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Accompanying material, text, data and figures for the article de Vargas et al., 'Eukaryotic plankton diversity in the sunlit ocean', Science 348, 1261605 (2015), doi: 10.1126/science.1261605

This paper aims to stimulate discussion based on the experiences derived from the QUICS project (Quantifying Uncertainty in Integrated Catchment Studies). First it briefly discusses the current state of knowledge on uncertainties in sub-models of integrated catchment models and the existing frameworks for analysing uncertainty. Furthermore, it compares the relative approaches of both building and calibrating fully integrated models or linking separate sub-models. It also discusses the implications of model linkage on overall uncertainty and how to define an acceptable level of model complexity. This discussion includes, whether we should shift our attention from uncertainties due to linkage, when using linked models, to uncertainties in model structure by necessary simplification or by using more parameters. This discussion attempts to address the question as to whether there is an increase in uncertainty by linking these models or if a compensation effect could take place and that overall uncertainty in key water quality parameters actually decreases. Finally, challenges in the application of uncertainty analysis in integrated catchment water quality modelling, as encountered in this project, are discussed and recommendations for future research areas are highlighted.

This repository provides the code and data for the study "Drivers of Surface Ocean Acidity Extremes in an Earth System Model". The GFDL ESM2M model data is only provided in preprocessed form (see subdirectory 'scripts_used_for_model_data_preprocessing'), because the file size of the raw model output is too large to be uploaded. The preprocessed data is stored in the subdirectory 'data'. To access the raw ESM2M model data, please contact me (friedrich.burger@unibe.ch). The results of the study can be reproduced by running the respective Python scripts in the analysis_scripts subdirectories.

The workshop “Strategy towards JERICO-NEXT” took place on April 30, 2015, in Brest, as a closure for the JERICO(FP7) project and a bridge towards JERICO-NEXT (H2020). The workshop focused on four topical round tables addressing key issues for the JERICO RI long-term sustainability in the context of European Strategies. It aimed at initiating an appropriate coordination between JERICO-NEXT and relevant European organizations, to be followed up during the JERICO-NEXT project

The Surface Mass Balance (SMB) can be seen, in first approximation, as the water mass gained by the winter snowfall accumulation minus the mass lost by the meltwater run-off in summer. The mass gain from rainfall as well as the mass loss from erosion from the net water fluxes (the sum of the evaporation, sublimation, deposition and condensation) and from the wind (blowing snow) are negligible in the SMB equation of the Greenland Ice Sheet (GrIS) compared to the snowfall and the melt (Box et al., 2004). The ice sheet mass balance takes also into account the mass loss from iceberg calving. Consequences of a warmer climate on the Greenland ice sheet SMB will be a thickening inland, due to increased solid precipitation, and a thinning at the Greenland ice sheet periphery, due to an increasing surface melt. A climatic warming increases the snow and ice melting in summer but it enhances also evaporation above the ocean. This leads to higher moisture transport inland and, consequently, higher precipitation. The response of the iceberg calving to the climate change could be an acceleration of the glacier flow (Nick et al., 2009; Zwally et al., 2002) but these projections are very uncertain (Sundal et al., 2011) and a lot of developments are still needed in the glaciology models for improving our knowledge and modelling of the Greenland ice sheet dynamics. That is why we will focus our study only on the SMB of the Greenland ice sheet. The IPCC (Intergovernmental Panel on Climate Change) projects, in response to global warming induced by human activities, that the run-off increase will exceed the precipitation increase and therefore that the currently observed surface melting of the Greenland ice sheet (Fettweis et al., 2011b; Tedesco et al., 2011; Van den Broeke et al., 2009) will continue and intensify during the next decades (IPCC, 2007). An increasing freshwater flux from the Greenland ice sheet melting could perturb the thermohaline circulation (by reducing the density contrast driving this last one) in the North Atlantic including the drift which tempers the European climate. In addition, an enduring Greenland ice sheet melting, combined with the thermal expansion of the oceans and the melt of continental glaciers, will raise the sea level with well-known consequences for countries such as the Netherlands, Bangladesh,... The contribution of the Greenland ice sheet SMB decrease to the sea level rise is currently evaluated to be 5-10 cm by 2100 (Gregory and Huybrechts, 2006; Fettweis et al., Estimation of the Sea Level Rise by 2100 Resulting from Changes in the Surface Mass Balance of the Greenland Ice Sheet 25

Abstract. Ocean color remote sensing offers two decades-long time series of information on phytoplankton abundance. However, determining the structure of the phytoplankton community from this signal is not straightforward, and many uncertainties remain to be evaluated, despite multiple intercomparison efforts of the different available algorithms. Here, we use remote sensing and machine learning to infer the abundance of seven phytoplankton groups at a global scale based on a new molecular method from Tara Oceans. Our dataset is to our knowledge the most comprehensive and complete, available to describe phytoplankton community structure at a global scale using a molecular marker that defines relative abundances of all phytoplankton groups simultaneously. The methodology shows satisfying performances to provide robust estimates of phytoplankton groups using satellite data, with few limitations regarding the global generalization of the method. Furthermore, this new satellite-based methodology allows a valuable global intercomparison with the pigment-based approach used in in-situ and satellite data to identify phytoplankton groups. Nevertheless, these datasets show different, yet coherent information on the phytoplankton, valuable for the understanding of community structure. This makes remote sensing observations excellent tools to collect Essential Biodiversity Variables and provide a foundation for developing marine biodiversity forecasts.

AbstractA deep-water approximation of the Stokes drift velocity profile is explored as an alternative to the monochromatic profile. The alternative profile investigated relies on the same two quantities required for the monochromatic profile, namely, the Stokes transport and the surface Stokes drift velocity. Comparisons with parametric spectra and profiles under wave spectra from the Interim ECMWF Re-Analysis (ERA-Interim) and buoy observations reveal much better agreement than the monochromatic profile even for complex sea states. That the profile gives a closer match and a more correct shear has implications for ocean circulation models since the Coriolis–Stokes force depends on the magnitude and direction of the Stokes drift profile, and Langmuir turbulence parameterizations depend sensitively on the shear of the profile. The alternative profile comes at no added numerical cost compared to the monochromatic profile.