Global distributions of picoheterothrophs (Bacteria and Archaea) abundance and biomass - Gridded data product (NetCDF) - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

We compiled a database of bacterial abundance of 39 766 data points. After gridding with 1° spacing, the database covers 1.3% of the ocean surface. There is data covering all ocean basins and depth except the Southern Hemisphere below 350 m or from April until June. The average bacterial biomass is 3.9 ± 3.6 µg l-1 with a 20-fold decrease between the surface and the deep sea. We estimate a total ocean inventory of about 1.3 - 1029 bacteria. Using an average of published open ocean measurements for the conversion from abundance to carbon biomass of 9.1 fg cell-1, we calculate a bacterial carbon inventory of about 1.2 Pg C. The main source of uncertainty in this inventory is the conversion factor from abundance to biomass.

GPS raw data (control points and ground control points) from the Liguria Region, Borghetto Santo Spirito, Italy

Monitoring the impact of sea storms on coastal areas is fundamental to study beach evolution and the vulnerability of low-lying coasts to erosion and flooding. Modelling wave runup on a beach is possible, but it requires accurate topographic data and model tuning, that can be done comparing observed and modeled runup. In this study we collected aerial photos using an Unmanned Aerial Vehicle after two different swells on the same study area. We merged the point cloud obtained with photogrammetry with multibeam data, in order to obtain a complete beach topography. Then, on each set of rectified and georeferenced UAV orthophotos, we identified the maximum wave runup for both events recognizing the wet area left by the waves. We then used our topography and numerical models to simulate the wave runup and compare the model results to observed values during the two events. Our results highlight the potential of the methodology presented, which integrates UAV platforms, photogrammetry and Geographic Information Systems to provide faster and cheaper information on beach topography and geomorphology compared with traditional techniques without losing in accuracy. We use the results obtained from this technique as a topographic base for a model that calculates runup for the two swells. The observed and modeled runups are consistent, and open new directions for future research.

Simulated Methyl iodide emission and concentration using the ocean biogeochemistry model MPIOM/HAMOCC forced by OMIP data

Production pathways of the prominent volatile organic halogen compound methyl iodide (CH3I) are not fully understood. Based on observations, production of CH3I via photochemical degradation of organic material or via phytoplankton production has been proposed. Additional insights could not be gained from correlations between observed biological and environmental variables or from biogeochemical modeling to identify unambiguously the source of methyl iodide. In this study, we aim to address this question of source mechanisms with a three-dimensional global ocean general circulation model including biogeochemistry (MPIOM-HAMOCC (MPIOM - Max Planck Institute Ocean Model HAMOCC - HAMburg Ocean Carbon Cycle model)) by carrying out a series of sensitivity experiments. The simulated fields are compared with a newly available global data set. Simulated distribution patterns and emissions of CH3I differ largely for the two different production pathways. The evaluation of our model results with observations shows that, on the global scale, observed surface concentrations of CH3I can be best explained by the photochemical production pathway. Our results further emphasize that correlations between CH3I and abiotic or biotic factors do not necessarily provide meaningful insights concerning the source of origin. Overall, we find a net global annual CH3I air-sea flux that ranges between 70 and 260 Gg/yr. On the global scale, the ocean acts as a net source of methyl iodide for the atmosphere, though in some regions in boreal winter, fluxes are of the opposite direction (from the atmosphere to the ocean).

Reflectances transect from coast to open sea, Baltic Sea

In this study, retrievals of the medium resolution imaging spectrometer (MERIS) reflectances and water quality products using 4 different coastal processing algorithms freely available are assessed by comparison against sea-truthing data. The study is based on a pair-wise comparison using processor-dependent quality flags for the retrieval of valid common macro-pixels. This assessment is required in order to ensure the reliability of monitoring systems based on MERIS data, such as the Swedish coastal and lake monitoring system (http.vattenkvalitet.se). The results show that the pre-processing with the Improved Contrast between Ocean and Land (ICOL) processor, correcting for adjacency effects, improve the retrieval of spectral reflectance for all processors, Therefore, it is recommended that the ICOL processor should be applied when Baltic coastal waters are investigated. Chlorophyll was retrieved best using the FUB (Free University of Berlin) processing algorithm, although overestimations in the range 18-26.5%, dependent on the compared pairs, were obtained. At low chlorophyll concentrations (< 2.5 mg/m**3), random errors dominated in the retrievals with the MEGS (MERIS ground segment processor) processor. The lowest bias and random errors were obtained with MEGS for suspended particulate matter, for which overestimations in te range of 8-16% were found. Only the FUB retrieved CDOM (Coloured Dissolved Organic Matter) correlate with in situ values. However, a large systematic underestimation appears in the estimates that nevertheless may be corrected for by using a~local correction factor. The MEGS has the potential to be used as an operational processing algorithm for the Himmerfjärden bay and adjacent areas, but it requires further improvement of the atmospheric correction for the blue bands and better definition at relatively low chlorophyll concentrations in presence of high CDOM attenuation.