Articles | Volume 19, issue 2
https://doi.org/10.5194/acp-19-987-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-19-987-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Jan 2019
Research article |
| 24 Jan 2019
| 24 Jan 2019
The value of satellite observations in the analysis and short-range prediction of Asian dust
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Francesca Di Giuseppe
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Luke Jones
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Vincent-Henri Peuch
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Samuel Rémy
Institut Pierre-Simon Laplace, CNRS/Sorbonne Université, Paris, France
Xiaoye Zhang
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, China
Center for Excellence in Regional Atmospheric Environment, IUE, CAS, Beijing, China
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Total article views: 3,542 (including HTML, PDF, and XML)
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Total article views: 1,096 (including HTML, PDF, and XML)
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Cited
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- A Global Bottom‐Up Approach to Estimate Fuel Consumed by Fires Using Above Ground Biomass Observations F. Di Giuseppe et al. https://doi.org/10.1029/2021GL095452
- Worldwide validation of CAMS and MERRA-2 reanalysis aerosol optical depth products using 15 years of AERONET observations C. Gueymard & D. Yang https://doi.org/10.1016/j.atmosenv.2019.117216
- Implementation of an ensemble Kalman filter in the Community Multiscale Air Quality model (CMAQ model v5.1) for data assimilation of ground-level PM2.5 S. Park et al. https://doi.org/10.5194/gmd-15-2773-2022
- Length Scale Analyses of Background Error Covariances for EnKF and EnSRF Data Assimilation S. Park et al. https://doi.org/10.3390/atmos13020160
- Improving Dust Aerosol Optical Depth (DAOD) Retrieval from the GEOKOMPSAT-2A (GK-2A) Satellite for Daytime and Nighttime Monitoring S. Ahn et al. https://doi.org/10.3390/s24051490
- Modeling an Extreme Dust Deposition Event to the French Alpine Seasonal Snowpack in April 2018: Meteorological Context and Predictions of Dust Deposition F. Baladima et al. https://doi.org/10.1029/2021JD035745
- El Niño Southern oscillation events contribute significantly to the interannual variations of dust activity over East Asia R. Zhao et al. https://doi.org/10.1016/j.atmosres.2024.107846
- Machine learning for observation bias correction with application to dust storm data assimilation J. Jin et al. https://doi.org/10.5194/acp-19-10009-2019
- Factors affecting particle number size distributions at a suburban and a rural site at the Anatolian Plateau E. Uzunpınar et al. https://doi.org/10.1016/j.apr.2022.101422
- The Effects of Offshore Wind Interpolation Methods on Wind Power Density and Energy Assessment T. Soukissian & V. Apostolou https://doi.org/10.3390/en19040971
- Performance comparisons of the three data assimilation methods for improved predictability of PM2·5: Ensemble Kalman filter, ensemble square root filter, and three-dimensional variational methods U. Dash et al. https://doi.org/10.1016/j.envpol.2023.121099
- Modification of Saharan dust size distribution during its transport over the Anatolian Plateau E. Uzunpinar et al. https://doi.org/10.1016/j.scitotenv.2023.164646
- Use of Satellite Data for Air Pollution Modeling in Bulgaria E. Georgieva et al. https://doi.org/10.3390/earth2030034
- Modelling the 2021 East Asia super dust storm using FLEXPART and FLEXDUST and its comparison with reanalyses and observations H. Tang et al. https://doi.org/10.3389/fenvs.2022.1013875
- Vertical aerosol data assimilation technology and application based on satellite and ground lidar: A review and outlook T. Yang et al. https://doi.org/10.1016/j.jes.2022.04.012
- Transport of Mineral Dust Into the Arctic in Two Reanalysis Datasets of Atmospheric Composition S. Böö et al. https://doi.org/10.16993/tellusb.1866
- A new threshold free dust storm detection index based on MODIS reflectance and thermal bands A. Jebali et al. https://doi.org/10.1080/15481603.2021.1988428
- A three-dimensional variational data assimilation system for aerosol optical properties based on WRF-Chem v4.0: design, development, and application of assimilating Himawari-8 aerosol observations D. Wang et al. https://doi.org/10.5194/gmd-15-1821-2022
- Worldwide validation of 8 satellite-derived and reanalysis solar radiation products: A preliminary evaluation and overall metrics for hourly data over 27 years D. Yang & J. Bright https://doi.org/10.1016/j.solener.2020.04.016
- The MONARCH high-resolution reanalysis of desert dust aerosol over Northern Africa, the Middle East and Europe (2007–2016) E. Di Tomaso et al. https://doi.org/10.5194/essd-14-2785-2022
- Assimilation of Aerosol Optical Depth Into the Warn‐on‐Forecast System for Smoke (WoFS‐Smoke) T. Jones et al. https://doi.org/10.1029/2022JD037454
- Multi-Sensor Retrieval of Aerosol Optical Properties for Near-Real-Time Applications Using the Metop Series of Satellites: Concept, Detailed Description, and First Validation M. Grzegorski et al. https://doi.org/10.3390/rs14010085
22 citations as recorded by crossref.
- A Global Bottom‐Up Approach to Estimate Fuel Consumed by Fires Using Above Ground Biomass Observations F. Di Giuseppe et al. https://doi.org/10.1029/2021GL095452
- Worldwide validation of CAMS and MERRA-2 reanalysis aerosol optical depth products using 15 years of AERONET observations C. Gueymard & D. Yang https://doi.org/10.1016/j.atmosenv.2019.117216
- Implementation of an ensemble Kalman filter in the Community Multiscale Air Quality model (CMAQ model v5.1) for data assimilation of ground-level PM2.5 S. Park et al. https://doi.org/10.5194/gmd-15-2773-2022
- Length Scale Analyses of Background Error Covariances for EnKF and EnSRF Data Assimilation S. Park et al. https://doi.org/10.3390/atmos13020160
- Improving Dust Aerosol Optical Depth (DAOD) Retrieval from the GEOKOMPSAT-2A (GK-2A) Satellite for Daytime and Nighttime Monitoring S. Ahn et al. https://doi.org/10.3390/s24051490
- Modeling an Extreme Dust Deposition Event to the French Alpine Seasonal Snowpack in April 2018: Meteorological Context and Predictions of Dust Deposition F. Baladima et al. https://doi.org/10.1029/2021JD035745
- El Niño Southern oscillation events contribute significantly to the interannual variations of dust activity over East Asia R. Zhao et al. https://doi.org/10.1016/j.atmosres.2024.107846
- Machine learning for observation bias correction with application to dust storm data assimilation J. Jin et al. https://doi.org/10.5194/acp-19-10009-2019
- Factors affecting particle number size distributions at a suburban and a rural site at the Anatolian Plateau E. Uzunpınar et al. https://doi.org/10.1016/j.apr.2022.101422
- The Effects of Offshore Wind Interpolation Methods on Wind Power Density and Energy Assessment T. Soukissian & V. Apostolou https://doi.org/10.3390/en19040971
- Performance comparisons of the three data assimilation methods for improved predictability of PM2·5: Ensemble Kalman filter, ensemble square root filter, and three-dimensional variational methods U. Dash et al. https://doi.org/10.1016/j.envpol.2023.121099
- Modification of Saharan dust size distribution during its transport over the Anatolian Plateau E. Uzunpinar et al. https://doi.org/10.1016/j.scitotenv.2023.164646
- Use of Satellite Data for Air Pollution Modeling in Bulgaria E. Georgieva et al. https://doi.org/10.3390/earth2030034
- Modelling the 2021 East Asia super dust storm using FLEXPART and FLEXDUST and its comparison with reanalyses and observations H. Tang et al. https://doi.org/10.3389/fenvs.2022.1013875
- Vertical aerosol data assimilation technology and application based on satellite and ground lidar: A review and outlook T. Yang et al. https://doi.org/10.1016/j.jes.2022.04.012
- Transport of Mineral Dust Into the Arctic in Two Reanalysis Datasets of Atmospheric Composition S. Böö et al. https://doi.org/10.16993/tellusb.1866
- A new threshold free dust storm detection index based on MODIS reflectance and thermal bands A. Jebali et al. https://doi.org/10.1080/15481603.2021.1988428
- A three-dimensional variational data assimilation system for aerosol optical properties based on WRF-Chem v4.0: design, development, and application of assimilating Himawari-8 aerosol observations D. Wang et al. https://doi.org/10.5194/gmd-15-1821-2022
- Worldwide validation of 8 satellite-derived and reanalysis solar radiation products: A preliminary evaluation and overall metrics for hourly data over 27 years D. Yang & J. Bright https://doi.org/10.1016/j.solener.2020.04.016
- The MONARCH high-resolution reanalysis of desert dust aerosol over Northern Africa, the Middle East and Europe (2007–2016) E. Di Tomaso et al. https://doi.org/10.5194/essd-14-2785-2022
- Assimilation of Aerosol Optical Depth Into the Warn‐on‐Forecast System for Smoke (WoFS‐Smoke) T. Jones et al. https://doi.org/10.1029/2022JD037454
- Multi-Sensor Retrieval of Aerosol Optical Properties for Near-Real-Time Applications Using the Metop Series of Satellites: Concept, Detailed Description, and First Validation M. Grzegorski et al. https://doi.org/10.3390/rs14010085
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