, Information and Communication, ICCPEIC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 58-62. 7557223 https://doi.org/10.1109/ICCPEIC.2016.7557223