Abstract

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 organizations, 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 at 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 (https://www.climateprediction.net/, last access: 1 June 2021) 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 2000-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 and discuss the use of large ensembles in the context of forecasting extreme events.

Highlights

  • Today there are many ways in which the public can directly participate in scientific research, otherwise known as citizen science

  • 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

  • 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

Read more

Summary

Introduction

Today there are many ways in which the public can directly participate in scientific research, otherwise known as citizen science. There is an extremely wide variety of different projects making use of this paradigm, the most wellknown of which is searching for extra-terrestrial life with SETI@home (Sullivan III et al, 1997) Projects of this type are underpinned by the Berkeley Open Infrastructure for Network Computing (BOINC, Anderson, 2004) that distributes simulations to the personal computers of their public volunteers that have donated their spare computing resources. In this paper we detail the deployment of the European Centre for Medium-Range Weather Forecasts (ECMWF) OpenIFS model within the CPDN infrastructure as the OpenIFS@home application This new facility enables the execution of ensembles of weather forecast simulations (ranging from 1 to 10 000+ members) at scientifically relevant resolutions to achieve the following goals. – To support the deployment of current experiments performed with OpenIFS to run in OpenIFS@home provided certain resource constraints are met

The ECMWF OpenIFS model
Technical requirements and challenges
Porting OpenIFS to a BOINC environment
Case study
Experimental setup and initial conditions
BOINC application performance
Meteorological performance
Findings
Conclusions
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call