The hectometric modelling challenge: Gaps in the current state of the art and ways forward towards the implementation of 100‐m scale weather and climate models

Abstract For a number of years research has been carried out in several centres which has demonstrated the potential benefits of 100‐m scale models for a range of meteorological phenomena. More recently, some meteorological services have started to consider seriously the operational implementation of practical hectometric models. Many, but by no means all, of the applications are likely to relate to urban areas, where the enhanced resolution has obvious benefits. This article is concerned with the issues that need to be addressed to bridge the gap between research at 100‐m scales and practical models. We highlight a number of key issues that need to be addressed, with suggestions of important avenues for future development. An overarching issue is the high computational cost of these models. Although some ideas to reduce this are presented, it will always be a serious constraint. This means that the benefits of these models over lower resolution ones, or other techniques for generating high‐resolution forecasts, will need to be clearly understood, as will the trade‐offs with resolution. We discuss issues with model dynamical cores and physics–dynamics coupling. There are a number of challenges around model parameterisations, where some of the traditional problems (e.g., convection) become easier but a number of new challenges (e.g., around surface parameterisations) appear. Observational data at these scales present a challenge and novel types of observations will need to be considered. Data assimilation will be needed for short‐range forecasts, but there is currently little knowledge of this, although some of the likely issues are clear. An ensemble approach will be essential in many cases (e.g., convection), but research is needed into ensembles at these scales and significant work on post‐processing systems is required to make the best use of models at these grid lengths.

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Publication Details

Journal
Quarterly Journal of the Royal Meteorological Society
Published
2024-10-01
DOI
https://doi.org/10.1002/qj.4858
Citations
31
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
11.67

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article

The hectometric modelling challenge: Gaps in the current state of the art and ways forward towards the implementation of 100‐m scale weather and climate models

A. Pier Siebesma, Michael Baldauf, Chiel C. van Heerwaarden, Valéry Masson et al.
31 citations
Quarterly Journal of the Royal Meteorological Society
Meteorological Phenomena and Simulations
11.67
article

The hectometric modelling challenge: Gaps in the current state of the art and ways forward towards the implementation of 100‐m scale weather and climate models

A. Pier Siebesma, Michael Baldauf, Chiel C. van Heerwaarden, Valéry Masson, Peter Dueben, Natalie Theeuwes, Chiara Marsigli, Maarten van Reeuwijk, Jan Barkmeijer, Ian Boutle, Peter Clark, Geoffrey Bessardon, Rachel Honnert, Matthias Demuzere, Inger‐Lise Frogner, Adrian Lock, Humphrey Lean, Siebren de Haan, Lewis Blunn, Jelena Bojarova, Petra Smolíková, Dawn Harrison, Anne McCabe, Xiaohua Yang, Nigel Roberts
article en
31 citations

Abstract

Abstract For a number of years research has been carried out in several centres which has demonstrated the potential benefits of 100‐m scale models for a range of meteorological phenomena. More recently, some meteorological services have started to consider seriously the operational implementation of practical hectometric models. Many, but by no means all, of the applications are likely to relate to urban areas, where the enhanced resolution has obvious benefits. This article is concerned with the issues that need to be addressed to bridge the gap between research at 100‐m scales and practical models. We highlight a number of key issues that need to be addressed, with suggestions of important avenues for future development. An overarching issue is the high computational cost of these models. Although some ideas to reduce this are presented, it will always be a serious constraint. This means that the benefits of these models over lower resolution ones, or other techniques for generating high‐resolution forecasts, will need to be clearly understood, as will the trade‐offs with resolution. We discuss issues with model dynamical cores and physics–dynamics coupling. There are a number of challenges around model parameterisations, where some of the traditional problems (e.g., convection) become easier but a number of new challenges (e.g., around surface parameterisations) appear. Observational data at these scales present a challenge and novel types of observations will need to be considered. Data assimilation will be needed for short‐range forecasts, but there is currently little knowledge of this, although some of the likely issues are clear. An ensemble approach will be essential in many cases (e.g., convection), but research is needed into ensembles at these scales and significant work on post‐processing systems is required to make the best use of models at these grid lengths.

Quarterly Journal of the Royal Meteorological SocietyVol. 150(765)
Met Office (GB), Swedish Meteorological and Hydrological Institute (SE), Centre National de la Recherche Scientifique (FR), Royal Netherlands Meteorological Institute (NL), Norwegian Meteorological Institute (NO), European Centre for Medium-Range Weather Forecasts (GB), Deutscher Wetterdienst (DE), Université Fédérale de Toulouse Midi-Pyrénées (FR), Czech Hydrometeorological Institute (CZ), Danish Meteorological Institute (DK), Met Éireann (IE), Météo-France (FR), Imperial College London (GB), University of Reading (GB), Ruhr University Bochum (DE), Wageningen University & Research (NL), Delft University of Technology (NL)
European Commission, Deutsche Forschungsgemeinschaft, HORIZON EUROPE Framework Programme, HORIZON EUROPE Climate, Energy and Mobility
Climate action
Openalex Percentile: Top 1%
Meteorological Phenomena and Simulations
11.67
DOIOpen Access PDFOpenAlex
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