Articles | Volume 9, issue 3
https://doi.org/10.5194/gmd-9-1143-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-1143-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Validation of the ALARO-0 model within the EURO-CORDEX framework
Olivier Giot
CORRESPONDING AUTHOR
Royal Meteorological Institute, Brussels, Belgium
Centre of Excellence PLECO (Plant and Vegetation Ecology), Department of Biology, University of Antwerp, Wilrijk, Belgium
Piet Termonia
Royal Meteorological Institute, Brussels, Belgium
Department of Physics and Astronomy, Ghent University, Ghent, Belgium
Daan Degrauwe
Royal Meteorological Institute, Brussels, Belgium
Rozemien De Troch
Royal Meteorological Institute, Brussels, Belgium
Department of Physics and Astronomy, Ghent University, Ghent, Belgium
Steven Caluwaerts
Department of Physics and Astronomy, Ghent University, Ghent, Belgium
Geert Smet
Royal Meteorological Institute, Brussels, Belgium
Julie Berckmans
Royal Meteorological Institute, Brussels, Belgium
Centre of Excellence PLECO (Plant and Vegetation Ecology), Department of Biology, University of Antwerp, Wilrijk, Belgium
Alex Deckmyn
Royal Meteorological Institute, Brussels, Belgium
Lesley De Cruz
Royal Meteorological Institute, Brussels, Belgium
Pieter De Meutter
Royal Meteorological Institute, Brussels, Belgium
Department of Physics and Astronomy, Ghent University, Ghent, Belgium
Annelies Duerinckx
Royal Meteorological Institute, Brussels, Belgium
Department of Physics and Astronomy, Ghent University, Ghent, Belgium
Luc Gerard
Royal Meteorological Institute, Brussels, Belgium
Rafiq Hamdi
Royal Meteorological Institute, Brussels, Belgium
Joris Van den Bergh
Royal Meteorological Institute, Brussels, Belgium
Michiel Van Ginderachter
Royal Meteorological Institute, Brussels, Belgium
Department of Physics and Astronomy, Ghent University, Ghent, Belgium
Bert Van Schaeybroeck
Royal Meteorological Institute, Brussels, Belgium
Related authors
No articles found.
Martin Bonte, Lesley De Cruz, Fabian Debal, and Stéphane Vannitsem
EGUsphere, https://doi.org/10.5194/egusphere-2026-1460, https://doi.org/10.5194/egusphere-2026-1460, 2026
Short summary
Short summary
The predictability of the generative AI-based nowcasting model LDCast is evaluated over Belgium, together with the pysteps implementation of the nowcasting algorithm STEPS. It appears that the ensembles of both models correctly estimate the error size through their spread, but fail at spatially representing the error. The analysis is done for two dynamically different types of events, showing how the models adapt their ensembles depending on the situation.
Wout Dewettinck, Hans Van de Vyver, Daan Degrauwe, Rafiq Hamdi, Michiel Van Ginderachter, Bert Van Schaeybroeck, Kwinten Van Weverberg, Kobe Vandelanotte, Steven Caluwaerts, and Piet Termonia
EGUsphere, https://doi.org/10.5194/egusphere-2025-2043, https://doi.org/10.5194/egusphere-2025-2043, 2026
Short summary
Short summary
This study assesses an updated version of the ALARO regional climate model over Belgium at multiple resolutions, by using long-term climate simulations. Incorporating the land surface model SURFEX and simulating at higher resolutions led to improved simulation of temperature, precipitation, and extreme rainfall events. These findings support the value of high-resolution modelling for better representing local climate extremes and informing adaptation measures.
Kwinten Van Weverberg, Nina Neutens, Simon De Corte, Armani Passtoors, Stephan Calderan, Nicolas Ghilain, Ricardo Reinoso-Rondinel, Maarten Reyniers, Aart Overeem, Hans Van de Vyver, Bert Van Schaeybroeck, Bart De Wit, and Remko Uijlenhoet
EGUsphere, https://doi.org/10.5194/egusphere-2026-457, https://doi.org/10.5194/egusphere-2026-457, 2026
Short summary
Short summary
Accurate rainfall estimation remains challenging. This study tested whether signals from telecommunications networks could help track rainfall alongside traditional rain gauges and weather radar. Analyzing four intense summer storms in Belgium using over 2800 microwave links, researchers found that with careful processing, these signals match or outperform standard methods, especially in cities. Integrating such data could improve predictions for urban flooding and extreme weather.
Anouk Dierickx, Wout Dewettinck, Bert Van Schaeybroeck, Lesley De Cruz, Steven Caluwaerts, Piet Termonia, and Hans Van de Vyver
Earth Syst. Sci. Data, 17, 6747–6762, https://doi.org/10.5194/essd-17-6747-2025, https://doi.org/10.5194/essd-17-6747-2025, 2025
Short summary
Short summary
This study introduces the EURO-SUPREME dataset consisting of extreme precipitation events selected from a large ensemble of climate models over Europe. The dataset contains information on extreme precipitation events with a precipitation duration of 1 to 72 h that can lead to flooding, high mortality rates and infrastructure damage. We highlight the usefulness of the dataset as a benchmark for improving high-resolution climate models for risk assessment of future extreme floods.
Dieter Van den Bleeken, Geert Smet, Joris Van den Bergh, Idir Dehmous, Daan Degrauwe, Michiel Van Ginderachter, and Alex Deckmyn
Adv. Sci. Res., 22, 59–67, https://doi.org/10.5194/asr-22-59-2025, https://doi.org/10.5194/asr-22-59-2025, 2025
Short summary
Short summary
To better predict offshore wind energy in Belgium, we improved the Royal Meteorological Institute (RMI) weather model by directly incorporating the effects of wind turbines. We also used AI to account for wind farm wake effects, where turbines slow down wind for other turbines. By combining physics-based models with a neural network trained on observations from the Belgian Offshore Zone, we achieved more accurate forecasts. This helps ensure a stable power grid and supports the growing role of offshore wind in our energy mix.
Alexandros Palatos-Plexidas, Simone Gremmo, Jeroen van Beeck, Lesley De Cruz, and Wim Munters
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-202, https://doi.org/10.5194/wes-2025-202, 2025
Revised manuscript under review for WES
Short summary
Short summary
In this study, we use advanced weather simulations, real-world measurements, and satellite images, showing that modeling wind farm effects improves accuracy, especially in areas influenced by turbine wakes. Focusing on a large wind farm cluster in the North Sea, we also investigate different atmospheric conditions. These findings help quantify the influence of large wind farm clusters, improve predictions, and support planning for future wind energy development.
Stijn Van Leuven, Pieter De Meutter, Johan Camps, Piet Termonia, and Andy Delcloo
Atmos. Chem. Phys., 25, 9199–9218, https://doi.org/10.5194/acp-25-9199-2025, https://doi.org/10.5194/acp-25-9199-2025, 2025
Short summary
Short summary
We use deposition measurements to trace the source of the radioactive isotope 106Ru released into the atmosphere in 2017, which led to detections in Europe and other parts of the Northern Hemisphere. Most frequently, measurements of air concentration are used for such purposes. Our research shows that, while air concentration data can provide more precise results, deposition measurements can still effectively pinpoint the release location, offering a less costly and more versatile alternative.
Vera Melinda Galfi, Tommaso Alberti, Lesley De Cruz, Christian L. E. Franzke, and Valerio Lembo
Nonlin. Processes Geophys., 31, 185–193, https://doi.org/10.5194/npg-31-185-2024, https://doi.org/10.5194/npg-31-185-2024, 2024
Short summary
Short summary
In the online seminar series "Perspectives on climate sciences: from historical developments to future frontiers" (2020–2021), well-known and established scientists from several fields – including mathematics, physics, climate science and ecology – presented their perspectives on the evolution of climate science and on relevant scientific concepts. In this paper, we first give an overview of the content of the seminar series, and then we introduce the written contributions to this special issue.
Jan De Pue, Sebastian Wieneke, Ana Bastos, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Maral Maleki, Fabienne Maignan, Françoise Gellens-Meulenberghs, Ivan Janssens, and Manuela Balzarolo
Biogeosciences, 20, 4795–4818, https://doi.org/10.5194/bg-20-4795-2023, https://doi.org/10.5194/bg-20-4795-2023, 2023
Short summary
Short summary
The gross primary production (GPP) of the terrestrial biosphere is a key source of variability in the global carbon cycle. To estimate this flux, models can rely on remote sensing data (RS-driven), meteorological data (meteo-driven) or a combination of both (hybrid). An intercomparison of 11 models demonstrated that RS-driven models lack the sensitivity to short-term anomalies. Conversely, the simulation of soil moisture dynamics and stress response remains a challenge in meteo-driven models.
Stijn Van Leuven, Pieter De Meutter, Johan Camps, Piet Termonia, and Andy Delcloo
Geosci. Model Dev., 16, 5323–5338, https://doi.org/10.5194/gmd-16-5323-2023, https://doi.org/10.5194/gmd-16-5323-2023, 2023
Short summary
Short summary
Precipitation collects airborne particles and deposits these on the ground. This process is called wet deposition and greatly determines how airborne radioactive particles (released routinely or accidentally) contaminate the surface. In this work we present a new method to improve the calculation of wet deposition in computer models. We apply this method to the existing model FLEXPART by simulating the Fukushima nuclear accident (2011) and show that it improves the simulation of wet deposition.
Jonathan Demaeyer, Jonas Bhend, Sebastian Lerch, Cristina Primo, Bert Van Schaeybroeck, Aitor Atencia, Zied Ben Bouallègue, Jieyu Chen, Markus Dabernig, Gavin Evans, Jana Faganeli Pucer, Ben Hooper, Nina Horat, David Jobst, Janko Merše, Peter Mlakar, Annette Möller, Olivier Mestre, Maxime Taillardat, and Stéphane Vannitsem
Earth Syst. Sci. Data, 15, 2635–2653, https://doi.org/10.5194/essd-15-2635-2023, https://doi.org/10.5194/essd-15-2635-2023, 2023
Short summary
Short summary
A benchmark dataset is proposed to compare different statistical postprocessing methods used in forecasting centers to properly calibrate ensemble weather forecasts. This dataset is based on ensemble forecasts covering a portion of central Europe and includes the corresponding observations. Examples on how to download and use the data are provided, a set of evaluation methods is proposed, and a first benchmark of several methods for the correction of 2 m temperature forecasts is performed.
Jan De Pue, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Manuela Balzarolo, Fabienne Maignan, and Françoise Gellens-Meulenberghs
Biogeosciences, 19, 4361–4386, https://doi.org/10.5194/bg-19-4361-2022, https://doi.org/10.5194/bg-19-4361-2022, 2022
Short summary
Short summary
The functioning of ecosystems involves numerous biophysical processes which interact with each other. Land surface models (LSMs) are used to describe these processes and form an essential component of climate models. In this paper, we evaluate the performance of three LSMs and their interactions with soil moisture and vegetation. Though we found room for improvement in the simulation of soil moisture and drought stress, the main cause of errors was related to the simulated growth of vegetation.
Núria Pérez-Zanón, Louis-Philippe Caron, Silvia Terzago, Bert Van Schaeybroeck, Llorenç Lledó, Nicolau Manubens, Emmanuel Roulin, M. Carmen Alvarez-Castro, Lauriane Batté, Pierre-Antoine Bretonnière, Susana Corti, Carlos Delgado-Torres, Marta Domínguez, Federico Fabiano, Ignazio Giuntoli, Jost von Hardenberg, Eroteida Sánchez-García, Verónica Torralba, and Deborah Verfaillie
Geosci. Model Dev., 15, 6115–6142, https://doi.org/10.5194/gmd-15-6115-2022, https://doi.org/10.5194/gmd-15-6115-2022, 2022
Short summary
Short summary
CSTools (short for Climate Service Tools) is an R package that contains process-based methods for climate forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination, and multivariate verification, as well as basic and advanced tools to obtain tailored products. In addition to describing the structure and methods in the package, we also present three use cases to illustrate the seasonal climate forecast post-processing for specific purposes.
Nicolas Ghilain, Stéphane Vannitsem, Quentin Dalaiden, Hugues Goosse, Lesley De Cruz, and Wenguang Wei
Earth Syst. Sci. Data, 14, 1901–1916, https://doi.org/10.5194/essd-14-1901-2022, https://doi.org/10.5194/essd-14-1901-2022, 2022
Short summary
Short summary
Modeling the climate at high resolution is crucial to represent the snowfall accumulation over the complex orography of the Antarctic coast. While ice cores provide a view constrained spatially but over centuries, climate models can give insight into its spatial distribution, either at high resolution over a short period or vice versa. We downscaled snowfall accumulation from climate model historical simulations (1850–present day) over Dronning Maud Land at 5.5 km using a statistical method.
Gerard van der Schrier, Richard P. Allan, Albert Ossó, Pedro M. Sousa, Hans Van de Vyver, Bert Van Schaeybroeck, Roberto Coscarelli, Angela A. Pasqua, Olga Petrucci, Mary Curley, Mirosław Mietus, Janusz Filipiak, Petr Štěpánek, Pavel Zahradníček, Rudolf Brázdil, Ladislava Řezníčková, Else J. M. van den Besselaar, Ricardo Trigo, and Enric Aguilar
Clim. Past, 17, 2201–2221, https://doi.org/10.5194/cp-17-2201-2021, https://doi.org/10.5194/cp-17-2201-2021, 2021
Short summary
Short summary
The 1921 drought was the most severe drought to hit Europe since the start of the 20th century. Here the climatological description of the drought is coupled to an overview of its impacts, sourced from newspapers, and an analysis of its drivers. The area from Ireland to the Ukraine was affected but hardest hit was the triangle between Brussels, Paris and Lyon. The drought impacts lingered on until well into autumn and winter, affecting water supply and agriculture and livestock farming.
Cited articles
ALADIN international team: The ALADIN project: Mesoscale modelling seen as
a
basic tool for weather forecasting and atmospheric research, WMO Bull., 46,
317–324, 1997.
Chan, S. C., Kendon, E. J., Fowler, H. J., Blenkinsop, S., Roberts, N. M.,
and
Ferro, C. A. T.: The Value of High-Resolution Met Office Regional Climate
Models in the Simulation of Multihourly Precipitation Extremes, J.
Climate, 27, 6155–6174, https://doi.org/10.1175/JCLI-D-13-00723.1, 2014.
Christensen, J. and Christensen, O.: A summary of the PRUDENCE model
projections of changes in European climate by the end of this century,
Climatic Change, 81, 7–30, https://doi.org/10.1007/s10584-006-9210-7, 2007.
Davies, H. C.: A lateral boundary formulation for multi-level prediction
models, Q. J. Roy. Meteor. Soc., 102, 405–418,
https://doi.org/10.1002/qj.49710243210, 1976.
De Meutter, P., Gerard, L., Smet, G., Hamid, K., Hamdi, R., Degrauwe, D.,
and Termonia, P.: Predicting Small-Scale, Short-Lived Downbursts: Case Study
with the NWP Limited-Area ALARO Model for the Pukkelpop Thunderstorm, Mon.
Weather Rev., 143, 742–756, https://doi.org/10.1175/MWR-D-14-00290.1,
2015.
De Troch, R., Hamdi, R., Van de Vyver, H., Geleyn, J.-F., and Termonia, P.:
Multiscale Performance of the ALARO-0 Model for Simulating Extreme Summer
Precipitation Climatology in Belgium, J. Climate, 26, 8895–8915,
https://doi.org/10.1175/JCLI-D-12-00844.1, 2013.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P.,
Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P.,
Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N.,
Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy,
S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P.,
Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette,
J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut,
J.-N., and Vitart,
F.: The ERA-Interim reanalysis: configuration and performance of the data
assimilation system, Q. J. Roy. Meteor. Soc.,
137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Dudhia, J.: A history of mesoscale model development, Asia-Pac. J.
Atmos. Sci., 50, 121–131, https://doi.org/10.1007/s13143-014-0031-8, 2014.
Gerard, L.: An integrated package for subgrid convection, clouds and
precipitation compatible with the meso-gamma scales, Q. J. Roy. Meteor.
Soc., 133, 711–730, 2007.
Gerard, L. and Geleyn, J.-F.: Evolution of a subgrid deep convection
parameterization in a limited area model with increasing resolution, Q.
J. Roy. Meteor. Soc., 131, 2293–2312, 2005.
Gerard, L., Piriou, J.-M., Brožková, R., Geleyn, J.-F., and Banciu,
D.:
Cloud and precipitation parameterization in a meso-gamma-scale operational
weather prediction model, Mon. Weather Rev., 137, 3960–3977, 2009.
Giorgi, F. and Mearns, L. O.: Introduction to special section: Regional
Climate
Modeling Revisited, J. Geophys. Res.-Atmos., 104,
6335–6352, https://doi.org/10.1029/98JD02072, 1999.
Giorgi, F., Jones, C., and Asrar, G. R.: Addressing climate information needs
at the regional level: the CORDEX framework, WMO Bulletin, 58, 175–183,
2009.
Hamdi, R., Giot, O., Troch, R. D., Deckmyn, A., and Termonia, P.: Future
climate of Brussels and Paris for the 2050s under the {A1B} scenario, Urban
Climate, 12, 160–182, https://doi.org/10.1016/j.uclim.2015.03.003, 2015.
Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P. D.,
and New, M.: A European daily high-resolution gridded data set of surface
temperature and precipitation for 1950–2006, J. Geophys.
Res.-Atmos., 113, D20119, https://doi.org/10.1029/2008JD010201, 2008.
Hohenegger, C., Brockhaus, P., and Schär, C.: Towards climate simulations
at
cloud-resolving scales, Meteorol. Z., 17, 383–394,
https://doi.org/10.1127/0941-2948/2008/0303, 2008.
IPCC: Summary for Policymakers, book section SPM, 1–30, Cambridge
University Press, Cambridge, United Kingdom and New York, NY, USA,
https://doi.org/10.1017/CBO9781107415324.004, 2013.
Kendon, E. J., Roberts, N. M., Senior, C. A., and Roberts, M. J.: Realism of
Rainfall in a Very High-Resolution Regional Climate Model, J.
Climate, 25, 5791–5806, https://doi.org/10.1175/JCLI-D-11-00562.1, 2012.
Kotlarski, S., Keuler, K., Christensen, O. B., Colette, A., Déqué,
M., Gobiet, A., Goergen, K., Jacob, D., Lüthi, D., van Meijgaard, E.,
Nikulin, G., Schär, C., Teichmann, C., Vautard, R., Warrach-Sagi, K., and
Wulfmeyer, V.: Regional climate modeling on European scales: a joint standard
evaluation of the EURO-CORDEX RCM ensemble, Geosci. Model Dev., 7,
1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, 2014.
Lin, J.-L., Qian, T., and Shinoda, T.: Stratocumulus Clouds in Southeastern
Pacific Simulated by Eight CMIP5-CFMIP Global Climate Models, J.
Climate, 27, 3000–3022, https://doi.org/10.1175/JCLI-D-13-00376.1, 2014.
Spiridonov, V., Déqué, M., and Somot, S.: ALADIN-CLIMATE: from the
origins to present date, ALADIN Newsletter, 29, 89–92, 2005.
Sun, D.-Z., Yu, Y., and Zhang, T.: Tropical Water Vapor and Cloud Feedbacks
in Climate Models: A Further Assessment Using Coupled Simulations, J.
Climate, 22, 1287–1304, https://doi.org/10.1175/2008JCLI2267.1, 2009.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and
the Experiment Design, B. Am. Meteorol. Soc., 93, 485–498,
https://doi.org/10.1175/BAMS-D-11-00094.1, 2011.
Teutschbein, C. and Seibert, J.: Regional Climate Models for Hydrological
Impact Studies at the Catchment Scale: A Review of Recent Modeling
Strategies, Geography Compass, 4, 834–860,
https://doi.org/10.1111/j.1749-8198.2010.00357.x, 2010.
Uppala, S. M., Kållberg, P. W., Simmons, A. J., Andrae, U., Bechtold, V.
D. C., Fiorino, M., Gibson, J. K., Haseler, J., Hernandez, A., Kelly, G. A.,
Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R. P., Andersson, E.,
Arpe, K., Balmaseda, M. A., Beljaars, A. C. M., Berg, L. V. D., Bidlot, J.,
Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher,
M., Fuentes, M., Hagemann, S., Hólm, E., Hoskins, B. J., Isaksen, L.,
Janssen, P. A. E. M., Jenne, R., Mcnally, A. P., Mahfouf, J.-F., Morcrette,
J.-J., Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A., Trenberth,
K. E., Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J.: The ERA-40
re-analysis, Q. J. Roy. Meteor. Soc., 131,
2961–3012, https://doi.org/10.1256/qj.04.176, 2005.
Short summary
The Royal Meteorological Institute of Belgium and Ghent University have performed two simulations with different horizontal resolutions of the past observed climate of Europe for the period 1979–2010. Of special interest is the new way of handling convective precipitation in the model that was used. Results show that the model is capable of representing the European climate and comparison with other models reveals that precipitation patterns are well represented.
The Royal Meteorological Institute of Belgium and Ghent University have performed two...