6th Data Science Symposium Abstracts

The Data Science Symposium at Haus der Wissenschaft on 8/9 November 2021 in Bremen was the 6th Symposium in this series since 2017

Using empirical orthogonal functions derived from remote sensing reflectance for the prediction of concentrations of phytoplankton pigments.

The composition and abundance of algal pigments provide information on characteristics of a phytoplankton community in respect to its photoacclimation, overall biomass, and taxonomic composition. Particularly, these pigments play a major role in photoprotection and in the light-driven part of photosynthesis. Most phytoplankton pigments can be measured by High Performance Liquid Chromatography (HPLC) techniques to filtered water samples. This method, like others when water samples have to be analysed in the laboratory, is time consuming and therefore only a limited number of data points can be obtained. In order to receive information on phytoplankton pigment composition with a higher temporal and spatial resolution, we have developed a method to assess pigment concentrations from continuous optical measurements. The method applies an Empirical Orthogonal Function (EOF) analysis to remote sensing reflectance data derived from ship-based hyper-spectral underwater radiometric and from multispectral satellite data (using the MERIS Polymer product developed by Steinmetz et al., 2011) measured in the Eastern Tropical Atlantic. Subsequently we developed statistically linear models with measured (collocated) pigment concentrations as the response variable and EOF loadings as predictor variables. The model results, show that surface concentrations of a suite of pigments and pigment groups can be well predicted from the ship-based reflectance measurements, even when only a multi-spectral resolution is chosen (i.e. eight bands similar to those used by MERIS). Based on the MERIS reflectance data, concentrations of total and monovinyl chlorophyll a and the groups of photoprotective and photosynthetic carotenoids can be predicted with high quality. The fitted statistical model constructed on the satellite reflectance data as input was applied to one month of MERIS Polymer data to predict the concentration of those pigment groups for the whole Eastern Tropical Atlantic area. Bootstrapping explorations of cross-validation error indicate that the method can produce reliable predictions with relatively small data sets (e.g., < 50 collocated values of reflectance and pigment concentration). The method allows for the derivation of time series from continuous reflectance data of various pigment groups at various regions, which can be used to study variability and change of phytoplankton composition and photo-physiology

Radiative transfer modeling through terrestrial atmosphere and ocean accounting for inelastic scattering processes: Software package SCIATRAN.

SCIATRAN is a comprehensive software package which is designed to model radiative transfer processes in the terrestrial atmosphere and ocean in the spectral range from the ultraviolet to the thermal infrared (0.18–40 μm). It accounts for multiple scattering processes, polarization, thermal emission and ocean–atmosphere coupling. The main goal of this paper is to present a recently developed version of SCIATRAN which takes into account accurately inelastic radiative processes in both the atmosphere and the ocean. In the scalar version of the coupled ocean–atmosphere radiative transfer solver presented by Rozanov et al. [61] we have implemented the simulation of the rotational Raman scattering, vibrational Raman scattering, chlorophyll and colored dissolved organic matter fluorescence. In this paper we discuss and explain the numerical methods used in SCIATRAN to solve the scalar radiative transfer equation including trans-spectral processes, and demonstrate how some selected radiative transfer problems are solved using the SCIATRAN package. In addition we present selected comparisons of SCIATRAN simulations with those published benchmark results, independent radiative transfer models, and various measurements from satellite, ground-based, and ship-borne instruments. The extended SCIATRAN software package along with a detailed User's Guide is made available for scientists and students, who are undertaking their own research typically at universities, via the web page of the Institute of Environmental Physics (IUP), University of Bremen: http://www.iup.physik.uni-bremen.de

Vertically resolved dust optical properties during SAMUM: Tinfou compared to Ouarzazate

Vertical profiles of dust key optical properties are presented from measurements during the Saharan Mineral Dust Experiment (SAMUM) by Raman and depolarization lidar at two ground-based sites and by airborne high spectral resolution lidar. One of the sites, Tinfou, is located close to the border of the Sahara in Southern Morocco and was the main in situ site during SAMUM. The other site was Ouarzazate airport, the main lidar site. From the lidar measurements the spatial distribution of the dust between Tinfou and Ouarzazate was derived for 1 d. The retrieved profiles of backscatter and extinction coefficients and particle depolarization ratios show comparable dust optical properties, a similar vertical structure of the dust layer, and a height of about 4 km asl at both sites. The airborne cross-section of the extinction coefficient at the two sites confirms the low variability in dust properties. Although the general picture of the dust layer was similar, the lidar measurements reveal a higher dust load closer to the dust source. Nevertheless, the observed intensive optical properties were the same. These results indicate that the lidar measurements at two sites close to the dust source are both representative for the SAMUM dust conditions

Underway spectrophotometry in the Fram Strait (European Arctic Ocean): a highly resolved chlorophyll a data source for complementing satellite ocean color

Satellite remote sensing of chlorophyll a concentration (Chl-a) in the Arctic Ocean is spatially and temporally limited and needs to be supplemented and validated with substantial volumes of in situ observations. Here, we evaluated the capability of obtaining highly resolved in situ surface Chl-a using underway spectrophotometry operated during two summer cruises in 2015 and 2016 in the Fram Strait. Results showed that Chl-a measured using high pressure liquid chromatography (HPLC) was well related (R2 = 0.90) to the collocated particulate absorption line height at 676 nm obtained from the underway spectrophotometry system. This enabled continuous surface Chl-a estimation along the cruise tracks. When used to validate Chl-a operational products as well as to assess the Chl-a algorithms of the aqua moderate resolution imaging spectroradiometer (MODIS-A) and Sentinel-3 Ocean Land Color Imager (OLCI) Level 2 Chl-a operational products, and from OLCI Level 2 products processed with Polymer atmospheric correction algorithm (version 4.1), the underway spectrophotometry based Chl-a data sets proved to be a much more sufficient data source by generating over one order of magnitude more match-ups than those obtained from discrete water samples. Overall, the band ratio (OCI, OC4) Chl-a operational products from MODIS-A and OLCI as well as OLCI C2RCC products showed acceptable results. The OLCI Polymer standard output provided the most reliable Chl-a estimates, and nearly as good results were obtained from the OCI algorithm with Polymer atmospheric correction method. This work confirms the great advantage of the underway spectrophotometry in enlarging in situ Chl-a data sets for the Fram Strait and improving satellite Chl-a validation and Chl-a algorithm assessment over discrete water sample analysis in the laboratory

Desert Dust Air Mass Mapping in the Western Sahara, using Particle Properties Derived from Space-based Multi-angle Imaging

Coincident observations made over the Moroccan desert during the SAhara Mineral dUst experiMent (SAMUM) 2006 field campaign are used both to validate aerosol amount and type retrieved from Multi-angle Imaging SpectroRadiometer (MISR) observations, and to place the sub-orbital aerosol measurements into the satellite's larger regional context. On three moderately dusty days for which coincident observations were made, MISR mid-visible aerosol optical thickness (AOT) agrees with field measurements point-by-point to within 0.05 to 0.1. This is about as well as can be expected given spatial sampling differences; the space-based observations capture AOT trends and variability over an extended region. The field data also validate MISR's ability to distinguish and to map aerosol air masses, from the combination of retrieved constraints on particle size, shape, and single-scattering albedo. For the three study days, the satellite observations (a) highlight regional gradients in the mix of dust and background spherical particles, (b) identify a dust plume most likely part of a density flow, and (c) show an air mass containing a higher proportion of small, spherical particles than the surroundings, that appears to be aerosol pollution transported from several thousand kilometers away