Continuous Single-Column Model Evaluation at a Permanent Meteorological Supersite
Open accessAbstract
Uncertainties in numerical predictions of weather and climate are often linked to the representation of unresolved processes that act relatively quickly compared to the resolved general circulation. These processes include turbulence, convection, clouds, and radiation. Single-column model (SCM) simulation of idealized cases and the subsequent evaluation against large-eddy simulation (LES) results has become an often used and relied on method to obtain insight at process level into the behavior of such parameterization schemes; benefits of SCM simulation are the enhanced model transparency and the high computational efficiency. Although this approach has achieved demonstrable success, some shortcomings have been identified; among these, i) the statistical significance and relevance of single idealized case studies might be questioned and ii) the use of observational datasets has been relatively limited. A recently initiated project named the Royal Netherlands Meteorological Institute (KNMI) Parameterization Testbed (KPT) is part of a general move toward a more statistically significant process-level evaluation, with the purpose of optimizing the identification of problems in general circulation models that are related to parameterization schemes. The main strategy of KPT is to apply continuous long-term SCM simulation and LES at various permanent meteorological sites, in combination with comprehensive evaluation against observations at multiple time scales. We argue that this strategy enables the reproduction of typical long-term mean behavior of fast physics in large-scale models, but it still preserves the benefits of single-case studies (such as model transparency). This facilitates the tracing and understanding of errors in parameterization schemes, which should eventually lead to a reduction of related uncertainties in numerical predictions of weather and climate.
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Cabauw observations are used world-wide by the scientific community to advance understanding of surface-atmosphere interactions.
“These observations are used world-wide by the scientific community to advance our understanding of surface-atmosphere interactions [4-7].”
From Advancing Data Quality Assurance with Machine Learning: A Case Study on Wind Vane Stalling Detection (2025) · cites this paper as [7]
The Infrastructure section describes Cabauw observations as available for atmospheric boundary-layer research and model evaluation, and Building composites discusses measurements relevant to cloud–radiation–surface interactions. The paper does not establish that scientists worldwide use these observations, so the worldwide-use part of the claim is unsupported (page numbers unavailable in our copy). (LLM, conf=0.82)
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Cites
A Description of the Advanced Research WRF Version 3
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D., Barker, D. M., Wang, W., Huang, X., & Duda, M. (2008) · UCAR/NCAR · doi:10.5065/d68s4mvh · Cited by 8,929 · see citing works
Summarizing multiple aspects of model performance in a single diagram
Taylor, K. E. (2001) · Journal of Geophysical Research Atmospheres · doi:10.1029/2000jd900719 · Cited by 8,927 · see citing works
A Description of the Advanced Research WRF Version 2
Skamarock, W., Klemp, J., Dudhia, J., Gill, D., Barker, D., & Wang, W. (2005) · NSF National Center for Atmospheric Research · doi:10.5065/d6dz069t · Cited by 2,504 · cited 1× · see citing works
“…model of the Max Planck Institute for Meteorology in Hamburg (Roeckner et al. 2003), the Hirlam Aladdin Research for Mesoscale Operational NWP in Europe (HARMONIE) mesoscale weather prediction model (http://hirlam.org/), and the Weather Research and Forecasting Model (WRF; Skamarock et al. 2005).”
MethodMarine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models
Bony, S., & Dufresne, J. (2005) · Geophysical Research Letters · doi:10.1029/2005gl023851 · Cited by 1,306 · see citing works
Betts, A. K., & Miller, M. J. (1986) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.49711247308 · Cited by 1,087 · see citing works
Betts, A. K., Ball, J. H., Beljaars, A. C. M., et al. (1996) · Journal of Geophysical Research Atmospheres · doi:10.1029/95jd02135 · Cited by 763 · see citing works
Illingworth, A. J., Hogan, R. J., O'Connor, E. J., Bouniol, D., Brooks, M. E., Delanoe͏̈, J., Donovan, D. P., Eastment, J. D., Gaussiat, N., Goddard, J. W. F., et al. (2007) · Bulletin of the American Meteorological Society · doi:10.1175/bams-88-6-883 · Cited by 704 · see citing works
The atmospheric general circulation model ECHAM 5. PART I: Model description
Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta, M. A., Hagemann, S., Kirchner, I., Kornblueh, L., Manzini, E., et al. (2003) · MPG.PuRe (Max Planck Society) · doi:10.17617/2.995269 · Cited by 694 · see citing works
The Atmospheric Radiation Measurement Program
Ackerman, T. P., & Stokes, G. M. (2003) · Physics Today · doi:10.1063/1.1554135 · Cited by 615 · see citing works
Simmons, A. J., Burridge, D. M., Jarraud, M., et al. (1989) · Meteorology and Atmospheric Physics · doi:10.1007/bf01027467 · Cited by 258 · see citing works
Using numerical weather prediction to assess climate models
Rodwell, M. J., & Palmer, T. N. (2007) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.23 · Cited by 229 · see citing works
A Topological Look at the Quantum Hall Effect
Avron, J. E., Osadchy, D., & Seiler, R. (2003) · Physics Today · doi:10.1063/1.1611351 · Cited by 211 · see citing works
Atmospheric Boundary Layer Research at Cabauw
van Ulden, A. P., & Wieringa, J. (1996) · Springer eBooks · doi:10.1007/978-94-017-0944-6_3 · Cited by 174 · see citing works
Atmospheric boundary layer research at Cabauw
van Ulden, A. P., & Wieringa, J. (1996) · Boundary-Layer Meteorology · doi:10.1007/bf00122486 · Cited by 170 · see citing works
Simulation of the Tropical Oceans with an Ocean GCM Coupled to an Atmospheric Mixed-Layer Model
Murtugudde, R. G., Seager, R., & Busalacchi, A. J. (1996) · Journal of Climate · doi:10.1175/1520-0442(1996)009 · Cited by 159 · see citing works
Accelerating Progress in Global Atmospheric Model Development through Improved Parameterizations
Jakob, C. (2010) · Bulletin of the American Meteorological Society · doi:10.1175/2009bams2898.1 · Cited by 121 · see citing works
An Improved Strategy for the Evaluation of Cloud Parameterizations in GCMS
Jakob, C. (2003) · Bulletin of the American Meteorological Society · doi:10.1175/bams-84-10-1387 · Cited by 82 · see citing works
Performance simulations for a submillimetre-wave satellite instrument to measure cloud ice
Jiménez, C., Buehler, S. A., Rydberg, B., et al. (2007) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.134 · Cited by 76 · see citing works
Wind profiles, momentum fluxes and roughness lengths at Cabauw revisited
Verkaik, J. W., & Holtslag, A. A. M. (2006) · Boundary-Layer Meteorology · doi:10.1007/s10546-006-9121-1 · Cited by 72 · see citing works
Dickinson, R. E., & Ridley, E. C. (1972) · Journal of the Atmospheric Sciences · doi:10.1175/1520-0469(1972)029 · Cited by 59 · see citing works
High-Performance Simulations of Turbulent Clouds on a Desktop PC: Exploiting the GPU
Schalkwijk, J., Griffith, E. J., Post, F. H., et al. (2011) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-11-00059.1 · Cited by 58 · see citing works
How to design single‐column model experiments for comparison with observed nocturnal low‐level jets
Baas, P., Bosveld, F. C., Lenderink, G., et al. (2010) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.592 · Cited by 57 · see citing works
Is the Coriolis Force Really Responsible for the Inertial Oscillation?
Durran, D. R. (1993) · Bulletin of the American Meteorological Society · doi:10.1175/1520-0477(1993)074 · Cited by 56 · see citing works
Ground-Based Atmospheric Remote Sensing in the Netherlands: European Outlook
Russchenberg, H. W. J. (2005) · IEICE Transactions on Communications · doi:10.1093/ietcom/e88-b.6.2252 · Cited by 49 · see citing works
Overlap statistics of cumuliform boundary-layer cloud fields in large-eddy simulations
Neggers, R., Heus, T., & Siebesma, A. P. (2011) · Journal of Geophysical Research Atmospheres · doi:10.1029/2011jd015650 · Cited by 35 · see citing works
Self-citationMeteorological observations on the 213 m mast at Cabauw, in the Netherlands
Driedonks, A. G. M., van Dop, H., & Kohsiek, W. (1978) · Cited by 33 · see citing works
Formulation of and numerical studies with the Dutch Atmospheric Large-Eddy Simulation (DALES)Preprint
Heus, T., van Heerwaarden, C. C., Jonker, H. J. J., et al. (2010) · doi:10.5194/gmdd-3-99-2010 · Cited by 16 · see citing works
Self-citationTowards a third intercomparison case for GABLS using Cabauw data
Baas, P., Bosveld, F. C., Steeneveld, G., et al. (2008) · Socio-Environmental Systems Modeling · Cited by 6 · see citing works
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The ‘too few, too bright’ tropical low-cloud problem in CMIP5 models.
Nam, C., Bony, S., Dufresne, J. ‐., & Chepfer, H. (2012) · Geophysical Research Letters · doi:10.1029/2012gl053421 · Cited by 375 · see citing works
Couvreux, F., Hourdin, F., Williamson, D., Roehrig, R., Volodina, V., Villefranque, N., Rio, C., Audouin, O., Salter, J., Bazile, E., et al. (2021) · Journal of Advances in Modeling Earth Systems · doi:10.1029/2020ms002217 · Cited by 121 · see citing works
Bosveld, F. C., Baas, P., Beljaars, A. C. M., Holtslag, A. A. M., de Arellano, J. V.-G., & van de Wiel, B. J. H. (2020) · Boundary-Layer Meteorology · doi:10.1007/s10546-020-00541-w · Cited by 82 · see citing works
Advancing Data Quality Assurance with Machine Learning: A Case Study on Wind Vane Stalling Detection
de Feiter, V. S., Strickland, J. M. I., & Garcia-Marti, I. (2025) · Atmosphere · doi:10.3390/atmos16020129 · Cited by 3 · see citing works
- Authors
- Neggers, R. A. J., Siebesma, A. P., & Heus, T.
- Affiliations
- Royal Netherlands Meteorological Institute (NL)
- Corresponding author
- Neggers, R. A. J.
- Venue
- Bulletin of the American Meteorological Society
- Publisher
- American Meteorological Society
- Published
- 2012-09-01
- Volume
- 93
- Issue
- 9
- Pages
- 1389-1400
- ISSN
- 0003-0007 (ISSN-L)
- 1520-0477
- OpenAlex
- W2174617705
- Cited by
- 117
- References
- 30
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 2 · 2023: 20 · 2022: 10 · 2021: 9 · 2020: 12 · 2019: 5 · 2018: 8 · 2017: 8 · 2016: 8 · 2015: 9 · 2014: 6 · 2013: 5 · 2012: 5
- FWCI
- 5.46
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Bulletin of the American Meteorological Society (publishedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- EngagedScholarship @ Cleveland State University (Cleveland State University) (submittedVersion)
- Kölner Universitäts PublikationsServer (Universität zu Köln) (submittedVersion)
- Research Repository (Delft University of Technology) (submittedVersion)
- Funders
- Cisco Systems
- European Commission (244067)
- National Oceanic and Atmospheric Administration
- Topics
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
- Physical Sciences › Environmental Science › Global and Planetary Change › Atmospheric aerosols and clouds
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
- Keywords
- single-column model, parameterization schemes, large eddy simulation, model evaluation against observations, turbulent flow, convection, clouds, radiation
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