| 1. |
- Faber, Anne Katrine, et al.
(author)
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How does sea ice influence δ18O of Arctic precipitation?
- 2017
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In: Atmospheric Chemistry and Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 17:9, s. 5865-5876
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Journal article (peer-reviewed)abstract
- This study investigates how variations in Arctic sea ice and sea surface conditions influence δ18O of present-day Arctic precipitation. This is done using the model isoCAM3, an isotope-equipped version of the National Center for Atmospheric Research Community Atmosphere Model version 3. Four sensitivity experiments and one control simulation are performed with prescribed sea surface temperature (SST) and sea ice. Each of the four experiments simulates the atmospheric and isotopic response to Arctic oceanic conditions for selected years after the beginning of the satellite era in 1979. Changes in sea ice extent and SSTs have different impacts in Greenland and the rest of the Arctic. The simulated changes in central Arctic sea ice do not influence δ18O of Greenland precipitation, only anomalies of Baffin Bay sea ice. However, this does not exclude the fact that simulations based on other sea ice and sea surface temperature distributions might yield changes in the δ18O of precipitation in Greenland. For the Arctic, δ18O of precipitation and water vapour is sensitive to local changes in sea ice and sea surface temperature and the changes in water vapour are surface based. Reduced sea ice extent yields more enriched isotope values, whereas increased sea ice extent yields more depleted isotope values. The distribution of the sea ice and sea surface conditions is found to be essential for the spatial distribution of the simulated changes in δ18O.
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| 2. |
- Olsen, Jogvan Magnus Haugaard, et al.
(author)
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Dalton Project : A Python platform for molecular- and electronic-structure simulations of complex systems
- 2020
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In: Journal of Chemical Physics. - : AIP Publishing. - 0021-9606 .- 1089-7690. ; 152:21
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Journal article (peer-reviewed)abstract
- The Dalton Project provides a uniform platform access to the underlying full-fledged quantum chemistry codes Dalton and LSDalton as well as the PyFraME package for automatized fragmentation and parameterization of complex molecular environments. The platform is written in Python and defines a means for library communication and interaction. Intermediate data such as integrals are exposed to the platform and made accessible to the user in the form of NumPy arrays, and the resulting data are extracted, analyzed, and visualized. Complex computational protocols that may, for instance, arise due to a need for environment fragmentation and configuration-space sampling of biochemical systems are readily assisted by the platform. The platform is designed to host additional software libraries and will serve as a hub for future modular software development efforts in the distributed Dalton community.
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