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Publications

Zhang W. & Wirtz K. (2017): Mutual dependence between sedimentary organic carbon and infaunal macrobenthos resolved by mechanistic modeling. Journal of Geophysical Research: Biogeosciences, 122. DOI:10.1002/2017JG003909

Abstract:

The mutual dependence between sedimentary total organic carbon (TOC) and infaunal macrobenthos is here quantified by a mechanistic model. The model describes (i) the vertical distribution of infaunal macrobenthic biomass resulting from a trade-off between nutritional benefit (quantity and quality of TOC) and the costs of burial (respiration) and mortality, and (ii) the variable vertical distribution of TOC being in turn shaped by bioturbation of local macrobenthos. In contrast to conventional approaches, our model emphasizes variations of bioturbation both spatially and temporally depending on local food resources and macrobenthic biomass. Our implementation of the dynamic interaction between TOC and infaunal macrobenthos is able to capture a temporal benthic response to both depositional and erosional environments and provides improved estimates of the material exchange flux at the sediment-water interface. Applications to literature data for the North Sea demonstrate the robustness and accuracy of the model and its potential as an analysis tool for the status of TOC and macrobenthos in marine sediments. Results indicate that the vertical distribution of infaunal biomass is shaped by both the quantity and the quality of OC, while the community structure is determined only by the quality of OC. Bioturbation intensity may differ by one order of magnitude over different seasons owing to variations in the OC input, resulting in a significant modulation on the distribution of OC. Our relatively simple implementation may further improve models of early diagenesis and marine food-web dynamics by mechanistically connecting the vertical distribution of both TOC and macrobenthic biomass.


Publications

Daewel, U. and Schrum, C. (2017): Low-frequency variability in North Sea and Baltic Sea identified through simulations with the 3-D coupled physical–biogeochemical model ECOSMO. Earth Syst. Dynam., 8, 801-815, DOI:10.5194/esd-8-801-2017

Abstract:

Here we present results from a long-term model simulation of the 3-D coupled ecosystem model ECOSMO II for a North Sea and Baltic Sea set-up. The model allows both multi-decadal hindcast simulation of the marine system and specific process studies under controlled environmental conditions. Model results have been analysed with respect to long-term multi-decadal variability in both physical and biological parameters with the help of empirical orthogonal function (EOF) analysis. The analysis of a 61-year (1948–2008) hindcast reveals a quasi-decadal variation in salinity, temperature and current fields in the North Sea in addition to singular events of major changes during restricted time frames. These changes in hydrodynamic variables were found to be associated with changes in ecosystem productivity that are temporally aligned with the timing of reported regime shifts in the areas. Our results clearly indicate that for analysing ecosystem productivity, spatially explicit methods are indispensable. Especially in the North Sea, a correlation analysis between atmospheric forcing and primary production (PP) reveals significant correlations between PP and the North Atlantic Oscillation (NAO) and wind forcing for the central part of the region, while the Atlantic Multi-decadal Oscillation (AMO) and air temperature are correlated to long-term changes in PP in the southern North Sea frontal areas. Since correlations cannot serve to identify causal relationship, we performed scenario model runs perturbing the temporal variability in forcing condition to emphasize specifically the role of solar radiation, wind and eutrophication. The results revealed that, although all parameters are relevant for the magnitude of PP in the North Sea and Baltic Sea, the dominant impact on long-term variability and major shifts in ecosystem productivity was introduced by modulations of the wind fields.


Publications

Lefering, Ina; Utschig, Christian; McKee, David (2017): Uncertainty budgets for liquid waveguide CDOM absorption measurements. Applied Optics. 56. 6357. doi:10.1364/AO.56.006357

Abstract:

Long path length liquid waveguide capillary cell (LWCC) systems using simple spectrometers to determine the spectral absorption by colored dissolved organic matter (CDOM) have previously been shown to have better measurement sensitivity compared to high-end spectrophotometers using 10 cm cuvettes. Information on the magnitude of measurement uncertainties for LWCC systems, however, has remained scarce. Cross-comparison of three different LWCC systems with three different path lengths (50, 100, and 250 cm) and two different cladding materials enabled quantification of measurement precision and accuracy, revealing strong wavelength dependency in both parameters. Stable pumping of the sample through the capillary cell was found to improve measurement precision over measurements made with the sample kept stationary. Results from the 50 and 100 cm LWCC systems, with higher refractive index cladding, showed systematic artifacts including small but unphysical negative offsets and high-frequency spectral perturbations due to limited performance of the salinity correction. In comparison, the newer 250 cm LWCC with lower refractive index cladding returned small positive offsets that may be physically correct. After null correction of measurements at 700 nm, overall agreement of CDOM absorption data at 440 nm was found to be within 5% root mean square percentage error.

 

Hiroyuki Tan, Tomohiko Oishi, Akihiko Tanaka, Roland Doerffer, and Yasuhiro Tan (2017): Chlorophyll-a specific volume scattering function of phytoplankton. Opt. Express 25, A564-A573, DOI: 10.1364/OE.25.00A564

Abstract:

Chlorophyll-A specific light volume scattering functions (VSFs) by cultured phytoplankton in visible spectrum range is presented. Chlorophyll-A specific VSFs were determined based on the linear least squares method using a measured VSFs with different chlorophyll-A concentrations. We found obvious variability of it in terms of spectral and angular shapes of VSF between cultures. It was also presented that chlorophyll-A specific scattering significantly affected on spectral variation of the remote sensing reflectance, depending on spectral shape of b. This result is useful for developing an advance algorithm of ocean color remote sensing and for deep understanding of light in the sea.


Publications

Hongyan Xi, Martin Hieronymi, Hajo Krasemann and Rüdiger Röttgers (2017): Phytoplankton Group Identification Using Simulated and In situ Hyperspectral Remote Sensing Reflectance. Front. Mar. Sci. 4:272, doi:10.3389/fmars.2017.00272

Abstract:

In the present study we investigate the bio-geo-optical boundaries for the possibility to identify dominant phytoplankton groups from hyperspectral ocean color data. A large dataset of simulated remote sensing reflectance spectra, Rrs(λ), was used. The simulation was based on measured inherent optical properties of natural water and measurements of five phytoplankton light absorption spectra representing five major phytoplankton spectral groups. These simulated data, named as C2X data, contain more than 105 different water cases, including cases typical for clearest natural waters as well as for extreme absorbing and extreme scattering waters. For the simulation the used concentrations of chlorophyll a (representing phytoplankton abundance), Chl, are ranging from 0 to 200 mg m−3, concentrations of non-algal particles, NAP, from 0 to 1,500 g m−3, and absorption coefficients of chromophoric dissolved organic matter (CDOM) at 440 nm from 0 to 20 m−1. A second, independent, smaller dataset of simulated Rrs(λ) used light absorption spectra of 128 cultures from six phytoplankton taxonomic groups to represent natural variability. Spectra of this test dataset are compared with spectra from the C2X data in order to evaluate to which extent the five spectral groups can be correctly identified as dominant under different optical conditions. The results showed that the identification accuracy is highly subject to the water optical conditions, i.e., contribution of and covariance in Chl, NAP, and CDOM. The identification in the simulated data is generally effective, except for waters with very low contribution by phytoplankton and for waters dominated by NAP, whereas contribution by CDOM plays only a minor role. To verify the applicability of the presented approach for natural waters, a test using in situ Rrs(λ) dataset collected during a cyanobacterial bloom in Lake Taihu (China) is carried out and the approach predicts blue cyanobacteria to be dominant. This fits well with observation of the blue cyanobacteria Microcystis sp. in the lake. This study provides an efficient approach, which can be promisingly applied to hyperspectral sensors, for identifying dominant phytoplankton spectral groups purely based on Rrs(λ) spectra.

 

Evers-King, V. Martinez-Vicente, R. J. W. Brewin, G. Dall’Olmo, A. E. Hickman, T. Jackson, T. S. Kostadinov, H. Krasemann, H. Loisel, R. Röttgers, S. Roy, D. Stramski, S. Thomalls, T. Platt, and S. Sathyendranath (2017): Validation and Intercomparison of Ocean Color Algorithms for Estimating Particulate Organic Carbon in the Oceans. Front. Mar. Sci. 4(August), 1–20, doi:10.3389/fmars.2017.00251

Abstract:

Particulate Organic Carbon (POC) plays a vital role in the ocean carbon cycle. Though relatively small compared with other carbon pools, the POC pool is responsible for large fluxes and is linked to many important ocean biogeochemical processes. The satellite ocean-color signal is influenced by particle composition, size, and concentration and provides a way to observe variability in the POC pool at a range of temporal and spatial scales. To provide accurate estimates of POC concentration from satellite ocean color data requires algorithms that are well validated, with uncertainties characterized. Here, a number of algorithms to derive POC using different optical variables are applied to merged satellite ocean color data provided by the Ocean Color Climate Change Initiative (OC-CCI) and validated against the largest database of in situ POC measurements currently available. The results of this validation exercise indicate satisfactory levels of performance from several algorithms (highest performance was observed from the algorithms of Loisel et al., 2002; Stramski et al., 2008) and uncertainties that are within the requirements of the user community. Estimates of the standing stock of the POC can be made by applying these algorithms, and yield an estimated mixed-layer integrated global stock of POC between 0.77 and 1.3 Pg C of carbon. Performance of the algorithms vary regionally, suggesting that blending of region-specific algorithms may provide the best way forward for generating global POC products.


Publications

Meinke, I. (2017): Stakeholder-based evaluation categories for regional climate services – a case study at the German Baltic Sea coast. Adv. Sci. Res., 14, 279-291, doi:10.5194/asr-14-279-2017

Abstract:

In this study, categories, dimensions, and criteria for evaluating regional climate services are derived by a participatory approach with potential service users at the German Baltic Sea coast. The development is carried out within nine face-to-face interviews conducted with decision makers, working in climate sensitive sectors at the German Baltic Sea coast. Three main groups of categories were localized which seem to matter most to the considered stakeholders and which seem to be crucial evaluation categories for regional climate services: (1) credibility, (2) relevance, and (3) appropriateness. For each of these evaluation categories several dimensions emerged, indicating certain perspectives of stakeholder demands. When summarizing these evaluation categories and their dimensions, 13 evaluation criteria for regional climate services can be derived (see Table 1). The results show that stakeholders do mainly address components other than those found in the literature (e.g. inputs, process, outputs, outcomes, and impacts). This might indicate that an evaluation, following solely literature-based (non-participative) components, is not sufficient to localize deficiencies or efficiencies within a regional climate service, since it might lead to results which are not relevant for potential users.


Publications

Schaaf, B., H. von Storch, and F. Feser (2017): Has spectral nudging an effect for dynamical downscaling applied in small regional model domains? Monthly Weather Review DOI:10.1175/MWR-D-17-0087.1

Abstract:

Spectral nudging is a method which was developed to constrain regional climate models so that they reproduce the development of the large-scale atmospheric state, while permitting the formation of regional-scale details as conditioned by the large-scales. Besides keeping the large-scale development in the interior close to a given state, the method also suppresses the emergence of ensemble variability. The method is mostly applied to reconstructions of past weather developments in regions with an extension of typically 1000-8000 kilometers.

In this article, we examine if spectral nudging is having an effect on simulations with model regions of the size of about 700 km x 500 km at mid-latitudes located mainly over flat terrain. We first compare two pairs of simulations, two runs each with and without spectral nudging, and find that the four simulations are very similar, without systematic or intermittent phases of divergence. Smooth fields, which are mainly determined by spatial patterns, such as air pressure show hardly any differences, while small-scale and heterogeneous fields such as precipitation vary strongly, mostly on the grid-point scale, irrespective if spectral nudging is employed or not. We conclude that the application of spectral nudging has little effect on the simulation when the model region is relatively small.


Publications

von Storch, H., F. Feser, B. Geyer, K. Klehmet, D. Li, B. Rockel, M. Schubert-Frisius, N. Tim, E. Zorita (2017): Regional re-analysis without local data – exploiting the downscaling paradigm. Journal of Geophysical Research – Atmospheres, DOI 10.1002/2016JD026332

Abstract:

This paper demonstrates two important aspects of regional dynamical downscaling of multi-decadal atmospheric re-analysis. First, that in this way skillful regional descriptions of multi-decadal climate variability may be constructed in regions with little or no local data. Secondly, that the concept of large-scale constraining allows global downscaling, so that global re-analyses may be completed by additions of consistent detail in all regions of the world.

Global re-analyses suffer from inhomogeneities. However, their largescale componenst are mostly homogeneous; Therefore, the concept of downscaling may be applied to homogeneously complement the large-scale state of the re-analyses with regional detail – wherever the condition of homogeneity of the description of large scales is fulfilled.

Technically this can be done by dynamical downscaling using a regional or global climate model, which’s large scales are constrained by spectral nudging. This approach has been developed and tested for the region of Europe, and a skillful representation of regional weather risks – in particular marine risks – was identified. We have run this system in regions with reduced or absent local data coverage, such as Central Siberia, the Bohai and Yellow Sea, Southwestern Africa and the South Atlantic. Also a global simulation was computed, which adds regional features to prescribed global dynamics. Our cases demonstrate that spatially detailed reconstructions of the climate state and its change in the recent three to six decades add useful supplementary information to existing observational data for mid-latitude and sub-tropical regions of the world.

Plain Language Summary:

This paper demonstrates two important aspects of regional dynamical downscaling of multi-decadal atmospheric re-analysis. First, in this way skillful regional descriptions of multi-decadal climate variability may be constructed in regions with little or no local data. Secondly, the concept of large-scale constraining allows global dynamical downscaling so that global re-analyses may be completed by additions of consistent detail in all regions of the world.


Publications

Zhao, Z.; Tang, J.; Mi, L.; Tian, C.; Zhong, G.; Zhang, G.; Wang, S.; Li, Q.; Ebinghaus, R.; Xie, Z.; Sun, H. (2017): Perfluoroalkyl and polyfluoroalkyl substances in the lower atmospheres and surface waters of the Chinese Bohai Sea, Yellow Sea, and Yangtze River Estuary. Science of the Total Environment 599–600, 114–123, doi:10.1016/j.scitotenv.2017.04.147

Abstract:

Polyfluoroalkyl and perfluoroalkyl substances (PFASs), in the forms of neutral polyfluoroalkyl substances in the gas phase of air and ionic perfluoroalkyl substances in the dissolved phase of surface water, were investigated during a sampling campaign in the Bohai Sea, Yellow Sea, and Yangtze River estuary in May 2012. In the gas phase, the concentrations of neutral ∑ PFASs were within the range of 76–551 pg/m3. Higher concentrations were observed in the South Yellow Sea. 8:2 fluorotelomer alcohol (FTOH) was the predominant compound as it accounted for 92%–95% of neutral ∑ PFASs in all air samples. Air mass backward trajectory analysis indicated that neutral ∑ PFASs came mainly from the coast of the Yellow Sea, including the Shandong, Jiangsu, and Zhejiang provinces of China, and the coastal region of South Korea. The fluxes of gas phase dry deposition were simulated for neutral PFASs, and neutral ∑ PFASs fluxes varied from 0.37 to 2.3 pg/m2/s. In the dissolved phase of the surface water, concentrations of ionic ∑ PFASs ranged from 1.6 to 118 ng/L, with the Bohai Sea exhibiting higher concentrations than both the Yellow Sea and the Yangtze River estuary. Perfluorooctanoic acid (PFOA) was the predominant compound accounting for 51%–90% of the ionic ∑ PFAS concentrations. Releases from industrial and domestic activities as well as the semiclosed geographical conditions increased the level of ionic ∑ PFASs in the Bohai Sea. The spatial distributions of perfluoroalkyl carboxylic acids (PFCAs) and perfluoroalkane sulfonic acids (PFSAs) were different significantly. The Laizhou Bay was the major source region of PFCAs and the Yangtze River estuary was the major source of PFSAs.


Publications

Li, J.; Xie, Z.; Mi, W.; Lai, S.; Tian, C.; Emeis, K.-C.; Ebinghaus, R. (2017): Organophosphate Esters in Air, Snow, and Seawater in the North Atlantic and the Arctic. Environmental Science & Technology 51, 6887−6896, doi:10.1021/acs.est.7b01289

Abstract:

The concentrations of eight organophosphate esters (OPEs) have been investigated in air, snow and seawater samples collected during the cruise of ARK-XXVIII/2 from sixth June to third July 2014 across the North Atlantic and the Arctic. The sum of gaseous and particle concentrations (ΣOPE) ranged from 35 to 343 pg/m3. The three chlorinated OPEs accounted for 88 ± 5% of the ΣOPE. The most abundant OPE was tris(2-chloroethyl) phosphate (TCEP), with concentrations ranging from 30 to 227 pg/m3, followed by three major OPEs, such as tris(1-chloro-2-propyl) phosphate (TCPP, 0.8 to 82 pg/m3), tri-n-butyl phosphate (TnBP, 2 to 19 pg/m3), and tri-iso-butyl phosphate (TiBP, 0.3 to 14 pg/m3). The ΣOPE concentrations in snow and seawater ranged from 4356 to 10561 pg/L and from 348 to 8396 pg/L, respectively. The atmospheric particle-bound dry depositions of TCEP ranged from 2 to 12 ng/m2/day. The air–seawater gas exchange fluxes were dominated by net volatilization from seawater to air for TCEP (mean, 146 ± 239 ng/m2/day), TCPP (mean, 1670 ± 3031 ng/m2/day), TiBP (mean, 537 ± 581 ng/m2/day) and TnBP (mean, 230 ± 254 ng/m2/day). This study highlighted that OPEs are subject to long-range transport via both air and seawater from the European continent and seas to the North Atlantic and the Arctic.


Publications

Markus Schultze, Burkhardt Rockel (2017): Direct and semi-direct effects of aerosol climatologies on long-term climate simulations over Europe. Climate Dynamics, pp 1–24, DOI: 10.1007/s00382-017-3808-5

Abstract:

This study compares the direct and semi-direct aerosol effects of different annual cycles of tropospheric aerosol loads for Europe from 1950 to 2009 using the regional climate model COSMO-CLM, which is laterally forced by reanalysis data and run using prescribed, climatological aerosol optical properties. These properties differ with respect to the analysis strategy and the time window, and are then used for the same multi-decadal period. Five simulations with different aerosol loads and one control simulation without any tropospheric aerosols are integrated and compared. Two common limitations of our simulation strategy, to fully assess direct and semi-direct aerosol effects, are the applied observed sea surface temperatures and sea ice conditions, and the lack of short-term variations in the aerosol load. Nevertheless, the impact of different aerosol climatologies on common regional climate model simulations can be assessed. The results of all aerosol-including simulations show a distinct reduction in solar irradiance at the surface compared with that in the control simulation. This reduction is strongest in the summer season and is balanced primarily by a weakening of turbulent heat fluxes and to a lesser extent by a decrease in longwave emissions. Consequently, the seasonal mean surface cooling is modest. The temperature profile responses are characterized by a shallow near-surface cooling and a dominant warming up to the mid-troposphere caused by aerosol absorption. The resulting stabilization of stratification leads to reduced cloud cover and less precipitation. A decrease in cloud water and ice content over Central Europe in summer possibly reinforce aerosol absorption and thus strengthen the vertical warming. The resulting radiative forcings are positive. The robustness of the results was demonstrated by performing a simulation with very strong aerosol forcing, which lead to qualitatively similar results. A distinct added value over the default aerosol setup of Tanré et al. (1984) was found in the simulations with more recent aerosol data sets for solar irradiance. The improvements are largest under low cloud conditions, while overestimated cloud cover in all setups causes a common underestimation of low and medium values of solar irradiance. In addition, the prevalent cold bias in the COSMO-CLM is reduced in winter and spring when using updated aerosol data. Our results emphasize the importance of semi-direct aerosol effects, especially over Central Europe in terms of changes in turbulent fluxes and changes in cloud properties. We also suggest to replace the default Tanré et al. (1984) aerosol climatology with more recent and realistic data sets. Thereby, a better model performance in comparison to observations can be achieved, or the masking of model shortcomings due to a too strong direct aerosol forcing thus far is prevented.