Best Practices for Increasing Data Return: Case Study From Indian Ocean Observation Network

Author:

Venkatesan Ramasamy,Muthiah Manickavasagam Arul,Vengatesan Gopalakrishnan,Kesavakumar Balakrishnan,Vedachalam Narayanaswamy

Abstract

AbstractSustained real-time ocean observation systems using moored data buoys are vital for understanding ocean dynamics and variability, which are essential for improving oceanographic services including weather prediction, ocean state forecast, cyclone tracking, tsunami monitoring, and climate change studies. This paper describes the significant rapid restoration techniques implemented to increase the availability of the Indian Ocean observation networks over the past two decades. The efforts have helped in achieving availability of 97.9%, 82.3%, and 98.7% for the meteorological sensors, subsea surface oceanographic sensors, and tsunami buoy network, respectively.

Publisher

Marine Technology Society

Subject

Ocean Engineering,Oceanography

Reference24 articles.

1. Observed year-to-year sea surface variability in the Bay of Bengal during the 2009–2014 period;Chaitanya;Ocean Dynam,2015

2. Bay of Bengal: from monsoon to mixing, decay mechanism of near inertial mixed layer oscillations in the Bay of Bengal;Johnston;Oceanography,2016

3. Design, analysis and installation of offshore instrumented moored data buoy system;Kaliyaperumal;J Ship Ocean Eng,2015

4. RAMA: the research moored array for African-Asian-Australian monsoon analysis and prediction;McPhaden;Bull Am Meteorol Soc,2009

5. Indian Ocean is no more under observed;Ravichandran;Ocean Soc India,2015

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3