Fundamentals of ocean colour remote sensing

Remote sensing refers to collection of information about an object without being in direct contact with the object. Remote sensing aids in measuring remote areas which are inaccessible by any other means and offer less expense than in-situ measurements. Remote sensing facilitates creation of long time series and extended measurement. This has the advantage that several parameters can be measured at same time and satellite-based remote sensing measurements allow global observations. Remote sensing has its own advantages and disadvantages. The limitation includes indirect measurements of large areas which are not of interest to the user. The automated instrument degradation creates retrieval errors and are affected by several factors/processes, and not only by the object of interest. Additional assumptions and models are needed for the interpretation of the measurements and before using these models in oceanographic studies, it is extremely important to validate the performance of the various ocean colour algorithms with in-situ observations (Swirgon et al., 2015)

Hoe lawaaierig is de oceaan?

Onder de zeespiegel is het nooit stil. De mens – wat dacht je – drukt er zijn stempel. Al gaat de natuur niet vrijuit. En het geluid zit werkelijk overal. Zelfs in de Marianentrog, met 11 km het diepste punt van de wereldzeeën, is geluid alomtegenwoordig. Aardbevingen, walvissen, schepen en orkanen creëren er een kakafonie van geluiden. In wat volgt gaan we op zoek naar het voorkomen en de invloed van onderwatergeluiden in de oceaan. We zoeken een antwoord op de vraag: hoe natuurlijk is het geluid in de oceaan, wat betekent dit voor zeedieren en wat kunnen we doen om extra geluidvervuiling te voorkomen of te milderen

Cyclone Phailin enhanced the productivity following its passage: evidence from satellite data

This article does not have an abstract

Penetrative radiative flux in the Bay of Bengal

Author Posting. © The Oceanography Society, 2016. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 29, no. 2 (2016): 214–221, doi:10.5670/oceanog.2016.53.The Bay of Bengal (BoB), a semi-enclosed basin in the northern Indian Ocean, is a complex region with large freshwater inputs and strong vertical stratification that result in a shallow, spatially variable mixed layer. With the exception of shortwave insolation, the air-sea heat exchange occurs at the sea surface and is vertically redistributed by mixing and advection. Strongly stratified, shallow mixed layers inhibit vertical mixing, and the penetration of solar radiation through the base of the mixed layer can lead to redistribution of upper-ocean heat. This paper compiles observations of hyperspectral downwelling irradiance (Ed) from 67 profiles collected during six research cruises in the BoB that span a broad range of regions and seasons between 2009 and 2014. We report attenuation length scales computed using double and single exponential models and quantify the penetration of radiative flux below the mixed layer depth (Qpen). We then evaluate estimates of Qpen obtained from published chlorophyll-based models and compare them to our observations. We find that the largest penetrative heat flux (up to 40% of the incident Ed) occurs near 16°N where the mixed layers are shallow and the water is optically clear.AAL acknowledges funding of the Ocean Mixing and Monsoon (OMM) and SATellite Coastal and Oceanographic REsearch (SATCORE) programs by the Ministry of Earth Sciences, government of India. MMO was supported by the Office of Naval Researchfunded Coastal and Submesoscale Process Studies for Air-Sea Interactions Regional Initiative (ASIRI) in the Bay of Bengal

Bio-Optical Sensors on Argo Floats

The general objective of the IOCCG BIO-Argo working group is to elaborate recommendations for establishing a framework for the future development of a cost-effective, bio-optical float network corresponding to the needs and expectations of the scientific community. In this context, our recommendations will necessarily be broad; they range from the identification of key bio-optical measurements to be implemented on floats, to the real-time management of the data flux resulting from the deployment of a "fleet of floats". Each chapter of this report is dedicated to an essential brick leading towards the goal of implementing a bio-optical profiling float network. The following topics are discussed in the Chapters listed below: - Chapter 2 reviews the scientific objectives that could be tackled through the development of such networks, by allowing some of the gaps in the present spatio-temporal resolution of bio-optical variables to be progressively filled. - Chapter 3 identifies the optical and bio-optical properties that are now amenable to remote and autonomous measurement through the use of optical sensors mounted on floats. - Chapter 4 addresses the question of sensor requirements, in particular with respect to measurements performed from floats. - Chapter 5 proposes and argues for the development of dedicated float missions corresponding to specific scientific objectives and relying on specific optical sensor suites, as well as on specific modes of float operation. - Chapter 6 identifies technological issues that need to be addressed for the various bio-optical float missions to become even more cost-effective. - Chapter 7 covers all aspects of data treatment ranging from the development of various quality control procedures (from real-time to delayed mode) to the architecture required for favoring easy access to data. - Chapter 8 reviews the necessary steps and experience required before the operational implementation of different types of float networks can become a reality.JRC.H.5-Land Resources Managemen

<span style="font-size:15.0pt;font-family: "Times New Roman";mso-fareast-font-family:"Times New Roman";mso-bidi-font-family: "Times New Roman";mso-ansi-language:EN-US;mso-fareast-language:EN-US; mso-bidi-language:HI;mso-bidi-font-weight:bold" lang="EN-US">Spatio-Temporal Distribution of Physico-Chemical Parameters and Chlorophyll-<i style="mso-bidi-font-style:normal">a</i> in Chilika Lagoon, East Coast of India</span>

614-627<span style="font-size:9.0pt;font-family: " times="" new="" roman";mso-fareast-font-family:"times="" roman";mso-bidi-font-family:="" "times="" roman";mso-ansi-language:en-us;mso-fareast-language:en-us;="" mso-bidi-language:hi"="" lang="EN-US">Present study contains the current status of Chilika Lagoon water quality during pre-monsoon, monsoon and post-monsoon seasons of the year 2012. Spatial and seasonal distributions of water quality parameters viz. WT, pH, Salinity, DO, TSM, Chl-a and inorganic nutrients (NO , NO , NH, PO, SiO) were examined in this study. Twenty locations were selected covering all the ecological sectors of the lagoon. Study reveals significant spatio-temporal variation in water quality parameters. The pH of the lagoon was found to be slightly alkaline. DO concentration was controlled by photosynthetic activities of autotrophs. Results of one-way ANOVA indicated spatio-temporal variation in the nutrients especially NH  and SiO (p  was found below the pollution limit for aquatic lives. Among the nutrients SiO, was the most influencing factor regulating phytoplankton production of the lagoon throughout the year.  However, NH was found as the second influencing factor for distribution of Chl-a

<span style="font-size:15.0pt;font-family: "Times New Roman";mso-fareast-font-family:"Times New Roman";mso-bidi-font-family: Mangal;mso-ansi-language:EN-US;mso-fareast-language:EN-US;mso-bidi-language: HI" lang="EN-US">Occurrence of a new species of toxic Cnidaria (<i style="mso-bidi-font-style: normal">Pelagia noctiluca</i><b> </b>Forskål, 1775) from estuarine waters of Rushikulya River, Western Bay of Bengal</span>

580-58

<span style="font-size:15.0pt;font-family: "Times New Roman";mso-fareast-font-family:"Times New Roman";mso-bidi-font-family: Mangal;mso-ansi-language:EN-US;mso-fareast-language:EN-US;mso-bidi-language: HI;mso-bidi-font-weight:bold" lang="EN-US">First record of <i style="mso-bidi-font-style: normal">Desmoscolex falcatus</i> (Nematoda: Adenophorea: Desmoscolecida: Desmoscolecidae) from Rushikulya estuary, Odisha, India</span>

487-489<i style="mso-bidi-font-style: normal">Desmoscolex falcatus<span style="font-size:9.0pt;mso-ansi-language: EN-US" lang="EN-US"> (Nematoda: Adenophorea: Desmoscolecida: Desmoscolecidae) is reported for the first time from Rushikulya estuary. </span

First record of fourteen phytoplankton species off Rushikulya estuary, Northwestern Bay of Bengal

490-494Fourteen numbers of phytoplankton species have been reported for the first time in coastal waters off Rushikulya estuary. </span

Seasonal variation of phytoplankton community composition in coastal waters off Rushikulya Estuary, East Coast of India

508-526<span style="font-size:9.0pt;line-height: 115%;font-family:" times="" new="" roman";mso-fareast-font-family:"times="" roman";="" mso-bidi-font-family:"times="" roman";mso-ansi-language:en-us;mso-fareast-language:="" en-us;mso-bidi-language:ar-sa"="" lang="EN-US">A total of 149 phytoplankton species were identified during the study period wherein diatoms contributed 109, dinoflagellates 28, green algae 6, cyanobacteria 4 and cocolithophores 2. A striking feature of the study is the new record of 26 species from coastal waters vicinity off Rushikulya estuary (coastal and estuarine waters extending from Rushikulya to Bahuda) and 15 species from entire coastal waters of Odisha. A contrast in phytoplankton species composition was noticed in all seasons. Diatoms found as the dominant prevailing phytoplankton group in all seasons in terms of number of species and abundance. Diatom species <i style="mso-bidi-font-style: normal">viz. Thalassiothix longissima, Skeletonema costatum, Coscinodiscus eccentricus were ubiquitous off Rushikulya estuary throughout the year. River and monsoon influence coastal waters in supplying macronutrients for phytoplankton growth. Nitrogenous nutrients were found to be controlling factor for phytoplankton growth. A linear relationship between phytoplankton abundance and chlorophyll-a was observed during three seasons. Despite the highest species abundance during premonsoon, species diversity index showed maximum for postmonsoon and monsoon periods due to preponderance of few diatom species. Species were found to be more evenly distributed during monsoon as indicated from the Pielou’s evenness (J’) index. Non-metric multidimensional scaling (MDS) ordinations based on Bray-Curtis similarities indicated that phytoplankton communities prevailed in March and April were the least similar to those on other sampling occasions.</span