16 Nov 2020
| 16 Nov 2020
HARMONIE-AROME single-column tools and experiments
Met Éireann, Glasnevin Hill, Dublin 9, D09 Y921, Ireland
Stephen Outten
Nansen Environmental and Remote Sensing Centre, Thormøhlens gate 47, 5006, Bergen, Norway
Bjørg Jenny Kokkvoll Engdahl
Norwegian Meteorological Institute, P.O. Box 43, Blindern 0313, Oslo, Norway
Eoin Whelan
Met Éireann, Glasnevin Hill, Dublin 9, D09 Y921, Ireland
Ulf Andrae
Swedish Meteorological Hydrological Institute, 60176 Norrköping, Sweden
Laura Rontu
Finnish Meteorological Institute, Helsinki, Finland
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Eoghan Keany, Geoffrey Bessardon, and Emily Gleeson
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Ruth Mottram, Kristian Pagh Nielsen, Emily Gleeson, and Xiaohua Yang
Adv. Sci. Res., 14, 323–334, https://doi.org/10.5194/asr-14-323-2017, https://doi.org/10.5194/asr-14-323-2017, 2017
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The HARMONIE weather forecasting model is used successfully in Greenland, but there are some problems over the ice sheet due to the lack of realistic glacier surface characteristics. By introducing a correction to the model, preventing glacier surface temperatures over 0 °C, we improve both 2 m air temperature and the surface winds (both strength and direction) forecast by the model.
We also identify other corrections needed before HARMONIE can be used for climate and ice sheet modelling.
Laura Rontu, Emily Gleeson, Petri Räisänen, Kristian Pagh Nielsen, Hannu Savijärvi, and Bent Hansen Sass
Adv. Sci. Res., 14, 195–215, https://doi.org/10.5194/asr-14-195-2017, https://doi.org/10.5194/asr-14-195-2017, 2017
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This paper provides an overview of the HLRADIA shortwave (SW) and longwave (LW) broadband radiation schemes used in the HIRLAM numerical weather prediction (NWP) model and available in the HARMONIE-AROME mesoscale NWP model. The advantage of broadband, over spectral, schemes is that they can be called more frequently within the NWP model, without compromising on computational efficiency. Fast physically based radiation parametrizations are also valuable for high-resolution ensemble forecasting.
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Emily Gleeson, Sarah Gallagher, Colm Clancy, and Frédéric Dias
Adv. Sci. Res., 14, 23–33, https://doi.org/10.5194/asr-14-23-2017, https://doi.org/10.5194/asr-14-23-2017, 2017
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K. P. Nielsen, E. Gleeson, and L. Rontu
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Stephen Outten, Camille Li, Martin P. King, Lingling Suo, Peter Y. F. Siew, Hoffman Cheung, Richard Davy, Etienne Dunn-Sigouin, Tore Furevik, Shengping He, Erica Madonna, Stefan Sobolowski, Thomas Spengler, and Tim Woollings
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Strong disagreement exists in the scientific community over the role of Arctic sea ice in shaping wintertime Eurasian cooling. The observed Eurasian cooling can arise naturally without sea-ice loss but is expected to be a rare event. We propose a framework that incorporates sea-ice retreat and natural variability as contributing factors. A helpful analogy is of a dice roll that may result in cooling, warming, or anything in between, with sea-ice loss acting to load the dice in favour of cooling.
Eoghan Keany, Geoffrey Bessardon, and Emily Gleeson
Adv. Sci. Res., 19, 13–27, https://doi.org/10.5194/asr-19-13-2022, https://doi.org/10.5194/asr-19-13-2022, 2022
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This work used machine learning to produce the first open source building height map of Ireland. This map is intended to more accurately determine Local Climate Zones for use in the underlying physiography dataset in the HARMONIE AROME numerical weather prediction model.
Clio Michel, Erica Madonna, Clemens Spensberger, Camille Li, and Stephen Outten
Weather Clim. Dynam., 2, 1131–1148, https://doi.org/10.5194/wcd-2-1131-2021, https://doi.org/10.5194/wcd-2-1131-2021, 2021
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Eoin Walsh, Geoffrey Bessardon, Emily Gleeson, and Priit Ulmas
Adv. Sci. Res., 18, 65–87, https://doi.org/10.5194/asr-18-65-2021, https://doi.org/10.5194/asr-18-65-2021, 2021
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Danijel Belušić, Hylke de Vries, Andreas Dobler, Oskar Landgren, Petter Lind, David Lindstedt, Rasmus A. Pedersen, Juan Carlos Sánchez-Perrino, Erika Toivonen, Bert van Ulft, Fuxing Wang, Ulf Andrae, Yurii Batrak, Erik Kjellström, Geert Lenderink, Grigory Nikulin, Joni-Pekka Pietikäinen, Ernesto Rodríguez-Camino, Patrick Samuelsson, Erik van Meijgaard, and Minchao Wu
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A new regional climate modelling system, HCLIM38, is presented and shown to be applicable in different regions ranging from the tropics to the Arctic. The main focus is on climate simulations at horizontal resolutions between 1 and 4 km, the so-called convection-permitting scales, even though the model can also be used at coarser resolutions. The benefits of simulating climate at convection-permitting scales are shown and are particularly evident for climate extremes.
Laura Rontu, Kalle Eerola, and Matti Horttanainen
Geosci. Model Dev., 12, 3707–3723, https://doi.org/10.5194/gmd-12-3707-2019, https://doi.org/10.5194/gmd-12-3707-2019, 2019
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Numerical weather prediction model HIRLAM includes prognostic treatment of lake surface state since 2012. Forecast is based on the Freshwater Lake model (Flake). We compared the predicted lake water temperature, freeze-up and break-up dates as well as the ice thickness and snow depth during six years over 45 lakes in Finland against observations by Finnish Environment Institute. Water surface temperatures and freezing of lakes were well predicted but the ice tended to melt too early in spring.
Laura Rontu, Joni-Pekka Pietikäinen, and Daniel Martin Perez
Adv. Sci. Res., 16, 129–136, https://doi.org/10.5194/asr-16-129-2019, https://doi.org/10.5194/asr-16-129-2019, 2019
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Radiative transfer calculations in numerical weather prediction (NWP)
and climate models require reliable information about aerosol
concentration in the atmosphere, combined with data on aerosol optical
properties. Data from the Copernicus atmosphere monitoring service
(CAMS) and European Centre for Medium-Range Weather Forecasts (ECMWF)
were implemented to the limited area, short-range HARMONIE-AROME NWP
model.
Emily Gleeson, Colm Clancy, Laura Zubiate, Jelena Janjić, Sarah Gallagher, and Frédéric Dias
Adv. Sci. Res., 16, 11–29, https://doi.org/10.5194/asr-16-11-2019, https://doi.org/10.5194/asr-16-11-2019, 2019
Short summary
Short summary
The Northeast Atlantic possesses an energetic and variable wind and wave climate which has a large potential for renewable energy extraction. The role of surface winds in the generation of ocean waves means that global atmospheric circulation patterns and wave climate characteristics are inherently connected. In this study we investigated the influence of large scale atmospheric oscillations on waves in the Northeast Atlantic using a high resolution wave projection dataset.
Laura Rontu and Anders V. Lindfors
Adv. Sci. Res., 15, 81–90, https://doi.org/10.5194/asr-15-81-2018, https://doi.org/10.5194/asr-15-81-2018, 2018
Short summary
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Global radiation forecasts by HARMONIE-AROME numerical weather prediction model were compared to observations over Finland in spring 2017 when convective clouds, rain and snow showers were frequent. In HARMONIE-AROME, three different schemes for parametrization of the atmospheric radiation transfer are available. Differences between the schemes and observations showed up especially as variations in the hourly scale. The results by the schemes were closer to each other than to the observations.
Ruth Mottram, Kristian Pagh Nielsen, Emily Gleeson, and Xiaohua Yang
Adv. Sci. Res., 14, 323–334, https://doi.org/10.5194/asr-14-323-2017, https://doi.org/10.5194/asr-14-323-2017, 2017
Short summary
Short summary
The HARMONIE weather forecasting model is used successfully in Greenland, but there are some problems over the ice sheet due to the lack of realistic glacier surface characteristics. By introducing a correction to the model, preventing glacier surface temperatures over 0 °C, we improve both 2 m air temperature and the surface winds (both strength and direction) forecast by the model.
We also identify other corrections needed before HARMONIE can be used for climate and ice sheet modelling.
Laura Rontu, Emily Gleeson, Petri Räisänen, Kristian Pagh Nielsen, Hannu Savijärvi, and Bent Hansen Sass
Adv. Sci. Res., 14, 195–215, https://doi.org/10.5194/asr-14-195-2017, https://doi.org/10.5194/asr-14-195-2017, 2017
Short summary
Short summary
This paper provides an overview of the HLRADIA shortwave (SW) and longwave (LW) broadband radiation schemes used in the HIRLAM numerical weather prediction (NWP) model and available in the HARMONIE-AROME mesoscale NWP model. The advantage of broadband, over spectral, schemes is that they can be called more frequently within the NWP model, without compromising on computational efficiency. Fast physically based radiation parametrizations are also valuable for high-resolution ensemble forecasting.
Emily Gleeson, Eoin Whelan, and John Hanley
Adv. Sci. Res., 14, 49–61, https://doi.org/10.5194/asr-14-49-2017, https://doi.org/10.5194/asr-14-49-2017, 2017
Short summary
Short summary
This paper is a summary of a very high resolution climate reanalysis carried out for a domain covering Ireland, using the HARMONIE-AROME numerical weather prediction model. Details of the simulations and set-up as well as a preliminary analysis of the main output variables are included in the study.
Emily Gleeson, Sarah Gallagher, Colm Clancy, and Frédéric Dias
Adv. Sci. Res., 14, 23–33, https://doi.org/10.5194/asr-14-23-2017, https://doi.org/10.5194/asr-14-23-2017, 2017
Short summary
Short summary
Large scale atmospheric oscillations, such as the North Atlantic Oscillation are known to have an influence on waves in the North Atlantic. This study investigated the influence of the NAO on the present and future wind and wave climate in the Northeast Atlantic near Ireland.
Emily Gleeson, Velle Toll, Kristian Pagh Nielsen, Laura Rontu, and Ján Mašek
Atmos. Chem. Phys., 16, 5933–5948, https://doi.org/10.5194/acp-16-5933-2016, https://doi.org/10.5194/acp-16-5933-2016, 2016
Short summary
Short summary
The direct shortwave (SW) radiative effect of aerosols under clear-sky conditions in the ALADIN-HIRLAM numerical weather prediction system was investigated using three SW radiation schemes in diagnostic single-column experiments. Each scheme accurately simulates the direct SW effect when observed aerosols are used, particularly for heavy pollution scenarios.
Sarah Gallagher, Emily Gleeson, Roxana Tiron, Ray McGrath, and Frédéric Dias
Adv. Sci. Res., 13, 75–80, https://doi.org/10.5194/asr-13-75-2016, https://doi.org/10.5194/asr-13-75-2016, 2016
Short summary
Short summary
As an island located in the North Atlantic Ocean with a highly energetic wave and wind climate, Ireland is uniquely placed in terms of its ocean renewable energy resource. The socio-economic importance of this resource makes it a priority to quantify how the wave and wind climate may change in the future. We examine how surface winds in the North Atlantic Ocean may change towards the end of this century due to global climate change, and how these changes may affect Ireland's wave climate.
Markku Kangas, Laura Rontu, Carl Fortelius, Mika Aurela, and Antti Poikonen
Geosci. Instrum. Method. Data Syst., 5, 75–84, https://doi.org/10.5194/gi-5-75-2016, https://doi.org/10.5194/gi-5-75-2016, 2016
Short summary
Short summary
Sodankylä, in the heart of the Arctic Research Centre of the Finnish Meteorological Institute in northern Finland with temperatures ranging from −50 to +30 °C, provides a challenging location for numerical weather forecasting (NWP) models. In this article, the use of measurements performed in Sodankylä for near-real time online verification of NWP models is described. A more specific case study of three different radiation schemes, applicable in NWP model HARMONIE-AROME, is also presented.
K. P. Nielsen, E. Gleeson, and L. Rontu
Geosci. Model Dev., 7, 1433–1449, https://doi.org/10.5194/gmd-7-1433-2014, https://doi.org/10.5194/gmd-7-1433-2014, 2014
I. Esau, R. Davy, S. Outten, S. Tyuryakov, and S. Zilitinkevich
Nonlin. Processes Geophys., 20, 589–604, https://doi.org/10.5194/npg-20-589-2013, https://doi.org/10.5194/npg-20-589-2013, 2013
S. D. Outten and I. Esau
Atmos. Chem. Phys., 13, 5163–5172, https://doi.org/10.5194/acp-13-5163-2013, https://doi.org/10.5194/acp-13-5163-2013, 2013
Cited articles
AROME: 2008 – 2nd AROME Training Course, available at:
http://www.umr-cnrm.fr/gmapdoc/spip.php?rubrique64 (last access: 14 November 2020), 2008. a
Bengtsson, L., Andrae, U., Aspelien, T., Batrak, Y., Calvo, J., de Rooy, W.,
Gleeson, E., Hansen-Sass, B., Homleid, M., Hortal, M., Ivarsson, K.-I.,
Lenderink, G., Niemelä, S., Nielsen, K. P., Onvlee, J., Rontu, L., Samuelsson, P., Muñoz, D. S., Subias, A., Tijm, S., Toll, V., Yang, X., and Køltzow, M. Ø.: The HARMONIE-AROME Model Configuration in the
ALADIN-HIRLAM NWP System, Mon. Weather Rev., 145, 1919–1935,
https://doi.org/10.1175/MWR-D-16-0417.1, 2017. a, b
Bosveld, F., Baas, P., Steeneveld, G., Holtslag, A., Angevine, W., Bazile, E., de Bruijn, E., Deacu, D., Edwards, J., Ek, M., Larson, V., Pleim, J.,
Raschendorfer, M., and Svensson, G.: The Third GABLS Intercomparison Case for
Evaluation Studies of Boundary-Layer Models. Part B: Results and Process
Understanding, Bound.-Lay. Meteorol., 152, 157–187, https://doi.org/10.1007/s10546-014-9919-1, 2014. a
Cohard, J.-M. and Pinty, J.-P.: A comprehensive two-moment warm microphysical
bulk scheme. I: Description and tests, Q. J. Roy. Meteorol. Soc., 126, 1815–1842, https://doi.org/10.1002/qj.49712656613, 2000a. a, b
Cohard, J.-M. and Pinty, J.-P.: A comprehensive two-moment warm microphysical
bulk scheme. II: 2D experiments with a non-hydrostatic model, Q. J. Roy. Meteorol. Soc., 126, 1843–1859, https://doi.org/10.1002/qj.49712656614, 2000b. a, b
Copernicus: Copernicus Atmosphere Monitoring Service (CAMS) Data, available at: https://atmosphere.copernicus.eu/data, last access: 14 November 2020. a
Cuxart, J., Holtslag, A. A. M., Beare, R. J., Bazile, E. B. A., Cheng, A.,
L. C., Ek, M., Freedman, F., Hamdi, R. K. A., Kitagawa, H., Lenderink, G.,
Lewellen, D., Mailhot, J., Mauritsen, T., Perov, V., Schayes, G., Steeneveld,
G.-J., Svensson, G., Taylor, P., Weng, W., Wunsch, S., and Xu, K.-M.:
Single-Column Model Intercomparison for a Stably Stratified Atmospheric
Boundary Layer, Bound.-Lay. Meteorol., 118, 273–303, https://doi.org/10.1007/s10546-005-3780-1, 2006. a
ECMWF: ECMWF IFS documentation Chapter 2, available at:
http://www.ecmwf.int/sites/default/files/elibrary/2015/9211-part-iv-physical-processes.pdf
(last access: 14 November 2020), 2015. a
ECMWF-ecCodes: ecCodes Home, available at:
https://confluence.ecmwf.int/display/ECC (last access: 14 November 2020), 2019. a
Engdahl, B. J. K., Nygaard, B. E. K., Losnedal, V., Thompson, G., and
Bengtsson, L.: Effects of the ICE-T microphysics scheme in HARMONIE-AROME on
estimated ice loads on transmission lines, Cold Reg. Sci. Technol. 179, 103139, https://doi.org/10.1016/j.coldregions.2020.103139, 2020a. a, b
Firl, G., Carso, L., Bernardet, L., and Heinzeller, D.: Global Model Test Bed
Single Column Model (SCM) User and Technical Guide v3.0, Tech. rep., National
Center for Atmospheric Research and Developmental Testbed Center, NOAA/ESRL
Global Systems Division, Developmental Testbed Center and CIRES/CU, available at: https://dtcenter.org/sites/default/files/community-code/ccpp/GMTB/scm-ccpp-guide-v4.0.pdf (last access: 14 November 2020), 2019. a
Frogner, I.-L., Andrae, U., Bojarova, J., Callado, A., Escribà, P., Feddersen, H., Hally, A., Kauhanen, J., Randriamampianina, R., Singleton, A., Smet, G., van der Veen, S., and Vignes, O.: HarmonEPS – The HARMONIE Ensemble Prediction System, Weather Forecast., 34, 1909–1937,
https://doi.org/10.1175/WAF-D-19-0030.1, 2019. a, b
Geleyn, J.-F., Mašek, J., Brožková, R., Kuma, P., Degrauwe, D., Hello, G., and Pristov, N.: Single interval longwave radiation scheme based on the net exchanged rate decomposition with bracketing, Q. J. Roy. Meteorol. Soc., 143, 1313–1335, https://doi.org/10.1002/qj.3006, 2017. a
Gleeson, E., Toll, V., Nielsen, K. P., Rontu, L., and Mašek, J.: Effects of aerosols on clear-sky solar radiation in the ALADIN-HIRLAM NWP system,
Atmos. Chem. Phys., 16, 5933–5948, https://doi.org/10.5194/acp-16-5933-2016, 2016. a, b, c, d
HIRLAM: Post processing with gl_grib_api, available at:
https://hirlam.org/trac/wiki/HarmonieSystemDocumentation/PostPP/gl_grib_api
(last access: 14 November 2020), 2019. a
Inness, A., Ades, M., Agustí-Panareda, A., Barré, J., Benedictow, A.,
Blechschmidt, A.-M., Dominguez, J. J., Engelen, R., Eskes, H., Flemming, J.,
Huijnen, V., Jones, L., Kipling, Z., Massart, S., Parrington, M., Peuch,
V.-H., Razinger, M., Remy, S., Schulz, M., and Suttie, M.: The CAMS
reanalysis of atmospheric composition, Atmo. Chem. Phys., 19, 3515–3556, https://doi.org/10.5194/acp-19-3515-2019, 2019. a
Koski, H.: Weather models developed through cloud computing, available at:
https://www.csc.fi/en/web/atcsc/-/pilvilaskenta-avuksi-saamallien-kehitykseen
(last access: 14 November 2020), 2017. a
Le Moigne, P.: SURFEX Scientific Documentation, Tech. rep., available at: https://www.umr-cnrm.fr/surfex/IMG/pdf/surfex_scidoc_v8.1.pdf (last access: 14 November 2020), 2018. a
Lin, Y.-L., Farley, R. D., and Orville, H. D.: Bulk Parameterization of the
Snow Field in a Cloud Model, J. Clim. Appl. Meteorol., 22, 1065–1092, https://doi.org/10.1175/1520-0450(1983)022<1065:BPOTSF>2.0.CO;2, 1983. a, b
Liu, C., Ikeda, K., Thompson, G., Rasmussen, R., and Dudhia, J.:
High-Resolution Simulations of Wintertime Precipitation in the Colorado
Headwaters Region: Sensitivity to Physics Parameterizations, Mon. Weather Rev., 139, 3533–3553, https://doi.org/10.1175/MWR-D-11-00009.1, 2011. a
Mašek, J., Geleyn, J.-F., Brožková, R., Giot, O., Achom, H. O., and Kuma, P.: Single interval shortwave radiation scheme with parameterized optical saturation and spectral overlaps, Q. J. Roy. Meteorol. Soc., 142, 304–326, https://doi.org/10.1002/qj.2653, 2016. a
Morrison, H., Thompson, G., and Tatarskii, V.: Impact of Cloud Microphysics on the Development of Trailing Stratiform Precipitation in a Simulated Squall
Line: Comparison of One- and Two-Moment Schemes, Mon. Weather Rev., 137,
991–1007, https://doi.org/10.1175/2008MWR2556.1, 2009. a
Mottram, R., Nielsen, K. P., Gleeson, E., and Yang, X.: Modelling Glaciers in
the HARMONIE-AROME NWP model, Adv. Sci. Res., 14, 323–334, https://doi.org/10.5194/asr-14-323-2017, 2017. a
MUSC: Hirlam-B working days on HARMONIE-MUSC, available at: http://netfam.fmi.fi/muscwd11/ (last access: 14 November 2020), 2011a. a
MUSC: Hirlam-B working days on HARMONIE-MUSC – Presentations, available at:
http://netfam.fmi.fi/muscwd11/Agenda.html (last access: 14 November 2020), 2011b. a
Neggers, R. and Siebesma, A.: The KNMI Parametrization Testbed User's Guide
Version 2, unpublished, 2010. a
Neggers, R. A. J., Ackerman, A. S., Angevine, W. M., Bazile, E., Beau, I.,
Blossey, P. N., Boutle, I. A., de Bruijn, C., Cheng, A., van der Dussen, J.,
Fletcher, J., Dal Gesso, S., Jam, A., Kawai, H., Cheedela, S. K., Larson, V. E., Lefebvre, M.-P., Lock, A. P., Meyer, N. R., de Roode, S. R., de Rooy, W., Sandu, I., Xiao, H., and Xu, K.-M.: Single-Column Model Simulations of
Subtropical Marine Boundary-Layer Cloud Transitions Under Weakening Inversions, J. Adv. Model. Earth Syst., 9, 2385–2412,
https://doi.org/10.1002/2017MS001064, 2017. a
Nielsen, K. P., Gleeson, E., and Rontu, L.: Radiation sensitivity tests of the HARMONIE 37h1 NWP model, Geosci. Model Dev., 7, 1433–1449,
https://doi.org/10.5194/gmd-7-1433-2014, 2014. a
Rontu, L., Gleeson, E., Räisänen, P., Pagh Nielsen, K., Savijärvi, H., and Hansen Sass, B.: The HIRLAM fast radiation scheme for mesoscale numerical weather prediction models, Adv. Sci. Res., 14, 195–215,
https://doi.org/10.5194/asr-14-195-2017, 2017. a
Stoelinga, M. T., Hobbs, P. V., Mass, C. F., Locatelli, J. D., Colle, B. A.,
Houze, R. A., Rangno, A. L., Bond, N. A., Smull, B. F., Rasmussen, R. M.,
Thompson, G., and Colman, B. R.: Improvement of Microphysical Parameterization through Observational Verification Experiment, B. Am. Meteorol. Soc., 84, 1807–1826, https://doi.org/10.1175/BAMS-84-12-1807, 2003. a
Svensson, G., Holtslag, A. A. M., Kumar, V., Mauritsen, T., Steeneveld, G. J., Angevine, W. M., Bazile, E., Beljaars, A., de Bruijn, E. I. F., Cheng, A., Conangla, L., Cuxart, J., Ek, M., Falk, M. J., Freedman, F., Kitagawa, H., Larson, V. E., Lock, A., Mailhot, J., Masson, V., Park, S., Pleim, J., Söderberg, S., Weng, W., and Zampieri, M.: Evaluation of the Diurnal Cycle in the Atmospheric Boundary Layer Over Land as Represented by a Variety of Single-Column Models: The Second GABLS Experiment, Bound.-Lay. Meteorol., 140, 177–206, https://doi.org/10.1007/s10546-011-9611-7, 2011. a
Termonia, P., Fischer, C., Bazile, E., Bouyssel, F., Brožková, R.,
Bénard, P., Bochenek, B., Degrauwe, D., Derková, M., El Khatib, R.,
Hamdi, R., Mašek, J., Pottier, P., Pristov, N., Seity, Y.,
Smolíková, P., Španiel, O., Tudor, M., Wang, Y., Wittmann, C., and Joly, A.: The ALADIN System and its canonical model configurations AROME
CY41T1 and ALARO CY40T1, Geosci. Model Dev., 11, 257–281,
https://doi.org/10.5194/gmd-11-257-2018, 2018. a, b
Thompson, G. and Eidhammer, T.: A Study of Aerosol Impacts on Clouds and
Precipitation Development in a Large Winter Cyclone, J. Atmos. Sci., 71, 3636–3658, https://doi.org/10.1175/JAS-D-13-0305.1, 2014. a
Thompson, G., Rasmussen, R. M., and Manning, K.: Explicit Forecasts of Winter
Precipitation Using an Improved Bulk Microphysics Scheme. Part I: Description
and Sensitivity Analysis, Mon. Weather Rev., 132, 519–542,
https://doi.org/10.1175/1520-0493(2004)132<0519:EFOWPU>2.0.CO;2, 2004. a
Thompson, G., Field, P. R., Rasmussen, R. M., and Hall, W. D.: Explicit
Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme.
Part II: Implementation of a New Snow Parameterization, Mon. Weather Rev., 136, 5095–5115, https://doi.org/10.1175/2008MWR2387.1, 2008. a, b
Vignon, E., Hourdin, F., Genthon, C., Gallée, H., Bazile, E., Lefebvre, M.-P., Madeleine, J.-B., and Van de Wiel, B. J. H.: Antarctic boundary layer
parametrization in a general circulation model: 1-D simulations facing summer
observations at Dome C, J. Geophys. Res.-Atmos., 122, 6818–6843, https://doi.org/10.1002/2017JD026802, 2017.
a
Walters, D. N., Best, M. J., Bushell, A. C., Copsey, D., Edwards, J. M.,
Falloon, P. D., Harris, C. M., Lock, A. P., Manners, J. C., Morcrette, C. J.,
Roberts, M. J., Stratton, R. A., Webster, S., Wilkinson, J. M., Willett, M. R., Boutle, I. A., Earnshaw, P. D., Hill, P. G., MacLachlan, C., Martin, G. M., Moufouma-Okia, W., Palmer, M. D., Petch, J. C., Rooney, G. G., Scaife, A. A., and Williams, K. D.: The Met Office Unified Model Global Atmosphere 3.0/3.1 and JULES Global Land 3.0/3.1 configurations, Geosci. Model Dev., 4, 919–941, https://doi.org/10.5194/gmd-4-919-2011, 2011. a
Short summary
The single-column version of the shared ALADIN-HIRLAM numerical weather prediction system, called MUSC, was developed by Météo-France in the 2000s and has a growing user-base. Tools to derive the required input, to run experiments and to handle outputs have been developed within the HARMONIE-AROME configuration of the ALADIN-HIRLAM system. We also illustrate the usefulness of MUSC for testing and developing physical parametrizations related to cloud microphysics and radiative transfer.
The single-column version of the shared ALADIN-HIRLAM numerical weather prediction system,...
