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ANNUAL REPORT 2017- 2018 ANNUAL REPORT 2017- 2018

REPORT FROM THE BOARD

Prof. (Dr.) N.R. Menon, Co-Chairman of the Board of Directors of NERCI on Vision Administrative Staff 17th March, 2018, passed away. He was a leading Marine Scientist, and Dean, To serve the society through advancing knowledge on Monsoon, Ms. Anu Chacko – Finance, Manuel Prakasia – Assistant Faculty of Climate Variability and Aquatic Ecosystem, Kerala University of Ocean Variability and Coastal Marine Ecosystem for sustainable Fisheries and Ocean Studies. His field of expertise was in Taxonomy and development by promoting inter disciplinary research and Nansen Environmental Research Ecology of Marine Foulers; Marine Bio deterioration; Marine Pollution education cooperation programs in the spirit of Fridtjof Nansen. Centre (India), Kochi, Kerala. Monitoring; Toxicology Biodiversity and coastal zone management. He has worked in various capacities at different institutes for more than thirty years Main scientific research areas of NERCI are: Founded in 1999 http://www.nerci.in and had more than 200 publications and guided 40 PhDs. He worked as a senior · Monsoon and ocean variability, Climate change, Sea level scientist in International Indian Ocean Expedition. He was involved in the variations investigation on the distribution of the Toxic Algal Blooms along the EEZ of ·Marine Ecosystem studies including algal blooms Board of Directors India and the distribution of micro and macro benthos along the EEZ of India ·Coastal Zone Management and Societal issues. involving planning the experiments, deployment of suitable scientific Lasse H. Pettersson (Chairman), Director of International personnel, analyses and interpretation of data. He was the Principal investiga- Cooperation, NERSC, Norway. tor and Co-ordinator for two multi-institutional projects of the Marine Living Organization Prof. N. R. Menon (Co-Chairman), Professor Emeritus, CUSAT, Resources Programme sponsored by the Department of Ocean Development, Kochi, India.(until March, 2018) Govt. of India (MLR-DOD). He worked as a Member of National Research Nansen Environmental Research Centre India (NERCI) was Advisory Committee for the MLR- DOD Programme, Project Director, established in 1999 as a joint venture between the Indian and Dr. Sebastian H. Mernild, Director, NERSC, Norway. Integrated Coastal Zone Management, NUFFIC - MHO Programme, Norwegian partners. NERCI conducts basic and applied research in Dr. Annette Samuelsen, Scientist, NERSC, Norway Government of Netherlands and CUSAT, November in 1999 and as Principal ocean and atmospheric sciences funded by national and Dr. K. Ajith Joseph, Executive Director, NERCI. Investigator, Digitized Inventory of Marine Bio Resources – National Project, international agencies. Core funding is received from the Nansen Dept. of Bio technology, 2001 – 2004. He also served as a Member of Kerala Prof. P. V. Joseph, Director (Rtd), India Meteorological Depart- Centre and the Nansen Scientific Society, Bergen, Norway. NERCI Prof.(Dr.) N.R.Menon, State Coastal Zone Management Authority, 2002- 2005. 2006-2009, 2009- ment, Kochi, India. is recognized by DSIR (Department of Scientific and Industrial 2012, 2014-2017 and Technical committee, National Fisheries Development Research) Ministry of Science and Technology, Govt. of India, as a Dr. N. Nandini Menon, Deputy Director, NERCI. Board, 2008- 2011. He has also served as the Member, Working Group of non-profit Scientific and Industrial Research Organization (SIRO) Co-Chairman, Experts- Revalidation of Potential Fishery Resources of Indian EEZ(2010- from 2012. NERCI capitalizes on the joint scientific expertise of the NERCI (2012-2018) 2015). Prof. Menon coordinated EU- INDO-MARECLIM, an EU-FP7 project International network of Nansen Centers (http://www.nersc.no). Observers under INCO-LAB programme at NERCI during 2012-2015. He also served as Dr. Annalisa Cherchi, CMCC,Italy the Chairman, Research Advisory Committee, Ecology and Environment, KCSTE, Govt. of Kerala and Chairman of research advisory committee, Staff Dr. Christian Siderus, Alterra,Netherlands Dr. Shubha Sathyendranath, PML, UK CMFRI, Kochi and Expert member Kerala Coastal Zone Management The Centre has a staff strength of 16 with five full time scientists, Authority. He received late Padmasree Prof. N. Balakrishnan Nair award of two associate scientists, two consultant scientists, one Junior Environmental Excellence 2013 and Best Fishery Educationist 2015 by World Research Fellow (funded by DST project), two Research Assistants Scientific Research Advisory Board Fisheries Congress. (funded by DST projects), one Post doc fellow, one Project staff and Prof. N. R. Menon (Chairman), Professor Emeritus, School of two administrative staff as per 31.12.18. Currently seven students Marine Sciences, CUSAT, Kochi, India. (until March, 2018). are supervised at NERCI (six students registered for Ph.D. at CUSAT and one student at KUFOS), including one Nansen Dr. Shailesh Nayak, Former Secretary, Ministry of Earth Fellowship student. Sciences, Govt. of India, New Delhi. Prof. P. V. Joseph, Director (Rtd.), India Meteorological Office and Environment Department, Kochi, India. NERCI is an equal opportunity employer and has improved its research facilities in 2018 and moved its office to KUFOS Amenity Lasse H. Pettersson, Director of International Cooperation, Scientists Centre, Kochi. NERCI has been recognised by Kerala University of Fisheries and Ocean Studies (KUFOS) as a research centre for NERSC, Bergen, Norway. Ajith Joseph. K – Oceanography & Remote Sensing Ocean Science and Technology, Ocean Engineering and Climate Variability and Aquatic Ecosystems. Nandini Menon. N – Marine ecosystem studies Prof. B. Madhusoodana Kurup, Former Vice -Chancellor, Kerala Syam Sankar – Climate & Ecosystem modelling University of Fisheries and Ocean Studies (KUFOS) Bindu. G – Climate change Dr. N. P. Kurian, Director(Rtd.), National Centre for Earth Scientific Outreach Abish B - Aerosols and Indian Monsoon Science Studies. Trivandrum Outreach is actively done through press releases, conducting popular science lectures, international and national workshops, Dr. Laurent Bertino, Research Director, Mohn-Sverdrup Center for conferences and release of newsletters. Awareness campaigns are also conducted as part of ongoing projects. Global Ocean Studies and Operational Oceanography, NERSC, Associate Scientists Bergen, Norway. P. V. Joseph – Monsoon & Ocean variability, sea level variations Dr. M. Ramalingam, Former Director, Institute of Remote Sensing, Lasse H Pettersson – Oceanography & Remote sensing Anna University, Chennai, India National and International Cooperation Prof. T. Balasubramanian, Former Dean, Faculty of Marine Memorandum of Understanding (MoU) between Cochin University of Science and Technology (CUSAT), Kerala University of Sciences, Annammalai University. Fisheries and Ocean Studies (KUFOS), Central Marine Fisheries Research Institute (CMFRI), Toc H Institute of Science and Consultant Scientists Dr. K. Ajith Joseph, Executive Director, NERCI. Technology (TIST), Sathyabama University, Anna University, Nansen Environmental Remote Sensing Center (NERSC), Bergen, Harenduprakash. L – Ocean modeling Dr. Nandini Menon, Member Secretary, NERCI Board. Norway and NERCI are in operation. K. Shadananan Nair- Hydro meteorology MoUs focus on development of bilateral cooperation in satellite remote sensing, operational oceanography and ocean modeling. The Honorary Member fellowship program of Nansen Scientific Society implemented at the Faculty of Marine Sciences, Cochin University of Science and Project fellows Mr. Thomas Mathew, Advisor (Rtd.), NORINCO Pvt. Limited, Technology (CUSAT) under the MoU signed between NERSC, CUSAT and NERCI is continuing and currently one student is doing Smitha A- DST-NPD Fellow, Oceanography and Modeling Kochi, India. PhD under this scheme with co-supervisors from NERSC (Norway) and NERCI. Poornima Rajan- Remote Sensing and GIS Cover page: Temporal changes in bamboo coverage in Wayanad district, Kerala, India from 2011-2018 from LISS-4 Image Arun, K- Aerosol and Indian monsoon variability 04 05 ANNUAL REPORT 2017- 2018 ANNUAL REPORT 2017- 2018

REPORT FROM THE BOARD

Prof. (Dr.) N.R. Menon, Co-Chairman of the Board of Directors of NERCI on Vision Administrative Staff 17th March, 2018, passed away. He was a leading Marine Scientist, and Dean, To serve the society through advancing knowledge on Monsoon, Ms. Anu Chacko – Finance, Manuel Prakasia – Assistant Faculty of Climate Variability and Aquatic Ecosystem, Kerala University of Ocean Variability and Coastal Marine Ecosystem for sustainable Fisheries and Ocean Studies. His field of expertise was in Taxonomy and development by promoting inter disciplinary research and Nansen Environmental Research Ecology of Marine Foulers; Marine Bio deterioration; Marine Pollution education cooperation programs in the spirit of Fridtjof Nansen. Centre (India), Kochi, Kerala. Monitoring; Toxicology Biodiversity and coastal zone management. He has worked in various capacities at different institutes for more than thirty years Main scientific research areas of NERCI are: Founded in 1999 http://www.nerci.in and had more than 200 publications and guided 40 PhDs. He worked as a senior · Monsoon and ocean variability, Climate change, Sea level scientist in International Indian Ocean Expedition. He was involved in the variations investigation on the distribution of the Toxic Algal Blooms along the EEZ of ·Marine Ecosystem studies including algal blooms Board of Directors India and the distribution of micro and macro benthos along the EEZ of India ·Coastal Zone Management and Societal issues. involving planning the experiments, deployment of suitable scientific Lasse H. Pettersson (Chairman), Director of International personnel, analyses and interpretation of data. He was the Principal investiga- Cooperation, NERSC, Norway. tor and Co-ordinator for two multi-institutional projects of the Marine Living Organization Prof. N. R. Menon (Co-Chairman), Professor Emeritus, CUSAT, Resources Programme sponsored by the Department of Ocean Development, Kochi, India.(until March, 2018) Govt. of India (MLR-DOD). He worked as a Member of National Research Nansen Environmental Research Centre India (NERCI) was Advisory Committee for the MLR- DOD Programme, Project Director, established in 1999 as a joint venture between the Indian and Dr. Sebastian H. Mernild, Director, NERSC, Norway. Integrated Coastal Zone Management, NUFFIC - MHO Programme, Norwegian partners. NERCI conducts basic and applied research in Dr. Annette Samuelsen, Scientist, NERSC, Norway Government of Netherlands and CUSAT, November in 1999 and as Principal ocean and atmospheric sciences funded by national and Dr. K. Ajith Joseph, Executive Director, NERCI. Investigator, Digitized Inventory of Marine Bio Resources – National Project, international agencies. Core funding is received from the Nansen Dept. of Bio technology, 2001 – 2004. He also served as a Member of Kerala Prof. P. V. Joseph, Director (Rtd), India Meteorological Depart- Centre and the Nansen Scientific Society, Bergen, Norway. NERCI Prof.(Dr.) N.R.Menon, State Coastal Zone Management Authority, 2002- 2005. 2006-2009, 2009- ment, Kochi, India. is recognized by DSIR (Department of Scientific and Industrial 2012, 2014-2017 and Technical committee, National Fisheries Development Research) Ministry of Science and Technology, Govt. of India, as a Dr. N. Nandini Menon, Deputy Director, NERCI. Board, 2008- 2011. He has also served as the Member, Working Group of non-profit Scientific and Industrial Research Organization (SIRO) Co-Chairman, Experts- Revalidation of Potential Fishery Resources of Indian EEZ(2010- from 2012. NERCI capitalizes on the joint scientific expertise of the NERCI (2012-2018) 2015). Prof. Menon coordinated EU- INDO-MARECLIM, an EU-FP7 project International network of Nansen Centers (http://www.nersc.no). Observers under INCO-LAB programme at NERCI during 2012-2015. He also served as Dr. Annalisa Cherchi, CMCC,Italy the Chairman, Research Advisory Committee, Ecology and Environment, KCSTE, Govt. of Kerala and Chairman of research advisory committee, Staff Dr. Christian Siderus, Alterra,Netherlands Dr. Shubha Sathyendranath, PML, UK CMFRI, Kochi and Expert member Kerala Coastal Zone Management The Centre has a staff strength of 16 with five full time scientists, Authority. He received late Padmasree Prof. N. Balakrishnan Nair award of two associate scientists, two consultant scientists, one Junior Environmental Excellence 2013 and Best Fishery Educationist 2015 by World Research Fellow (funded by DST project), two Research Assistants Scientific Research Advisory Board Fisheries Congress. (funded by DST projects), one Post doc fellow, one Project staff and Prof. N. R. Menon (Chairman), Professor Emeritus, School of two administrative staff as per 31.12.18. Currently seven students Marine Sciences, CUSAT, Kochi, India. (until March, 2018). are supervised at NERCI (six students registered for Ph.D. at CUSAT and one student at KUFOS), including one Nansen Dr. Shailesh Nayak, Former Secretary, Ministry of Earth Fellowship student. Sciences, Govt. of India, New Delhi. Prof. P. V. Joseph, Director (Rtd.), India Meteorological Office and Environment Department, Kochi, India. NERCI is an equal opportunity employer and has improved its research facilities in 2018 and moved its office to KUFOS Amenity Lasse H. Pettersson, Director of International Cooperation, Scientists Centre, Kochi. NERCI has been recognised by Kerala University of Fisheries and Ocean Studies (KUFOS) as a research centre for NERSC, Bergen, Norway. Ajith Joseph. K – Oceanography & Remote Sensing Ocean Science and Technology, Ocean Engineering and Climate Variability and Aquatic Ecosystems. Nandini Menon. N – Marine ecosystem studies Prof. B. Madhusoodana Kurup, Former Vice -Chancellor, Kerala Syam Sankar – Climate & Ecosystem modelling University of Fisheries and Ocean Studies (KUFOS) Bindu. G – Climate change Dr. N. P. Kurian, Director(Rtd.), National Centre for Earth Scientific Outreach Abish B - Aerosols and Indian Monsoon Science Studies. Trivandrum Outreach is actively done through press releases, conducting popular science lectures, international and national workshops, Dr. Laurent Bertino, Research Director, Mohn-Sverdrup Center for conferences and release of newsletters. Awareness campaigns are also conducted as part of ongoing projects. Global Ocean Studies and Operational Oceanography, NERSC, Associate Scientists Bergen, Norway. P. V. Joseph – Monsoon & Ocean variability, sea level variations Dr. M. Ramalingam, Former Director, Institute of Remote Sensing, Lasse H Pettersson – Oceanography & Remote sensing Anna University, Chennai, India National and International Cooperation Prof. T. Balasubramanian, Former Dean, Faculty of Marine Memorandum of Understanding (MoU) between Cochin University of Science and Technology (CUSAT), Kerala University of Sciences, Annammalai University. Fisheries and Ocean Studies (KUFOS), Central Marine Fisheries Research Institute (CMFRI), Toc H Institute of Science and Consultant Scientists Dr. K. Ajith Joseph, Executive Director, NERCI. Technology (TIST), Sathyabama University, Anna University, Nansen Environmental Remote Sensing Center (NERSC), Bergen, Harenduprakash. L– Ocean modeling Dr. Nandini Menon, Member Secretary, NERCI Board. Norway and NERCI are in operation. K. Shadananan Nair- Hydro meteorology MoUs focus on development of bilateral cooperation in satellite remote sensing, operational oceanography and ocean modeling. The Honorary Member fellowship program of Nansen Scientific Society implemented at the Faculty of Marine Sciences, Cochin University of Science and Project fellows Mr. Thomas Mathew, Advisor (Rtd.), NORINCO Pvt. Limited, Technology (CUSAT) under the MoU signed between NERSC, CUSAT and NERCI is continuing and currently one student is doing Smitha A- DST-NPD Fellow, Oceanography and Modeling Kochi, India. PhD under this scheme with co-supervisors from NERSC (Norway) and NERCI. Poornima Rajan- Remote Sensing and GIS Cover page: Temporal changes in bamboo coverage in Wayanad district, Kerala, India from 2011-2018 from LISS-4 Image Arun, K- Aerosol and Indian monsoon variability 04 05 ANNUAL REPORT 2017- 2018 ANNUAL REPORT 2017- 2018

ONGOING PROJECTS

Bhagyalakshmi S - registered for Ph.D at KUFOS under the NERCI has the following ongoing external funded projects from agencies like Department of Science and Technology, ESSO - Indian PhD students under joint projects guidance of Dr.Bindhu, G. National Centre for Ocean Information Services (INCOIS), Direct Aid Program- Australia, Norwegian Research Council (RCN), and Two fulltime and five part time doctoral students are currently Partnership for Observation of Global Oceans (POGO). Ph.D. program by Nansen Scientific Society is continuing at NERCI. Topic of research : Assessment of impact of flood and development carrying out their research work jointly at CUSAT and KUFOS in of hazard map using GIS. affiliation with NERCI and NERSC including the Nansen Scientific Society Ph.D. fellowship program. Modeling bio-geochemical Cycles in Coastal Oceans (2014 - Impact of Atmospheric Aerosols on the Large Scale Smitha A- INDO-MARECLIM fellow and part-time Ph.D student Funding 2018) Circulation over the Indian Summer Monsoon Region at CUSAT under the guidance of Prof. H. S. Ram Mohan. Funded by SAC-ISRO. Funded by DST NERCI is a non-profit research organization recognized by Kerala Topic of research: Wind induced upwelling and the response of University of Fisheries and Ocean Studies (KUFOS) and registered Principal Investigator: Principal Investigator: Dr. Abish B. surface chlorophyll in the Bay of Bengal. (Defended on 18/5/2017) under Article25 of Indian company act. It mainly receives funding Dr. Mohamed Hatha, CUSAT, The objective of this project is to study the interaction of aerosols Ajin A M -Registered for Ph.D under the guidance of Prof. N. R. from Nansen Environmental and Remote Sensing Center and Menon at CUSAT. Co-PI: Dr. Nandini Menon N, NERCI on the large scale atmospheric circulation over the Indian Nansen Scientific Society, Norway. It also receives funding through summer monsoon region. Topic of research: Marine ecosystem studies and biodiversity projects from European Commission, Norwegian Research Council, Co-ordinator: Dr. Mini Raman, SAC concepts. United Nations Environmental Programme (UNEP) and other national agencies like Department of Science and Technology, Aim of this project is to study the carbon pools (organic carbon Nashad. M - Registered for PhD under the guidance of Prof. N. R. Arctic cooperation between Norway, Russia, India, China and Govt.of India, Space Application Centre, ISRO and Dept of components), fluxes (the rates of primary, new and export Menon at CUSAT. Co-guide at NERCI Dr.Nandini Menon. N. Co- US in satellite Earth observation and Education Environment and Climate Change, Govt. of Kerala. production) and organic nitrogen components involved in the guide at NERSC – Lasse H Pettersson. biogeochemistry of coastal oceans around Indian subcontinent (ARCONOR) - research and higher education related to sea Topic of research: Monitoring and modeling of Harmful algal using satellite data. ice, environment, climate change, and operational conditions in the Arctic Ocean focusing on the Northern Sea Route blooms along the South West coast of India. Prospects for 2019 Funded by- Research Council of Norway Shinu Sheela Wilson- Nansen Scientific Society fellow, doing NERCI enters 2019 with plans to strengthen their national and HABAQUA - Harmful Algal Blooms in Aquaculture Ph.D under the guidance of Prof. Mohankumar at CUSAT. Co- Coordinator- Lasse H. Pettersson, NERSC, Norway Indian international cooperation within the Nansen Group and other Indo- ecosystems: a modeling and remote sensing perspective (2016- guides at NERCI- Dr. P. V. Joseph and Dr. Ajith Joseph. Co-guides at European research institutions. The new office premises at KUFOS 2017) Coordinator- Dr. K. Ajith Joseph NERSC - Prof. Ola. M. Johannessen. campus will strengthen the research infrastructure and increased the Topic of research: Inter annual variability of monsoon over research cooperation with Indian Academia. The ongoing Funded by NF-POGO Alumni Network for Oceans (NANO) Objective of this project is to sustain long term international India.(Defended dissertation) ARCONOR project funded by Research Council of Norway is a Project Leader: Dr. Ravidas Naik, NIO, Goa partnership and cooperation between Norway, Russia, India, platform for NERCI to enter into Arctic Research. China and US through advancing research, higher education and R. Renju – DST-INSPIRE Fellow, doing research under the Co-leader: Dr. Nandini Menon N (NERCI) recruitment within satellite Earth Observations for monitoring guidance of Prof. N. R. Menon at CUSAT. Scientists and PhD students from NERCI will also visit European Aim of the project is to monitor coastal waters of India and Sri and forecasting of the Arctic and support to Arctic shipping. Topic of research: Taxonomy and Systematics of Benthic research institutions particularly NERSC, Bergen and Nansen Lanka for HABs in relation to mariculture activities. Along with in Scientific Society to work on ocean and atmospheric modelling, Collaborating Institutions- Nansen Environmental and Foraminiferans from the South-West Coast of India. situ sampling, Remote Sensing and mathematical modeling ecosystem modelling and satellite Earth observation research in Remote Sensing Center (Bergen), Nansen Scientific Society P.Soorya - registered for Ph.D at CUSAT under the guidance of approaches will also be used to aid further understanding of HAB 2019 and NERCI expects more national projects in the coming year. (Bergen), Nansen International Environmental and Remote Prof. N.R. Menon. dynamics in the aquaculture areas. Sensing Centre (Russia), Nansen-Zhu International Research Topic of research: Structure, seasonality and trophic efficiency of Kochi 29 October, 2019 Centre (China), University of Connecticut (USA). autotrophic picoplankton and their importance in biogeochemistry Atmospheric carbon sequestration potential of trees in Kochi of Cochin backwater. City under the changing environmental scenario (2016 - 2019) Board of Directors Bamboo as a resource for community development and climate Jaini Sara Babu– registered for Ph.D at KUFOS under the Funded by DST change mitigation involving community bamboo plantation to guidance of Dr. K. Ajith Joseph . Lasse H. Pettersson (Chairman), Director of International mitigate climate change and skill development training (2018- Principal Investigator: Dr. Bindu. G Topic of research: Monitoring and forecasting of coastal cooperation, NERSC, Norway. 2019) circulation using remote sensing and hydrodynamic modeling Co-investigator: Dr. K. Ajith Joseph Dr. Sebastian H. Mernild, Director, NERSC, Norway. Funded by Australian Consulate, Chennai. Rakhi N. Raj -registered for Ph.D at KUFOS under the guidance of Dr. Annette Samuelsen, Scientist, NERSC, Norway The idea of the project is to estimate the sequestration potential of Dr. Bindhu ,G Prof.P.V.Joseph,Director(Rtd),IndiaMeteorological Department, the city with the existing vegetation pattern, projecting the carbon Project Leader: Dr. Bindu. G Topic of Research: Status of Air Quality in most polluted cities in Kochi, India. balance for business as usual scenario and potential scenario and Co-PI- Dr. K. Ajith Joseph Dr. K. Ajith Joseph, Executive Director, NERCI suggest measures to be taken for a sustainable city. Kerala,India using GIS and its impact on health aspects. Aim of this project is to utilise satellite imageries for studying the Dr. N. Nandini Menon, Deputy Director, NERCI Normalized Difference Vegetative Index (NDVI) of the plantations Synergistic applications of earth observation data- microwave before and after the implementation of this project to estimate the SAR, IR and Visual data for the validation of Ocean State increase in the plantation area and carbon sequestration capacity of Key Research Areas forecast for north Kerala (2018-2020) the area. Funded by ESSO-INCOIS (Ministry of Earth Sciences) The current focus of research at NERCI are on the following: Principal Investigator- Dr. K. Ajith Joseph Rehabilitation of Vibrio Infested waters of VembanAd Lake: 1. Monsoon and ocean variability, Climate change and Sea level variation pollution and solution (REVIVAL) (2018-2021) Co-PI- Prof. S. Suresh Kumar, KUFOS Co-heads - Prof. P. V. Joseph, NERCI and Prof. Ola, M. Johannessen, NERCI / NANSI Funded by DST The main objective of this project is to utilize the directional wave rider buoy data from wave rider buoy (WRB's) along the Kerala Project leader from NERCI- Dr. Nandini Menon, N. Research Topics: coast, particularly off Kozhikode in synergy with earth observation The main objective is to identify the reservoirs of Vibrio cholera  Relation between Atlantic Multi-decadal Oscillation and the Indian Summer Monsoon Rainfall data-microwave SAR, IR and Visual for collection of site specific and pathogenic viruses in the Vembanad Lake and to assess the  The role of Indian Ocean in the intra-seasonal and inter annual variability of Indian monsoon rainfall real time wave data for the validation of the daily Ocean State seasonal and spatial variation in the hosts/reservoirs of  The rapid warming of the equatorial Indian Ocean and its impact on the regional climate Forecast (OSF) for Indian National Centre for Ocean Information pathogenic Vibrios employing remote sensing and in-situ  The cold pool of the Bay of Bengal during the summer monsoon season Services. methods.  Sea level variations in the Indian Ocean. 06 07 ANNUAL REPORT 2017- 2018 ANNUAL REPORT 2017- 2018

ONGOING PROJECTS

Bhagyalakshmi S - registered for Ph.D at KUFOS under the NERCI has the following ongoing external funded projects from agencies like Department of Science and Technology, ESSO - Indian PhD students under joint projects guidance of Dr.Bindhu, G. National Centre for Ocean Information Services (INCOIS), Direct Aid Program- Australia, Norwegian Research Council (RCN), and Two fulltime and five part time doctoral students are currently Partnership for Observation of Global Oceans (POGO). Ph.D. program by Nansen Scientific Society is continuing at NERCI. Topic of research : Assessment of impact of flood and development carrying out their research work jointly at CUSAT and KUFOS in of hazard map using GIS. affiliation with NERCI and NERSC including the Nansen Scientific Society Ph.D. fellowship program. Modeling bio-geochemical Cycles in Coastal Oceans (2014 - Impact of Atmospheric Aerosols on the Large Scale Smitha A- INDO-MARECLIM fellow and part-time Ph.D student Funding 2018) Circulation over the Indian Summer Monsoon Region at CUSAT under the guidance of Prof. H. S. Ram Mohan. Funded by SAC-ISRO. Funded by DST NERCI is a non-profit research organization recognized by Kerala Topic of research: Wind induced upwelling and the response of University of Fisheries and Ocean Studies (KUFOS) and registered Principal Investigator: Principal Investigator: Dr. Abish B. surface chlorophyll in the Bay of Bengal. (Defended on 18/5/2017) under Article25 of Indian company act. It mainly receives funding Dr. Mohamed Hatha, CUSAT, The objective of this project is to study the interaction of aerosols Ajin A M -Registered for Ph.D under the guidance of Prof. N. R. from Nansen Environmental and Remote Sensing Center and Menon at CUSAT. Co-PI: Dr. Nandini Menon N, NERCI on the large scale atmospheric circulation over the Indian Nansen Scientific Society, Norway. It also receives funding through summer monsoon region. Topic of research: Marine ecosystem studies and biodiversity projects from European Commission, Norwegian Research Council, Co-ordinator: Dr. Mini Raman, SAC concepts. United Nations Environmental Programme (UNEP) and other national agencies like Department of Science and Technology, Aim of this project is to study the carbon pools (organic carbon Nashad. M - Registered for PhD under the guidance of Prof. N. R. Arctic cooperation between Norway, Russia, India, China and Govt.of India, Space Application Centre, ISRO and Dept of components), fluxes (the rates of primary, new and export Menon at CUSAT. Co-guide at NERCI Dr.Nandini Menon. N. Co- US in satellite Earth observation and Education Environment and Climate Change, Govt. of Kerala. production) and organic nitrogen components involved in the guide at NERSC – Lasse H Pettersson. biogeochemistry of coastal oceans around Indian subcontinent (ARCONOR) - research and higher education related to sea Topic of research: Monitoring and modeling of Harmful algal using satellite data. ice, environment, climate change, and operational conditions inthe ArcticOcean focusingonthe NorthernSea Route blooms along the South West coast of India. Prospects for 2019 Funded by- Norway Research Council Shinu Sheela Wilson- Nansen Scientific Society fellow, doing NERCI enters 2019 with plans to strengthen their national and HABAQUA - Harmful Algal Blooms in Aquaculture Ph.D under the guidance of Prof. Mohankumar at CUSAT. Co- Coordinator- Lasse H. Pettersson, NERSC, Norway Indian international cooperation within the Nansen Group and other Indo- ecosystems: a modeling and remote sensing perspective (2016- guides at NERCI- Dr. P. V. Joseph and Dr. Ajith Joseph. Co-guides at European research institutions. The new office premises at KUFOS 2017) Coordinator- Dr. K. Ajith Joseph NERSC - Prof. Ola. M. Johannessen. campus will strengthen the research infrastructure and increased the Topic of research: Inter annual variability of monsoon over research cooperation with Indian Academia. The ongoing Funded by NF-POGO Alumni Network for Oceans (NANO) Objective of this project is to sustain long term international India.(Defended dissertation) ARCONOR project funded by Research Council of Norway is a Project Leader: Dr. Ravidas Naik, NIO, Goa partnership and cooperation between Norway, Russia, India, platform for NERCI to enter into Arctic Research. China and US through advancing research, higher education and R. Renju – DST-INSPIRE Fellow, doing research under the Co-leader: Dr. Nandini Menon N (NERCI) recruitment within satellite Earth Observations for monitoring guidance of Prof. N. R. Menon at CUSAT. Scientists and PhD students from NERCI will also visit European Aim of the project is to monitor coastal waters of India and Sri and forecasting of the Arctic and support to Arctic shipping. Topic of research: Taxonomy and Systematics of Benthic research institutions particularly NERSC, Bergen and Nansen Lanka for HABs in relation to mariculture activities. Along with in Scientific Society to work on ocean and atmospheric modelling, Collaborating Institutions- Nansen Environmental and Foraminiferans from the South-West Coast of India. situ sampling, Remote Sensing and mathematical modeling ecosystem modelling and satellite Earth observation research in Remote Sensing Center (Bergen), Nansen Scientific Society P.Soorya - registered for Ph.D at CUSAT under the guidance of approaches will also be used to aid further understanding of HAB 2019 and NERCI expects more national projects in the coming year. (Bergen), Nansen International Environmental and Remote Prof. N.R. Menon. dynamics in the aquaculture areas. Sensing Centre (Russia), Nansen-Zhu International Research Topic of research: Structure, seasonality and trophic efficiency of Kochi 29 October, 2019 Centre (China), University of Connecticut (USA). autotrophic picoplankton and their importance in biogeochemistry Atmospheric carbon sequestration potential of trees in Kochi of Cochin backwater. City underthe changing environmental scenario (2016 - 2019) Board of Directors Bamboo as a resource for community development and climate Jaini Sara Babu– registered for Ph.D at KUFOS under the Funded by DST change mitigation involving community bamboo plantation to guidance of Dr. K. Ajith Joseph . Lasse H. Pettersson (Chairman), Director of International mitigate climate change and skill development training (2018- Principal Investigator: Dr. Bindu. G Topic of research: Monitoring and forecasting of coastal cooperation, NERSC, Norway. 2019) circulation using remote sensing and hydrodynamic modeling Co-investigator: Dr. K. Ajith Joseph Dr. Sebastian H. Mernild, Director, NERSC, Norway. Funded by Australian Consulate, Chennai. Rakhi N. Raj -registered for Ph.D at KUFOS under the guidance of Dr. Annette Samuelsen, Scientist, NERSC, Norway The idea of the project is to estimate the sequestration potential of Dr. Bindhu ,G Prof.P.V.Joseph,Director(Rtd),IndiaMeteorological Department, the city with the existing vegetation pattern, projecting the carbon Project Leader: Dr. Bindu. G Topic of Research: Status of Air Quality in most polluted cities in Kochi, India. balance for business as usual scenario and potential scenario and Co-PI- Dr. K. Ajith Joseph Dr. K. Ajith Joseph, Executive Director, NERCI suggest measures to be taken for a sustainable city. Kerala,India using GIS and its impact on health aspects. Aim of this project is to utilise satellite imageries for studying the Dr. N. Nandini Menon, Deputy Director, NERCI Normalized Difference Vegetative Index (NDVI) of the plantations Synergistic applications of earth observation data- microwave before and after the implementation of this project to estimate the SAR, IR and Visual data for the validation of Ocean State increase in the plantation area and carbon sequestration capacity of Key Research Areas forecast for north Kerala (2018-2020) the area. Funded by ESSO-INCOIS (Ministry of Earth Sciences) The current focus of research at NERCI are on the following: Principal Investigator- Dr. K. Ajith Joseph Rehabilitation of Vibrio Infested waters of VembanAd Lake: 1. Monsoon and ocean variability, Climate change and Sea level variation pollution and solution (REVIVAL) (2018-2021) Co-PI- Prof. S. Suresh Kumar, KUFOS Co-heads - Prof. P. V. Joseph, NERCI and Prof. Ola, M. Johannessen, NERCI / NANSI Funded by DST The main objective of this project is to utilize the directional wave rider buoy data from wave rider buoy (WRB's) along the Kerala Project leader from NERCI- Dr. Nandini Menon, N. Research Topics: coast, particularly off Kozhikode in synergy with earth observation The main objective is to identify the reservoirs of Vibrio cholera  Relation between Atlantic Multi-decadal Oscillation and the Indian Summer Monsoon Rainfall data-microwave SAR, IR and Visual for collection of site specific and pathogenic viruses in the Vembanad Lake and to assess the  The role of Indian Ocean in the intra-seasonal and inter annual variability of Indian monsoon rainfall real time wave data for the validation of the daily Ocean State seasonal and spatial variation in the hosts/reservoirs of  The rapid warming of the equatorial Indian Ocean and its impact on the regional climate Forecast (OSF) for Indian National Centre for Ocean Information pathogenic Vibrios employing remote sensing and in-situ  The cold pool of the Bay of Bengal during the summer monsoon season Services. methods.  Sea level variations in the Indian Ocean. 06 07 ANNUAL REPORT 2017- 2018 ANNUAL REPORT 2017- 2018

2. Marine ecosystem studies including algal blooms Year Break periods Numbers of days cold pool region. The surface winds show a shift towards the south of India during break periods, while in the active monsoon period the axis 2002 5 July to 16 July 12 Co-heads- Dr. Nandini Menon, N., NERCI, Lasse H. Pettersson, Dr. A. Samuelsen, NERSC of the wind is over mainland India. The winds are stronger south of 6°N Research Topics: 2002 22 July to 31 July 10 during break spells, as compared to active periods. It is shown that this  Vulnerability of marine ecosystems to climate change and its relevance to marine food resources 2004 26 August to 10September 16 enhanced cooling is due to increased wind stress that happens over the  The effect of seasonal and inter-annual monsoon variations on primary production and higher trophic levels of the food in the region during break phases of the summer monsoon, thus confirming Indian Ocean 2005 8 August to 14August 7 our hypothesis.  Increased incidence of Harmful Algal Bloom (HAB) in the Indian Exclusive Economic Zone (EEZ) and the relevance of physical 2005 26 August to 3September 9 and chemical oceanographic parameters Surface winds during break and active phases of 2006 9 July to 24 July 16  Modelling studies and possible development of early warning systems. the monsoon 2009 28 July to 10August 14 The surface wind at 10 m over the region for the composites of break 3. Coastal zone Management and Societal issues Table 1. The break period chosen for the study spells and active periods are presented in Figure 2. The strength of the Co-heads- Prof. N. R. Menon and Dr. K. Ajith Joseph, NERCI; Lasse H Pettersson, NERCI / NERSC winds over the Bay of Bengal, south of 4°N, is enhanced during the break spells (Figure 2) compared to the active period. The strong winds Research Topics: From the 1° × 1° gridded rainfall data (Rajeevan et al. 2006), the in these two periods also show a difference in their distributional  Contemporary challenges in Coastal Zone Management in India including the impact on coastal society normalized daily rainfall is calculated for the area over India pattern. During the break period, stronger winds blow south of India,  Focus on the problem in fisheries sector and help in bringing up guidelines to policy makers in fishing sector (21°–27°N, 72°–85°E) during June– September for the years 2001 to and the maximum wind speeds lie within the cold pool region.  The formulation of more meaningful coastal zone regulations of regional relevance 2010. Prolonged break phases, especially those with normalized However, during active periods, there is a shift in the axis of the surface Utilization of satellite data for the development of decision making tools with linkage to the other research areas rainfall below winds (Joseph and Sijikumar, 2004) and the winds get stronger over −1.0 for seven consecutive days or more and the active phases, with the northern Bay of Bengal. The differences in surface wind between normalized rainfall above +1.0 for six consecutive days or more. the two phases of the monsoon are shown in Figure 2. These break days for the seven cases are listed in Table 1. The periods SCIENCE REPORT FOR 2017-2018 selected for calculating the composites of active monsoon are: (1) 7 August to 15 August 2004; (2) 30 June to 5 July 2005; and (3) 26 August to 31 August 2006. The Cold Pool intrusion into Bay of Bengal during the Break phase of the Indian summer Studying the break periods in the Indian summer monsoon and the monsoon daily SSTevolution in the cold pool region (figure not shown) for the years from 2001 to 2009, it is apparent that a close relationship exists between the enhanced cooling that occurs within the cold pool 1 1 1 that occur within the cold pool region, using SST data from satellite Mary Swapna George , P. V. Joseph , K. Ajith Joseph , Laurent region and break periods during the summer monsoon. We further 2 3 observations. Bertino and Ola M. Johannessen analyze this relationship in the following section. 1 Nansen Environmental Research Centre (India), Cochin Data sets used 2 Nansen Environmental and Remote Sensing Center, Bergen, Tropical Rainfall Measuring Mission Microwave Imager (TMI) Break periods and enhanced cooling within the Norway data from 2001 to 2010 with a 1° resolution were used to verify the cold pool 3 Nansen Scientific Society, Bergen, Norway intra-seasonal and inter-annual variability of SST in the cold pool The composite of ocean surface temperatures for the above region. The Ocean Surface Current Analysis Real-time (OSCAR) The surface winds over the southwest coast of India cause mentioned break and active spells of the summer monsoon, based data- for the study period (2001–2010) obtained from NASA's divergence of the near-surface waters and play a role in bringing on TMI SST data, are presented in Figure 1. The SST pattern during Physical Oceanography Distributed Active Archive Center (https:// upwelled colder subsurface waters to the surface, causing a cooling the break period shows a southward spread of the cold pool, as well Fig. 1 Composites of SST (units: °C) from TMI, for the seven break podaac.jpl.nasa.gov/) at five-day intervals and a spatial resolution of SST (Shetye 1984; Johannessen et al. 1987; Shetye et al. 1990). as enhanced cooling (SST < 28.5°C) within the cold pool region. periods and three active periods of summer monsoon during of 1/3°, are used to identify the characteristics of the Southwest During June to September, the summer monsoon current (SMC) There is a marked between the SST patterns during break and active 2002–2009. The mean differences of SST (units: °C) between the Monsoon current that flows into the Bay of Bengal. flows eastwards around the southern part of India and Sri Lanka phases of the summer monsoon. The mean difference between the two phases (break minus active) are also plotted. into the Bay of Bengal (Vinayachandran et al. 1999, 2004). This The rainfall data over the Indian subcontinent from Indian two phases (break minus active) is also presented in the figure. The current carries the cold upwelled waters into the Bay of Bengal. Meteorological Department, as gridded rainfall data used toIdentify mean difference reaches more than 1°C inside the cold pool region, Joseph et al. (2005) established the existence of the 'cold pool of the the active–break cycles of the Indian summer monsoon, especially towards the southern parts of India. It is particularly clear Bay of Bengal between 3°N and 10°N during the summer monsoon. from Figure 1a that, during the composite of break spells, the cold For wind analysis over the study region, we used the surface winds pool SST is colder compared to the composite of active spells. It is During the summer monsoon, strong cross-equatorial winds flow in at a height of 10 m from ERA-Interim. The data-set contains winds also apparent that there is a cold region north of 15°N in the Bay of the lower levels of the atmosphere over the Indian Ocean, called the at six-hour intervals and at a spatial resolution of 0.5°. The surface Bengal in the active monsoon composite, which is due to the low-level jet stream (LLJ), the existence of which was established winds were used to verify the shift in the LLJ between the location of the LLJ around 15°N during active monsoon spells by Joseph and Raman (1966) and Findlater (1969), and the core of active–break phases of the summer monsoon. (Joseph and Sijikumar 2004). which is at around 850 hPa (at a height of about 1.5 km). The active phase of the monsoon is associated with increased convection and The active–break cycle of the summer monsoon rainfall over India, the eastern Arabian Sea, and the Bay of Bengal, Intra-seasonal variability of the summer monsoon is observed in the Summary when the core of the LLJ passes over the Indian peninsular region wind, convection, and rainfall mainly associated with the The upwelled waters from the southwest coast of India are advected between 12.5°N and 17.5°N. Whereas, during the break phase, the active–break cycles of the Indian summer monsoon (Goswami into areas south of Sri Lanka and further into the south-central Bay of LLJ turns clockwise over the Arabian Sea, bypasses India and flows 2005; Joseph and Sabin 2008). The active spells are associated with Bengal by the Southwest Monsoon Current. During the break spells south of India with its core between 2.5°N and 7.5°N (Joseph and high rainfall and strong low-level winds over India, and break in most of the years studied, an intensification of cooling within the Sijikumar 2004). During break periods, which last from a few days periods are accompanied by decreased winds and subdued monsoon cold pool region is apparent, especially during July–September. Fig.2 Composites of surface winds (vectors; units: m s−1) and their to more than two weeks, the wind stress increases south of latitude rainfall over India. The large-scale rainfall over India is interrupted There are significant differences between the SST patterns during magnitude (shaded; units: m s−1) from ERA-Interim surface wind 10°N in the Bay of Bengal. We hypothesize that the increase in wind for several days during break periods. Rajeevan et al. (2006) break and active periods of the summer monsoon. Intense cooling in data, for the seven break periods and three active periods of the summer monsoon during 2002–2009. The mean differences in wind stress during break monsoon periods over the low latitudes of the suggested a criterion to identify these active– break spells during the the cold pool region is found during break periods. Also observed is a speed (units: m s−1) between the two phases (break minus active) Bay of Bengal cause enhanced SST cooling in the cold pool region. summer monsoon, based on gridded rainfall data. For our analysis, southward extension of these cold waters towards the equator. we follow their criteria to define active and break spells. are also plotted. Note: The cold pool box is marked in black. We study the role of break monsoon spells in the SST fluctuations Whereas, during active periods, the enhanced cooling is absent in the 08 09 ANNUAL REPORT 2017- 2018 ANNUAL REPORT 2017- 2018

2. Marine ecosystem studies including algal blooms Year Break periods Numbers of days cold pool region. The surface winds show a shift towards the south of India during break periods, while in the active monsoon period the axis 2002 5 July to 16 July 12 Co-heads- Dr. Nandini Menon, N., NERCI, Lasse H. Pettersson, Dr. A. Samuelsen, NERSC of the wind is over mainland India. The winds are stronger south of 6°N Research Topics: 2002 22 July to 31 July 10 during break spells, as compared to active periods. It is shown that this  Vulnerability of marine ecosystems to climate change and its relevance to marine food resources 2004 26 August to 10September 16 enhanced cooling is due to increased wind stress that happens over the  The effect of seasonal and inter-annual monsoon variations on primary production and higher trophic levels of the food in the region during break phases of the summer monsoon, thus confirming Indian Ocean 2005 8 August to 14August 7 our hypothesis.  Increased incidence of Harmful Algal Bloom (HAB) in the Indian Exclusive Economic Zone (EEZ) and the relevance of physical 2005 26 August to 3September 9 and chemical oceanographic parameters Surface winds during break and active phases of 2006 9 July to 24 July 16  Modelling studies and possible development of early warning systems. the monsoon 2009 28 July to 10August 14 The surface wind at 10 m over the region for the composites of break 3. Coastal zone Management and Societal issues Table 1. The break period chosen for the study spells and active periods are presented in Figure 2. The strength of the Co-heads- Prof. N. R. Menon and Dr. K. Ajith Joseph, NERCI; Lasse H Pettersson, NERCI / NERSC winds over the Bay of Bengal, south of 4°N, is enhanced during the break spells (Figure 2) compared to the active period. The strong winds Research Topics: From the 1° × 1° gridded rainfall data (Rajeevan et al. 2006), the in these two periods also show a difference in their distributional  Contemporary challenges in Coastal Zone Management in India including the impact on coastal society normalized daily rainfall is calculated for the area over India pattern. During the break period, stronger winds blow south of India,  Focus on the problem in fisheries sector and help in bringing up guidelines to policy makers in fishing sector (21°–27°N, 72°–85°E) during June– September for the years 2001 to and the maximum wind speeds lie within the cold pool region.  The formulation of more meaningful coastal zone regulations of regional relevance 2010. Prolonged break phases, especially those with normalized However, during active periods, there is a shift in the axis of the surface Utilization of satellite data for the development of decision making tools with linkage to the other research areas rainfall below winds (Joseph and Sijikumar, 2004) and the winds get stronger over −1.0 for seven consecutive days or more and the active phases, with the northern Bay of Bengal. The differences in surface wind between normalized rainfall above +1.0 for six consecutive days or more. the two phases of the monsoon are shown in Figure 2. These break days for the seven cases are listed in Table 1. The periods SCIENCE REPORT FOR 2017-2018 selected for calculating the composites of active monsoon are: (1) 7 August to 15 August 2004; (2) 30 June to 5 July 2005; and (3) 26 August to 31 August 2006. The Cold Pool intrusion into Bay of Bengal during the Break phase of the Indian summer Studying the break periods in the Indian summer monsoon and the monsoon daily SST evolution in the cold pool region (figure not shown) for the years from 2001 to 2009, it is apparent that a close relationship exists between the enhanced cooling that occurs within the cold pool 1 1 1 that occur within the cold pool region, using SST data from satellite Mary Swapna George , P. V. Joseph , K. Ajith Joseph , Laurent region and break periods during the summer monsoon. We further 2 3 observations. Bertino and Ola M. Johannessen analyze this relationship in the following section. 1 Nansen Environmental Research Centre (India), Cochin Data sets used 2 Nansen Environmental and Remote Sensing Center, Bergen, Tropical Rainfall Measuring Mission Microwave Imager (TMI) Break periods and enhanced cooling within the Norway data from 2001 to 2010 with a 1° resolution were used to verify the cold pool 3 Nansen Scientific Society, Bergen, Norway intra-seasonal and inter-annual variability of SST in the cold pool The composite of ocean surface temperatures for the above region. The Ocean Surface Current Analysis Real-time (OSCAR) The surface winds over the southwest coast of India cause mentioned break and active spells of the summer monsoon, based data- for the study period (2001–2010) obtained from NASA's divergence of the near-surface waters and play a role in bringing on TMI SST data, are presented in Figure 1. The SST pattern during Physical Oceanography Distributed Active Archive Center (https:// upwelled colder subsurface waters to the surface, causing a cooling the break period shows a southward spread of the cold pool, as well Fig. 1 Composites of SST (units: °C) from TMI, for the seven break podaac.jpl.nasa.gov/) at five-day intervals and a spatial resolution of SST (Shetye 1984; Johannessen et al. 1987; Shetye et al. 1990). as enhanced cooling (SST < 28.5°C) within the cold pool region. periods and three active periods of summer monsoon during of 1/3°, are used to identify the characteristics of the Southwest During June to September, the summer monsoon current (SMC) There is a marked between the SST patterns during break and active 2002–2009. The mean differences of SST (units: °C) between the Monsoon current that flows into the Bay of Bengal. flows eastwards around the southern part of India and Sri Lanka phases of the summer monsoon. The mean difference between the two phases (break minus active) are also plotted. into the Bay of Bengal (Vinayachandran et al. 1999, 2004). This The rainfall data over the Indian subcontinent from Indian two phases (break minus active) is also presented in the figure. The current carries the cold upwelled waters into the Bay of Bengal. Meteorological Department, as gridded rainfall data used toIdentify mean difference reaches more than 1°C inside the cold pool region, Joseph et al. (2005) established the existence of the 'cold pool of the the active–break cycles of the Indian summer monsoon, especially towards the southern parts of India. It is particularly clear Bay of Bengal between 3°N and 10°N during the summer monsoon. from Figure 1a that, during the composite of break spells, the cold For wind analysis over the study region, we used the surface winds pool SST is colder compared to the composite of active spells. It is During the summer monsoon, strong cross-equatorial winds flow in at a height of 10 m from ERA-Interim. The data-set contains winds also apparent that there is a cold region north of 15°N in the Bay of the lower levels of the atmosphere over the Indian Ocean, called the at six-hour intervals and at a spatial resolution of 0.5°. The surface Bengal in the active monsoon composite, which is due to the low-level jet stream (LLJ), the existence of which was established winds were used to verify the shift in the LLJ between the location of the LLJ around 15°N during active monsoon spells by Joseph and Raman (1966) and Findlater (1969), and the core of active–break phases of the summer monsoon. (Joseph and Sijikumar 2004). which is at around 850 hPa (at a height of about 1.5 km). The active phase of the monsoon is associated with increased convection and The active–break cycle of the summer monsoon rainfall over India, the eastern Arabian Sea, and the Bay of Bengal, Intra-seasonal variability of the summer monsoon is observed in the Summary when the core of the LLJ passes over the Indian peninsular region wind, convection, and rainfall mainly associated with the The upwelled waters from the southwest coast of India are advected between 12.5°N and 17.5°N. Whereas, during the break phase, the active–break cycles of the Indian summer monsoon (Goswami into areas south of Sri Lanka and further into the south-central Bay of LLJ turns clockwise over the Arabian Sea, bypasses India and flows 2005; Joseph and Sabin 2008). The active spells are associated with Bengal by the Southwest Monsoon Current. During the break spells south of India with its core between 2.5°N and 7.5°N (Joseph and high rainfall and strong low-level winds over India, and break in most of the years studied, an intensification of cooling within the Sijikumar 2004). During break periods, which last from a few days periods are accompanied by decreased winds and subdued monsoon cold pool region is apparent, especially during July–September. Fig.2 Composites of surface winds (vectors; units: m s−1) and their to more than two weeks, the wind stress increases south of latitude rainfall over India. The large-scale rainfall over India is interrupted There are significant differences between the SST patterns during magnitude (shaded; units: m s−1) from ERA-Interim surface wind 10°N in the Bay of Bengal. We hypothesize that the increase in wind for several days during break periods. Rajeevan et al. (2006) break and active periods of the summer monsoon. Intense cooling in data, for the seven break periods and three active periods of the summer monsoon during 2002–2009. The mean differences in wind stress during break monsoon periods over the low latitudes of the suggested a criterion to identify these active– break spells during the the cold pool region is found during break periods. Also observed is a speed (units: m s−1) between the two phases (break minus active) Bay of Bengal cause enhanced SST cooling in the cold pool region. summer monsoon, based on gridded rainfall data. For our analysis, southward extension of these cold waters towards the equator. we follow their criteria to define active and break spells. are also plotted. Note: The cold pool box is marked in black. We study the role of break monsoon spells in the SST fluctuations Whereas, during active periods, the enhanced cooling is absent in the 08 09 ANNUAL REPORT 2017- 2018 ANNUAL REPORT 2017- 2018

Cited References Sciences-Earth and Planetary Sciences, 93(4),399-411. Goswami, B. N., 2005: South Asian monsoon. Springer Berlin Shetye, S. R., A. D. Gouveia, S. S. C. Shenoi, D. Sundar,G. S. Cited References Ratna SB, Cherchi A, Joseph PV, Behera S, Abish B, Masina Heidelberg, 19– 61. India. Proceedings of the Indian Academy of S. 2016. Moisture variability over the Indo-Pacific region and Michael, A. M. Almeida, and K. Santanam, 1990: Hydrography and Abish B, Joseph PV, Johannessen OM. 2013. Weakening Sciences-Earth and Planetary Sciences, 93(4), 399-411. its influence on the Indian summer monsoon rainfall. Climate circulation off the west coast of India during the Southwest trend of the tropical easterly jet stream of the boreal summer Dynamics, 46: 949–965. Joseph, P. V. and P. L. Raman, 1966: Existence of low level westerly Monsoon 1987. Journal of Marine Research, 48, 359378. monsoon season 1950--2009. J. Climate 26 9408-9414, jet stream over Peninsular India during July. Indian. J. Meteorol. Vinayachandran, P. N., Yukio Masumoto, Tetsuya Mikawa and doi: 10.1175/JCLI-D-13-00440.1. Geophys., 17, 407–410. Toshio Yamagata, 1999: Intrusion of the Southwest Monsoon Published results: Cherchi A, Navarra A. 2013. Influence of ENSO and of the Joseph, P. V. and S. Sijikumar, 2004: Intra seasonal variability of the Current into the Bay of Bengal, Journal of Geophysical Research, (Published article: Abish B., Cherchi, A. and Ratna, S. B. Indian Ocean Dipole on the Indian summer monsoon low-level jet stream of the Asian summer monsoon. Journal of 104(C5), 11,077–11,085. (2018), ENSO and the recent warming of the Indian Ocean. variability. Clim Dyn 41: 81-103 DOI 10.1007/s00382- Climate, 17, 1449 – 1458. Vinayachandran, P.N., P. Chauhan, M. Mohan, and S. Nayak, 2004: Int. J. Climatol, 38: 203-214. doi:10.1002/joc.5170 ) Joseph, P. V., and T. P. Sabin, 2008: An ocean–atmosphere interac- Biological response of the sea around Sri Lanka to summer 012- 1602-y tion mechanism for the active break cycle of the Asian summer monsoon. Geophysical Research Letters, 31(1). monsoon. Climate dynamics, 30(6), 553- 566. Joseph, P. V., K. P. Sooraj, C. A. Babu and T. P. Sabin, 2005. : A Cold Published results: Pool in the Bay of Bengal and its interaction with the active–break (This article is an extract from the paper: George, M.S., Joseph, P.V., cycles of monsoon. CLIVAR Exchanges, 10(3), 10–12. Ajith Joseph, K. Laurent Bertino and O. M. Johannessen. 2017. The Statistical analysis of convective indices derived from radiosonde and a wind profiling Radar Rajeevan, M., Bhate, J., Kale, J. D., and B. Lal, 2006: High Cold Pool of the Bay of Bengal and its association with the break resolution daily gridded rainfall data for the Indian region: Analysis phase of the Indian summer monsoon. Atmospheric and Oceanic of break and active monsoon spells. Current Science, 91(3), 296- Science Letters. Arun K1,2 , Abish B1 and Manoj MG3 thunderstorm propagation and evolution and thunderstorm- 306. , http://dx.doi.org/10.1080/16742834.2017.1294017) 1 Nansen Environmental Research Centre (India), Cochin related hazards like heavy rain, hail and lightning strikes are Shetye, S. R., 1984: Seasonal variability of the temperature field off of high benefit for weather-dependent industries. Although and Ph.D. dissertation 2 Cochin University of Science and Technology, Cochin the south-west coast of India. Proceedings of the Indian Academy of embedded in a synoptic environment, thunderstorms internal 3 Advanced Centre for Atmospheric Radar Research,Cochin dynamics can restrict a reliable nowcasting to very short lead- times (Doswell and Bosart,2001). Depending on the thunderstorm Warming of the Indian Ocean during La Niña Most of the weather phenomena in tropics are related with system, the lead- time can fall to tens of minutes. A better convective activities. The convective activity of atmosphere understanding of the driving processes, a well-set crucial storm is driven by the instability prevailing over the atmosphere. parameter and an accurate index would help improve the prediction Abish B1 , Annalisa Cherchi2 , Satyaban B. Ratna3 The weakening of wind is associated with a strong anomalous Thunderstorms are the most dangerous convective systems, skills of their non-linear behavior. Here we derive the indices 1 Nansen Environmental Research Centre (India), Cochin Showalter index (SI, Showalter, 1953), lifted index (LI, Galway, descending motion over the eastern IO compared to the west. because of their large vertical extension, strong updrafts 2 Fondazione Centro Euro-Mediterraneo sui Cambiamenti Therefore, the combined warming due to El Niño and La Niña is 1956), severe weather index (SWEAT, Miller, 1972), K index (KI, Climatici, and Istituto Nazionale di Geofisicae Vulcanologia, considered to have contributed to the recent persistent warming of and their extreme intensity in terms of precipitation in short George 1960), total totals index (TTI), convective available potential Bologna, Italy IO with strong warming from 90°E to the western IO. Analysis of period of time. So, the thunderstorm prediction is very energy (CAPE, Moncrieff and Miller, 1976), convective inhibition 3 Application Laboratory, Japan Agency for Marine-Earth Science oceanic data confirms the penetration of warm waters into deeper essential but really a challenging task. energy (CINE) and bulk Richardson number (BRN); and analyze the levels during both the events. The accumulation of heat in the upper and Technology, Japan The conditions require for thunderstorm formation are statistical probability of each of the indices in nowcasting levels favour the warming towards the western IO post 1976 by thunderstorm development. The recent Indian Ocean (IO) warming and its relation with the El slowing down the mixed layer cooling by vertical processes (Fig 4). instability, convection, moisture and lifting mechanism. Niño Southern Oscillation (ENSO) is investigated using available Many methods and indices are available for assessing the ocean and atmospheric reanalysis. Though the ENSO peaks during convective activity of atmosphere. But those indices are not winter, the IO warming is larger in summer (Ratna et al. 2016) and capable of accurate prediction in all regions. Most of the its tele-connection with the summer monsoon is known to be strong indices do not consider all parameters, and they are based in this season (Cherchi and Navarra, 2013). High IO SST weakens mostly on the single parameter which influences the the horizontal thermal gradient that drives the Indian summer monsoon circulation (Abish et al. 2013). By comparing the events thunderstorm activity and they are valid only for specific before and after 1976, our results indicate that the Indian Ocean had regions. These methods will not give an accurate experienced a distinct change in the warming pattern. After 1976, prediction. This difficulty demands a comprehensive study during the boreal summer season the cold anomalies in the IO were of creating an accurate thunderstorm index for our region by replaced by warm anomalies in both warm (El Niño) and cold (La considering all parameters like temperature, moisture and Niña) ENSO events (Fig 3). wind shear. It will be very useful to prevent extensive damage and losses to lives and property, thunderstorm Fig 4 (a,b) El Niño and (c,d) La Niña composite anomalies of temperature (°K) profiles in the first 300 m averaged in 0-20° N hazards in aviation and agriculture. during pre and post 1976 events, respectively. This study aims to perform a statistical analysis of various convective indices to test their skill in predicting The warming during La Niña events post-1976 may have a contribution thunderstorms. We intend to estimate the success ratio of from the preceding strong El Niño as evident from the prominent warming in 1988, 1998 and 2010. It is likely that these few La Niña each index in predicting either formation or non-formation events contributed the most to the post-1976 composite warming. of thunderstorms and compare their performance under Compared to the very large positive SST anomalies of the strong El Niño various atmospheric conditions over the monsoon- events, the La Niña that followed were less intense in IO to cool the SST, dominated Western Ghats region. It is also planned to leading to the sustained warming of the IO. However, even after propose the major short comings of various stability indices removing the strong El Niño events of 1982 and 1997 from the post- and propose to improve the prediction skill of the same. Fig 3 Composite anomalies of detrended SST (°C) of (a,b) El Niño 1976 composite, the IO shows warm anomalies almost covering the Fig. 5 The study region, we made analysis for the two stations: and (c,d) La Niña events in the periods pre and post 1976, entire basin indicating that the changes in the composite post-1976 are Improved short-term prediction (especially nowcasting) of Thiruvananthapuram (TVM: 8˚48'N, 79˚5'E) Cochin (CHN:9˚5'N, respectively. Contours indicate regions significant at 95% level only partially driven by the two extreme events recorded. 76˚27'E) 10 11 ANNUAL REPORT 2017- 2018 ANNUAL REPORT 2017- 2018

This study primarily used data from radiosonde observations. The Statistical analysis of each Convective Index For thunderstorms formation, the suitability is of the order given we suggest that there is an utmost requirement of explicitly benefit of this approach is that it is based on direct observations of the In the following table.3, we list out the details of various indices in below: incorporating the most influential parameters such as vertical atmosphere. Archived upper air soundings from all the study area in velocity and moisture in the development of the new index. Hence southern peninsular India were retrieved from the website of fulfilling both the conditions of occurrence and non-occurrence of TTI > CINE ≥ KI > SSI > SWEAT > LI > CAPE > BRN thunderstorms. It also details the cases where each index precisely it is proposed to develop a new index based on the appropriate University of Wyoming's Department of Atmospheric Science predicted. For non-formation of thunderstorms, the suitability is of the order combination these indices, and by considering all the influential (http://weather.uwyo.edu/upperair/sounding.html). The website given below: factors over the tropical sub-continent by employing data from provides calculations for many different stability indices for each Radiosonde, Radar and Microwave Radiometer. sounding. The stations which were considered part of Southeast Asia. KI > SSI > SWEAT > TTI > CAPE ≥ CINE > LI > BRN The above objective was achieved by means of creating an The main shortcoming of radiosonde soundings is that they are only By sorting the available indices based on their success rate and accurate thunderstorm index suitable for our region in various launched from two locations in the Kerala region. Even when using commonality in both the categories, it is seen that the indices viz. seasons by considering all influential parameters like temperature, criteria that assume a sounding can represent a large section of the TTI, SSI, and KI are the most appropriate indices for the prediction moisture, wind shear etc. A detailed analysis of the performance of atmosphere, a large portion of Kerala cannot be included. To attain of both the formation and non- formation of thunderstorms. The this new index will be tested by suitable mesoscale numerical data for a larger number of thunderstorms, more years were examined mean success ratios of formation and non-formation of weather prediction models such as the Weather Research and than in most studies of this nature. While performing quality control thunderstorms for all indices are 27% and 84 %, respectively. Thus, Forecasting (WRF) model. Further, we propose to differentiate the on all the soundings would be a very time-consuming task, the large it is observed that the likelihood of success of predicting non- roles of dynamics and thermodynamics in triggering number of soundings included in the analysis should ensure that formation of thunderstorm is much higher (> 300%) than that of thunderstorms with the help of a mesoscale model (WRF) by outliers and erroneous soundings would have a minimal effect on the formation of thunderstorms. Hence it is proposed to develop a new classifying thunderclouds formed under thermal instability and results of statistical analyses (Craven et al. 2002). Daily Weather index based on the appropriate combination these indices. dynamical instability. Reports were obtained from the daily weather report of India Hence, we conceptualize the development of a new convective Meteorological Department's regional centre in Kerala (KDWR). Index primarily based on the prioritized Indices which are common Published results: This data is used to determine the thunderstorm days and to both the categories, i.e., the formation and non-formation of Abstract published: Arun K, MG Manoj, Santosh KR, K corresponding temperature, humidity and rainfall measurements for thunderstorms. However, it is observed from this analysis that the Mohankumar and Abish B (2018), Statistical analysis of the pre-monsoon (March, April, May -MAM) and post- monsoon success rate for prediction of thunderstorms formation is convective indices derived from radiosonde and a wind profiling (October, November, December -OND) monthsbetween the years of significantly less compared to that of non-formation. This indicates radar, iRAD2018 conference proceedings, H-09,3. 2005 and 2014 over Cochin and Thiruvananthapuram. Table 3. Success ratio of prediction (%) of each of the Indices for that the existing indices have shortcomings in the prediction. This Presented this paper in Indian Radar Meteorology Conference formation and non-formation of thunderstorms could be because those indices do not take into consideration all the (iRAD-2018), conducted by National Atmospheric Research Variation of Indices during thunderstorm (TS) factors that lead to the genesis and development of thunderstorms. A Laboratory (NARL), Tirupati, Andhra Pradesh. suitable combination of the existing indices could lead to a better and non- thunderstorm events (NTS). prediction of the same. In addition, we may need to consider any We analyze the variation of the convective indices viz. CAPE, other missing but relevant parameter once the combined success CINE, LI, KI, SSI, TTI, BRN and SWEAT during thunderstorm rate is below the level of expectation. Cited References and non-thunderstorm days. In general, the parameters showed a Craven, JP, Brooks, HE and Hart, JA, (2002), Baseline Climatology wide range of values irrespective of thunderstorm day or not, and of Sounding Derived Parameters Associated with Deep, Moist hence it is difficult to observe a sound criterion for each category as Convection, Preprints, 21st Conf. Severe Local Storms, San Summary Antonio. stipulated by the established criteria by previous researchers. This work aims at describing the proper use of diagnostic variables in thunderstorm forecasting. A comprehensive review of the Doswell, CA, and Bosart LF, (2001), Extratropical synoptic-scale existing indices has been undertaken processes and severe convection, Meteorological Monographs, 28:27–70. revealing their merits and shortcomings. A classification of George, JJ, (1960), Weather Forecasting for Aeronautics. Academic diagnostic variables is developed, indicating the limitations of Press, 673 pp. such variables and their suitability for operational diagnosis and forecasting. The utility of diagnostic variables as forecast J. G. Galway, (1956), The Lifted Index as a Predictor of Latent parameters is thus revealed. Many diagnostic variables in Instability, Bulletin of the American Meteorological Society, Vol. operational use in forecasting thunderstorms have not met these 37, pp. 528-529. criteria for demonstrated utility as forecast parameters. For most Miller, RC, (1972), Notes on analysis and severe storm forecasting such variables, their forecast value generally has not been procedures of the Air Force Global Weather Central, Tech. established via rigorous verification. In this work, the essential Report200(R), Headquarters, Air Weather Service, Scott Air Force criteria required to determine whether a new diagnostic variable Base, IL 62225, 190 pp. represents an operational forecast parameter is proposed. Moncrieff, MW, and Miller, MJ, (1976), The dynamics and By sorting the available indices based on their success rate and simulation of tropical cumulonimbus and squall lines, Q.J.R. Roy. commonality in both the categories, it is seen that the indices viz. Meteorol. Soc., 102, 373-394. Fig. 6 The success ratio of different indices in predicting the TTI, SSI, and KI are the most appropriate indices for the prediction Showalter, AK, (1953), A Stability Index for Thunderstorm Table 2. Mean and standard deviation of each of the index. occurrence and non-occurrence of thunderstorms of both the formation and non- formation of thunderstorms. Here Forecasting, Bulletin of the American Meteorological Society, Vol. 34, No. 6, pp. 250- 252.

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derivative of the model output y with respect to an input factor Xi , realizations of the input factor vector X. The input-output relationship Sensitivity of the simulated Oxygen Minimum Zone to biogeochemical processes at an i.e. a model parameter. If a model has k number of independent was represented by means of a multiple- regression model: input factors Xi , where i = 1, 2,...,k, the elementary effect of the oligotrophic site in the Arabian Sea yi = b 0 + b i X 1 + b 2 X 2 +... +bi X i + residuals - (3) parameter Xi is given by: and the standardized regression coefficients βi were used as global sensitivity indices of the input factors (Saltelli et al.,2008): 1 2 2,3 Syam Sankar , Luca Polimene , Lorenzo Marin , N. Nandini dissolved nutrients, organic detritus, oxygen and CO2 . Pelagic living 1 4 3 β = b σ /σ - (4) Menon , Annette Samuelsen , Roberto Pastres , Stefano organisms are subdivided in three functional groups describing the i i Xi y 2,5 planktonic trophic chain: primary producers (phyto-plankton), - (1) Ciavatta Where σXiand σ y are the standard deviations of the realizations of the 1. consumers (zooplankton) and decomposers (bacteria). Primary Nansen Environmental Research Centre (India), Cochin input factor Xi and of the model output y, respectively. The regression 2. producers and consumers are subdivided into 4 and 3 size-based Plymouth Marine Laboratory, United Kingdom Where j represents an initial point in the space of the parameters, y coefficients in equation (4) provide meaningful parameter rankings functional types, respectively. The phytoplankton community is 3. represents the model output, and the increment Δ∈ [0,1] is a pre- only when the linear regression explains a relatively large fraction of Ca' Foscari University of Venice, Italy composed of picophytoplankton, nanoflagellates, dinoflagellates 4. defined proportion of the range of variation of the parameters, the model output variability (Saltelli et al., 2000). Nansen Environmental Remote Sensing Center and Bjerknes and diatoms, while the zooplankton community is composed of which, being constant, allows the sensitivity index to account for Centre for Climate Research, Norway mesozoo plankton, microzooplankton and heterotrophic the statistical distribution of the input factors. Following The configuration of ERSEM applied here has 342 pelagic 5. National Centre for Earth Observation, Plymouth Marine nanoflagellates. A key feature of ERSEM is the decoupling between Campolongo et al. (2007), we computed the sensitivity index for parameters. However, parameters defining biogeochemical carbon and nutrient dynamics allowing the simulation of variable Laboratory, United Kingdom the input parameter Xi by averaging the absolute values of the analysis of the input-output relationship was performed using the stoichiometry within the modeled organisms. elementary effects of that parameter across all the trajectories software Origin, and the regression coefficients defining the sensitivity index for the parameter ranking were estimated using the Introduction least-squares method proposed by Draper and Smith (1981). Oxygen minimum zones (OMZs) are areas of the oceans Sensitivity index = characterized by low dissolved oxygen concentrations at Results intermediate depths (50–1000 m). Paulmier and Ruiz-Pino (2009) - (2) defined OMZs as regions where dissolved oxygen (DO) The 1-D GOTM-ERSEM model was implemented for an oligotrophic concentrations are less than 20 μmol L−1 , decreasing to 1μmol L−1 in The sensitivity index (μ *) is computed by averaging |EE j| site in the central Arabian Sea (65°E, 13°N), which falls within the OMZ in this region (Paulmier and Ruiz-Pino, 2009). The actual depth the core of the OMZ. The formation, maintenance and constants (e.g. the inverse of the Redfield ratio of phosphorous to of the central Arabian Sea is close to 4500 m, but we have simulated intensification of the OMZs are governed by the interaction of carbon) were not object of this investigation, thus the number of the water column up to a depth of 500 m only, using 100 m vertical physical processes (oxygen solubility driven by temperature and parameters included in the screening analysis was 207. These levels. The selection of this maximum depth was based on previous salinity, presence of regions of low ventilation and subsurface parameters were categorized and divided into k = 21 groups. The studies, indicating that the upper 500 meters include the upper currents of poorly oxygenated water) with biological processes increment of the input factors was set Δ=2/3, following the oxycline and the absolute minimum of oxygen (McCreary et al., (primary production, heterotrophic activities, bacterial respiration recommendation in Saltelli et al., 2008. and remineralization of organic matter). 2013), as confirmed here by test simulations extending till the depth of Groups 1–7 comprised of parameters characterizing primary 1500 meters. The model had significant skill in simulating the The objective of the present study is to identify the important production, whereas groups 8 to 12 were bacteria- related climatology of oxygen and nutrient observations at the study site. biogeochemical processes which need to be carefully described to parameters. The remaining groups included zooplankton understand, simulate and predict OMZ formation and evolution in parameters, food matrix parameters, deep- water remineralization The result of the screening analysis based on the Morris method the oceans. This was done by ranking the importance of showed that the 14th group (zooplankton loss parameters), 9th group closure parameters, sedimentation parameters and light extinction th biogeochemical parameters of a complex marine ecosystem model. parameters. The analysis was carried out with the range of (bacterial loss parameters) and 11 group (additional nutrient This model is the European Regional Seas Ecosystem Model variability of the uniform distribution of the parameters kept within remineralization parameters) were found to be the three most relevant (ERSEM) (Butenschön et al., 2016), which includes most of the −30% to + 30% of the reference value of the parameters. groups for the simulation of the OMZ, in order (Fig. 8). The biogeochemical processes driving OMZ dynamics. New for this Fig. 7 Schematic of the coupled GOTM-ERSEM parameters included in the groups 14 and 9 characterize the biological study is that we included denitrification in ERSEM, since this model configuration used in this study. The Monte Carlo sampling-based sensitivity analysis was processes of oxygen consumption by the zooplankton functional process is relevant in OMZ systems, but it was not represented in performed by selecting n = 1000 random values for each of the m groups and by bacterial functional group, respectively. The 38 model the pelagic component of the model (Butenschön et al., 2016). We independent input parameters found to be the most relevant in the parameters that emerged collectively as the most important in the ranked the importance of ERSEM parameters for OMZ simulation, The hydrodynamic model GOTM screening analysis. In choosing this number n of model simulations, screening analysis were the input factors to the Monte Carlo sampling- by using in sequence the Morris screening technique, followed by a we considered the rule of thumb of at least 20 realizations for each based sensitivity and ranking analysis. Monte Carlo sampling-based ranking. GOTM (General Ocean Turbulence Model; Burchard et al., 1999) is input factor desirable fori i multiple regression analysis. The multiple a 1-D water column model used for the computation of regressioncomputed at points sampled within the whole space of the In the present study, the analysis was performed using a one- hydrodynamic and thermodynamic processes related to vertical parameters. Therefore, this technique can be considered as a global dimensional (1-D) implementation of ERSEM for an oligotrophic mixing. The model calculates velocities, turbulence, temperature screening technique, though each single elementary effect is a first site in the open Arabian Sea (65°E, 13°N), advancing a comparable and salinity, as well as heat, momentum and freshwater fluxes order derivative, i.e. a local sensitivity (Campolongo et al., 2007). model configuration in this region by Blackford et al. (2004). The between the ocean and the atmosphere, when forced with local Importantly, the index μ* allows one to reduce the computational Arabian Sea is characterized by a vast OMZ with DO meteorological inputs. Routines for nudging observations also exist −1 cost of the screening analysis by computing the sensitivity of input concentrations below 0.05 ml L , at depths between 150 and 1250 in GOTM and they were applied here for the relaxation of the model parameters pooled in groups. The drawback of grouping input m, and it is one of the three major denitrification sites in world simulation towards salinity and water temperature profiles. factors is the loss of information regarding the relative importance oceans. of factors belonging to the same group. This was addressed by The screening Morris method performing a Monte Carlo-based sensitivity analysis of the The GOTM-ERSEM model was subjected initially to a screening parameters within the groups. The biogeochemical model ERSEM sensitivity analysis. This aimed to identify the subset of ERSEM The vertical dynamics of the water column were represented by parameters that are most important for the simulation of the coupling ERSEM with the 1-D hydrodynamic model GOTM (Fig. minimum oxygen concentration at the study site. The screening Monte Carlo simulations and ranking method 7) (Butenschön et al., 2016). ERSEM (Baretta et al., 1995; Fig. 8 Result of the screening analysis based on the Morris method sensitivity analysis used the Morris method, as proposed in Morris A Monte Carlo sampling-based sensitivity analysis was applied to Blackford et al., 2004; Butenschön et al., 2016) is a biomass and applied to 21 groups of model parameters. The three most important (1991), modified by Campolongo et al. (2007). The Morris rank the importance of the m parameters X = (X , X , ..., X ..., X ), i functional group- based biogeochemical model describing the 1 2 i m groups (i.e. the ones with the highest values of the sensitivity index technique, described thoroughly in Saltelli et al. (2008), is a = 1, 2, ..., m, within the groups identified as most important in the nutrient and carbon cycle within the low trophic levels of the marine μ*) were, in order: I) group 14 (zooplankton loss parameters); II) qualitative sensitive analysis based on the concept of Elementary Morris screening analysis (Saltelli et al., 2008). A crude Monte ecosystem. Model state variables include living organisms, group 9 (bacterial loss parameters); and III) group 11 (additional Effect (EE), which is an approximation of the first order partial Carlo sampling scheme was used to generate a number n of nutrient remineralization parameters). 14 15 ANNUAL REPORT 2017- 2018 ANNUAL REPORT 2017- 2018

derivative of the model output y with respect to an input factor Xi , realizations of the input factor vector X. The input-output relationship Sensitivity of the simulated Oxygen Minimum Zone to biogeochemical processes at an i.e. a model parameter. If a model has k number of independent was represented by means of a multiple- regression model: input factors Xi , where i = 1, 2,...,k, the elementary effect of the oligotrophic site in the Arabian Sea yi = b 0 + b i X 1 + b 2 X 2 +... +bi X i + residuals - (3) parameter Xi is given by: and the standardized regression coefficients βi were used as global sensitivity indices of the input factors (Saltelli et al.,2008): 1 2 2,3 Syam Sankar , Luca Polimene , Lorenzo Marin , N. Nandini dissolved nutrients, organic detritus, oxygen and CO2 . Pelagic living 1 4 3 β = b σ /σ - (4) Menon , Annette Samuelsen , Roberto Pastres , Stefano organisms are subdivided in three functional groups describing the i i Xi y 2,5 planktonic trophic chain: primary producers (phyto-plankton), - (1) Ciavatta Where σXi and σ y are the standard deviations of the realizations of the 1. consumers (zooplankton) and decomposers (bacteria). Primary Nansen Environmental Research Centre (India), Cochin input factor Xi and of the model output y, respectively. The regression 2. producers and consumers are subdivided into 4 and 3 size-based Plymouth Marine Laboratory, United Kingdom Where j represents an initial point in the space of the parameters, y coefficients in equation (4) provide meaningful parameter rankings functional types, respectively. The phytoplankton community is 3. represents the model output, and the increment Δ∈ [0,1] is a pre- only when the linear regression explains a relatively large fraction of Ca' Foscari University of Venice, Italy composed of picophytoplankton, nanoflagellates, dinoflagellates 4. defined proportion of the range of variation of the parameters, the model output variability (Saltelli et al., 2000). Nansen Environmental Remote Sensing Center and Bjerknes and diatoms, while the zooplankton community is composed of which, being constant, allows the sensitivity index to account for Centre for Climate Research, Norway mesozoo plankton, microzooplankton and heterotrophic the statistical distribution of the input factors. Following The configuration of ERSEM applied here has 342 pelagic 5. National Centre for Earth Observation, Plymouth Marine nanoflagellates. A key feature of ERSEM is the decoupling between Campolongo et al. (2007), we computed the sensitivity index for parameters. However, parameters defining biogeochemical carbon and nutrient dynamics allowing the simulation of variable Laboratory, United Kingdom the input parameter Xi by averaging the absolute values of the analysis of the input-output relationship was performed using the stoichiometry within the modeled organisms. elementary effects of that parameter across all the trajectories software Origin, and the regression coefficients defining the sensitivity index for the parameter ranking were estimated using the Introduction least-squares method proposed by Draper and Smith (1981). Oxygen minimum zones (OMZs) are areas of the oceans Sensitivity index = characterized by low dissolved oxygen concentrations at Results intermediate depths (50–1000 m). Paulmier and Ruiz-Pino (2009) - (2) defined OMZs as regions where dissolved oxygen (DO) The 1-D GOTM-ERSEM model was implemented for an oligotrophic concentrations are less than 20 μmol L−1 , decreasing to 1μmol L−1 in The sensitivity index (μ *) is computed by averaging |EE j| site in the central Arabian Sea (65°E, 13°N), which falls within the OMZ in this region (Paulmier and Ruiz-Pino, 2009). The actual depth the core of the OMZ. The formation, maintenance and constants (e.g. the inverse of the Redfield ratio of phosphorous to of the central Arabian Sea is close to 4500 m, but we have simulated intensification of the OMZs are governed by the interaction of carbon) were not object of this investigation, thus the number of the water column up to a depth of 500 m only, using 100 m vertical physical processes (oxygen solubility driven by temperature and parameters included in the screening analysis was 207. These levels. The selection of this maximum depth was based on previous salinity, presence of regions of low ventilation and subsurface parameters were categorized and divided into k = 21 groups. The studies, indicating that the upper 500 meters include the upper currents of poorly oxygenated water) with biological processes increment of the input factors was set Δ=2/3, following the oxycline and the absolute minimum of oxygen (McCreary et al., (primary production, heterotrophic activities, bacterial respiration recommendation in Saltelli et al., 2008. and remineralization of organic matter). 2013), as confirmed here by test simulations extending till the depth of Groups 1–7 comprised of parameters characterizing primary 1500 meters. The model had significant skill in simulating the The objective of the present study is to identify the important production, whereas groups 8 to 12 were bacteria- related climatology of oxygen and nutrient observations at the study site. biogeochemical processes which need to be carefully described to parameters. The remaining groups included zooplankton understand, simulate and predict OMZ formation and evolution in parameters, food matrix parameters, deep- water remineralization The result of the screening analysis based on the Morris method the oceans. This was done by ranking the importance of showed that the 14th group (zooplankton loss parameters), 9th group closure parameters, sedimentation parameters and light extinction th biogeochemical parameters of a complex marine ecosystem model. parameters. The analysis was carried out with the range of (bacterial loss parameters) and 11 group (additional nutrient This model is the European Regional Seas Ecosystem Model variability of the uniform distribution of the parameters kept within remineralization parameters) were found to be the three most relevant (ERSEM) (Butenschön et al., 2016), which includes most of the −30% to + 30% of the reference value of the parameters. groups for the simulation of the OMZ, in order (Fig. 8). The biogeochemical processes driving OMZ dynamics. New for this Fig. 7 Schematic of the coupled GOTM-ERSEM parameters included in the groups 14 and 9 characterize the biological study is that we included denitrification in ERSEM, since this model configuration used in this study. The Monte Carlo sampling-based sensitivity analysis was processes of oxygen consumption by the zooplankton functional process is relevant in OMZ systems, but it was not represented in performed by selecting n = 1000 random values for each of the m groups and by bacterial functional group, respectively. The 38 model the pelagic component of the model (Butenschön et al., 2016). We independent input parameters found to be the most relevant in the parameters that emerged collectively as the most important in the ranked the importance of ERSEM parameters for OMZ simulation, The hydrodynamic model GOTM screening analysis. In choosing this number n of model simulations, screening analysis were the input factors to the Monte Carlo sampling- by using in sequence the Morris screening technique, followed by a we considered the rule of thumb of at least 20 realizations for each based sensitivity and ranking analysis. Monte Carlo sampling-based ranking. GOTM (General Ocean Turbulence Model; Burchard et al., 1999) is input factor desirable fori i multiple regression analysis. The multiple a 1-D water column model used for the computation of regressioncomputed at points sampled within the whole space of the In the present study, the analysis was performed using a one- hydrodynamic and thermodynamic processes related to vertical parameters. Therefore, this technique can be considered as a global dimensional (1-D) implementation of ERSEM for an oligotrophic mixing. The model calculates velocities, turbulence, temperature screening technique, though each single elementary effect is a first site in the open Arabian Sea (65°E, 13°N), advancing a comparable and salinity, as well as heat, momentum and freshwater fluxes order derivative, i.e. a local sensitivity (Campolongo et al., 2007). model configuration in this region by Blackford et al. (2004). The between the ocean and the atmosphere, when forced with local Importantly, the index μ* allows one to reduce the computational Arabian Sea is characterized by a vast OMZ with DO meteorological inputs. Routines for nudging observations also exist −1 cost of the screening analysis by computing the sensitivity of input concentrations below 0.05 ml L , at depths between 150 and 1250 in GOTM and they were applied here for the relaxation of the model parameters pooled in groups. The drawback of grouping input m, and it is one of the three major denitrification sites in world simulation towards salinity and water temperature profiles. factors is the loss of information regarding the relative importance oceans. of factors belonging to the same group. This was addressed by The screening Morris method performing a Monte Carlo-based sensitivity analysis of the The GOTM-ERSEM model was subjected initially to a screening parameters within the groups. The biogeochemical model ERSEM sensitivity analysis. This aimed to identify the subset of ERSEM The vertical dynamics of the water column were represented by parameters that are most important for the simulation of the coupling ERSEM with the 1-D hydrodynamic model GOTM (Fig. minimum oxygen concentration at the study site. The screening Monte Carlo simulations and ranking method 7) (Butenschön et al., 2016). ERSEM (Baretta et al., 1995; Fig. 8 Result of the screening analysis based on the Morris method sensitivity analysis used the Morris method, as proposed in Morris A Monte Carlo sampling-based sensitivity analysis was applied to Blackford et al., 2004; Butenschön et al., 2016) is a biomass and applied to 21 groups of model parameters. The three most important (1991), modified by Campolongo et al. (2007). The Morris rank the importance of the m parameters X = (X , X , ..., X ..., X ), i functional group- based biogeochemical model describing the 1 2 i m groups (i.e. the ones with the highest values of the sensitivity index technique, described thoroughly in Saltelli et al. (2008), is a = 1, 2, ..., m, within the groups identified as most important in the nutrient and carbon cycle within the low trophic levels of the marine μ*) were, in order: I) group 14 (zooplankton loss parameters); II) qualitative sensitive analysis based on the concept of Elementary Morris screening analysis (Saltelli et al., 2008). A crude Monte ecosystem. Model state variables include living organisms, group 9 (bacterial loss parameters); and III) group 11 (additional Effect (EE), which is an approximation of the first order partial Carlo sampling scheme was used to generate a number n of nutrient remineralization parameters). 14 15 ANNUAL REPORT 2017- 2018 ANNUAL REPORT 2017- 2018

The four most important parameters after the Monte-Carlo sampling Burchard, H., Bolding, K., Villarreal, M.R., 1999. GOTM-A Using remote sensing to study phytoplankton biomass and its influence on based analysis, with |β| higher than 0.3, were found to be: 1) the cubic General Ocean Turbulence Model, Theory, Implementation and half saturation constant for oxygenic control of denitrification; 2) the Test Cases. Technical Report EUR 18745 EN. European Commis- herbivore fishery in the South-Eastern Arabian Sea parameter regulating the fraction of ingested matter excreted (i.e. not sion. assimilated) by the heterotrophic nanoflagellates; 3) the bacterial Butenschön, M., Clark, J., Aldridge, J.N. et al., 2016. ERSEM 1 1 1 2 efficiency at low oxygen levels; and 4) the specific rate of bacterial Smitha A. , Syam S. , Nandini N. Menon and Lasse H. Pettersson 15.06: a generic model for marine biogeochemistry and the 1. Nansen Environmental Research Centre (India), Cochin release of capsular material. ecosystem dynamics of the lower trophic levels. Geosci. Model 2. Nansen Environmental and Remote Sensing Center, Bergen, The results indicated that model parameters regulating the Dev. 9 (4), 1293–1339. http://dx.doi.org/10.5194/gmd-9-1293- Norway metabolism of aerobic and anaerobic (denitrifying) bacteria and the 2016. loss terms of zooplankton (heterotrophic nanoflagellates) play a Campolongo, F., Cariboni, J., Saltelli, A., 2007. An effective prime role in our simulation of the OMZ at the study site. Assuming screening design for sensitivity analysis of large models. Environ. that the ranking of the model parameters reflects the relevance of the Model. Softw. 22 (10), 1509–1518. processes they characterize, we have inferred a conceptual model Wind driven coastal upwelling is a major feature during describing the most important biogeochemical processes affecting Draper, N.R., Smith, H., 1981. Applied Regression Analysis. John southwest monsoon in the coastal Arabian Sea. Upwelling that the OMZ in the oligotrophic site of the Arabian Sea area studied here. Wiley & Sons, New York, pp. 407. brings nutrient rich water to the surface supports the primary This outcome also highlights the relevance of our new McCreary, J.P., Yu, Z., Hood, R.R., Vinaychandran, P.N., Furue, R., productivity of South Eastern Arabian Sea (SEAS) and in turn representation of denitrification in ERSEM. Other processes, like Ishida, A., Richards, K.J., 2013. Dynamics of the Indian-ocean the coastal fisheries, especially that of the Kerala state in the primary production, were found to be less relevant. Presently, only oxygen minimum zones. Prog. Oceanogr. 112, 15–37. southwest tip of India. The coastal upwelling processes along few marine ecosystem models include an explicit description of the the west coast of Kerala and its impact on regional pelagic Morris, M.D., 1991. Factorial sampling plans for preliminary fisheries was first addressed by Johannessen et al. (1987). microbial loop, but our study strongly indicates that OMZ models computational experiments. Technometrics 33, 161–174. should explicitly include heterotrophic bacteria and their production Satellite remote sensing and model data have been used to of recalcitrant carbon. Despite the clear limits of our 1-D model Paulmier, A., Ruiz-Pino, D., 2009. Oxygen minimum zones analyse the dominant physical forcings in the coastal SEAS configuration, our application provided an objective list of the most (OMZs) in the modern ocean.Prog. Oceanogr. (80), 113–128. (72-78°E, 7-13°N) and its influence on phytoplankton biomass important biogeochemical parameters that need to be quantified for Saltelli, A., Ratto, M., Andres, T., Campolongo, M., Cariboni, J., for a period of future applications of a global configuration of ERSEM Gatelli, D., Saisana, M., Tarntola, S., 2008. Global sensitivity 14 years from 1998 to 2011. The influence of varying oceano- (Kwiatkowski et al., 2014) aiming to simulate the biogeochemical analysis. The Primer. John Wiley & Sons Ltd, Chichester, UK. graphic forcing on the fishery of Indian oil sardine (Sardinella and physical dynamic underpinning OMZs and their predicted Kwiatkowski, L., Yool, A., Allen, J.I., et al., 2014. iMarNet: an longiceps) - a major pelagic herbivore, is also analysed in this expansions. ocean biogeochemistry model intercomparison project within a study. common physical ocean modelling framework. Biogeosciences 11, 7291–7304. http://dx.doi.org/10.5194/bg-11-7291-2014. Physical forcing in the SEAS Cited References From the analysis of seasonal winds computed from European Published results: Baretta, J.W., Ebenhoh, W., Ruardij, P., 1995. The European Centre for Medium-Range Weather Forecasts (ECMWF) regional Seas Ecosystem Model, a complex marine Ecosystem (This article is an extract from the paper “Sankar, S., Polimene, L., monthly reanalysis wind and SST from Advanced Very High Model. Neth. J. Sea Res. 33, 233–246. Marin, L., Menon, N.N., Samuelsen, A., Pastres, R. and Ciavatta, Resolution Radiometer (AVHRR) monthly data, the well- S., 2018. Sensitivity of the simulated Oxygen Minimum Zone to developed warm pool (SSTs > 29°C) in the SEAS during pre- Blackford, J.C., Allen, J.I., Gilbert, F.J., 2004. Ecosystem dynamics biogeochemical processes at an oligotrophic site in the Arabian monsoon season is clearly observed. With the onset of at six contrasting sites: a generic modelling study. J. Marine Syst. 52 Sea. Ecological Modelling, 372, pp.12-23.”) southwest monsoon in June, this warm pool breaks down quite (1), 191–215. -1 rapidly under the influence of strong surface winds (~ 6 -7 ms ). The shift in the prevailing wind direction results in the development of an upwelling zone off the southwest coast of India along with the SST decreasing to about 27.5°C. During northeast monsoon, the magnitude of north westerlies that dominate the southern parts of the SEAS is less than half of that during southwest monsoon. The temporal variability in the shoaling of thermocline and the evolution of upwelling phenomenon has been monitored using monthly values of the depth of 20°C isotherm (D20) (Ishii et al., 2006). Strong alongshore winds during the southwest monsoon cause intense upwelling in the SEAS. As a result, D20 shoals to about 80 m depth from the winter time depth of ~ 140 m (Fig. 9). The withdrawal of monsoon in October accompanied by weak and variable surface winds with little wind induced mixing cause the 20°C isotherms to deepen to its maximum depth in winter. The large seasonal variability of D20 in the SEAS can Fig. 9 Depth of the 20°C isotherm (D20) in SEAS (72-78°E; be attributed to coastal dynamics associated with boundary 7- 13°N) depicting the shoaling of thermocline during currents, upwelling and propagating Kelvin and Rossby waves. southwest monsoon season (JJAS).

16 17 ANNUAL REPORT 2017- 2018 ANNUAL REPORT 2017- 2018

Variability in sea level in response to coastal upwelling induced Surface chlorophyll-a concentration in the Seasonal fish landing in the Kerala coast by alongshore winds has been analysed using monthly climatol- SEAS ogy of Sea Level Anomaly (SLA) Oil sardine is a pelagic herbivore whose presence and accordingly Seasonal variability in the spatial distribution of fishery is directly related to the phytoplankton abundance and computed from merged data by Archiving, Validation and phytoplankton biomass (Fig. 11) is studied using merged concentration in the coastal waters. Fishery of S. longiceps is Interpretation of Satellite Oceanographic Data (AVISO). During important as the fish is restricted to a narrow coastal belt of about Jan-Feb, the well-developed Lakshadweep High (LH) is present chlorophyll-a (chl-a) data from Ocean Colour-Climate Change Initiative (OC-CCI) by the European Space 15km offshore (Mohanty et al. 2005) and is important for artisanal in the SEAS, reflecting positive SLA as well as anti-cyclonic and coastal fisheries. The link between chl-a variability to that of S. surface current pattern. With the onset of monsoon in June, SLA Agency (ESA).Chl-a concentration near the coast is lowest longiceps gradually becomes negative and the anticyclonic currents are during the northeast monsoon (~0.2-0.5 mg m-3 ). It reaches replaced by cyclonic currents. The Lakshadweep Low (LL) -3 landings is analysed using monthly oil sardine landing data from as high as 8 mg m along the coast during southwest Central Marine Fisheries Research Institute (CMFRI) for the develops in June, reaches maximum intensity in Jul-Aug and -3 monsoon, and extends offshore ranging from 2 to 5 mg m . Kerala coast. The linear correlation coefficient between seasonal weakens by September. Signatures of strong upwelling off the During pre- monsoon season, high chlorophyll is observed west coast are manifested as regions of negative SLA during chl-a anomaly and seasonal oil sardine landing anomaly with a southwest monsoon. During the post-monsoon season, LL in the southern parts of the SEAS. time lag of one season for the sardine is 0.56 (Fig. 12) statistically propagates westward as a Rossby wave and the currents start to significant at the 99% confidence level. The lag is because in the reverse direction again. By Nov-Dec, the SEAS again develop case of S. longiceps, which has a zero year fishery in India, into a region of positive SLA with northward boundary currents. It spawning usually occurs during May-Sept. Larval development is rapid during the first few months and the earliest spawned and has been observed that upwelling signals first appear at southern Fig. 13 Mean chl-a concentration (black dotted line) during latitudes and proceed towards north along the coast. survived individuals are recruited to the fishery in the post- monsoon months. This in turn determines the yearly landings. The southwest monsoon and the annual sardine landings (red line) of period of high chl-a matches with the active breeding period of Kerala during 1998-2011 sardine i.e., southwest monsoon, in most of the years studied. The high positive correlation between chl-a concentration and sardine Accordingly, chl-a concentration is high during southwest monsoon landings indicates that in most of the years studied, increased food compared to non-monsoon months when the waters are typically availability for the larvae during the southwest monsoon season oligotrophic with chl-a concentrations resulted in high landings of sardine in that particular year -3 ≤ 0.5 mg m . However, maximum offshore extent of chl-a concentration is observed during deficient monsoon years. Variation of mean chl-a concentration during the southwest Variability in chl-a concentration during the southwest monsoon monsoon in the SEAS against annual sardine landings of Kerala season is reflected strongly on the catch of oil sardines with a lag of (Fig. 13) shows that chl-a is not the sole factor controlling the one season. This proves that the availability of food during the sardine fishery in Kerala. Naturally there will be a difference developmental stages of sardines has a decisive role in the success of between the fish landings/catch and their actual abundance due to fishery. environmental conditions. Using chl-a as an index, this study analysed only the direct trophic link to sardine. Southwest monsoon is the season when major variations are brought about in the physical forcings like wind, temperature, upwelling and SLA, which in turn influence the phytoplankton biomass. The shoaling of D20 and negative SLA maximum occur Cited References during southwest monsoon indicating upwelling. Strong offshore Ishii M, Kimoto M, Sakamoto K, Iwasaki SI (2006) mass transport occurs during the southwest monsoon season, Steric sea level changes estimated from historical mainly up to 10°N. ocean subsurface temperature and salinity analyses. Journal of Oceanography, 62(2):155-170. Johannessen OM, Subbaraju G, Blindheim J (1987) Seasonal variations of the oceanographic conditions Fig. 11 Seasonal Chl-a concentration (mg m-3 ) in the SEAS for a) off the southwest coast of India during 1971 – 1975 northeast monsoon (DJF), b) pre-monsoon (MAM), c) southwest Fisk DirSkrHavUnders. 18:247 – 261. monsoon (JJAS), and d) post-monsoon season (ON). Fig. 10 Hovmoller plots of monthly mean Ekman mass transport (kg Mohanty PK, Khora SS, Panda US, Mohapatra GN, m-1 s -1 ) in the SEAS between 7° to 13°N averaged over 72- 78°E Mishra P (2005) An overview of Sardines and Even though upwelling in the region started well before the onset of Anchovies fishery along the Indian coasts. Department southwest monsoon, increased chl-a is observed only after the of Marine Sciences, Berhampur University, Smitha et al. (2014) found that the prominent region of upwelling southwest monsoon has set in. Chl-a concentration increases to Berhampur, Orissa, India. -3 -3 along the southwest coast of India lies between 8°N and 14°N. about 1 mg m during June, with the high (~8 mg m ) occurring in Smitha A, Ajith Joseph K, Chiranjivi Jayaram, Ekman mass transport is computed from monthly ECMWF Jul-Aug. High chl-a sometimes sustain also in October. During other Balchand AN (2014) Upwelling in the southeastern reanalysis winds to describe and understand the coastal upwelling. seasons, chl-a concentration is low (~ 0.5 mg m-3 ). The offshore -3 Arabian Sea as evidenced by Ekman mass transport Ekman mass transport is generally negative in the SEAS indicating extent of high chlorophyll (>3 mg m ) during the southwest using wind observations from OCEANSAT–II offshore water movement, with the high negative values responsible monsoon season shows inter-annual variability. Offshore extent was Scatterometer. Indian Journal of Geo-Marine for coastal upwelling. Strong offshore transport occur during the maximum during 2002 (upto 73°E) which was a deficient monsoon Sciences, 43(1):111-116. southwest monsoon mostly upto 10°N. Ekman mass transport was year, followed by 1998, 2004, 2009 and 2010. These years except strong during the southwest monsoon seasons of 1998, 2000-2002 2009 experienced high offshore mass transport in the SEAS. During Published results. and 2004 (-1400 to -1500 kg m-1 s -1 ) 2007, which was an excess monsoon year, the offshore extent was (From Smitha A., Syam S., Menon N.N., Pettersson and was about -2000 kg m-1 s -1 in 2010 indicating strong upwelling less and chl-a was significantly low compared to other years. From L.H., Using Remote Sensing to Study Phytoplankton along the coastal regions of SEAS. Ekman transport is positive with 2005 to 2008, there was a decrease in chl-a and its offshore extent Fig. 12 Standardized anomalies of seasonal chl-a concentration Biomass and its Influence on Herbivore Fishery in the varying intensity during most pre- monsoon seasons and during pre- during the southwest monsoon irrespective of the intensity of (black dotted line) and oil sardine landing (red line) for the SEAS South-Eastern Arabian Sea. In: Barale V., Gade M. monsoon periods of 1998-1999 and 2008-2009 it is high extending monsoon. This coincides with a decrease in the wind and offshore with a time lag of one season for the sardine for the period 1998- (eds) Remote Sensing of the Asian Seas. Springer, from 7° to 13°N in SEAS indicating coastal downwelling (Fig. 10). transport reducing the upwelling in the SEAS. 2011 Cham, accepted in 2017). 18 19 ANNUAL REPORT 2017- 2018 ANNUAL REPORT 2017- 2018

Variability in sea level in response to coastal upwelling induced Surface chlorophyll-a concentration in the Seasonal fish landing in the Kerala coast by alongshore winds has been analysed using monthly climatol- SEAS ogy of Sea Level Anomaly (SLA) Oil sardine is a pelagic herbivore whose presence and accordingly Seasonal variability in the spatial distribution of fishery is directly related to the phytoplankton abundance and computed from merged data by Archiving, Validation and phytoplankton biomass (Fig. 11) is studied using merged concentration in the coastal waters. Fishery of S. longiceps is Interpretation of Satellite Oceanographic Data (AVISO). During important as the fish is restricted to a narrow coastal belt of about Jan-Feb, the well-developed Lakshadweep High (LH) is present chlorophyll-a (chl-a) data from Ocean Colour-Climate Change Initiative (OC-CCI) by the European Space 15km offshore (Mohanty et al. 2005) and is important for artisanal in the SEAS, reflecting positive SLA as well as anti-cyclonic and coastal fisheries. The link between chl-a variability to that of S. surface current pattern. With the onset of monsoon in June, SLA Agency (ESA).Chl-a concentration near the coast is lowest longiceps gradually becomes negative and the anticyclonic currents are during the northeast monsoon (~0.2-0.5 mg m-3 ). It reaches replaced by cyclonic currents. The Lakshadweep Low (LL) -3 landings is analysed using monthly oil sardine landing data from as high as 8 mg m along the coast during southwest Central Marine Fisheries Research Institute (CMFRI) for the develops in June, reaches maximum intensity in Jul-Aug and -3 monsoon, and extends offshore ranging from 2 to 5 mg m . Kerala coast. The linear correlation coefficient between seasonal weakens by September. Signatures of strong upwelling off the During pre- monsoon season, high chlorophyll is observed west coast are manifested as regions of negative SLA during chl-a anomaly and seasonal oil sardine landing anomaly with a southwest monsoon. During the post-monsoon season, LL in the southern parts of the SEAS. time lag of one season for the sardine is 0.56 (Fig. 12) statistically propagates westward as a Rossby wave and the currents start to significant at the 99% confidence level. The lag is because in the reverse direction again. By Nov-Dec, the SEAS again develop case of S. longiceps, which has a zero year fishery in India, into a region of positive SLAwith northward boundary currents. It spawning usually occurs during May-Sept. Larval development is rapid during the first few months and the earliest spawned and has been observed that upwelling signals first appear at southern Fig. 13 Mean chl-a concentration (black dotted line) during latitudes and proceed towards north along the coast. survived individuals are recruited to the fishery in the post- monsoon months. This in turn determines the yearly landings. The southwest monsoon and the annual sardine landings (red line) of period of high chl-a matches with the active breeding period of Kerala during 1998-2011 sardine i.e., southwest monsoon, in most of the years studied. The high positive correlation between chl-a concentration and sardine Accordingly, chl-a concentration is high during southwest monsoon landings indicates that in most of the years studied, increased food compared to non-monsoon months when the waters are typically availability for the larvae during the southwest monsoon season oligotrophic with chl-a concentrations resulted in high landings of sardine in that particular year -3 ≤ 0.5 mg m . However, maximum offshore extent of chl-a concentration is observed during deficient monsoon years. Variation of mean chl-a concentration during the southwest Variability in chl-a concentration during the southwest monsoon monsoon in the SEAS against annual sardine landings of Kerala season is reflected strongly on the catch of oil sardines with a lag of (Fig. 13) shows that chl-a is not the sole factor controlling the one season. This proves that the availability of food during the sardine fishery in Kerala. Naturally there will be a difference developmental stages of sardines has a decisive role in the success of between the fish landings/catch and their actual abundance due to fishery. environmental conditions. Using chl-a as an index, this study analysed only the direct trophic link to sardine. Southwest monsoon is the season when major variations are brought about in the physical forcings like wind, temperature, upwelling and SLA, which in turn influence the phytoplankton biomass. The shoaling of D20 and negative SLA maximum occur Cited References during southwest monsoon indicating upwelling. Strong offshore Ishii M, Kimoto M, Sakamoto K, Iwasaki SI (2006) mass transport occurs during the southwest monsoon season, Steric sea level changes estimated from historical mainly up to 10°N. ocean subsurface temperature and salinity analyses. Journal of Oceanography, 62(2):155-170. Johannessen OM, Subbaraju G, Blindheim J (1987) Seasonal variations of the oceanographic conditions Fig. 11 Seasonal Chl-a concentration (mg m-3 ) in the SEAS for a) off the southwest coast of India during 1971 – 1975 northeast monsoon (DJF), b) pre-monsoon (MAM), c) southwest Fisk DirSkrHavUnders. 18:247 – 261. monsoon (JJAS), and d) post-monsoon season (ON). Fig. 10 Hovmoller plots of monthly mean Ekman mass transport (kg Mohanty PK, Khora SS, Panda US, Mohapatra GN, m-1 s -1 ) in the SEAS between 7° to 13°N averaged over 72- 78°E Mishra P (2005) An overview of Sardines and Even though upwelling in the region started well before the onset of Anchovies fishery along the Indian coasts. Department southwest monsoon, increased chl-a is observed only after the of Marine Sciences, Berhampur University, Smitha et al. (2014) found that the prominent region of upwelling southwest monsoon has set in. Chl-a concentration increases to Berhampur, Orissa, India. -3 -3 along the southwest coast of India lies between 8°N and 14°N. about 1 mg m during June, with the high (~8 mg m ) occurring in Smitha A, Ajith Joseph K, Chiranjivi Jayaram, Ekman mass transport is computed from monthly ECMWF Jul-Aug. High chl-a sometimes sustain also in October. During other Balchand AN (2014) Upwelling in the southeastern reanalysis winds to describe and understand the coastal upwelling. seasons, chl-a concentration is low (~ 0.5 mg m-3 ). The offshore -3 Arabian Sea as evidenced by Ekman mass transport Ekman mass transport is generally negative in the SEAS indicating extent of high chlorophyll (>3 mg m ) during the southwest using wind observations from OCEANSAT–II offshore water movement, with the high negative values responsible monsoon season shows inter-annual variability. Offshore extent was Scatterometer. Indian Journal of Geo-Marine for coastal upwelling. Strong offshore transport occur during the maximum during 2002 (upto 73°E) which was a deficient monsoon Sciences, 43(1):111-116. southwest monsoon mostly upto 10°N. Ekman mass transport was year, followed by 1998, 2004, 2009 and 2010. These years except strong during the southwest monsoon seasons of 1998, 2000-2002 2009 experienced high offshore mass transport in the SEAS. During Published results. and 2004 (-1400 to -1500 kg m-1 s -1 ) 2007, which was an excess monsoon year, the offshore extent was (From Smitha A., Syam S., Menon N.N., Pettersson and was about -2000 kg m-1 s -1 in 2010 indicating strong upwelling less and chl-a was significantly low compared to other years. From L.H., Using Remote Sensing to Study Phytoplankton along the coastal regions of SEAS. Ekman transport is positive with 2005 to 2008, there was a decrease in chl-a and its offshore extent Fig. 12 Standardized anomalies of seasonal chl-a concentration Biomass and its Influence on Herbivore Fishery in the varying intensity during most pre- monsoon seasons and during pre- during the southwest monsoon irrespective of the intensity of (black dotted line) and oil sardine landing (red line) for the SEAS South-Eastern Arabian Sea. In: Barale V., Gade M. monsoon periods of 1998-1999 and 2008-2009 it is high extending monsoon. This coincides with a decrease in the wind and offshore with a time lag of one season for the sardine for the period 1998- (eds) Remote Sensing of the Asian Seas. Springer, from 7° to 13°N in SEAS indicating coastal downwelling (Fig. 10). transport reducing the upwelling in the SEAS. 2011 Cham, accepted in 2017). 18 19 ANNUAL REPORT 2017- 2018 ANNUAL REPORT 2017- 2018

Publications in 2017 Defended Doctoral Thesis Nandini Menon N and Ravi Kumar Avadhanula. 2018. A multi- Muhammad Shafeeque, Trevor Platt, Phiros Shah, Shubha method approach for marine phytoplanktonic community structure Sathyendranath, Grinson George, Ajith Joseph K and Balchand A. Smitha, A.,2017. Wind induced upwelling and the response of N., 2018. Prevalence of mesoscale eddies and chlorophyll Referred Journals surface chlorophyll in the Bay of Bengal. PhD Thesis, Cochin determination with special emphasis on High Performance Liquid Chromatography (HPLC) and Scanning Electron Microscopy variability in the southeastern Arabian Sea. Societal applications in Abish B, Annalisa Cherchi and Satyaban B. Ratna. 2017. ENSO and University of Science and Technology, pp. 197. (SEM). Societal applications in Fisheries and Aquaculture using Fisheries and Aquaculture using Remote Sensing Imagery, The the recent warming of the Indian Ocean. Intl.Jl.of Climatology. DOI: Anoop VM Kumar., 2017. Study on shoreline changes in the Remote Sensing Imagery, The Second International Symposium on Second International Symposium on Remote Sensing for 10.1002/joc.5170. Eraviputhenthurai beach, Kanyakumari coast, Tamilnadu., M.Tech Remote Sensing for Ecosystem Analysis and Fisheries, Book of Ecosystem Analysis and Fisheries, Book of Abstracts and Lead George, M.S., Joseph, P.V., Ajith Joseph, K. Laurent Bertino and thesis in Ocean and Coastal safety Engineering, Kerala University of Abstracts and Lead Articles.p.72. Article. p.88. O. M. Johannessen. 2017. The Cold Pool of the Bay of Bengal and Fisheries and Ocean studies. PP.88. Arun K , MG Manoj, Santosh KR, K Mohankumar , Abish B and its association with the break phase of the Indian summer monsoon. Suresh N. (2018). Statistical Analysis of Convective Indices Shaju. S. S, AnilkumarVijayan, Muhamed Ashraf P and Nandini Atmospheric and Oceanic Science Letters., http://dx.doi.org/10. Technical report Derived from Radiosonde and a Wind Profiling Radar. 2nd Menon N. 2018. Variability of in-situ and satellite derived 1080/16742834.2017.1294017. Bindu, G. and Ajith Joseph K., 2017. Estimating carbon sequestra- Conference on India Radar Meteorology, NARL(ISRO),Gadanki. reflectance of Trichodesmium during bloom and non- bloom Jishnu E S, Ajith Joseph K, Sreenal Sreedhar and George Basil. tion potential of Mangroves in Kunhimangalam area using Remote Menon, N.R., 2018. Biodiversity- A depletable product of organic regions in south eastern Arabian Sea. Societal applications in 2017. Hazard Mapping of Landslide Vulnerable Zones in a Rainfed Sensing and GIS system supported by field observations. NERCI evolution!. Societal applications in Fisheries and Aquaculture Fisheries and Aquaculture using Remote Sensing Imagery, The Region of Southern Peninsular India- A Geospatial Perspective. Technical report. 43pp. using Remote Sensing Imagery, The Second International Second International Symposium on Remote Sensing for International Research Journal of Engineering and Technology. Symposium on Remote Sensing for Ecosystem Analysis and Ecosystem Analysis and Fisheries, Book of Abstracts and Lead Volume: 04 Issue: 07 | July - 1350-1357. Fisheries. Book of Abstracts and Lead Articles.p.32-33. Article, p.94. Nashad, M., Nandini Menon, N., Ajith Joseph K, Lasse. H. Nandini Menon N, Trevor Platt, Shubha Sathyendranath, Grinson Smitha A, Syam Sankar and Nandini Menon N., 2018. Impact of Pettersson and N. R. Menon. (2017). First report of Leptocylindrus George and Sophie Seeyave., 2018. NF-POGO Alumni Network tropical Indian Ocean warming on phytoplankton biomass sp. bloom in the coastal waters of South Eastern Arabian Sea and Publications in 2018 For Oceans (NANO) - activities in a nutshell. Societal applications concentration in the south eastern Arabian Sea using satellite coagulation of cells. Marine Biology Association of India – JMBAI Chiranjivi Jayaram , Niraj Priyadarshia, Jonnakuti Pavan Kumar, in Fisheries and Aquaculture using Remote Sensing Imagery, The observations. Societal applications in Fisheries and Aquaculture JMBAI vol 51, issue 1, 1-6. doi: 10.6024/jmbai.2017.59.1.1937-00. Tata Venkata Sai Udayabhaskar , Devendar Raju , Ajith Joseph Second International Symposium on Remote Sensing for Ecosys- using Remote Sensing Imagery, The Second International Racault, M. F., Raitsos, D., Shubha Satyendranath, Nandini Menon Kochuparambil. 2018. Analysis of gap free chlorophyll data from tem Analysis and Fisheries, Book of Abstracts and Lead Articles Symposium on Remote Sensing for Ecosystem Analysis and & T. Platt 2017. Phenological responses to ENSO in the global MODIS in Arabian Sea, reconstructed using DINEOF. p.99. Fisheries, Book of Abstracts and Lead Article,p.91. oceans. Surveys in Geophysics. January 2017, Volume Intl.Journal of Remote Sensing. Ranju R., Nandini Menon N., and Menon N. R. 2018. Ecological Syam Sankar, Nandini Menon, Smitha A, Annette Samuelsen, 38, Issue 1, pp 277–293. DOI: 10.1080/01431161.2018.1471540. observations on some symbiont bearing foraminifera from the shelf Lasse H.Pettersson., 2018. Does the Indian Ocean Dipole (IOD) regulate the annual oil sardine (Sardinella longiceps) landings in Saleem Shalin, Annette Samuelsen , Anton Korosov , Nandini Saleem Shalin, Annette Samuelsen , Anton Korosov , Nandini sediments of eastern Arabian Sea. Societal applications in Fisheries kerala? Societal applications in Fisheries and Aquaculture using Menon , Björn C. Backeberg and Lasse H. Pettersson. 2017. Menon N, Björn C. Backeberg and Lasse H. Pettersson. 2018. and Aquaculture using Remote Remote Sensing Imagery, The Second International Symposium Delineation of marine ecosystem zones in the northern Arabian Sea Delineation of marine ecosystem zones in the northern Arabian Sea Sensing Imagery, The Second International Symposium on Remote on Remote Sensing for Ecosystem Analysis and Fisheries, Book of using an objective method. Journal of Biogeosciences Discuss., EGU., using an objective method. Biogeosciences, 15, 1395 - 1414. Sensing for Ecosystem Analysis and Fisheries, Book of Abstracts Abstracts and Lead Article.p.154. https://doi.org/10.5194/bg-2017-285. https://doi.org/10.5194/bg-15-1395-2018. and Lead Articles.p.64.. Vishnu P. S, Tiwari S. P, Shaju S. S, Mohamed Hatha, Nandini Sankar, S., Polimene, L., Marin, L., Menon, N.N., Samuelsen, A., Shalin S, ShubhaSathyendranath, Eldho Varghese, Grinson Menon, AjithJoseph N. C, Mini Raman and Mohandas A., 2018. Pastres, R. and Ciavatta, S., 2018. Sensitivity of the simulated George,Trevor Platt, Nandini Menon N, Samuelsen A and Anton Evaluation of empirical and semi analytical down welling diffuse Oxygen Minimum Zone to biogeochemical processes at an Conference Proceeding papers in 2017 Korosov., 2018. Assessment of chlorophyll-a vertical profiles in the attenuation coefficient models along the coastal waters off Cochin. oligotrophic site in the Arabian Sea. Ecological Modeling, tropical Indian Ocean over six decades. Societal applications in Ajith Joseph K., Syam Sankar and Abish, B., 2017. Changes in Societal applications in Fisheries and Aquaculture using Remote 372,pp.12-23. Fisheries and Aquaculture using Remote Sensing Imagery, The Ocean circulation due to Climate change and possible impacts on the Sensing Imagery, The Second International Symposium on Second International Symposium on Remote Sensing for Ecosys- global and regional climate system with particular focus on the Vishnu P.S., S.S. Shaju, S.P. Tiwari, Nandini Menon, M. Nashad, Remote Sensing for Ecosystem Analysis and Fisheries, Book of tem Analysis and Fisheries, Book of Abstracts Indian Ocean region- A review. Our Seas: Theories, Data and C. Ajith Joseph, Mini Raman, Mohamed Hatha, M.P. Prabhakaran, Abstracts and Lead Article,p.90. Policies Symposium” November 18-21, 2017- KFAS,Kuwait. A. Mohandas. 2018. Seasonal variability in bio- optical properties Ajith Joseph K, Lasse H.Pettersson and N.R.Menon,2017. Harmful along the coastal waters off Cochin. Int J Appl Earth Obs algae bloom monitoring using satellite observations. Course manual on Geoinformation 66, 184–195. Winter School on Structure and Functions of Marine Ecosystem: Wilson, S.S., Joseph, P.V., Mohanakumar, K. and Johannessen, Fisheries CMFRI Lecture Note Series No. 12/2017 ICAR-Central O.M., 2018. Interannual and long term variability of low level Marine Fisheries Research Institute,1-21 December 2017, 36,300-315. jetstream of the Asian summer monsoon. Tellus A: Dynamic Bindu.G, Prabha R Nair & Ajo Abraham Kurian, 2017. ' The impact Meteorology and Oceanography, 70(1), p.1445380. of PM10 on Acute Respiratory Illness in children: Results from a case study over an urban area', Air pollution, Climate and Health in Southern Asia and the HKH:Workshop & Science‐Policy Dialogue, Conference Proceeding papers in 2018 ICIMOD, Nepal, November 2017. Grinson G., Minu, P., Nandini Menon, N. And Gopalakrishnan, A., 2018. SAFARI- A retrospection and future plans. Societal applica- Bindu.G, Poornima Rajan, Jishnu.E.S Ajith Joseph K, 2017. tions in Fisheries and Aquaculture using Remote Sensing Imagery, Estimating carbon sequestration potential of mangroves in The Second International Symposium on Remote Sensing for kunhimangalam area using remote sensing and geographic Ecosystem Analysis and Fisheries. Book of Abstracts and Lead information system supported by field observations National Articles, p. 27-28. Conclave on Mangrove Conservation, December 2017. Amir Kumar Samal, Grinson George, Jayasankar J, Nazar A. K. A,

20 21 ANNUAL REPORT 2017- 2018 ANNUAL REPORT 2017- 2018

Publications in 2017 Defended Doctoral Thesis Nandini Menon N and Ravi Kumar Avadhanula. 2018. A multi- Muhammad Shafeeque, Trevor Platt, Phiros Shah, Shubha method approach for marine phytoplanktonic community structure Sathyendranath, Grinson George, Ajith Joseph K and Balchand A. Smitha, A.,2017. Wind induced upwelling and the response of N., 2018. Prevalence of mesoscale eddies and chlorophyll Referred Journals surface chlorophyll in the Bay of Bengal. PhD Thesis, Cochin determination with special emphasis on High Performance Liquid Chromatography (HPLC) and Scanning Electron Microscopy variability in the southeastern Arabian Sea. Societal applications in Abish B, Annalisa Cherchi and Satyaban B. Ratna. 2017. ENSO and University of Science and Technology, pp. 197. (SEM). Societal applications in Fisheries and Aquaculture using Fisheries and Aquaculture using Remote Sensing Imagery, The the recent warming of the Indian Ocean. Intl.Jl.of Climatology. DOI: Anoop VM Kumar., 2017. Study on shoreline changes in the Remote Sensing Imagery, The Second International Symposium on Second International Symposium on Remote Sensing for 10.1002/joc.5170. Eraviputhenthurai beach, Kanyakumari coast, Tamilnadu., M.Tech Remote Sensing for Ecosystem Analysis and Fisheries, Book of Ecosystem Analysis and Fisheries, Book of Abstracts and Lead George, M.S., Joseph, P.V., Ajith Joseph, K. Laurent Bertino and thesis in Ocean and Coastal safety Engineering, Kerala University of Abstracts and Lead Articles.p.72. Article. p.88. O. M. Johannessen. 2017. The Cold Pool of the Bay of Bengal and Fisheries and Ocean studies. PP.88. Arun K , MG Manoj, Santosh KR, K Mohankumar , Abish B and its association with the break phase of the Indian summer monsoon. Suresh N. (2018). Statistical Analysis of Convective Indices Shaju. S. S, AnilkumarVijayan, Muhamed Ashraf P and Nandini Atmospheric and Oceanic Science Letters., http://dx.doi.org/10. Technical report Derived from Radiosonde and a Wind Profiling Radar. 2nd Menon N. 2018. Variability of in-situ and satellite derived 1080/16742834.2017.1294017. Bindu, G. and Ajith Joseph K., 2017. Estimating carbon sequestra- Conference on India Radar Meteorology, NARL(ISRO),Gadanki. reflectance of Trichodesmium during bloom and non- bloom Jishnu E S, Ajith Joseph K, Sreenal Sreedhar and George Basil. tion potential of Mangroves in Kunhimangalam area using Remote Menon, N.R., 2018. Biodiversity- A depletable product of organic regions in south eastern Arabian Sea. Societal applications in 2017. Hazard Mapping of Landslide Vulnerable Zones in a Rainfed Sensing and GIS system supported by field observations. NERCI evolution!. Societal applications in Fisheries and Aquaculture Fisheries and Aquaculture using Remote Sensing Imagery, The Region of Southern Peninsular India- A Geospatial Perspective. Technical report. 43pp. using Remote Sensing Imagery, The Second International Second International Symposium on Remote Sensing for International Research Journal of Engineering and Technology. Symposium on Remote Sensing for Ecosystem Analysis and Ecosystem Analysis and Fisheries, Book of Abstracts and Lead Volume: 04 Issue: 07 | July - 1350-1357. Fisheries. Book of Abstracts and Lead Articles.p.32-33. Article, p.94. Nashad, M., Nandini Menon, N., Ajith Joseph K, Lasse. H. Nandini Menon N, Trevor Platt, Shubha Sathyendranath, Grinson Smitha A, Syam Sankar and Nandini Menon N., 2018. Impact of Pettersson and N. R. Menon. (2017). First report of Leptocylindrus George and Sophie Seeyave., 2018. NF-POGO Alumni Network tropical Indian Ocean warming on phytoplankton biomass sp. bloom in the coastal waters of South Eastern Arabian Sea and Publications in 2018 For Oceans (NANO) - activities in a nutshell. Societal applications concentration in the south eastern Arabian Sea using satellite coagulation of cells. Marine Biology Association of India – JMBAI Chiranjivi Jayaram , Niraj Priyadarshia, Jonnakuti Pavan Kumar, in Fisheries and Aquaculture using Remote Sensing Imagery, The observations. Societal applications in Fisheries and Aquaculture JMBAI vol 51, issue 1, 1-6. doi: 10.6024/jmbai.2017.59.1.1937-00. Tata Venkata Sai Udayabhaskar , Devendar Raju , Ajith Joseph Second International Symposium on Remote Sensing for Ecosys- using Remote Sensing Imagery, The Second International Racault, M. F., Raitsos, D., Shubha Satyendranath, Nandini Menon Kochuparambil. 2018. Analysis of gap free chlorophyll data from tem Analysis and Fisheries, Book of Abstracts and Lead Articles Symposium on Remote Sensing for Ecosystem Analysis and & T. Platt 2017. Phenological responses to ENSO in the global MODIS in Arabian Sea, reconstructed using DINEOF. p.99. Fisheries, Book of Abstracts and Lead Article,p.91. oceans. Surveys in Geophysics. January 2017, Volume Intl.Journal of Remote Sensing. Ranju R., Nandini Menon N., and Menon N. R. 2018. Ecological Syam Sankar, Nandini Menon, Smitha A, Annette Samuelsen, 38, Issue 1, pp 277–293. DOI: 10.1080/01431161.2018.1471540. observations on some symbiont bearing foraminifera from the shelf Lasse H.Pettersson., 2018. Does the Indian Ocean Dipole (IOD) regulate the annual oil sardine (Sardinella longiceps) landings in Saleem Shalin, Annette Samuelsen , Anton Korosov , Nandini Saleem Shalin, Annette Samuelsen , Anton Korosov , Nandini sediments of eastern Arabian Sea. Societal applications in Fisheries kerala? Societal applications in Fisheries and Aquaculture using Menon , Björn C. Backeberg and Lasse H. Pettersson. 2017. Menon N, Björn C. Backeberg and Lasse H. Pettersson. 2018. and Aquaculture using Remote Remote Sensing Imagery, The Second International Symposium Delineation of marine ecosystem zones in the northern Arabian Sea Delineation of marine ecosystem zones in the northern Arabian Sea Sensing Imagery, The Second International Symposium on Remote on Remote Sensing for Ecosystem Analysis and Fisheries, Book of using an objective method. Journal of Biogeosciences Discuss., EGU., using an objective method. Biogeosciences, 15, 1395 - 1414. Sensing for Ecosystem Analysis and Fisheries, Book of Abstracts Abstracts and Lead Article.p.154. https://doi.org/10.5194/bg-2017-285. https://doi.org/10.5194/bg-15-1395-2018. and Lead Articles.p.64.. Vishnu P. S, Tiwari S. P, Shaju S. S, Mohamed Hatha, Nandini Sankar, S., Polimene, L., Marin, L., Menon, N.N., Samuelsen, A., Shalin S, ShubhaSathyendranath, Eldho Varghese, Grinson Menon, AjithJoseph N. C, Mini Raman and Mohandas A., 2018. Pastres, R. and Ciavatta, S., 2018. Sensitivity of the simulated George,Trevor Platt, Nandini Menon N, Samuelsen A and Anton Evaluation of empirical and semi analytical down welling diffuse Oxygen Minimum Zone to biogeochemical processes at an Conference Proceeding papers in 2017 Korosov., 2018. Assessment of chlorophyll-a vertical profiles in the attenuation coefficient models along the coastal waters off Cochin. oligotrophic site in the Arabian Sea. Ecological Modeling, tropical Indian Ocean over six decades. Societal applications in Ajith Joseph K., Syam Sankar and Abish, B., 2017. Changes in Societal applications in Fisheries and Aquaculture using Remote 372,pp.12-23. Fisheries and Aquaculture using Remote Sensing Imagery, The Ocean circulation due to Climate change and possible impacts on the Sensing Imagery, The Second International Symposium on Second International Symposium on Remote Sensing for Ecosys- global and regional climate system with particular focus on the Vishnu P.S., S.S. Shaju, S.P. Tiwari, Nandini Menon, M. Nashad, Remote Sensing for Ecosystem Analysis and Fisheries, Book of tem Analysis and Fisheries, Book of Abstracts Indian Ocean region- A review. Our Seas: Theories, Data and C. Ajith Joseph, Mini Raman, Mohamed Hatha, M.P. Prabhakaran, Abstracts and Lead Article,p.90. Policies Symposium” November 18-21, 2017- KFAS,Kuwait. A. Mohandas. 2018. Seasonal variability in bio- optical properties Ajith Joseph K, Lasse H.Pettersson and N.R.Menon,2017. Harmful along the coastal waters off Cochin. Int J Appl Earth Obs algae bloom monitoringusing satellite observations. Coursemanualon Geoinformation 66, 184–195. Winter School on Structure and Functions of Marine Ecosystem: Wilson, S.S., Joseph, P.V., Mohanakumar, K. and Johannessen, Fisheries CMFRI Lecture Note Series No. 12/2017 ICAR-Central O.M., 2018. Interannual and long term variability of low level MarineFisheries ResearchInstitute,1-21December2017, 36,300-315. jetstream of the Asian summer monsoon. Tellus A: Dynamic Bindu.G, Prabha R Nair & Ajo Abraham Kurian, 2017. ' The impact Meteorology and Oceanography, 70(1), p.1445380. of PM10 on Acute Respiratory Illness in children: Results from a case study over an urban area', Air pollution, Climate and Health in Southern Asia and the HKH:Workshop & Science‐Policy Dialogue, Conference Proceeding papers in 2018 ICIMOD, Nepal, November 2017. Grinson G., Minu, P., Nandini Menon, N. And Gopalakrishnan, A., 2018. SAFARI- A retrospection and future plans. Societal applica- Bindu.G, Poornima Rajan, Jishnu.E.S Ajith Joseph K, 2017. tions in Fisheries and Aquaculture using Remote Sensing Imagery, Estimating carbon sequestration potential of mangroves in The Second International Symposium on Remote Sensing for kunhimangalam area using remote sensing and geographic Ecosystem Analysis and Fisheries. Book of Abstracts and Lead information system supported by field observations National Articles, p. 27-28. Conclave on Mangrove Conservation, December 2017. Amir Kumar Samal, Grinson George, Jayasankar J, Nazar A. K. A,

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