Investigation of spectral band requirements for improving retrievals of phytoplankton functional types.

Studying phytoplankton functional types (PFTs) from space is possible due to recent advances in remote sensing. Though a variety of products are available, the limited number of wavelengths available compared to the number of model parameters needed to be retrieved is still a major problem in using ocean-color data for PFT retrievals. Here, we investigated which band placement could improve retrievals of three particular PFTs (diatoms, coccolithophores and cyanobacteria). In addition to analyzing dominant spectral features in the absorption spectra of the target PFTs, two previously-developed methods using measured spectra were applied to simulated data. Such a synthetic dataset allowed for significantly increasing the number of scenarios and enabled a full control over parameters causing spectral changes. We evaluated the chosen band placement by applying an adapted ocean reflectance inversion, as utilized in the generalized inherent optical properties (GIOP) retrieval. Results show that the optimal band settings depend on the method applied to determine the bands placement, as well as on the internal variability of the dataset investigated. Therefore, continuous hyperspectral instruments would be most beneficial for discriminating multiple PFTs, though a small improvement in spectral sampling and resolution does not significantly modify the results. Bands, which could be added to future instruments (e.g., Ocean and Land Colour Instrument (OLCI) instrument on the upcoming Sentinel-3B,-3C,-3D, etc., and further satellites) in order to enhance PFT retrieval capabilities, were also determined

Assessment of Polymer Atmospheric Correction Algorithm for Hyperspectral Remote Sensing Imagery over Coastal Waters

Spaceborne imaging spectroscopy, also called hyperspectral remote sensing, has shown huge potential to improve current water colour retrievals and, thereby, the monitoring of inland and coastal water ecosystems. However, the quality of water colour retrievals strongly depends on successful removal of the atmospheric/surface contributions to the radiance measured by satellite sensors. Atmospheric correction (AC) algorithms are specially designed to handle these effects, but are challenged by the hundreds of narrow spectral bands obtained by hyperspectral sensors. In this paper, we investigate the performance of Polymer AC for hyperspectral remote sensing over coastal waters. Polymer is, in nature, a hyperspectral algorithm that has been mostly applied to multispectral satellite data to date. Polymer was applied to data from the Hyperspectral Imager for the Coastal Ocean (HICO), validated against in situ multispectral (AERONET-OC) and hyperspectral radiometric measurements, and its performance was compared against that of the hyperspectral version of NASA’s standard AC algorithm, L2gen. The match-up analysis demonstrated very good performance of Polymer in the green spectral region. The mean absolute percentage difference across all the visible bands varied between 16% (green spectral region) and 66% (red spectral region). Compared with L2gen, Polymer remote sensing reflectances presented lower uncertainties, greater data coverage, and higher spectral similarity to in situ measurements. These results demonstrate the potential of Polymer to perform AC on hyperspectral satellite data over coastal waters, thus supporting its application in current and future hyperspectral satellite missions

The Southern Ocean phytoplankton diversity from space and numerical modelling

This thesis consists of three chapters. The first chapter is devoted to the introduction and provides a generel knowledge about the existing literatüre. In the second chapter, we give some basic definitions and preliminary that be used in further sections. In the third chapter we provide new sufficient conditions fort he oscillation of all solution of the neutral differential equation with variable coefficients Also, in the third chapter is corcorned with the oscillatory behaviour of first order delay differential equations of the formBu tez çalışması üç bölümden oluşmaktadır. Birinci bölüm, giriş kısmına ayrılarak genel bir literatür bilgisi verilmiştir. İkinci bölümde, gerekli temel kavramlardan söz edilmiştir. Üçüncü bölümün ilk kısmında pozitif ve negatif katsayılı birinci mertebeden nötral gecikmeli diferensiyel denklemi incelenmiştir. Üçüncü bölümün ikinci kısmında ise, formundaki birinci mertebeden geciklemeli diferensiyel denklemlerin salınımlığı incelenmiştir

Investigating the phytoplankton diversity in the Great Calcite Belt: perspective from modelling and satellite retrievals

This study highlights benefits and challenges of applying coupled physical/biogeochemical modeling and the synergistic use of different satellite retrieval algorithms for investigating the phytoplankton diversity in the Great Calcite Belt. This area is of great interest for understanding biogeochemical cycling and ecosystem functioning under present climate changes observed in the Southern Ocean. Our coupled model simulations of the phenology of various Phytoplankton Functional Types (PFTs) are based on a version of the Darwin biogeochemical model (Dutkiewicz et al., 2015) coupled to the MITgcm circulation model (MITgcm Group 2012), where both - the physical and biogeochemical modules - are adapted for the Southern Ocean. As satellite-based PFT information, we consider products of the PhytoDOAS (Bracher et al. 2009, Sadeghi et al. 2012) using SCIAMACHY and OMI hyper-spectral optical satellite measurements. We also address aspects of combining this information synergistically (SynSenPFT, Losa et al. 2017) with the phytoplankton composition retrieved with OC-PFT (Hirata et al. 2011, Soppa et. al. 2014, 2016) based on multi-spectral optical satellite data (OC-CCI) and obtained by numerical modelling to allow for long time-series on the Southern Ocean phytoplankton diversity. To evaluate the satellite retrievals and model simulations we use in situ PFTs obtained a diagnostic pigment analysis (Soppa et al., 2017) as well as by scanning electron microscopy (Smith et al., 2017)

Assessing the Influence of Water Constituents on the Radiative Heating of Laptev Sea Shelf Waters.

The presence of optically active water constituents is known to attenuate the light penetration in the ocean and impact the ocean heat content. Here, we investigate the influence of colored dissolved organic matter (CDOM) and total suspended matter (TSM) on the radiative heating of the Laptev Sea shelf waters. The Laptev Sea region is heavily influenced by the Lena River, one of the largest river systems in the Arctic region. We simulate the radiative heating by using a coupled atmosphere-ocean radiative transfer model (RTM) and in situ measurements from the TRANSDRIFT XVII expedition carried out in September 2010. The results indicate that CDOM and TSM have significant influence on the energy budget of the Laptev Sea shelf waters, absorbing most of the solar energy in the first 2 m of the water column. In the station with the highest CDOM absorption (aCDOM(443) = 1.77 m−1) ~43% more energy is absorbed in the surface layer compared to the station with the lowest aCDOM(443) (~0.2 m−1), which translates to an increased radiative heating of ~0.6°C/day. The increased absorbed energy by the water constituents also implies increased sea ice melt rate and changes in the surface heat fluxes to the atmosphere. By using satellite remote sensing and RTM we quantify the spatial distribution of the radiative heating in the Laptev Sea for a typical summer day. The combined use of satellite remote sensing, RT modeling and in situ observations can be used to improve parameterization schemes in atmosphere-ocean circulation models to assess the role of the ocean in the effect of Arctic amplification

Corrigendum: Synergistic Exploitation of Hyper- and Multi-Spectral Precursor Sentinel Measurements to Determine Phytoplankton Functional Types (SynSenPFT)

We derive the chlorophyll a concentration (Chla) for three main phytoplankton functional types (PFTs) – diatoms, coccolithophores and cyanobacteria – by combining satellite multispectral-based information, being of a high spatial and temporal resolution, with retrievals based on high resolution of PFT absorption properties derived from hyperspectral satellite measurements. The multispectral-based PFT Chla retrievals are based on a revised version of the empirical OC-PFT algorithm applied to the Ocean Color Climate Change Initiative (OC-CCI) total Chla product. The PhytoDOAS analytical algorithm is used with some modifications to derive PFT Chla from SCIAMACHY hyperspectral measurements. To combine synergistically these two PFT products (OC-PFT and PhytoDOAS), an optimal interpolation is performed for each PFT in every OC-PFT sub-pixel within a PhytoDOAS pixel, given its Chla and its a priori error statistics. The synergistic product (SynSenPFT) is presented for the period of August 2002 March 2012 and evaluated against PFT Chla data obtained from in situ marker pigment data and the NASA Ocean Biogeochemical Model simulations and satellite information on phytoplankton size. The most challenging aspects of the SynSenPFT algorithm implementation are discussed. Perspectives on SynSenPFT product improvements and prolongation of the time series over the next decades by adaptation to Sentinel multi- and hyperspectral instruments are highlighted