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Aerosol analysis and forecast in the European Centre for Medium‐Range Weather Forecasts Integrated Forecast System: Forward modeling
Open accessAbstract
This paper presents the aerosol modeling now part of the ECMWF Integrated Forecasting System (IFS). It includes new prognostic variables for the mass of sea salt, dust, organic matter and black carbon, and sulphate aerosols, interactive with both the dynamics and the physics of the model. It details the various parameterizations used in the IFS to account for the presence of tropospheric aerosols. Details are given of the various formulations and data sets for the sources of the different aerosols and of the parameterizations describing their sinks. Comparisons of monthly mean and daily aerosol quantities like optical depths against satellite and surface observations are presented. The capability of the forecast model to simulate aerosol events is illustrated through comparisons of dust plume events. The ECMWF IFS provides a good description of the horizontal distribution and temporal variability of the main aerosol types. The forecast‐only model described here generally gives the total aerosol optical depth within 0.12 of the relevant observations and can therefore provide the background trajectory information for the aerosol assimilation system described in part 2 of this paper.
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Citations
Cited by
Global dust model intercomparison in AeroCom phase I
Huneeus, N., Schulz, M., Balkanski, Y., Griesfeller, J., Prospero, J., Kinne, S., Bauer, S., Boucher, O., Chin, M., Dentener, F., et al. (2011) · Atmospheric Chemistry and Physics · doi:10.5194/acp-11-7781-2011 · Cited by 1,074
Self-citationColarco, P., da Silva, A., Chin, M., & Diehl, T. (2010) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2009jd012820 · Cited by 668
Benedetti, A., Morcrette, J. ‐., Boucher, O., Dethof, A., Engelen, R. J., Fisher, M., Flentje, H., Huneeus, N., Jones, L., Kaiser, J. W., et al. (2009) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2008jd011115 · Cited by 608
Self-citationGueymard, C. A., & Yang, D. (2020) · Atmospheric Environment · doi:10.1016/j.atmosenv.2019.117216 · Cited by 292
Cloud condensation nuclei concentrations derived from the CAMS reanalysis
Block, K., Haghighatnasab, M., Partridge, D. G., Stier, P., & Quaas, J. (2024) · Earth System Science Data · doi:10.5194/essd-16-443-2024 · Cited by 14
“…to constrain black carbon emissions from wildfires and biomass burning (Kapsomenakis et al., 2022) Freshly emitted BC is partitioned into 80 % hydrophobic and 20 % hydrophilic (Morcrette et al., 2009), while the partitioning of OM is set to 16 % hydrophobic and 84 % hydrophilic (Bozzo et al., 2020).”
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Metadata
- Authors
- Morcrette, J. ‐., Boucher, O., Jones, L., Salmond, D., Bechtold, P., Beljaars, A., Benedetti, A., Bonet, A., Kaiser, J. W., Razinger, M., Schulz, M., Serrar, S., Simmons, A. J., Sofiev, M., Suttie, M., Tompkins, A. M., & Untch, A.
- Venue
- Journal of Geophysical Research: Atmospheres
- Publisher
- American Geophysical Union (AGU)
- Published
- 2009-03-25
- Volume
- 114
- Issue
- D6
- ISSN
- 0148-0227 (ISSN-L)
- OpenAlex
- W1970047006
- Cited by
- 511
- References
- 0
- FWCI
- 7.41
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Morcrette, J. ‐., Boucher, O., Jones, L., Salmond, D., Bechtold, P., Beljaars, A., Benedetti, A., Bonet, A., Kaiser, J. W., Razinger, M., Schulz, M., Serrar, S., Simmons, A. J., Sofiev, M., Suttie, M., Tompkins, A. M., & Untch, A. (2009). Aerosol analysis and forecast in the European Centre for Medium‐Range Weather Forecasts Integrated Forecast System: Forward modeling. Journal of Geophysical Research: Atmospheres. https://doi.org/10.1029/2008jd011235
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
