Back to Search Start Over

Modelling of marine ecosystem in regional scale for short term prediction of satellite-aided operational fishery advisories.

Authors :
Chakraborty, Kunal
Maity, Sourav
Lotliker, Aneesh A.
Samanta, Alakes
Ghosh, Jayashree
Masuluri, Nagaraja Kumar
Swetha, Naga
Bright, Rose P.
Source :
Journal of Operational Oceanography; 2019Supplement, Vol. 12 Issue 2, pS157-S175, 19p
Publication Year :
2019

Abstract

The operational Potential Fishing Zone (PFZ) advisory generated and disseminated by the ESSO-Indian National Centre for Ocean Information Services has a significant impact on the livelihood of coastal community of India. PFZs are identified as the relatively narrow zones in the ocean where horizontal gradients of physical and/or biological properties are enhanced. The advisories are provided to fishermen on a daily basis using remotely sensed sea surface temperature (SST) and chlorophyll-a (Chl-a) data from NOAA-AVHRR and MODIS-AQUA and/or Oceansat-2 satellites, respectively. Sometimes it becomes a major challenge to retrieve SST/Chl-a data from satellite images, particularly during the extensive cloud coverage. To overcome this operational difficulty, the satellite data is replaced by a coupled physical-biogeochemical model data capable of simulating ocean features leading to PFZs. The use of model data provides an additional advantage towards transforming the existing service from advisories to forecast. The average length of PFZs identified from satellite (model) data (2010–2016) for off Gujarat is 27.80 ± 7.2 km (33.07 ± 3.2 km) whereas for off Andhra Pradesh, it is 28.27 ± 10.9 km (52.48 ± 8.7 km). Considering the capability of the model in identifying PFZs, the existing advisory service can be transitioned into a short term PFZ forecast. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1755876X
Volume :
12
Issue :
2
Database :
Complementary Index
Journal :
Journal of Operational Oceanography
Publication Type :
Academic Journal
Accession number :
139117899
Full Text :
https://doi.org/10.1080/1755876X.2019.1574951