Submitted as: model description paper 30 Sep 2020

Submitted as: model description paper | 30 Sep 2020

Review status: a revised version of this preprint was accepted 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 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.

Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Sarah Sparrow et al.

Model code and software

Instructions and code for controlling ECMWF OpenIFS application in (CPDN) Bowery, A. and Carver, G.

OpenIFS@home submission xml generation scripts Sparrow, S.

OpenIFS@home ancillary file repository scripts Sparrow, S.

OpenIFS@home webpages and dashboard Sparrow, S.

Code for sorting results uploaded to into project, batches and result status Uhe, P. and Sparrow, S.

Sarah Sparrow et al.


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Short summary
This paper describes how the research version of the European Centre for Medium-Range Weather Forecasts' Integrated Forecast System is combined with'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.