VisMetHack2022: Visualizing winds and surface variables from the ECMWF IFS 1-km nature run
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 acc...
Main Authors: | , , , , |
---|---|
Language: | unknown |
Published: |
2022
|
Subjects: | |
Online Access: | http://www.osti.gov/servlets/purl/1899914 https://www.osti.gov/biblio/1899914 https://doi.org/10.5281/zenodo.6633929 |
id |
ftosti:oai:osti.gov:1899914 |
---|---|
record_format |
openpolar |
spelling |
ftosti:oai:osti.gov:1899914 2023-07-30T04:05:35+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 2022-11-29 application/pdf http://www.osti.gov/servlets/purl/1899914 https://www.osti.gov/biblio/1899914 https://doi.org/10.5281/zenodo.6633929 unknown http://www.osti.gov/servlets/purl/1899914 https://www.osti.gov/biblio/1899914 https://doi.org/10.5281/zenodo.6633929 doi:10.5281/zenodo.6633929 54 ENVIRONMENTAL SCIENCES 2022 ftosti https://doi.org/10.5281/zenodo.6633929 2023-07-11T10:16:24Z 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, and the then outgoing Editor-in-Chief of AGU JAMES commended the project as one of “stunning ambitions,” enabled by computational capacity at scale. 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. Other/Unknown Material North Atlantic SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
institution |
Open Polar |
collection |
SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
op_collection_id |
ftosti |
language |
unknown |
topic |
54 ENVIRONMENTAL SCIENCES |
spellingShingle |
54 ENVIRONMENTAL SCIENCES Anantharaj, Valentine Hatfield, Samuel Vukovic, Milana Polichtchouk, Inna Wedi, Nils VisMetHack2022: Visualizing winds and surface variables from the ECMWF IFS 1-km nature run |
topic_facet |
54 ENVIRONMENTAL SCIENCES |
description |
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, and the then outgoing Editor-in-Chief of AGU JAMES commended the project as one of “stunning ambitions,” enabled by computational capacity at scale. 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. |
author |
Anantharaj, Valentine Hatfield, Samuel Vukovic, Milana Polichtchouk, Inna Wedi, Nils |
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 |
http://www.osti.gov/servlets/purl/1899914 https://www.osti.gov/biblio/1899914 https://doi.org/10.5281/zenodo.6633929 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
http://www.osti.gov/servlets/purl/1899914 https://www.osti.gov/biblio/1899914 https://doi.org/10.5281/zenodo.6633929 doi:10.5281/zenodo.6633929 |
op_doi |
https://doi.org/10.5281/zenodo.6633929 |
_version_ |
1772817581148733440 |