The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Aerosol analysis and forecast in the European Centre for Medium‐Range Weather Forecasts Integrated Forecast System: 2. Data assimilation
Abstract
This study presents the new aerosol assimilation system, developed at the European Centre for Medium‐Range Weather Forecasts, for the Global and regional Earth‐system Monitoring using Satellite and in‐situ data (GEMS) project. The aerosol modeling and analysis system is fully integrated in the operational four‐dimensional assimilation apparatus. Its purpose is to produce aerosol forecasts and reanalyses of aerosol fields using optical depth data from satellite sensors. This paper is the second of a series which describes the GEMS aerosol effort. It focuses on the theoretical architecture and practical implementation of the aerosol assimilation system. It also provides a discussion of the background errors and observations errors for the aerosol fields, and presents a subset of results from the 2‐year reanalysis which has been run for 2003 and 2004 using data from the Moderate Resolution Imaging Spectroradiometer on the Aqua and Terra satellites. Independent data sets are used to show that despite some compromises that have been made for feasibility reasons in regards to the choice of control variable and error characteristics, the analysis is very skillful in drawing to the observations and in improving the forecasts of aerosol optical depth.
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Cites
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The MODIS Aerosol Algorithm, Products, and Validation
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Cited by
Bounding Global Aerosol Radiative Forcing of Climate Change
Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson‐Parris, D., Boucher, O., Carslaw, K. S., Christensen, M., Daniau, A. ‐., et al. (2020) · Reviews of Geophysics · doi:10.1029/2019rg000660 · Cited by 1,116
“By determining the anthropogenic contribution to τPDa in the Monitoring At-705 mospheric Composition and Climate (MACC) Reanalysis (Benedetti et al., 2009), Bellouin,706 Quaas, et al. (2013) determine ∆τa as 0.06.”
BackgroundInfluentialSelf-citationGlobal 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
Gueymard, C. A., & Yang, D. (2020) · Atmospheric Environment · doi:10.1016/j.atmosenv.2019.117216 · Cited by 292
MAC‐v1: A new global aerosol climatology for climate studies
Kinne, S., O'Donnel, D., Stier, P., Kloster, S., Zhang, K., Schmidt, H., Rast, S., Giorgetta, M., Eck, T. F., & Stevens, B. (2013) · Journal of Advances in Modeling Earth Systems · doi:10.1002/jame.20035 · Cited by 253
Self-citation
Metadata
- Authors
- Benedetti, A., Morcrette, J. ‐., Boucher, O., Dethof, A., Engelen, R. J., Fisher, M., Flentje, H., Huneeus, N., Jones, L., Kaiser, J. W., Kinne, S., Mangold, A., Razinger, M., Simmons, A. J., & Suttie, M.
- Venue
- Journal of Geophysical Research: Atmospheres
- Publisher
- American Geophysical Union (AGU)
- Published
- 2009-07-11
- Volume
- 114
- Issue
- D13
- ISSN
- 0148-0227 (ISSN-L)
- OpenAlex
- W2092548950
- Cited by
- 608
- References
- 24
- FWCI
- 10.55
- Type
- journal article
- Language
- en
- Open access
- closed
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- Benedetti, A., Morcrette, J. ‐., Boucher, O., Dethof, A., Engelen, R. J., Fisher, M., Flentje, H., Huneeus, N., Jones, L., Kaiser, J. W., Kinne, S., Mangold, A., Razinger, M., Simmons, A. J., & Suttie, M. (2009). Aerosol analysis and forecast in the European Centre for Medium‐Range Weather Forecasts Integrated Forecast System: 2. Data assimilation. Journal of Geophysical Research: Atmospheres. https://doi.org/10.1029/2008jd011115
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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.
