Articles | Volume 10, issue 8
https://doi.org/10.5194/gmd-10-2971-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/gmd-10-2971-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
08 Aug 2017
Model description paper |
| 08 Aug 2017
Enviro-HIRLAM online integrated meteorology–chemistry modelling system: strategy, methodology, developments and applications (v7.2)
Alexander Baklanov
CORRESPONDING AUTHOR
Danish Meteorological Institute (DMI), Copenhagen, Denmark
now at: World Meteorological Organization (WMO), Geneva,
Switzerland
Ulrik Smith Korsholm
Danish Meteorological Institute (DMI), Copenhagen, Denmark
Roman Nuterman
Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
Alexander Mahura
Danish Meteorological Institute (DMI), Copenhagen, Denmark
now at: University of Helsinki, Helsinki, Finland
Kristian Pagh Nielsen
Danish Meteorological Institute (DMI), Copenhagen, Denmark
Bent Hansen Sass
Danish Meteorological Institute (DMI), Copenhagen, Denmark
Alix Rasmussen
Danish Meteorological Institute (DMI), Copenhagen, Denmark
Ashraf Zakey
Danish Meteorological Institute (DMI), Copenhagen, Denmark
now at: The Egyptian Meteorological Authority, Cairo, Egypt
Eigil Kaas
Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
Alexander Kurganskiy
Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
Russian State Hydrometeorological University, St. Petersburg, Russia
Brian Sørensen
Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
Iratxe González-Aparicio
European Commission, DG – Joint Research Centre, Institute for Energy
and Transport, Petten, the Netherlands
Viewed
Total article views: 5,777 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 04 Jan 2017)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 4,215 | 1,377 | 185 | 5,777 | 162 | 186 |
- HTML: 4,215
- PDF: 1,377
- XML: 185
- Total: 5,777
- BibTeX: 162
- EndNote: 186
Total article views: 4,533 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 08 Aug 2017)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 3,356 | 1,028 | 149 | 4,533 | 138 | 142 |
- HTML: 3,356
- PDF: 1,028
- XML: 149
- Total: 4,533
- BibTeX: 138
- EndNote: 142
Total article views: 1,244 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 04 Jan 2017)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 859 | 349 | 36 | 1,244 | 24 | 44 |
- HTML: 859
- PDF: 349
- XML: 36
- Total: 1,244
- BibTeX: 24
- EndNote: 44
Viewed (geographical distribution)
Total article views: 5,777 (including HTML, PDF, and XML)
Thereof 5,395 with geography defined
and 382 with unknown origin.
Total article views: 4,533 (including HTML, PDF, and XML)
Thereof 4,210 with geography defined
and 323 with unknown origin.
Total article views: 1,244 (including HTML, PDF, and XML)
Thereof 1,185 with geography defined
and 59 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
31 citations as recorded by crossref.
- Dispersion of particulate matter (PM<sub>2.5</sub>) from wood combustion for residential heating: optimization of mitigation actions based on large-eddy simulations T. Wolf et al. 10.5194/acp-21-12463-2021
- Enviro-HIRLAM model estimates of elevated black carbon pollution over Ukraine resulted from forest fires M. Savenets et al. 10.5194/acp-22-15777-2022
- Reflections on the Scientific Legacy of Sergej S. Zilitinkevich on PBL and Urban Parameterizations in NWP Models R. Bornstein & A. Baklanov 10.1007/s10546-023-00789-y
- Overview: Recent advances in the understanding of the northern Eurasian environments and of the urban air quality in China – a Pan-Eurasian Experiment (PEEX) programme perspective H. Lappalainen et al. 10.5194/acp-22-4413-2022
- A perspective on the development of gas-phase chemical mechanisms for Eulerian air quality models W. Stockwell et al. 10.1080/10962247.2019.1694605
- Columnar and surface urban aerosol in the Moscow megacity according to measurements and simulations with the COSMO-ART model N. Chubarova et al. 10.5194/acp-22-10443-2022
- Seamless Modeling of Direct and Indirect Aerosol Effects during April 2020 Wildfire Episode in Ukraine M. Savenets et al. 10.3390/atmos15050550
- An enhanced integrated approach to knowledgeable high-resolution environmental quality assessment I. Esau et al. 10.1016/j.envsci.2021.03.020
- Towards seamless environmental prediction – development of Pan-Eurasian EXperiment (PEEX) modelling platform A. Mahura et al. 10.1080/20964471.2024.2325019
- Aerosols, Clusters, Greenhouse Gases, Trace Gases and Boundary-Layer Dynamics: on Feedbacks and Interactions M. Kulmala et al. 10.1007/s10546-022-00769-8
- Integration of Satellite Monitoring and Mathematical Modeling in Analyzing the Nature of Elevated Sulfur Dioxide Concentrations in the Surface Air of Northern Finland E. Dryukova et al. 10.1134/S0001433823040047
- Short-Term Forecast of the Carbon Monoxide Concentration Over the Moscow Region by COSMO-ART A. Revokatova et al. 10.1007/s00024-018-2001-z
- Sensitivity of Radiative Fluxes to Aerosols in the ALADIN-HIRLAM Numerical Weather Prediction System L. Rontu et al. 10.3390/atmos11020205
- THE OPTIMAL SETTINGS FOR THE ONLINE-INTEGRATED MODEL ENVIRO-HIRLAM IN ORDER TO SIMULATE THE ATMOSPHERE-CHEMISTRY INTERACTION FOR THE UKRAINIAN TERRITORY M. Savenets & L. Pysarenko 10.15407/Meteorology2022.02.035
- Implementation of Aerosol-Cloud Interaction within WRF-CHIMERE Online Coupled Model: Evaluation and Investigation of the Indirect Radiative Effect from Anthropogenic Emission Reduction on the Benelux Union P. Tuccella et al. 10.3390/atmos10010020
- Advances in air quality modeling and forecasting A. Baklanov & Y. Zhang 10.1016/j.glt.2020.11.001
- Atmospheric and ecosystem big data providing key contributions in reaching United Nations’ Sustainable Development Goals M. Kulmala et al. 10.1080/20964471.2021.1936943
- A new implementation of FLEXPART with Enviro-HIRLAM meteorological input, and a case study during a heavy air pollution event B. Foreback et al. 10.1080/20964471.2024.2316320
- The On-Line Integrated Mesoscale Chemistry Model BOLCHEM R. Cesari et al. 10.3390/atmos12020192
- Applications of Models and Tools for Mesoscale and Microscale Thermal Analysis in Mid-Latitude Climate Regions—A Review G. Lobaccaro et al. 10.3390/su132212385
- ONLINE INTEGRATED MODELING ON REGIONAL SCALE IN NORTH-WEST RUSSIA: EVALUATION OF AEROSOLS INFLUENCE ON METEOROLOGICAL PARAMETERS G. Nerobelov et al. 10.24057/2071-9388-2018-11-2-73-83
- Numerical modeling of atmospheric pollution in the approaches of random selection of discrete dusting sites and interval distribution of dust size P. Amosov et al. 10.21443/1560-9278-2022-25-1-61-73
- Integration of Satellite Monitoring and Mathematical Modeling in the Analysis of the Nature of Elevated Sulfur Dioxide Concentrations in the Surface Air of the Northern Part of Finland E. Dryukova et al. 10.31857/S0002351523040041
- Modelling and inference of maize pollen emission rate with a Lagrangian dispersal model using Monte Carlo method O. Souhar et al. 10.1017/S0021859620000763
- When Do Subpollen Particles Become Relevant for Ice Nucleation Processes in Clouds? S. Werchner et al. 10.1029/2021JD036340
- Forecasting daily PM2.5 concentrations in Wuhan with a spatial-autocorrelation-based long short-term memory model Z. Liu et al. 10.1016/j.atmosenv.2024.120605
- Incorporation of pollen data in source maps is vital for pollen dispersion models A. Kurganskiy et al. 10.5194/acp-20-2099-2020
- The Silk Road agenda of the Pan-Eurasian Experiment (PEEX) program H. Lappalainen et al. 10.1080/20964471.2018.1437704
- Predicting next hour fine particulate matter (PM2.5) in the Istanbul Metropolitan City using deep learning algorithms with time windowing strategy B. Eren et al. 10.1016/j.uclim.2023.101418
- Current state of aerosol nucleation parameterizations for air-quality and climate modeling K. Semeniuk & A. Dastoor 10.1016/j.atmosenv.2018.01.039
- The HIRLAM fast radiation scheme for mesoscale numerical weather prediction models L. Rontu et al. 10.5194/asr-14-195-2017
29 citations as recorded by crossref.
- Dispersion of particulate matter (PM<sub>2.5</sub>) from wood combustion for residential heating: optimization of mitigation actions based on large-eddy simulations T. Wolf et al. 10.5194/acp-21-12463-2021
- Enviro-HIRLAM model estimates of elevated black carbon pollution over Ukraine resulted from forest fires M. Savenets et al. 10.5194/acp-22-15777-2022
- Reflections on the Scientific Legacy of Sergej S. Zilitinkevich on PBL and Urban Parameterizations in NWP Models R. Bornstein & A. Baklanov 10.1007/s10546-023-00789-y
- Overview: Recent advances in the understanding of the northern Eurasian environments and of the urban air quality in China – a Pan-Eurasian Experiment (PEEX) programme perspective H. Lappalainen et al. 10.5194/acp-22-4413-2022
- A perspective on the development of gas-phase chemical mechanisms for Eulerian air quality models W. Stockwell et al. 10.1080/10962247.2019.1694605
- Columnar and surface urban aerosol in the Moscow megacity according to measurements and simulations with the COSMO-ART model N. Chubarova et al. 10.5194/acp-22-10443-2022
- Seamless Modeling of Direct and Indirect Aerosol Effects during April 2020 Wildfire Episode in Ukraine M. Savenets et al. 10.3390/atmos15050550
- An enhanced integrated approach to knowledgeable high-resolution environmental quality assessment I. Esau et al. 10.1016/j.envsci.2021.03.020
- Towards seamless environmental prediction – development of Pan-Eurasian EXperiment (PEEX) modelling platform A. Mahura et al. 10.1080/20964471.2024.2325019
- Aerosols, Clusters, Greenhouse Gases, Trace Gases and Boundary-Layer Dynamics: on Feedbacks and Interactions M. Kulmala et al. 10.1007/s10546-022-00769-8
- Integration of Satellite Monitoring and Mathematical Modeling in Analyzing the Nature of Elevated Sulfur Dioxide Concentrations in the Surface Air of Northern Finland E. Dryukova et al. 10.1134/S0001433823040047
- Short-Term Forecast of the Carbon Monoxide Concentration Over the Moscow Region by COSMO-ART A. Revokatova et al. 10.1007/s00024-018-2001-z
- Sensitivity of Radiative Fluxes to Aerosols in the ALADIN-HIRLAM Numerical Weather Prediction System L. Rontu et al. 10.3390/atmos11020205
- THE OPTIMAL SETTINGS FOR THE ONLINE-INTEGRATED MODEL ENVIRO-HIRLAM IN ORDER TO SIMULATE THE ATMOSPHERE-CHEMISTRY INTERACTION FOR THE UKRAINIAN TERRITORY M. Savenets & L. Pysarenko 10.15407/Meteorology2022.02.035
- Implementation of Aerosol-Cloud Interaction within WRF-CHIMERE Online Coupled Model: Evaluation and Investigation of the Indirect Radiative Effect from Anthropogenic Emission Reduction on the Benelux Union P. Tuccella et al. 10.3390/atmos10010020
- Advances in air quality modeling and forecasting A. Baklanov & Y. Zhang 10.1016/j.glt.2020.11.001
- Atmospheric and ecosystem big data providing key contributions in reaching United Nations’ Sustainable Development Goals M. Kulmala et al. 10.1080/20964471.2021.1936943
- A new implementation of FLEXPART with Enviro-HIRLAM meteorological input, and a case study during a heavy air pollution event B. Foreback et al. 10.1080/20964471.2024.2316320
- The On-Line Integrated Mesoscale Chemistry Model BOLCHEM R. Cesari et al. 10.3390/atmos12020192
- Applications of Models and Tools for Mesoscale and Microscale Thermal Analysis in Mid-Latitude Climate Regions—A Review G. Lobaccaro et al. 10.3390/su132212385
- ONLINE INTEGRATED MODELING ON REGIONAL SCALE IN NORTH-WEST RUSSIA: EVALUATION OF AEROSOLS INFLUENCE ON METEOROLOGICAL PARAMETERS G. Nerobelov et al. 10.24057/2071-9388-2018-11-2-73-83
- Numerical modeling of atmospheric pollution in the approaches of random selection of discrete dusting sites and interval distribution of dust size P. Amosov et al. 10.21443/1560-9278-2022-25-1-61-73
- Integration of Satellite Monitoring and Mathematical Modeling in the Analysis of the Nature of Elevated Sulfur Dioxide Concentrations in the Surface Air of the Northern Part of Finland E. Dryukova et al. 10.31857/S0002351523040041
- Modelling and inference of maize pollen emission rate with a Lagrangian dispersal model using Monte Carlo method O. Souhar et al. 10.1017/S0021859620000763
- When Do Subpollen Particles Become Relevant for Ice Nucleation Processes in Clouds? S. Werchner et al. 10.1029/2021JD036340
- Forecasting daily PM2.5 concentrations in Wuhan with a spatial-autocorrelation-based long short-term memory model Z. Liu et al. 10.1016/j.atmosenv.2024.120605
- Incorporation of pollen data in source maps is vital for pollen dispersion models A. Kurganskiy et al. 10.5194/acp-20-2099-2020
- The Silk Road agenda of the Pan-Eurasian Experiment (PEEX) program H. Lappalainen et al. 10.1080/20964471.2018.1437704
- Predicting next hour fine particulate matter (PM2.5) in the Istanbul Metropolitan City using deep learning algorithms with time windowing strategy B. Eren et al. 10.1016/j.uclim.2023.101418
2 citations as recorded by crossref.
Saved (final revised paper)
Latest update: 17 Nov 2024
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...
Special issue