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111 Research products, page 1 of 12

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  • Open Access English
    Authors: 
    Romero-Alvarez, Johana; Lupaşcu, Aurelia; Lowe, Douglas; Badia, Alba; Acher-Nicholls, Scott; Dorling, Steve R.; Reeves, Claire E.; Butler, Tim;
    Project: EC | ASIBIA (616938)

    Tropospheric ozone (O3) concentrations depend on a combination of hemispheric, regional, and local-scale processes. Estimates of how much O3 is produced locally vs. transported from further afield are essential in air quality management and regulatory policies. Here, a tagged-ozone mechanism within the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) is used to quantify the contributions to surface O3 in the UK from anthropogenic nitrogen oxide (NOx) emissions from inside and outside the UK during May–August 2015. The contribution of the different source regions to three regulatory O3 metrics is also examined. It is shown that model simulations predict the concentration and spatial distribution of surface O3 with a domain-wide mean bias of −3.7 ppbv. Anthropogenic NOx emissions from the UK and Europe account for 13 % and 16 %, respectively, of the monthly mean surface O3 in the UK, as the majority (71 %) of O3 originates from the hemispheric background. Hemispheric O3 contributes the most to concentrations in the north and the west of the UK with peaks in May, whereas European and UK contributions are most significant in the east, south-east, and London, i.e. the UK's most populated areas, intensifying towards June and July. Moreover, O3 from European sources is generally transported to the UK rather than produced in situ. It is demonstrated that more stringent emission controls over continental Europe, particularly in western Europe, would be necessary to improve the health-related metric MDA8 O3 above 50 and 60 ppbv. Emission controls over larger areas, such as the Northern Hemisphere, are instead required to lessen the impacts on ecosystems as quantified by the AOT40 metric.

  • Research software . 2022
    Open Access English
    Authors: 
    Hassell, David; Gregory, Jonathan; Bartholomew, Sadie L.;
    Publisher: Zenodo
    Project: EC | SEACHANGE (247220), UKRI | Addressing the Grand Chal... (NE/R000727/1), EC | Couplet (786427), EC | IS-ENES2 (312979), EC | IS-ENES3 (824084)

    {"references": ["Hassell, D., Gregory, J., Blower, J., Lawrence, B. N., and Taylor, K. E.: A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1), Geosci. Model Dev., 10, 4619\u20134646, https://doi.org/10.5194/gmd-10-4619-2017, 2017.", "Hassell et al., (2020). cfdm: A Python reference implementation of the CF data model. Journal of Open Source Software, 5(54), 2717, https://doi.org/10.21105/joss.02717"]} A CF-compliant Earth Science data analysis library

  • Research software . 2022
    Open Access English
    Authors: 
    Hassell, David; Gregory, Jonathan; Bartholomew, Sadie L.;
    Publisher: Zenodo
    Project: EC | IS-ENES2 (312979), EC | SEACHANGE (247220), UKRI | Addressing the Grand Chal... (NE/R000727/1), EC | Couplet (786427), EC | IS-ENES3 (824084)

    A CF-compliant Earth Science data analysis library

  • Research software . 2022
    Open Access English
    Authors: 
    Hassell, David; Gregory, Jonathan; Bartholomew, Sadie L.;
    Publisher: Zenodo
    Project: EC | IS-ENES3 (824084), EC | SEACHANGE (247220), UKRI | Addressing the Grand Chal... (NE/R000727/1), EC | Couplet (786427), EC | IS-ENES2 (312979)

    A CF-compliant Earth Science data analysis library

  • Research software . 2021
    Open Access English
    Authors: 
    Hassell, David; Gregory, Jonathan;
    Publisher: Zenodo
    Project: EC | SEACHANGE (247220), UKRI | Addressing the Grand Chal... (NE/R000727/1), EC | Couplet (786427), EC | IS-ENES2 (312979), EC | IS-ENES3 (824084)

    A CF-compliant Earth Science data analysis library

  • Open Access English
    Authors: 
    Hassell, David; Bartholomew, Sadie L.;
    Publisher: Zenodo
    Project: EC | SEACHANGE (247220), UKRI | Addressing the Grand Chal... (NE/R000727/1), EC | Couplet (786427), EC | IS-ENES2 (312979), EC | IS-ENES3 (824084)

    A Python reference implementation of the CF data model.

  • Open Access
    Authors: 
    Giorgio Dall'Olmo; Francesco Nencioli; Thomas Jackson; Robert J. W. Brewin; John A. Gittings; Dionysios E. Raitsos;
    Publisher: Zenodo
    Project: UKRI | NCEO Carbon Cycle (earth010003), EC | AtlantECO (862923)

    Set of examples to demonstrate how to use OLTraj to implement Lagrangian analyses.

  • Open Access
    Authors: 
    Thomas, Simon Donald Alistair;
    Project: UKRI | The North Atlantic Climat... (NE/N018028/1), EC | WAPITI (637770), UKRI | INSPIRE: Interdisciplinar... (NE/S007210/1), UKRI | UKRI Centre for Doctoral ... (EP/S022961/1)

    Documentation: https://so-fronts.readthedocs.io/en/latest/ Paper: https://doi.org/10.5194/os-17-1545-2021 Preprint: https://doi.org/10.5194/os-2021-40 Presentation at AGU2021: https://doi.org/10.1002/essoar.10507114.1 Change-log: Improved the geographical plot of hard clustering vs. I-metric (Figure 4 in the paper). Changed velocity comparison from 135m to 2m depth (lowers correlation with Sobel edge detection method slightly). Made README.md more readable. Added new plots to visualise the preprocessing steps: Mean and standard deviation of profiles from the sample. Principal components in terms of their effect on the vertical profiles. Short description In the Southern Ocean, fronts delineate water masses, which correspond to upwelling and downwelling branches of the overturning circulation. Classically, oceanographers define Southern Ocean fronts as a small number of continuous linear features that encircle Antarctica. However, modern observational and theoretical developments are challenging this traditional framework to accommodate more localized views of fronts [Chapman et al. 2020]. Here we present code for implementing two related methods for calculating fronts from oceanographic data. The first method uses unsupervised classification (specifically, Gaussian Mixture Modeling or GMM) and a novel interclass metric to define fronts. This approach produces a discontinuous, probabilistic view of front location, emphasising the fact that the boundaries between water masses are not uniformly sharp across the entire Southern Ocean. The second method uses Sobel edge detection to highlight rapid changes [Hjelmervik & Hjelmervik, 2019]. This approach produces a more local view of fronts, with the advantage that it can highlight the movement of individual eddy-like features (such as the Agulhas rings). Chapman, C. C., Lea, M.-A., Meyer, A., Sallee, J.-B. & Hindell, M. Defining Southern Ocean fronts and their influence on biological and physical processes in a changing climate. Nature Climate Change (2020). https://doi.org/10.1038/s41558-020-0705-4 Maze, G. et al. Coherent heat patterns revealed by unsupervised classification of Argo temperature profiles in the North Atlantic Ocean. Progress in Oceanography (2017). https://doi.org/10.1016/j.pocean.2016.12.008, https://doi.org/10.5281/zenodo.3906236 Hjelmervik, K. B. & Hjelmervik, K. T. Detection of oceanographic fronts on variable water depths using empirical orthogonal functions. IEEE Journal of Oceanic Engineering (2019). https://doi.org/10.1109/JOE.2019.2917456 If you use this software, please cite it as below.

  • Open Access
    Authors: 
    Simon D.A. Thomas;
    Publisher: Zenodo
    Project: UKRI | INSPIRE: Interdisciplinar... (NE/S007210/1), UKRI | The North Atlantic Climat... (NE/N018028/1), UKRI | UKRI Centre for Doctoral ... (EP/S022961/1), EC | WAPITI (637770)

    This version includes higher quality animations of the i-metric over the time period. The documentation is available at: https://so-fronts.readthedocs.io/ Code available here: https://github.com/so-wise/so-fronts Paper: https://doi.org/10.5194/os-17-1545-2021 Preprint: https://doi.org/10.5194/os-2021-40

  • Open Access English
    Authors: 
    Vries, Joost; Monteiro, Fanny; Wheeler, Glen; Poulton, Alex; Godrijan, Jelena; Cerino, Federica; Malinverno, Elisa; Langer, Gerald; Brownlee, Colin;
    Project: UKRI | GW4+ - a consortium of ex... (NE/L002434/1), UKRI | NSFGEO-NERC An unexpected... (NE/N011708/1), MZOS | Mechanism of long-term ch... (098-0982705-2731), EC | MEDSEA (265103), EC | SEACELLS (670390)

    Coccolithophores are globally important marine calcifying phytoplankton that utilize a haplo-diplontic life cycle. The haplo-diplontic life cycle allows coccolithophores to divide in both life cycle phases and potentially expands coccolithophore niche volume. Research has, however, to date largely overlooked the life cycle of coccolithophores and has instead focused on the diploid life cycle phase of coccolithophores. Through the synthesis and analysis of global scanning electron microscopy (SEM) coccolithophore abundance data (n=2534), we find that calcified haploid coccolithophores generally constitute a minor component of the total coccolithophore abundance (≈ 2 %–15 % depending on season). However, using case studies in the Atlantic Ocean and Mediterranean Sea, we show that, depending on environmental conditions, calcifying haploid coccolithophores can be significant contributors to the coccolithophore standing stock (up to ≈30 %). Furthermore, using hypervolumes to quantify the niche of coccolithophores, we illustrate that the haploid and diploid life cycle phases inhabit contrasting niches and that on average this allows coccolithophores to expand their niche by ≈18.8 %, with a range of 3 %–76 % for individual species. Our results highlight that future coccolithophore research should consider both life cycle stages, as omission of the haploid life cycle phase in current research limits our understanding of coccolithophore ecology. Our results furthermore suggest a different response to nutrient limitation and stratification, which may be of relevance for further climate scenarios. Our compilation highlights the spatial and temporal sparsity of SEM measurements and the need for new molecular techniques to identify uncalcified haploid coccolithophores. Our work also emphasizes the need for further work on the carbonate chemistry niche of the coccolithophore life cycle.

Advanced search in Research products
Research products
arrow_drop_down
Searching FieldsTerms
Any field
arrow_drop_down
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Include:
The following results are related to European Marine Science. Are you interested to view more results? Visit OpenAIRE - Explore.
111 Research products, page 1 of 12
  • Open Access English
    Authors: 
    Romero-Alvarez, Johana; Lupaşcu, Aurelia; Lowe, Douglas; Badia, Alba; Acher-Nicholls, Scott; Dorling, Steve R.; Reeves, Claire E.; Butler, Tim;
    Project: EC | ASIBIA (616938)

    Tropospheric ozone (O3) concentrations depend on a combination of hemispheric, regional, and local-scale processes. Estimates of how much O3 is produced locally vs. transported from further afield are essential in air quality management and regulatory policies. Here, a tagged-ozone mechanism within the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) is used to quantify the contributions to surface O3 in the UK from anthropogenic nitrogen oxide (NOx) emissions from inside and outside the UK during May–August 2015. The contribution of the different source regions to three regulatory O3 metrics is also examined. It is shown that model simulations predict the concentration and spatial distribution of surface O3 with a domain-wide mean bias of −3.7 ppbv. Anthropogenic NOx emissions from the UK and Europe account for 13 % and 16 %, respectively, of the monthly mean surface O3 in the UK, as the majority (71 %) of O3 originates from the hemispheric background. Hemispheric O3 contributes the most to concentrations in the north and the west of the UK with peaks in May, whereas European and UK contributions are most significant in the east, south-east, and London, i.e. the UK's most populated areas, intensifying towards June and July. Moreover, O3 from European sources is generally transported to the UK rather than produced in situ. It is demonstrated that more stringent emission controls over continental Europe, particularly in western Europe, would be necessary to improve the health-related metric MDA8 O3 above 50 and 60 ppbv. Emission controls over larger areas, such as the Northern Hemisphere, are instead required to lessen the impacts on ecosystems as quantified by the AOT40 metric.

  • Research software . 2022
    Open Access English
    Authors: 
    Hassell, David; Gregory, Jonathan; Bartholomew, Sadie L.;
    Publisher: Zenodo
    Project: EC | SEACHANGE (247220), UKRI | Addressing the Grand Chal... (NE/R000727/1), EC | Couplet (786427), EC | IS-ENES2 (312979), EC | IS-ENES3 (824084)

    {"references": ["Hassell, D., Gregory, J., Blower, J., Lawrence, B. N., and Taylor, K. E.: A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1), Geosci. Model Dev., 10, 4619\u20134646, https://doi.org/10.5194/gmd-10-4619-2017, 2017.", "Hassell et al., (2020). cfdm: A Python reference implementation of the CF data model. Journal of Open Source Software, 5(54), 2717, https://doi.org/10.21105/joss.02717"]} A CF-compliant Earth Science data analysis library

  • Research software . 2022
    Open Access English
    Authors: 
    Hassell, David; Gregory, Jonathan; Bartholomew, Sadie L.;
    Publisher: Zenodo
    Project: EC | IS-ENES2 (312979), EC | SEACHANGE (247220), UKRI | Addressing the Grand Chal... (NE/R000727/1), EC | Couplet (786427), EC | IS-ENES3 (824084)

    A CF-compliant Earth Science data analysis library

  • Research software . 2022
    Open Access English
    Authors: 
    Hassell, David; Gregory, Jonathan; Bartholomew, Sadie L.;
    Publisher: Zenodo
    Project: EC | IS-ENES3 (824084), EC | SEACHANGE (247220), UKRI | Addressing the Grand Chal... (NE/R000727/1), EC | Couplet (786427), EC | IS-ENES2 (312979)

    A CF-compliant Earth Science data analysis library

  • Research software . 2021
    Open Access English
    Authors: 
    Hassell, David; Gregory, Jonathan;
    Publisher: Zenodo
    Project: EC | SEACHANGE (247220), UKRI | Addressing the Grand Chal... (NE/R000727/1), EC | Couplet (786427), EC | IS-ENES2 (312979), EC | IS-ENES3 (824084)

    A CF-compliant Earth Science data analysis library

  • Open Access English
    Authors: 
    Hassell, David; Bartholomew, Sadie L.;
    Publisher: Zenodo
    Project: EC | SEACHANGE (247220), UKRI | Addressing the Grand Chal... (NE/R000727/1), EC | Couplet (786427), EC | IS-ENES2 (312979), EC | IS-ENES3 (824084)

    A Python reference implementation of the CF data model.

  • Open Access
    Authors: 
    Giorgio Dall'Olmo; Francesco Nencioli; Thomas Jackson; Robert J. W. Brewin; John A. Gittings; Dionysios E. Raitsos;
    Publisher: Zenodo
    Project: UKRI | NCEO Carbon Cycle (earth010003), EC | AtlantECO (862923)

    Set of examples to demonstrate how to use OLTraj to implement Lagrangian analyses.

  • Open Access
    Authors: 
    Thomas, Simon Donald Alistair;
    Project: UKRI | The North Atlantic Climat... (NE/N018028/1), EC | WAPITI (637770), UKRI | INSPIRE: Interdisciplinar... (NE/S007210/1), UKRI | UKRI Centre for Doctoral ... (EP/S022961/1)

    Documentation: https://so-fronts.readthedocs.io/en/latest/ Paper: https://doi.org/10.5194/os-17-1545-2021 Preprint: https://doi.org/10.5194/os-2021-40 Presentation at AGU2021: https://doi.org/10.1002/essoar.10507114.1 Change-log: Improved the geographical plot of hard clustering vs. I-metric (Figure 4 in the paper). Changed velocity comparison from 135m to 2m depth (lowers correlation with Sobel edge detection method slightly). Made README.md more readable. Added new plots to visualise the preprocessing steps: Mean and standard deviation of profiles from the sample. Principal components in terms of their effect on the vertical profiles. Short description In the Southern Ocean, fronts delineate water masses, which correspond to upwelling and downwelling branches of the overturning circulation. Classically, oceanographers define Southern Ocean fronts as a small number of continuous linear features that encircle Antarctica. However, modern observational and theoretical developments are challenging this traditional framework to accommodate more localized views of fronts [Chapman et al. 2020]. Here we present code for implementing two related methods for calculating fronts from oceanographic data. The first method uses unsupervised classification (specifically, Gaussian Mixture Modeling or GMM) and a novel interclass metric to define fronts. This approach produces a discontinuous, probabilistic view of front location, emphasising the fact that the boundaries between water masses are not uniformly sharp across the entire Southern Ocean. The second method uses Sobel edge detection to highlight rapid changes [Hjelmervik & Hjelmervik, 2019]. This approach produces a more local view of fronts, with the advantage that it can highlight the movement of individual eddy-like features (such as the Agulhas rings). Chapman, C. C., Lea, M.-A., Meyer, A., Sallee, J.-B. & Hindell, M. Defining Southern Ocean fronts and their influence on biological and physical processes in a changing climate. Nature Climate Change (2020). https://doi.org/10.1038/s41558-020-0705-4 Maze, G. et al. Coherent heat patterns revealed by unsupervised classification of Argo temperature profiles in the North Atlantic Ocean. Progress in Oceanography (2017). https://doi.org/10.1016/j.pocean.2016.12.008, https://doi.org/10.5281/zenodo.3906236 Hjelmervik, K. B. & Hjelmervik, K. T. Detection of oceanographic fronts on variable water depths using empirical orthogonal functions. IEEE Journal of Oceanic Engineering (2019). https://doi.org/10.1109/JOE.2019.2917456 If you use this software, please cite it as below.

  • Open Access
    Authors: 
    Simon D.A. Thomas;
    Publisher: Zenodo
    Project: UKRI | INSPIRE: Interdisciplinar... (NE/S007210/1), UKRI | The North Atlantic Climat... (NE/N018028/1), UKRI | UKRI Centre for Doctoral ... (EP/S022961/1), EC | WAPITI (637770)

    This version includes higher quality animations of the i-metric over the time period. The documentation is available at: https://so-fronts.readthedocs.io/ Code available here: https://github.com/so-wise/so-fronts Paper: https://doi.org/10.5194/os-17-1545-2021 Preprint: https://doi.org/10.5194/os-2021-40

  • Open Access English
    Authors: 
    Vries, Joost; Monteiro, Fanny; Wheeler, Glen; Poulton, Alex; Godrijan, Jelena; Cerino, Federica; Malinverno, Elisa; Langer, Gerald; Brownlee, Colin;
    Project: UKRI | GW4+ - a consortium of ex... (NE/L002434/1), UKRI | NSFGEO-NERC An unexpected... (NE/N011708/1), MZOS | Mechanism of long-term ch... (098-0982705-2731), EC | MEDSEA (265103), EC | SEACELLS (670390)

    Coccolithophores are globally important marine calcifying phytoplankton that utilize a haplo-diplontic life cycle. The haplo-diplontic life cycle allows coccolithophores to divide in both life cycle phases and potentially expands coccolithophore niche volume. Research has, however, to date largely overlooked the life cycle of coccolithophores and has instead focused on the diploid life cycle phase of coccolithophores. Through the synthesis and analysis of global scanning electron microscopy (SEM) coccolithophore abundance data (n=2534), we find that calcified haploid coccolithophores generally constitute a minor component of the total coccolithophore abundance (≈ 2 %–15 % depending on season). However, using case studies in the Atlantic Ocean and Mediterranean Sea, we show that, depending on environmental conditions, calcifying haploid coccolithophores can be significant contributors to the coccolithophore standing stock (up to ≈30 %). Furthermore, using hypervolumes to quantify the niche of coccolithophores, we illustrate that the haploid and diploid life cycle phases inhabit contrasting niches and that on average this allows coccolithophores to expand their niche by ≈18.8 %, with a range of 3 %–76 % for individual species. Our results highlight that future coccolithophore research should consider both life cycle stages, as omission of the haploid life cycle phase in current research limits our understanding of coccolithophore ecology. Our results furthermore suggest a different response to nutrient limitation and stratification, which may be of relevance for further climate scenarios. Our compilation highlights the spatial and temporal sparsity of SEM measurements and the need for new molecular techniques to identify uncalcified haploid coccolithophores. Our work also emphasizes the need for further work on the carbonate chemistry niche of the coccolithophore life cycle.