Towards a performance portable, architecture agnostic implementation strategy for weather and climate models

Fuhrer, Oliver; Osuna, Carlos; Lapillonne, Xavier; Gysi, Tobias; Cumming, Ben; Bianco, Mauro; Arteaga, Andrea; Schulthess, T. C.

doi:10.14529/jsfi140103

Cited by 68 publications

(50 citation statements)

References 17 publications

(15 reference statements)

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“…The simulations considered in this study have been performed with the RCM COSMO (Baldauf et al, 2011;Doms & Förstner, 2004;Steppler et al, 2003) in climate mode (Böhm et al, 2006). To run the computationally demanding high-resolution climate simulations necessary for our study, we have employed a version of COSMO adapted for hybrid GPU-CPU architectures (Fuhrer et al, 2014;Leutwyler et al, 2016). The nonhydrostatic fully compressible hydrothermodynamical governing equations are formulated in a rotated latitude-longitude coordinate system with terrain following vertical coordinates.…”

Section: Model Descriptionmentioning

confidence: 99%

“…Most of the already existing convection-resolving studies focus on precipitation and are limited by computational constraints to subcontinental domains or seasonal time scales. Using an efficient COSMO (Consortium for Small-Scale Modeling) model version that has recently been adapted to entirely run on graphics processing units (GPUs; Fuhrer et al, 2014;Leutwyler et al, 2016), it is now possible to perform multiyear convection-resolving simulations over continental-scale domains (Liu et al, 2017;Leutwyler et al, 2017). In this study, we use this new tool to address the cloud representation problem under a new perspective by analyzing clouds in decade-long convection-resolving climate simulations over Europe.…”

Section: Introductionmentioning

confidence: 99%

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Clouds in Convection‐Resolving Climate Simulations Over Europe

et al. 2019

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Although crucial for the Earth's climate, clouds are poorly represented in current climate models, which operate at too coarse grid resolutions and rely on convection parameterizations. Thanks to advances in high‐performance computing, it is becoming feasible to perform high‐resolution climate simulations with explicitly resolved deep convection. The added value of such convection‐resolving simulations for the representation of precipitation has already been demonstrated in a number of studies, but assessments about clouds are still rare. In the present study, we analyze the representation of clouds in decade‐long convection‐resolving climate simulations (2.2‐km horizontal grid spacing) over a computational domain with 1,536 × 1,536 × 60 grid points covering Europe and compare it against coarser‐resolution convection‐parameterizing simulations (12‐km horizontal spacing). The simulations have been performed with a version of the COSMO model that runs entirely on graphics processing units. The European Centre for Medium‐Range Weather Forecasts Re‐Analysis‐Interim reanalysis‐driven present climate simulations (1999–2008) show that biases in mean summertime cloudiness and top‐of‐the‐atmosphere radiation budget are reduced when convection is resolved instead of parameterized. Especially, the typically underestimated midtropospheric cloud layer is enhanced, thanks to stronger vertical exchange. Future climate simulations (2079–2088) conducted using pseudo global warming experiments for a Representative Concentration Pathway 8.5 scenario show a predominating reduction in low‐level and midlevel cloud cover fraction and an increase in cloud top height, implying positive cloud‐amount and cloud‐height feedbacks. These positive feedbacks are only partly compensated by the negative cloud‐thickness feedback. Although the simulations exhibit substantial differences in terms of clouds in the present climate, the simulated cloud feedbacks are similar between the 2.2‐ and 12‐km models.

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Section: Model Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Clouds in Convection‐Resolving Climate Simulations Over Europe

et al. 2019

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“…In addition, there are many smaller initiatives e.g., within the context of Partnership for Advanced Computing in Europe (http://www.prace-ri.euor). So far, to the author's knowledge, only one operational NWP model has been successfully ported to GPUs, namely that of MeteoSwiss (e.g., Fuhrer et al, 2014;Gysi et al, 2015;Leutwyler et al, 2016;Prein et al, 2017). The corresponding development branch of the code was largely decoupled from the operational version for years.…”

Section: Model Developmentmentioning

confidence: 99%

Climate, weather, space weather: model development in an operational context

Folini

2018

J. Space Weather Space Clim.

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-Aspects of operational modeling for climate, weather, and space weather forecasts are contrasted, with a particular focus on the somewhat conflicting demands of "operational stability" versus "dynamic development" of the involved models. Some common key elements are identified, indicating potential for fruitful exchange across communities. Operational model development is compelling, driven by factors that broadly fall into four categories: model skill, basic physics, advances in computer architecture, and new aspects to be covered, from costumer needs over physics to observational data. Evaluation of model skill as part of the operational chain goes beyond an automated skill score. Permanent interaction between "pure research" and "operational forecast" people is beneficial to both sides. This includes joint model development projects, although ultimate responsibility for the operational code remains with the forecast provider. The pace of model development reflects operational lead times. The points are illustrated with selected examples, many of which reflect the author's background and personal contacts, notably with the Swiss Weather Service and the Max Planck Institute for Meteorology, Hamburg, Germany. In view of current and future challenges, large collaborations covering a range of expertise are a must À within and across climate, weather, and space weather. To profit from and cope with the rapid progress of computer architectures, supercompute centers must form part of the team.

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“…By contrast, Fuhrer et al (2014b), in a partnership between meteorologist code owners and computer scientists, have rewritten ab initio the dynamical core of the COSMO weather forecasting model using a domain specific language approach (see section 3.1) -and it is now operational on a hybrid CPU/GPU machine. Their team is now working on extensions into the number of lines of Fortran.…”

Section: Progressmentioning

confidence: 99%

“…The GridTools project includes a wide range of 20 activities, some of which are discussed further below, but the DSL component of the work has evolved from an earlier DSL (Fuhrer et al 2014b andLeutwyler et al 2016). …”

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confidence: 99%

Crossing the Chasm: How to develop weather and climate models for next generation computers?

Budich¹,

Lawrence²,

Rezny³

2017

Preprint

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Abstract.Weather and climate models are complex pieces of software which include many individual components, each of which is evolving under the pressure to exploit advances in computing to enhance some combination of a range of possible improvements (higher spatio/temporal resolution, increased fidelity in terms of resolved processes, more quantification of uncertainty etc). However, after many years of a relatively stable computing environment with little choice in processing architecture or 5 programming paradigm (basically X86 processors using MPI for parallelism), the existing menu of processor choices includes significant diversity, and more is on the horizon. This computational diversity, coupled with ever increasing software complexity, leads to the very real possibility that weather and climate modelling will arrive at a chasm which will separate scientific aspiration from our ability to develop and/or rapidly adapt codes to the available hardware.In this paper we review the hardware and software trends which are leading us towards this chasm, before describing current 10 progress in addressing some of the tools which we may be able to use to bridge the chasm. This brief introduction to current tools and plans is followed by a discussion outlining the scientific requirements for quality model codes which have satisfactory performance and portability, while simultaneously supporting productive scientific evolution. We assert that the existing method of incremental model improvements employing small steps which adjust to the changing hardware environment is likely to be inadequate for crossing the chasm between aspiration and hardware at a satisfactory pace, in part because insti-15 tutions cannot have all the relevant expertise in house. Instead, we outline a methodology based on large community efforts in engineering and standardisation, one which will depend on identifying a taxonomy of key activities -perhaps based on 1 Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-186 Manuscript under review for journal Geosci. Model Dev. Discussion started: 5 September 2017 c Author(s) 2017. CC BY 4.0 License. existing efforts to develop domain specific languages, identify common patterns in weather and climate codes, and develop community approaches to commonly needed tools, libraries etc -and then collaboratively building up those key components. Such a collaborative approach will depend on institutions, projects and individuals adopting new interdependencies and ways of working.

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Towards a performance portable, architecture agnostic implementation strategy for weather and climate models

Cited by 68 publications

References 17 publications

Clouds in Convection‐Resolving Climate Simulations Over Europe

Clouds in Convection‐Resolving Climate Simulations Over Europe

Climate, weather, space weather: model development in an operational context

Crossing the Chasm: How to develop weather and climate models for next generation computers?

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