Suchergebnisse

This is the final version. Available on open access from the European Geosciences Union via the DOI in this record ; Code availability: S2P3Rv2.0 is available on GitHub: https://github.com/PaulHalloran/S2P3Rv2.0 (last access: 21 September 2021). The release associated with this paper (https://github.com/PaulHalloran/S2P3Rv2.0/releases/tag/v1.0.1, last access: 21 September 2021) has been archived on Zenodo with the following DOI: https://doi.org/10.5281/zenodo.4147559 (Halloran, 2020a). The readme file available on GitHub or via the DOI link provides step-by-step instructions for how to install, set up and run the model, and it provides a basic script for analysing the model output. At the bottom of the readme, a worked example is provided to help the user go through the full process from generating model forcing files, running the model and displaying the output with some example data. ; Data availability: The model minus satellite SST data from the global (65∘ S–65∘ N) simulation averaged between 2006 and 2016, from which the global validation has been undertaken in this paper, is archived as NetCDF and csv files to allow potential users to undertake bespoke assessment of the model http://doi.org/10.5281/zenodo.4018815 (Halloran, 2020b). ; The marine impacts of climate change on our societies will be largely felt through coastal waters and shelf seas. These impacts involve sectors as diverse as tourism, fisheries and energy production. Projections of future marine climate change come from global models. Modelling at the global scale is required to capture the feedbacks and large-scale transport of physical properties such as heat, which occur within the climate system, but global models currently cannot provide detail in the shelf seas. Version 2 of the regional implementation of the Shelf Sea Physics and Primary Production (S2P3-R v2.0) model bridges the gap between global projections and local shelf-sea impacts. S2P3-R v2.0 is a highly simplified coastal shelf model, computationally efficient enough to be run across the shelf seas of the whole globe. Despite the simplified nature of the model, it can display regional skill comparable to state-of-the-art models, and at the scale of the global (excluding high latitudes) shelf seas it can explain >50 % of the interannual sea surface temperature (SST) variability in ∼60 % of grid cells and >80 % of interannual variability in ∼20 % of grid cells. The model can be run at any resolution for which the input data can be supplied, without expert technical knowledge, and using a modest off-the-shelf computer. The accessibility of S2P3-R v2.0 places it within reach of an array of coastal managers and policy makers, allowing it to be run routinely once set up and evaluated for a region under expert guidance. The computational efficiency and relative scientific simplicity of the tool make it ideally suited to educational applications. S2P3-R v2.0 is set up to be driven directly with output from reanalysis products or daily atmospheric output from climate models such as those which contribute to the sixth phase of the Climate Model Intercomparison Project, making it a valuable tool for semi-dynamical downscaling of climate projections. The updates introduced into version 2.0 of this model are primarily focused around the ability to geographical relocate the model, model usability and speed but also scientific improvements. The value of this model comes from its computational efficiency, which necessitates simplicity. This simplicity leads to several limitations, which are discussed in the context of evaluation at regional and global scales. ; Natural Environment Research Council (NERC) ; European Union Horizon 2020 ; NOAA

This is the final version. Available on open access from nature Research via the DOI in this record ; Size is a fundamental cellular trait that is important in determining phytoplankton physiological and ecological processes. Fossil coccospheres, the external calcite structure produced by the excretion of interlocking plates by the phytoplankton coccolithophores, can provide a rare window into cell size in the past. Coccospheres are delicate however and are therefore poorly preserved in sediment. We demonstrate a novel technique combining imaging flow cytometry and cross-polarised light (ISX+PL) to rapidly and reliably visually isolate and quantify the morphological characteristics of coccospheres from marine sediment by exploiting their unique optical and morphological properties. Imaging flow cytometry combines the morphological information provided by microscopy with high sample numbers associated with flow cytometry. High throughput imaging overcomes the constraints of labour-intensive manual microscopy and allows statistically robust analysis of morphological features and coccosphere concentration despite low coccosphere concentrations in sediments. Applying this technique to the fine-fraction of sediments, hundreds of coccospheres can be visually isolated quickly with minimal sample preparation. This approach has the potential to enable rapid processing of down-core sediment records and/or high spatial coverage from surface sediments and may prove valuable in investigating the interplay between climate change and coccolithophore physiological/ecological response. ; Natural Environment Research Council (NERC) ; Shell Research Ltd ; European Union Horizon 2020

This is the final version of the article. Available from EGU via the DOI in this record. ; During the fifth phase of the Coupled Model Intercomparison Project (CMIP5) substantial efforts were made to systematically assess the skill of Earth system models. One goal was to check how realistically representative marine biogeochemical tracer distributions could be reproduced by models. In routine assessments model historical hindcasts were compared with available modern biogeochemical observations. However, these assessments considered neither how close modeled biogeochemical reservoirs were to equilibrium nor the sensitivity of model performance to initial conditions or to the spin-up protocols. Here, we explore how the large diversity in spin-up protocols used for marine biogeochemistry in CMIP5 Earth system models (ESMs) contributes to model-to-model differences in the simulated fields. We take advantage of a 500-year spin-up simulation of IPSL-CM5A-LR to quantify the influence of the spin-up protocol on model ability to reproduce relevant data fields. Amplification of biases in selected biogeochemical fields (O2, NO3, Alk-DIC) is assessed as a function of spin-up duration. We demonstrate that a relationship between spin-up duration and assessment metrics emerges from our model results and holds when confronted with a larger ensemble of CMIP5 models. This shows that drift has implications for performance assessment in addition to possibly aliasing estimates of climate change impact. Our study suggests that differences in spin-up protocols could explain a substantial part of model disparities, constituting a source of model-to-model uncertainty. This requires more attention in future model intercomparison exercises in order to provide quantitatively more correct ESM results on marine biogeochemistry and carbon cycle feedbacks. ; We sincerely thank I. Kriest, F. Joos, the anonymous reviewer and A. Yool for their useful comments on this paper. This work was supported by H2020 project CRESCENDO "Coordinated Research in Earth Systems and Climate: Experiments, kNowledge, Dissemination and Outreach", which received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 641816 and by the EU FP7 project CARBOCHANGE "Changes in carbon uptake and emissions by oceans in a changing climate" which received funding from the European community's Seventh Framework Programme under grant agreement no. 264879. Supercomputing time was provided by GENCI (Grand Equipement National de Calcul Intensif) at CCRT (Centre de Calcul Recherche et Technologie), allocation 016178. Finally, we are grateful to the ESGF project which makes data available for all the community. Roland Séférian is grateful to Aurélien Ribes for his kind advices on statistics. Jerry Tjiputra acknowledges ORGANIC project (239965/F20) funded by the Research Council of Norway. Christoph Heinze and Jerry Tjiputra are grateful for support through project EVA – Earth system modelling of climate variations in the Anthropocene (229771/E10) funded by the Research Council of Norway, as well as CPU-time and mass storage provided through NOTUR project NN2345K as well as NorStore project NS2345K. Keith Lindsay and Scott C. Doney acknowledge support from the National Science Foundation.