Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.240
IF5.240
IF 5-year value: 5.768
IF 5-year
5.768
CiteScore value: 8.9
CiteScore
8.9
SNIP value: 1.713
SNIP1.713
IPP value: 5.53
IPP5.53
SJR value: 3.18
SJR3.18
Scimago H <br class='widget-line-break'>index value: 71
Scimago H
index
71
h5-index value: 51
h5-index51
Preprints
https://doi.org/10.5194/gmd-2020-217
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-217
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model description paper 30 Sep 2020

Submitted as: model description paper | 30 Sep 2020

Review status
This preprint is currently under review for the journal GMD.

OpenIFS@home version 1: a citizen science project for ensemble weather and climate forecasting

Sarah Sparrow1, Andrew Bowery1, Glenn D. Carver2, Marcus O. Köhler2, Pirkka Ollinaho4, Florian Pappenberger2, David Wallom1, and Antje Weisheimer2,3 Sarah Sparrow et al.
  • 1Oxford e-Research Centre, Engineering Science, University of Oxford, UK
  • 2European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK.
  • 3National Centre for Atmospheric Science (NCAS), Atmospheric, Oceanic and Planetary Physics (AOPP), Physics department, University of Oxford, UK
  • 4Finnish Meteorological Institute (FMI), Helsinki, Finland

Abstract. Weather forecasts rely heavily on general circulation models of the atmosphere and other components of the Earth system. National meteorological and hydrological services and intergovernmental organisations, such as the European Centre for Medium-Range Weather Forecasts (ECMWF), provide routine operational forecasts on a range of spatio-temporal scales, by running these models in high resolution on state-of-the-art high-performance computing systems. Such operational forecasts are very demanding in terms of computing resources. To facilitate the use of a weather forecast model for research and training purposes outside the operational environment, ECMWF provides a portable version of its numerical weather forecast model, OpenIFS, for use by universities and other research institutes on their own computing systems.

In this paper, we describe a new project (OpenIFS@home) that combines OpenIFS with a citizen science approach to involve the general public in helping conduct scientific experiments. Volunteers from across the world can run OpenIFS@home on their computers at home and the results of these simulations can be combined into large forecast ensembles. The infrastructure of such distributed computing experiments is based on our experience and expertise with the climateprediction.net and weather@home systems.

In order to validate this first use of OpenIFS in a volunteer computing framework, we present results from ensembles of forecast simulations of tropical cyclone Karl from September 2016, studied during the NAWDEX field campaign. This cyclone underwent extratropical transition and intensified in mid-latitudes to give rise to an intense jet-streak near Scotland and heavy rainfall over Norway. For the validation we use a two thousand member ensemble of OpenIFS run on the OpenIFS@home volunteer framework and a smaller ensemble of the size of operational forecasts using ECMWF’s forecast model in 2016 run on the ECMWF supercomputer with the same horizontal resolution as OpenIFS@home. We present ensemble statistics that illustrate the reliability and accuracy of the OpenIFS@home forecasts as well as discussing the use of large ensembles in the context of forecasting extreme events.

Sarah Sparrow et al.

Interactive discussion

Status: open (until 25 Nov 2020)
Status: open (until 25 Nov 2020)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Sarah Sparrow et al.

Model code and software

Instructions and code for controlling ECMWF OpenIFS application in climateprediction.net (CPDN) Bowery, A. and Carver, G. https://doi.org/10.5281/zenodo.3999557

OpenIFS@home submission xml generation scripts Sparrow, S. https://doi.org/10.5281/zenodo.3999542

OpenIFS@home ancillary file repository scripts Sparrow, S. https://doi.org/10.5281/zenodo.3999551

OpenIFS@home webpages and dashboard Sparrow, S. https://doi.org/10.5281/zenodo.3999555

Code for sorting results uploaded to climatepredcition.net into project, batches and result status Uhe, P. and Sparrow, S. https://doi.org/10.5281/zenodo.3999563

Sarah Sparrow et al.

Viewed

Total article views: 192 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
161 29 2 192 2 1
  • HTML: 161
  • PDF: 29
  • XML: 2
  • Total: 192
  • BibTeX: 2
  • EndNote: 1
Views and downloads (calculated since 30 Sep 2020)
Cumulative views and downloads (calculated since 30 Sep 2020)

Viewed (geographical distribution)

Total article views: 105 (including HTML, PDF, and XML) Thereof 105 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 23 Oct 2020
Publications Copernicus
Download
Short summary
This paper describes how the research version of the European Centre for Medium-Range Weather Forecasts' Integrated Forecast System is combined with climateprediction.net's public volunteer computing resource to develop OpenIFS@home. Thousands of volunteer personal computers simulated slightly different realisations of the tropical storm Karl to demonstrate the performance of the large ensemble forecast. OpenIFS@Home offers researchers a new tool to study weather forecasts and related questions.
This paper describes how the research version of the European Centre for Medium-Range Weather...
Citation