Articles | Volume 6, issue 6
https://doi.org/10.5194/gmd-6-1961-2013
© Author(s) 2013. 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-6-1961-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
08 Nov 2013
Development and technical paper |
| 08 Nov 2013
EMPOL 1.0: a new parameterization of pollen emission in numerical weather prediction models
K. Zink
Federal Office of Meteorology and Climatology MeteoSwiss, Zürich, Switzerland
A. Pauling
Federal Office of Meteorology and Climatology MeteoSwiss, Zürich, Switzerland
M. W. Rotach
Institute for Meteorology and Geophysics, University of Innsbruck, Innsbruck, Austria
H. Vogel
Institute for Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
P. Kaufmann
Federal Office of Meteorology and Climatology MeteoSwiss, Zürich, Switzerland
B. Clot
Federal Office of Meteorology and Climatology MeteoSwiss, Zürich, Switzerland
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Cited
43 citations as recorded by crossref.
- Pollen forecasting and its relevance in pollen allergen avoidance C. Suanno et al. https://doi.org/10.1016/j.envres.2021.111150
- All-optical automatic pollen identification: Towards an operational system B. Crouzy et al. https://doi.org/10.1016/j.atmosenv.2016.05.062
- Artificial neural networks can be used for Ambrosia pollen emission parameterization in COSMO-ART C. Burki et al. https://doi.org/10.1016/j.atmosenv.2019.116969
- Quantitative DNA Analyses for Airborne Birch Pollen I. Müller-Germann et al. https://doi.org/10.1371/journal.pone.0140949
- Modelling of airborne birch pollen over Central Europe – model evaluation and sensitivity analysis J. Boreczek et al. https://doi.org/10.1016/j.scitotenv.2025.179873
- Development and implementation of the PEMM model for pollen emission and dispersion in the central Iberian Peninsula L. Tovar et al. https://doi.org/10.1016/j.envpol.2026.128534
- Statistical modelling of non-stationary processes of atmospheric pollution from natural sources: example of birch pollen O. Ritenberga et al. https://doi.org/10.1016/j.agrformet.2016.05.016
- On impact of transport conditions on variability of the seasonal pollen index M. Sofiev https://doi.org/10.1007/s10453-016-9459-x
- Measurement report: Characterization of the vertical distribution of airborne Pinus pollen in the atmosphere with lidar-derived profiles – a modeling case study in the region of Barcelona, NE Spain M. Sicard et al. https://doi.org/10.5194/acp-21-17807-2021
- Incorporation of pollen data in source maps is vital for pollen dispersion models A. Kurganskiy et al. https://doi.org/10.5194/acp-20-2099-2020
- Evaluation of the performance of short-term curated daily airborne grass pollen forecasts in diverse biogeographical regions during the AusPollen Partnership project 2016–2020 K. Emmerson et al. https://doi.org/10.1016/j.aeaoa.2022.100183
- When Do Subpollen Particles Become Relevant for Ice Nucleation Processes in Clouds? S. Werchner et al. https://doi.org/10.1029/2021JD036340
- Designing an automatic pollen monitoring network for direct usage of observations to reconstruct the concentration fields M. Sofiev et al. https://doi.org/10.1016/j.scitotenv.2023.165800
- Simulating the influence of primary biological aerosol particles on clouds by heterogeneous ice nucleation M. Hummel et al. https://doi.org/10.5194/acp-18-15437-2018
- Seasonal Hydrodynamic Forecasts Using the INM-CM5 Model for Estimating the Beginning of Birch Pollen Dispersion S. Emelina et al. https://doi.org/10.1134/S0001433823040059
- Extension of WRF-Chem for birch pollen modelling—a case study for Poland M. Werner et al. https://doi.org/10.1007/s00484-020-02045-1
- Investigation of Primary Factors Affecting the Variation of Modeled Oak Pollen Concentrations: A Case Study for Southeast Texas in 2010 W. Jeon et al. https://doi.org/10.1007/s13143-017-0057-9
- Comparing alder, birch and grass pollen concentrations derived from spatiotemporal statistical and dispersion models across Switzerland B. Valipour Shokouhi et al. https://doi.org/10.1016/j.atmosenv.2025.121486
- Ten questions about pollen and symptom load and the need for indoor measurements in built environment K. Bastl et al. https://doi.org/10.1016/j.buildenv.2016.01.006
- Ragweed pollen production and dispersion modelling within a regional climate system, calibration and application over Europe L. Liu et al. https://doi.org/10.5194/bg-13-2769-2016
- Mapping allergenic pollen vegetation in UK to study environmental exposure and human health R. McInnes et al. https://doi.org/10.1016/j.scitotenv.2017.04.136
- Numerical ragweed pollen forecasts using different source maps: a comparison for France K. Zink et al. https://doi.org/10.1007/s00484-016-1188-x
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- An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating E. Chan et al. https://doi.org/10.5194/gmd-18-1119-2025
- A prognostic pollen emissions model for climate models (PECM1.0) M. Wozniak & A. Steiner https://doi.org/10.5194/gmd-10-4105-2017
- Ice Nucleation Ability of Tree Pollen Altered by Atmospheric Processing E. Gute et al. https://doi.org/10.1021/acsearthspacechem.0c00218
- The need for Pan‐European automatic pollen and fungal spore monitoring: A stakeholder workshop position paper F. Tummon et al. https://doi.org/10.1002/clt2.12015
- Real-time pollen monitoring using digital holography E. Sauvageat et al. https://doi.org/10.5194/amt-13-1539-2020
- Numerical modelling of birch pollen dispersion in Canada A. Robichaud & P. Comtois https://doi.org/10.1016/j.envres.2020.110554
- A systematic review of the role of grass pollen and fungi in thunderstorm asthma N. Idrose et al. https://doi.org/10.1016/j.envres.2019.108911
- Drivers of the fungal spore bioaerosol budget: observational analysis and global modeling R. Janssen et al. https://doi.org/10.5194/acp-21-4381-2021
- Airborne Microalgae: Insights, Opportunities, and Challenges S. Tesson et al. https://doi.org/10.1128/AEM.03333-15
- MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe M. Sofiev et al. https://doi.org/10.5194/acp-15-8115-2015
- Impact of Ragweed Pollen Daily Release Intensity on Long-Range Transport in Western Europe L. Menut et al. https://doi.org/10.3390/atmos12060693
- A real-time calibration method for the numerical pollen forecast model COSMO-ART S. Adamov & A. Pauling https://doi.org/10.1007/s10453-023-09796-5
- Development and evaluation of pollen source methodologies for the Victorian Grass Pollen Emissions Module VGPEM1.0 K. Emmerson et al. https://doi.org/10.5194/gmd-12-2195-2019
- Seasonal Hydrodynamic Forecasts of INM-CM5 Model for Estimation of the Start of the Birch Pollen Season S. Emelina et al. https://doi.org/10.31857/S0002351523040053
- Alder pollen in Finland ripens after a short exposure to warm days in early spring, showing biennial variation in the onset of pollen ripening T. Linkosalo et al. https://doi.org/10.1016/j.agrformet.2017.08.030
- Artemisia pollen dispersal pattern and feasible intervention measures in Hohhot, China Y. Wang et al. https://doi.org/10.1007/s11252-023-01389-x
- The atmospheric composition component of the ICON modeling framework: ICON-ART version 2025.10 G. Hoshyaripour et al. https://doi.org/10.5194/gmd-19-1645-2026
- Quality of the Governing Temperature Variables in WRF in relation to Simulation of Primary Biological Aerosols C. Skjøth et al. https://doi.org/10.1155/2015/412658
- European pollen reanalysis, 1980–2022, for alder, birch, and olive M. Sofiev et al. https://doi.org/10.1038/s41597-024-03686-2
- Development and verification of a taxa-specific gridded pollen modelling system for the UK L. Neal et al. https://doi.org/10.1007/s10453-025-09858-w
43 citations as recorded by crossref.
- Pollen forecasting and its relevance in pollen allergen avoidance C. Suanno et al. https://doi.org/10.1016/j.envres.2021.111150
- All-optical automatic pollen identification: Towards an operational system B. Crouzy et al. https://doi.org/10.1016/j.atmosenv.2016.05.062
- Artificial neural networks can be used for Ambrosia pollen emission parameterization in COSMO-ART C. Burki et al. https://doi.org/10.1016/j.atmosenv.2019.116969
- Quantitative DNA Analyses for Airborne Birch Pollen I. Müller-Germann et al. https://doi.org/10.1371/journal.pone.0140949
- Modelling of airborne birch pollen over Central Europe – model evaluation and sensitivity analysis J. Boreczek et al. https://doi.org/10.1016/j.scitotenv.2025.179873
- Development and implementation of the PEMM model for pollen emission and dispersion in the central Iberian Peninsula L. Tovar et al. https://doi.org/10.1016/j.envpol.2026.128534
- Statistical modelling of non-stationary processes of atmospheric pollution from natural sources: example of birch pollen O. Ritenberga et al. https://doi.org/10.1016/j.agrformet.2016.05.016
- On impact of transport conditions on variability of the seasonal pollen index M. Sofiev https://doi.org/10.1007/s10453-016-9459-x
- Measurement report: Characterization of the vertical distribution of airborne Pinus pollen in the atmosphere with lidar-derived profiles – a modeling case study in the region of Barcelona, NE Spain M. Sicard et al. https://doi.org/10.5194/acp-21-17807-2021
- Incorporation of pollen data in source maps is vital for pollen dispersion models A. Kurganskiy et al. https://doi.org/10.5194/acp-20-2099-2020
- Evaluation of the performance of short-term curated daily airborne grass pollen forecasts in diverse biogeographical regions during the AusPollen Partnership project 2016–2020 K. Emmerson et al. https://doi.org/10.1016/j.aeaoa.2022.100183
- When Do Subpollen Particles Become Relevant for Ice Nucleation Processes in Clouds? S. Werchner et al. https://doi.org/10.1029/2021JD036340
- Designing an automatic pollen monitoring network for direct usage of observations to reconstruct the concentration fields M. Sofiev et al. https://doi.org/10.1016/j.scitotenv.2023.165800
- Simulating the influence of primary biological aerosol particles on clouds by heterogeneous ice nucleation M. Hummel et al. https://doi.org/10.5194/acp-18-15437-2018
- Seasonal Hydrodynamic Forecasts Using the INM-CM5 Model for Estimating the Beginning of Birch Pollen Dispersion S. Emelina et al. https://doi.org/10.1134/S0001433823040059
- Extension of WRF-Chem for birch pollen modelling—a case study for Poland M. Werner et al. https://doi.org/10.1007/s00484-020-02045-1
- Investigation of Primary Factors Affecting the Variation of Modeled Oak Pollen Concentrations: A Case Study for Southeast Texas in 2010 W. Jeon et al. https://doi.org/10.1007/s13143-017-0057-9
- Comparing alder, birch and grass pollen concentrations derived from spatiotemporal statistical and dispersion models across Switzerland B. Valipour Shokouhi et al. https://doi.org/10.1016/j.atmosenv.2025.121486
- Ten questions about pollen and symptom load and the need for indoor measurements in built environment K. Bastl et al. https://doi.org/10.1016/j.buildenv.2016.01.006
- Ragweed pollen production and dispersion modelling within a regional climate system, calibration and application over Europe L. Liu et al. https://doi.org/10.5194/bg-13-2769-2016
- Mapping allergenic pollen vegetation in UK to study environmental exposure and human health R. McInnes et al. https://doi.org/10.1016/j.scitotenv.2017.04.136
- Numerical ragweed pollen forecasts using different source maps: a comparison for France K. Zink et al. https://doi.org/10.1007/s00484-016-1188-x
- Changes in domestic heating fuel use in Greece: effects on atmospheric chemistry and radiation E. Athanasopoulou et al. https://doi.org/10.5194/acp-17-10597-2017
- An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating E. Chan et al. https://doi.org/10.5194/gmd-18-1119-2025
- A prognostic pollen emissions model for climate models (PECM1.0) M. Wozniak & A. Steiner https://doi.org/10.5194/gmd-10-4105-2017
- Ice Nucleation Ability of Tree Pollen Altered by Atmospheric Processing E. Gute et al. https://doi.org/10.1021/acsearthspacechem.0c00218
- The need for Pan‐European automatic pollen and fungal spore monitoring: A stakeholder workshop position paper F. Tummon et al. https://doi.org/10.1002/clt2.12015
- Real-time pollen monitoring using digital holography E. Sauvageat et al. https://doi.org/10.5194/amt-13-1539-2020
- Numerical modelling of birch pollen dispersion in Canada A. Robichaud & P. Comtois https://doi.org/10.1016/j.envres.2020.110554
- A systematic review of the role of grass pollen and fungi in thunderstorm asthma N. Idrose et al. https://doi.org/10.1016/j.envres.2019.108911
- Drivers of the fungal spore bioaerosol budget: observational analysis and global modeling R. Janssen et al. https://doi.org/10.5194/acp-21-4381-2021
- Airborne Microalgae: Insights, Opportunities, and Challenges S. Tesson et al. https://doi.org/10.1128/AEM.03333-15
- MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe M. Sofiev et al. https://doi.org/10.5194/acp-15-8115-2015
- Impact of Ragweed Pollen Daily Release Intensity on Long-Range Transport in Western Europe L. Menut et al. https://doi.org/10.3390/atmos12060693
- A real-time calibration method for the numerical pollen forecast model COSMO-ART S. Adamov & A. Pauling https://doi.org/10.1007/s10453-023-09796-5
- Development and evaluation of pollen source methodologies for the Victorian Grass Pollen Emissions Module VGPEM1.0 K. Emmerson et al. https://doi.org/10.5194/gmd-12-2195-2019
- Seasonal Hydrodynamic Forecasts of INM-CM5 Model for Estimation of the Start of the Birch Pollen Season S. Emelina et al. https://doi.org/10.31857/S0002351523040053
- Alder pollen in Finland ripens after a short exposure to warm days in early spring, showing biennial variation in the onset of pollen ripening T. Linkosalo et al. https://doi.org/10.1016/j.agrformet.2017.08.030
- Artemisia pollen dispersal pattern and feasible intervention measures in Hohhot, China Y. Wang et al. https://doi.org/10.1007/s11252-023-01389-x
- The atmospheric composition component of the ICON modeling framework: ICON-ART version 2025.10 G. Hoshyaripour et al. https://doi.org/10.5194/gmd-19-1645-2026
- Quality of the Governing Temperature Variables in WRF in relation to Simulation of Primary Biological Aerosols C. Skjøth et al. https://doi.org/10.1155/2015/412658
- European pollen reanalysis, 1980–2022, for alder, birch, and olive M. Sofiev et al. https://doi.org/10.1038/s41597-024-03686-2
- Development and verification of a taxa-specific gridded pollen modelling system for the UK L. Neal et al. https://doi.org/10.1007/s10453-025-09858-w
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