Articles | Volume 8, issue 3
https://doi.org/10.5194/acp-8-523-2008
© Author(s) 2008. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
Special issue:
https://doi.org/10.5194/acp-8-523-2008
© Author(s) 2008. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
06 Feb 2008
Towards improving the simulation of meteorological fields in urban areas through updated/advanced surface fluxes description
A. Baklanov
Meteorological Research Department, Danish Meteorological Institute, DMI, Copenhagen, Denmark
P. G. Mestayer
Laboratoire de Mécanique des Fluides, UMR CNRS 6598, Ecole Centrale de Nantes, ECN, France
A. Clappier
La section Sciences et Ingénierie de l'Environnement (SSIE), Ecole Polytechnique Fédérale de Lausanne, EPFL, Switzerland
S. Zilitinkevich
Division of Atmospheric Sciences, University of Helsinki, Finland
S. Joffre
Research & Development, Finnish Meteorological Institute, FMI, Helsinki, Finland
A. Mahura
Meteorological Research Department, Danish Meteorological Institute, DMI, Copenhagen, Denmark
Laboratoire de Mécanique des Fluides, UMR CNRS 6598, Ecole Centrale de Nantes, ECN, France
N. W. Nielsen
Meteorological Research Department, Danish Meteorological Institute, DMI, Copenhagen, Denmark
Viewed
Total article views: 3,234 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Feb 2013, article published on 24 Nov 2005)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,617 | 1,499 | 118 | 3,234 | 114 | 70 |
- HTML: 1,617
- PDF: 1,499
- XML: 118
- Total: 3,234
- BibTeX: 114
- EndNote: 70
Total article views: 2,561 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Feb 2013, article published on 06 Feb 2008)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,353 | 1,104 | 104 | 2,561 | 103 | 67 |
- HTML: 1,353
- PDF: 1,104
- XML: 104
- Total: 2,561
- BibTeX: 103
- EndNote: 67
Total article views: 673 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Feb 2013, article published on 24 Nov 2005)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 264 | 395 | 14 | 673 | 11 | 3 |
- HTML: 264
- PDF: 395
- XML: 14
- Total: 673
- BibTeX: 11
- EndNote: 3
Cited
60 citations as recorded by crossref.
- Real-time air quality forecasting, part II: State of the science, current research needs, and future prospects Y. Zhang et al. 10.1016/j.atmosenv.2012.02.041
- Deep particulate matter forecasting model using correntropy-induced loss J. Kim & C. Lee 10.1007/s12206-021-0817-4
- Morphological Database of Paris for Atmospheric Modeling Purposes A. Tack et al. 10.1109/JSTARS.2012.2201134
- Evaluating the Urban Canopy Scheme TERRA_URB in the COSMO Model for Selected European Cities V. Garbero et al. 10.3390/atmos12020237
- Large scale air pollution prediction with deep convolutional networks G. Huang et al. 10.1007/s11432-020-2951-1
- ВЛИЯНИЕ ЗАСТРОЙКИ НА ЗАГРЯЗНЕНИЕ ГОРОДСКИХ ПОЧВ ТЯЖЕЛЫМИ МЕТАЛЛАМИ В ВОСТОЧНОЙ МОСКВЕ Н. Кошелева et al. 10.36535/0235-5019-2020-12-4
- Deep Learning-Based PM2.5 Long Time-Series Prediction by Fusing Multisource Data—A Case Study of Beijing M. Niu et al. 10.3390/atmos14020340
- A perspective on urban canopy layer modeling for weather, climate and air quality applications J. Ching 10.1016/j.uclim.2013.02.001
- Improving PM2.5 Forecasting and Emission Estimation Based on the Bayesian Optimization Method and the Coupled FLEXPART-WRF Model L. Guo et al. 10.3390/atmos9110428
- Anthropogenic and natural drivers of a strong winter urban heat island in a typical Arctic city M. Varentsov et al. 10.5194/acp-18-17573-2018
- High Resolution Urban Air Quality Modeling by Coupling CFD and Mesoscale Models: a Review R. Kadaverugu et al. 10.1007/s13143-019-00110-3
- Online coupled regional meteorology chemistry models in Europe: current status and prospects A. Baklanov et al. 10.5194/acp-14-317-2014
- Impact of surface variations on the momentum flux above the urban canopy G. Liu & J. Sun 10.1007/s00704-009-0219-5
- Modeling an Urban Heat Island during Extreme Frost in Moscow in January 2017 V. Yushkov et al. 10.1134/S0001433819050128
- A Sensitivity Study of an Effective Aerodynamic Parameter Scheme in Simulating Land–Atmosphere Interaction for a Sea–Land Breeze Case Around the Bohai Gulf of China Z. Zhong et al. 10.1175/JHM-D-16-0184.1
- Enviro-HIRLAM online integrated meteorology–chemistry modelling system: strategy, methodology, developments and applications (v7.2) A. Baklanov et al. 10.5194/gmd-10-2971-2017
- 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
- Fuzzy-based missing value imputation technique for air pollution data A. Mustafi et al. 10.1007/s10462-022-10168-7
- Biomagnetic monitoring combined with support vector machine: a new opportunity for predicting particle-bound-heavy metals Q. Dai et al. 10.1038/s41598-020-65677-8
- Impact of Physics Parameterizations on High-Resolution Air Quality Simulations over the Paris Region L. Jiang et al. 10.3390/atmos11060618
- Joint modelling of obstacle induced and mesoscale changes—Current limits and challenges K. Schlünzen et al. 10.1016/j.jweia.2011.01.009
- Ensemble and enhanced PM10 concentration forecast model based on stepwise regression and wavelet analysis Y. Chen et al. 10.1016/j.atmosenv.2013.04.002
- Air Quality Estimation Using Dendritic Neural Regression with Scale-Free Network-Based Differential Evolution Z. Song et al. 10.3390/atmos12121647
- Deep learning architecture for air quality predictions X. Li et al. 10.1007/s11356-016-7812-9
- A hybrid model based on convolutional neural networks and long short-term memory for ozone concentration prediction U. Pak et al. 10.1007/s11869-018-0585-1
- Сontamination of urban soils with heavy metals in Moscow as affected by building development N. Kosheleva et al. 10.1016/j.scitotenv.2018.04.308
- DeepAirNet: Applying Recurrent Networks for Air Quality Prediction A. V et al. 10.1016/j.procs.2018.05.068
- ENVIRO-HIRLAM: on-line coupled modelling of urban meteorology and air pollution A. Baklanov et al. 10.5194/asr-2-41-2008
- Chemical weather forecasting: a new concept of integrated modelling A. Baklanov 10.5194/asr-4-23-2010
- Estimation of urban sensible heat flux using a dense wireless network of observations D. Nadeau et al. 10.1007/s10652-009-9150-7
- UrbClim – A fast urban boundary layer climate model K. De Ridder et al. 10.1016/j.uclim.2015.01.001
- Towards seamless environmental prediction – development of Pan-Eurasian EXperiment (PEEX) modelling platform A. Mahura et al. 10.1080/20964471.2024.2325019
- Modeling the Surface Energy Budget during the Thawing Period of the 2006 Montreal Urban Snow Experiment S. Leroyer et al. 10.1175/2009JAMC2153.1
- Deep learning-based PM2.5 prediction considering the spatiotemporal correlations: A case study of Beijing, China U. Pak et al. 10.1016/j.scitotenv.2019.07.367
- Daily urban air quality index forecasting based on variational mode decomposition, sample entropy and LSTM neural network Q. Wu & H. Lin 10.1016/j.scs.2019.101657
- Improving Intra-Urban Prediction of Atmospheric Fine Particles Using a Hybrid Deep Learning Approach Z. Zhang et al. 10.3390/atmos14030599
- Extended-Range Forecasting of PM2.5 Based on the S2S: A Case Study in Shanghai, China Y. Qu et al. 10.3389/fenvs.2022.882741
- Megacities, air quality and climate A. Baklanov et al. 10.1016/j.atmosenv.2015.11.059
- High-resolution urban observation network for user-specific meteorological information service in the Seoul Metropolitan Area, South Korea M. Park et al. 10.5194/amt-10-1575-2017
- An experimental study of atmospheric turbulence characteristics in an urban canyon A. Pashkin et al. 10.1088/1755-1315/386/1/012035
- On the Ensemble of Recurrent Neural Network for Air Pollution Forecasting: Issues and Challenges O. Surakhi et al. 10.25046/aj050265
- Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation X. Li et al. 10.1016/j.envpol.2017.08.114
- Advances in air quality research – current and emerging challenges R. Sokhi et al. 10.5194/acp-22-4615-2022
- Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF–Chem CO tracer model P. Saide et al. 10.1016/j.atmosenv.2011.02.001
- 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
- Assessing the Departures from the Energy- and Flux-Budget (EFB) Model in Heterogeneous and Urbanized Environment for Stable Atmospheric Stratification S. Trini Castelli et al. 10.1007/s10546-023-00785-2
- Influences of updated land-use datasets on WRF simulations for two Austrian regions I. Schicker et al. 10.1007/s00703-015-0416-y
- A novel optimal-hybrid model for daily air quality index prediction considering air pollutant factors Q. Wu & H. Lin 10.1016/j.scitotenv.2019.05.288
- AQE-Net: A Deep Learning Model for Estimating Air Quality of Karachi City from Mobile Images M. Ahmed et al. 10.3390/rs14225732
- Impact of surface variations on the momentum flux above the urban canopy G. Liu & J. Sun 10.1007/s00704-009-0219-5
- Urbanization influence on meteorological parameters of air pollution: Vilnius case study A. Mažeikis 10.5200/baltica.2013.26.06
- A perspective on urban canopy layer modeling for weather, climate and air quality applications J. Ching 10.1016/j.uclim.2013.02.001
- Modelling the impact of urbanisation on regional climate in the Greater London Area D. Grawe et al. 10.1002/joc.3589
- The surface energy balance and the mixing height in urban areas—activities and recommendations of COST-Action 715 M. Piringer et al. 10.1007/s10546-007-9170-0
- Mapping urban climate zones and quantifying climate behaviors – An application on Toulouse urban area (France) T. Houet & G. Pigeon 10.1016/j.envpol.2010.12.027
- The influence of large convective eddies on the surface-layer turbulence S. Zilitinkevich et al. 10.1256/qj.05.79
- Evaluation of high-resolution forecasts with the non-hydrostaticnumerical weather prediction model Lokalmodell for urban air pollutionepisodes in Helsinki, Oslo and Valencia B. Fay & L. Neunhäuserer 10.5194/acp-6-2107-2006
- Towards urbanisation of the non-hydrostatic numerical weather prediction model Lokalmodell (LM) L. Neunhäuserer et al. 10.1007/s10546-007-9159-8
- Integrated systems for forecasting urban meteorology, air pollution and population exposure A. Baklanov et al. 10.5194/acp-7-855-2007
- Anthropogenic Meso-Meteorological Feedbacks: A Review of a Recent Research A. Ginzburg & P. Demchenko 10.1134/S0001433819060045
49 citations as recorded by crossref.
- Real-time air quality forecasting, part II: State of the science, current research needs, and future prospects Y. Zhang et al. 10.1016/j.atmosenv.2012.02.041
- Deep particulate matter forecasting model using correntropy-induced loss J. Kim & C. Lee 10.1007/s12206-021-0817-4
- Morphological Database of Paris for Atmospheric Modeling Purposes A. Tack et al. 10.1109/JSTARS.2012.2201134
- Evaluating the Urban Canopy Scheme TERRA_URB in the COSMO Model for Selected European Cities V. Garbero et al. 10.3390/atmos12020237
- Large scale air pollution prediction with deep convolutional networks G. Huang et al. 10.1007/s11432-020-2951-1
- ВЛИЯНИЕ ЗАСТРОЙКИ НА ЗАГРЯЗНЕНИЕ ГОРОДСКИХ ПОЧВ ТЯЖЕЛЫМИ МЕТАЛЛАМИ В ВОСТОЧНОЙ МОСКВЕ Н. Кошелева et al. 10.36535/0235-5019-2020-12-4
- Deep Learning-Based PM2.5 Long Time-Series Prediction by Fusing Multisource Data—A Case Study of Beijing M. Niu et al. 10.3390/atmos14020340
- A perspective on urban canopy layer modeling for weather, climate and air quality applications J. Ching 10.1016/j.uclim.2013.02.001
- Improving PM2.5 Forecasting and Emission Estimation Based on the Bayesian Optimization Method and the Coupled FLEXPART-WRF Model L. Guo et al. 10.3390/atmos9110428
- Anthropogenic and natural drivers of a strong winter urban heat island in a typical Arctic city M. Varentsov et al. 10.5194/acp-18-17573-2018
- High Resolution Urban Air Quality Modeling by Coupling CFD and Mesoscale Models: a Review R. Kadaverugu et al. 10.1007/s13143-019-00110-3
- Online coupled regional meteorology chemistry models in Europe: current status and prospects A. Baklanov et al. 10.5194/acp-14-317-2014
- Impact of surface variations on the momentum flux above the urban canopy G. Liu & J. Sun 10.1007/s00704-009-0219-5
- Modeling an Urban Heat Island during Extreme Frost in Moscow in January 2017 V. Yushkov et al. 10.1134/S0001433819050128
- A Sensitivity Study of an Effective Aerodynamic Parameter Scheme in Simulating Land–Atmosphere Interaction for a Sea–Land Breeze Case Around the Bohai Gulf of China Z. Zhong et al. 10.1175/JHM-D-16-0184.1
- Enviro-HIRLAM online integrated meteorology–chemistry modelling system: strategy, methodology, developments and applications (v7.2) A. Baklanov et al. 10.5194/gmd-10-2971-2017
- 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
- Fuzzy-based missing value imputation technique for air pollution data A. Mustafi et al. 10.1007/s10462-022-10168-7
- Biomagnetic monitoring combined with support vector machine: a new opportunity for predicting particle-bound-heavy metals Q. Dai et al. 10.1038/s41598-020-65677-8
- Impact of Physics Parameterizations on High-Resolution Air Quality Simulations over the Paris Region L. Jiang et al. 10.3390/atmos11060618
- Joint modelling of obstacle induced and mesoscale changes—Current limits and challenges K. Schlünzen et al. 10.1016/j.jweia.2011.01.009
- Ensemble and enhanced PM10 concentration forecast model based on stepwise regression and wavelet analysis Y. Chen et al. 10.1016/j.atmosenv.2013.04.002
- Air Quality Estimation Using Dendritic Neural Regression with Scale-Free Network-Based Differential Evolution Z. Song et al. 10.3390/atmos12121647
- Deep learning architecture for air quality predictions X. Li et al. 10.1007/s11356-016-7812-9
- A hybrid model based on convolutional neural networks and long short-term memory for ozone concentration prediction U. Pak et al. 10.1007/s11869-018-0585-1
- Сontamination of urban soils with heavy metals in Moscow as affected by building development N. Kosheleva et al. 10.1016/j.scitotenv.2018.04.308
- DeepAirNet: Applying Recurrent Networks for Air Quality Prediction A. V et al. 10.1016/j.procs.2018.05.068
- ENVIRO-HIRLAM: on-line coupled modelling of urban meteorology and air pollution A. Baklanov et al. 10.5194/asr-2-41-2008
- Chemical weather forecasting: a new concept of integrated modelling A. Baklanov 10.5194/asr-4-23-2010
- Estimation of urban sensible heat flux using a dense wireless network of observations D. Nadeau et al. 10.1007/s10652-009-9150-7
- UrbClim – A fast urban boundary layer climate model K. De Ridder et al. 10.1016/j.uclim.2015.01.001
- Towards seamless environmental prediction – development of Pan-Eurasian EXperiment (PEEX) modelling platform A. Mahura et al. 10.1080/20964471.2024.2325019
- Modeling the Surface Energy Budget during the Thawing Period of the 2006 Montreal Urban Snow Experiment S. Leroyer et al. 10.1175/2009JAMC2153.1
- Deep learning-based PM2.5 prediction considering the spatiotemporal correlations: A case study of Beijing, China U. Pak et al. 10.1016/j.scitotenv.2019.07.367
- Daily urban air quality index forecasting based on variational mode decomposition, sample entropy and LSTM neural network Q. Wu & H. Lin 10.1016/j.scs.2019.101657
- Improving Intra-Urban Prediction of Atmospheric Fine Particles Using a Hybrid Deep Learning Approach Z. Zhang et al. 10.3390/atmos14030599
- Extended-Range Forecasting of PM2.5 Based on the S2S: A Case Study in Shanghai, China Y. Qu et al. 10.3389/fenvs.2022.882741
- Megacities, air quality and climate A. Baklanov et al. 10.1016/j.atmosenv.2015.11.059
- High-resolution urban observation network for user-specific meteorological information service in the Seoul Metropolitan Area, South Korea M. Park et al. 10.5194/amt-10-1575-2017
- An experimental study of atmospheric turbulence characteristics in an urban canyon A. Pashkin et al. 10.1088/1755-1315/386/1/012035
- On the Ensemble of Recurrent Neural Network for Air Pollution Forecasting: Issues and Challenges O. Surakhi et al. 10.25046/aj050265
- Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation X. Li et al. 10.1016/j.envpol.2017.08.114
- Advances in air quality research – current and emerging challenges R. Sokhi et al. 10.5194/acp-22-4615-2022
- Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF–Chem CO tracer model P. Saide et al. 10.1016/j.atmosenv.2011.02.001
- 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
- Assessing the Departures from the Energy- and Flux-Budget (EFB) Model in Heterogeneous and Urbanized Environment for Stable Atmospheric Stratification S. Trini Castelli et al. 10.1007/s10546-023-00785-2
- Influences of updated land-use datasets on WRF simulations for two Austrian regions I. Schicker et al. 10.1007/s00703-015-0416-y
- A novel optimal-hybrid model for daily air quality index prediction considering air pollutant factors Q. Wu & H. Lin 10.1016/j.scitotenv.2019.05.288
- AQE-Net: A Deep Learning Model for Estimating Air Quality of Karachi City from Mobile Images M. Ahmed et al. 10.3390/rs14225732
11 citations as recorded by crossref.
- Impact of surface variations on the momentum flux above the urban canopy G. Liu & J. Sun 10.1007/s00704-009-0219-5
- Urbanization influence on meteorological parameters of air pollution: Vilnius case study A. Mažeikis 10.5200/baltica.2013.26.06
- A perspective on urban canopy layer modeling for weather, climate and air quality applications J. Ching 10.1016/j.uclim.2013.02.001
- Modelling the impact of urbanisation on regional climate in the Greater London Area D. Grawe et al. 10.1002/joc.3589
- The surface energy balance and the mixing height in urban areas—activities and recommendations of COST-Action 715 M. Piringer et al. 10.1007/s10546-007-9170-0
- Mapping urban climate zones and quantifying climate behaviors – An application on Toulouse urban area (France) T. Houet & G. Pigeon 10.1016/j.envpol.2010.12.027
- The influence of large convective eddies on the surface-layer turbulence S. Zilitinkevich et al. 10.1256/qj.05.79
- Evaluation of high-resolution forecasts with the non-hydrostaticnumerical weather prediction model Lokalmodell for urban air pollutionepisodes in Helsinki, Oslo and Valencia B. Fay & L. Neunhäuserer 10.5194/acp-6-2107-2006
- Towards urbanisation of the non-hydrostatic numerical weather prediction model Lokalmodell (LM) L. Neunhäuserer et al. 10.1007/s10546-007-9159-8
- Integrated systems for forecasting urban meteorology, air pollution and population exposure A. Baklanov et al. 10.5194/acp-7-855-2007
- Anthropogenic Meso-Meteorological Feedbacks: A Review of a Recent Research A. Ginzburg & P. Demchenko 10.1134/S0001433819060045
Saved (final revised paper)
Saved (preprint)
Latest update: 20 Apr 2024
Altmetrics
Final-revised paper
Preprint