VisMetHack2022: Visualizing winds and surface variables from the ECMWF IFS 1-km nature run
Overview This data collection was contributed to the Visualisation Hackathon 2022 (#VisMetHack2022), in conjunction with the Using ECMWF's Forecasts (UEF2022) workshop. The European Center for Medium-Range Weather Forecasts (ECMWF) and the Oak Ridge National Laboratory (ORNL) are pleased to ann...
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ftzenodo:oai:zenodo.org:6633929 2023-05-15T17:32:01+02:00 VisMetHack2022: Visualizing winds and surface variables from the ECMWF IFS 1-km nature run Anantharaj, Valentine Hatfield, Samuel Vukovic, Milana Polichtchouk, Inna Wedi, Nils 2022-06-11 https://zenodo.org/record/6633929 https://doi.org/10.5281/zenodo.6633929 eng eng doi:10.5281/zenodo.6633928 https://zenodo.org/record/6633929 https://doi.org/10.5281/zenodo.6633929 oai:zenodo.org:6633929 info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode info:eu-repo/semantics/other dataset 2022 ftzenodo https://doi.org/10.5281/zenodo.663392910.5281/zenodo.6633928 2023-03-11T03:47:58Z Overview This data collection was contributed to the Visualisation Hackathon 2022 (#VisMetHack2022), in conjunction with the Using ECMWF's Forecasts (UEF2022) workshop. The European Center for Medium-Range Weather Forecasts (ECMWF) and the Oak Ridge National Laboratory (ORNL) are pleased to announce access to the data collection from global 1-km nature run (NR) simulations using the Integrated Forecast System (IFS) with explicit convection. We invite you to join us in exploring this precursor to a digital twin of the earth! The NR simulations reveal unprecedented detail of the earth’s atmosphere [1], and the then outgoing Editor-in-Chief of AGU JAMES commended the project as one of “stunning ambitions,” enabled by computational capacity at scale [2]. The project also won the 2020 HPCwire Readers Choice Award for Best Use of HPC in Physical Sciences. A set of two NR seasonal simulations have been completed, one corresponding to the northern hemispheric winter months (NDJF) and the other for the North Atlantic tropical cyclone season (ASO). The project used the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF). The simulations were facilitated with an INCITE award from the US Department of Energy Office of Science. For the first seasonal run of four months (NDJF), the hydrostatic IFS model was initialized at 00Z on 1 November 2018. The NR for the TC season (AS) was initialized at 00Z on 1 August 2019. The NR simulations were constrained only by sea surface temperatures (SST) at the lower boundary. The IFS output was saved every 3 hours. After feedback and interest from the scientific community, the simulations were rerun for four specific extreme events, with output every 15 minutes. The special cases include a tropical cycle and three severe storm events over the continental USA. NR Data for visualizing winds A small subset from the 1-km IFS NR collection is make available for #VisMetHack22. This subset is extracted from the tropical cyclone area in the North Atlantic from the ASO ... Dataset North Atlantic Zenodo |
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English |
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Overview This data collection was contributed to the Visualisation Hackathon 2022 (#VisMetHack2022), in conjunction with the Using ECMWF's Forecasts (UEF2022) workshop. The European Center for Medium-Range Weather Forecasts (ECMWF) and the Oak Ridge National Laboratory (ORNL) are pleased to announce access to the data collection from global 1-km nature run (NR) simulations using the Integrated Forecast System (IFS) with explicit convection. We invite you to join us in exploring this precursor to a digital twin of the earth! The NR simulations reveal unprecedented detail of the earth’s atmosphere [1], and the then outgoing Editor-in-Chief of AGU JAMES commended the project as one of “stunning ambitions,” enabled by computational capacity at scale [2]. The project also won the 2020 HPCwire Readers Choice Award for Best Use of HPC in Physical Sciences. A set of two NR seasonal simulations have been completed, one corresponding to the northern hemispheric winter months (NDJF) and the other for the North Atlantic tropical cyclone season (ASO). The project used the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF). The simulations were facilitated with an INCITE award from the US Department of Energy Office of Science. For the first seasonal run of four months (NDJF), the hydrostatic IFS model was initialized at 00Z on 1 November 2018. The NR for the TC season (AS) was initialized at 00Z on 1 August 2019. The NR simulations were constrained only by sea surface temperatures (SST) at the lower boundary. The IFS output was saved every 3 hours. After feedback and interest from the scientific community, the simulations were rerun for four specific extreme events, with output every 15 minutes. The special cases include a tropical cycle and three severe storm events over the continental USA. NR Data for visualizing winds A small subset from the 1-km IFS NR collection is make available for #VisMetHack22. This subset is extracted from the tropical cyclone area in the North Atlantic from the ASO ... |
format |
Dataset |
author |
Anantharaj, Valentine Hatfield, Samuel Vukovic, Milana Polichtchouk, Inna Wedi, Nils |
spellingShingle |
Anantharaj, Valentine Hatfield, Samuel Vukovic, Milana Polichtchouk, Inna Wedi, Nils VisMetHack2022: Visualizing winds and surface variables from the ECMWF IFS 1-km nature run |
author_facet |
Anantharaj, Valentine Hatfield, Samuel Vukovic, Milana Polichtchouk, Inna Wedi, Nils |
author_sort |
Anantharaj, Valentine |
title |
VisMetHack2022: Visualizing winds and surface variables from the ECMWF IFS 1-km nature run |
title_short |
VisMetHack2022: Visualizing winds and surface variables from the ECMWF IFS 1-km nature run |
title_full |
VisMetHack2022: Visualizing winds and surface variables from the ECMWF IFS 1-km nature run |
title_fullStr |
VisMetHack2022: Visualizing winds and surface variables from the ECMWF IFS 1-km nature run |
title_full_unstemmed |
VisMetHack2022: Visualizing winds and surface variables from the ECMWF IFS 1-km nature run |
title_sort |
vismethack2022: visualizing winds and surface variables from the ecmwf ifs 1-km nature run |
publishDate |
2022 |
url |
https://zenodo.org/record/6633929 https://doi.org/10.5281/zenodo.6633929 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
doi:10.5281/zenodo.6633928 https://zenodo.org/record/6633929 https://doi.org/10.5281/zenodo.6633929 oai:zenodo.org:6633929 |
op_rights |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode |
op_doi |
https://doi.org/10.5281/zenodo.663392910.5281/zenodo.6633928 |
_version_ |
1766129924090888192 |