Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
doi:10.5194/gmd-2016-319
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Model description paper
04 Jan 2017
Review status
This discussion paper is under review for the journal Geoscientific Model Development (GMD).
The Enviro-HIRLAM online integrated meteorology–chemistry modelling system: strategy, methodology, developments, and applications
Alexander Baklanov1,a, Ulrik Smith Korsholm1, Roman Nuterman2, Alexander Mahura1, Kristian Pagh Nielsen1, Bent Hansen Sass1, Alix Rasmussen1, Ashraf Zakey1,b, Eigil Kaas2, Alexander Kurganskiy2,3, Brian Sørensen2, and Iratxe González-Aparicio4 1Danish Meteorological Institute (DMI), Copenhagen, Denmark
2Niels Bohr Institute, University of Copenhagen, Denmark
3Russian State Hydrometeorological University, St.Petersburg, Russia
4European Commission, DG – Joint Research Centre, Institute for Energy and Transport, The Netherlands
anow at: World Meteorological Organization (WMO), Geneva, Switzerland
bnow at: The Egyptian Meteorological Authority, Cairo, Egypt
Abstract. The Environment – HIgh Resolution Limited Area Model (Enviro-HIRLAM) is developed as a fully online integrated numerical weather prediction (NWP) and atmospheric chemical transport (ACT) model for research and forecasting of joint meteorological, chemical and biological weather. The integrated modelling system is developed by DMI in collaboration with several European universities. It is the baseline system in the HIRLAM Chemical Branch and used in several countries and different applications. The development was initiated at DMI more than 15 years ago. The first version was based on the DMI-HIRLAM NWP model with online integrated passive pollutant transport and dispersion, chemistry, aerosol dynamics, deposition and indirect effects. To make the model suitable for chemical weather forecasting (CWF) in urban areas the meteorological part was improved by implementation of urban parameterizations. The dynamical core was improved by implementing a locally mass conserving semi-Lagrangian numerical advection scheme, which improves forecast accuracy and model performance. The latest developing version is based on HIRLAM reference v7.2 with a more advanced and effective chemistry, aerosol multi-compound approach, aerosol feedbacks (direct and semi-direct) on radiation and (first and second indirect effects) on cloud microphysics. Since 2004 the Enviro-HIRLAM is used for different studies, including operational pollen forecasting for Denmark since 2009. Following main research and development strategy the further model developments will be extended towards the new NWP platform – HARMONIE. Different aspects of online coupling methodology, research strategy and possible applications of the modelling system, and fit-for-purpose model configurations for the meteorological and air quality communities are discussed.

Citation: Baklanov, A., Korsholm, U. S., Nuterman, R., Mahura, A., Nielsen, K. P., Sass, B. H., Rasmussen, A., Zakey, A., Kaas, E., Kurganskiy, A., Sørensen, B., and González-Aparicio, I.: The Enviro-HIRLAM online integrated meteorology–chemistry modelling system: strategy, methodology, developments, and applications, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-319, in review, 2017.
Alexander Baklanov et al.
Alexander Baklanov et al.
Alexander Baklanov et al.

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Short summary
The Environment – HIgh Resolution Limited Area Model (Enviro-HIRLAM) is developed as a fully online integrated numerical weather prediction and atmospheric chemical transport model for research and forecasting of joint meteorological, chemical and biological weather. Different aspects of online coupling methodology, research strategy and possible applications of the modelling system, and fit-for-purpose model configurations for the meteorological and air quality communities are discussed.
The Environment – HIgh Resolution Limited Area Model (Enviro-HIRLAM) is developed as a fully...
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