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
37 citations as recorded by crossref.
- Pollen forecasting and its relevance in pollen allergen avoidance C. Suanno et al. 10.1016/j.envres.2021.111150
- All-optical automatic pollen identification: Towards an operational system B. Crouzy et al. 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. 10.1016/j.atmosenv.2019.116969
- Quantitative DNA Analyses for Airborne Birch Pollen I. Müller-Germann et al. 10.1371/journal.pone.0140949
- Statistical modelling of non-stationary processes of atmospheric pollution from natural sources: example of birch pollen O. Ritenberga et al. 10.1016/j.agrformet.2016.05.016
- On impact of transport conditions on variability of the seasonal pollen index M. Sofiev 10.1007/s10453-016-9459-x
- Measurement report: Characterization of the vertical distribution of airborne <i>Pinus</i> pollen in the atmosphere with lidar-derived profiles – a modeling case study in the region of Barcelona, NE Spain M. Sicard et al. 10.5194/acp-21-17807-2021
- Incorporation of pollen data in source maps is vital for pollen dispersion models A. Kurganskiy et al. 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. 10.1016/j.aeaoa.2022.100183
- When Do Subpollen Particles Become Relevant for Ice Nucleation Processes in Clouds? S. Werchner et al. 10.1029/2021JD036340
- Designing an automatic pollen monitoring network for direct usage of observations to reconstruct the concentration fields M. Sofiev et al. 10.1016/j.scitotenv.2023.165800
- Simulating the influence of primary biological aerosol particles on clouds by heterogeneous ice nucleation M. Hummel et al. 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. 10.1134/S0001433823040059
- Extension of WRF-Chem for birch pollen modelling—a case study for Poland M. Werner et al. 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. 10.1007/s13143-017-0057-9
- Ten questions about pollen and symptom load and the need for indoor measurements in built environment K. Bastl et al. 10.1016/j.buildenv.2016.01.006
- Mapping allergenic pollen vegetation in UK to study environmental exposure and human health R. McInnes et al. 10.1016/j.scitotenv.2017.04.136
- Numerical ragweed pollen forecasts using different source maps: a comparison for France K. Zink et al. 10.1007/s00484-016-1188-x
- Changes in domestic heating fuel use in Greece: effects on atmospheric chemistry and radiation E. Athanasopoulou et al. 10.5194/acp-17-10597-2017
- A prognostic pollen emissions model for climate models (PECM1.0) M. Wozniak & A. Steiner 10.5194/gmd-10-4105-2017
- Ice Nucleation Ability of Tree Pollen Altered by Atmospheric Processing E. Gute et al. 10.1021/acsearthspacechem.0c00218
- The need for Pan‐European automatic pollen and fungal spore monitoring: A stakeholder workshop position paper F. Tummon et al. 10.1002/clt2.12015
- Real-time pollen monitoring using digital holography E. Sauvageat et al. 10.5194/amt-13-1539-2020
- Numerical modelling of birch pollen dispersion in Canada A. Robichaud & P. Comtois 10.1016/j.envres.2020.110554
- A systematic review of the role of grass pollen and fungi in thunderstorm asthma N. Idrose et al. 10.1016/j.envres.2019.108911
- Drivers of the fungal spore bioaerosol budget: observational analysis and global modeling R. Janssen et al. 10.5194/acp-21-4381-2021
- Airborne Microalgae: Insights, Opportunities, and Challenges S. Tesson et al. 10.1128/AEM.03333-15
- MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe M. Sofiev et al. 10.5194/acp-15-8115-2015
- Impact of Ragweed Pollen Daily Release Intensity on Long-Range Transport in Western Europe L. Menut et al. 10.3390/atmos12060693
- A real-time calibration method for the numerical pollen forecast model COSMO-ART S. Adamov & A. Pauling 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. 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. 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. 10.1016/j.agrformet.2017.08.030
- Artemisia pollen dispersal pattern and feasible intervention measures in Hohhot, China Y. Wang et al. 10.1007/s11252-023-01389-x
- Quality of the Governing Temperature Variables in WRF in relation to Simulation of Primary Biological Aerosols C. Skjøth et al. 10.1155/2015/412658
- High temporal resolution of airborne Ambrosia pollen measurements above the source reveals emission characteristics B. Šikoparija et al. 10.1016/j.atmosenv.2018.08.040
- Stochastic flowering phenology in Dactylis glomerata populations described by Markov chain modelling C. Frisk et al. 10.1007/s10453-020-09685-1
35 citations as recorded by crossref.
- Pollen forecasting and its relevance in pollen allergen avoidance C. Suanno et al. 10.1016/j.envres.2021.111150
- All-optical automatic pollen identification: Towards an operational system B. Crouzy et al. 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. 10.1016/j.atmosenv.2019.116969
- Quantitative DNA Analyses for Airborne Birch Pollen I. Müller-Germann et al. 10.1371/journal.pone.0140949
- Statistical modelling of non-stationary processes of atmospheric pollution from natural sources: example of birch pollen O. Ritenberga et al. 10.1016/j.agrformet.2016.05.016
- On impact of transport conditions on variability of the seasonal pollen index M. Sofiev 10.1007/s10453-016-9459-x
- Measurement report: Characterization of the vertical distribution of airborne <i>Pinus</i> pollen in the atmosphere with lidar-derived profiles – a modeling case study in the region of Barcelona, NE Spain M. Sicard et al. 10.5194/acp-21-17807-2021
- Incorporation of pollen data in source maps is vital for pollen dispersion models A. Kurganskiy et al. 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. 10.1016/j.aeaoa.2022.100183
- When Do Subpollen Particles Become Relevant for Ice Nucleation Processes in Clouds? S. Werchner et al. 10.1029/2021JD036340
- Designing an automatic pollen monitoring network for direct usage of observations to reconstruct the concentration fields M. Sofiev et al. 10.1016/j.scitotenv.2023.165800
- Simulating the influence of primary biological aerosol particles on clouds by heterogeneous ice nucleation M. Hummel et al. 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. 10.1134/S0001433823040059
- Extension of WRF-Chem for birch pollen modelling—a case study for Poland M. Werner et al. 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. 10.1007/s13143-017-0057-9
- Ten questions about pollen and symptom load and the need for indoor measurements in built environment K. Bastl et al. 10.1016/j.buildenv.2016.01.006
- Mapping allergenic pollen vegetation in UK to study environmental exposure and human health R. McInnes et al. 10.1016/j.scitotenv.2017.04.136
- Numerical ragweed pollen forecasts using different source maps: a comparison for France K. Zink et al. 10.1007/s00484-016-1188-x
- Changes in domestic heating fuel use in Greece: effects on atmospheric chemistry and radiation E. Athanasopoulou et al. 10.5194/acp-17-10597-2017
- A prognostic pollen emissions model for climate models (PECM1.0) M. Wozniak & A. Steiner 10.5194/gmd-10-4105-2017
- Ice Nucleation Ability of Tree Pollen Altered by Atmospheric Processing E. Gute et al. 10.1021/acsearthspacechem.0c00218
- The need for Pan‐European automatic pollen and fungal spore monitoring: A stakeholder workshop position paper F. Tummon et al. 10.1002/clt2.12015
- Real-time pollen monitoring using digital holography E. Sauvageat et al. 10.5194/amt-13-1539-2020
- Numerical modelling of birch pollen dispersion in Canada A. Robichaud & P. Comtois 10.1016/j.envres.2020.110554
- A systematic review of the role of grass pollen and fungi in thunderstorm asthma N. Idrose et al. 10.1016/j.envres.2019.108911
- Drivers of the fungal spore bioaerosol budget: observational analysis and global modeling R. Janssen et al. 10.5194/acp-21-4381-2021
- Airborne Microalgae: Insights, Opportunities, and Challenges S. Tesson et al. 10.1128/AEM.03333-15
- MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe M. Sofiev et al. 10.5194/acp-15-8115-2015
- Impact of Ragweed Pollen Daily Release Intensity on Long-Range Transport in Western Europe L. Menut et al. 10.3390/atmos12060693
- A real-time calibration method for the numerical pollen forecast model COSMO-ART S. Adamov & A. Pauling 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. 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. 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. 10.1016/j.agrformet.2017.08.030
- Artemisia pollen dispersal pattern and feasible intervention measures in Hohhot, China Y. Wang et al. 10.1007/s11252-023-01389-x
- Quality of the Governing Temperature Variables in WRF in relation to Simulation of Primary Biological Aerosols C. Skjøth et al. 10.1155/2015/412658
2 citations as recorded by crossref.
- High temporal resolution of airborne Ambrosia pollen measurements above the source reveals emission characteristics B. Šikoparija et al. 10.1016/j.atmosenv.2018.08.040
- Stochastic flowering phenology in Dactylis glomerata populations described by Markov chain modelling C. Frisk et al. 10.1007/s10453-020-09685-1
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