Current state of the global operational aerosol multi-model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP)
dc.contributor.author | Xian, Peng | |
dc.contributor.author | Reid, Jeffrey S. | |
dc.contributor.author | Hyer, Edward J. | |
dc.contributor.author | Sampson, Charles R. | |
dc.contributor.author | Eck, Thomas | |
dc.contributor.author | et al. | |
dc.date.accessioned | 2024-02-14T18:51:12Z | |
dc.date.available | 2024-02-14T18:51:12Z | |
dc.date.issued | 2019-02-04 | |
dc.description | Authors: - Peng Xian, Jeffrey S. Reid, Edward J. Hyer, Charles R. Sampson, Juli I. Rubin, Melanie Ades, Nicole Asencio, Sara Basart, Angela Benedetti, Partha S. Bhattacharjee, Malcolm E. Brooks, Peter R. Colarco, Arlindo M. da Silva, Tom F. Eck, Jonathan Guth, Oriol Jorba, Rostislav Kouznetsov, Zak Kipling, Mikhail Sofiev, Carlos Perez Garcia-Pando, Yaswant Pradhan, Taichu Tanaka, Jun Wang, Douglas L. Westphal, Keiya Yumimoto, Jianglong Zhang | |
dc.description.abstract | Since the first International Cooperative for Aerosol Prediction (ICAP) multi-model ensemble (MME) study, the number of ICAP global operational aerosol models has increased from five to nine. An update of the current ICAP status is provided, along with an evaluation of the performance of ICAP-MME over 2012–2017, with a focus on June 2016–May 2017. Evaluated with ground-based Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) and data assimilation quality MODerate-resolution Imaging Spectroradiometer (MODIS) retrieval products, the ICAP-MME AOD consensus remains the overall top-scoring and most consistent performer among all models in terms of root-mean-square error (RMSE), bias and correlation for total, fine- and coarse-mode AODs as well as dust AOD; this is similar to the first ICAP-MME study. Further, over the years, the performance of ICAP-MME is relatively stable and reliable compared to more variability in the individual models. The extent to which the AOD forecast error of ICAP-MME can be predicted is also examined. Leading predictors are found to be the consensus mean and spread. Regression models of absolute forecast errors were built for AOD forecasts of different lengths for potential applications. ICAP-MME performance in terms of modal AOD RMSEs of the 21 regionally representative sites over 2012–2017 suggests a general tendency for model improvements in fine-mode AOD, especially over Asia. No significant improvement in coarse-mode AOD is found overall for this time period. | |
dc.description.sponsorship | The authors are greatly indebted to their individual programmes for supporting ICAP and the development of the multi-model ensemble. We recognize and appreciate the countless researchers and computer engineers whose work supports the development and distribution of aerosol forecasts. As data assimilation is key to model performance, we are grateful to NASA LANCE-MODIS for providing MODIS near-real-time data used in nearly all of the models here. We also acknowledge the effort of the NASA GSFC AERONET team (project leader Brent Holben) and the various site principal investigators and site managers of the numerous AERONET sites utilized in this study. Funding for the development of the construction of ICAP-MME was provided by the Office of Naval Research, Code 322. ECMWF/CAMS contributions were provided by the Copernicus Atmosphere Monitoring Service, operated by ECMWF on behalf of the European Commission (EC) based on the work of the EC-funded MACC projects. MASINGAR is developed in the Meteorological Research Institute of Japan Meteorological Agency, and a part of the development was funded by the Environmental Research and Technology Development Fund (B-1202) of the Ministry of the Environment (MOE) of Japan. NAAPS development is supported by the Office of Naval Research Code 322. GEOS-5 development is supported by the NASA Modeling, Analysis, and Prediction programme, and simulations are carried out at the NASA Center for Climate Simulation (NCCS). NGAC development has been supported by Joint Center for Satellite Data Assimilation, NOAA Modeling, Analysis, Prediction, and Projections programme and National Weather Service. The development of MONARCH at the Barcelona Supercomputing Center has been supported by the SEV-2011-00067 grant of the Severo Ochoa Program and grants CGL2006-11879, CGL2008-02818, CGL2010-19652, CGL-2013-46736-R and CSD2007-0050 awarded by the Spanish Ministry of Economy and Competitiveness. It is currently supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 773051) and the AXA Research Fund. Development of the Met Office Unified Model is funded by a combination of the UK Public Weather Service and the Hadley Centre Climate Programme supported by the Department of Business, Energy and Industrial Strategy (BEIS) and the Department for Environment, Food and Rural Affairs (Defra). MOCAGE development is supported by Centre National de Recherches Météorologiques (CNRM-GAME) of Météo-France and Centre National de la Recherche Scientifique (CNRS). The global SILAM version was developed under ASTREX, APTA and GLORIA projects of Academy of Finland; the fire emission system was developed within the Academy IS4FIRES project. | |
dc.description.uri | https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/qj.3497 | |
dc.format.extent | 34 pages | |
dc.genre | journal articles | |
dc.identifier | doi:10.13016/m2vdxc-71a9 | |
dc.identifier.citation | Xian, P, Reid, JS, Hyer, EJ et al. Current state of the global operational aerosol multi-model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP). Q J R Meteorol Soc 2019; 145 (Suppl. 1): 176–209. https://doi.org/10.1002/qj.3497 | |
dc.identifier.uri | https://doi.org/10.1002/qj.3497 | |
dc.identifier.uri | http://hdl.handle.net/11603/31621 | |
dc.language.iso | en_US | |
dc.publisher | Royal Meteorological Society | |
dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
dc.relation.ispartof | UMBC GESTAR II Collection | |
dc.rights | This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law. | |
dc.rights | Public Domain Mark 1.0 | en |
dc.rights.uri | https://creativecommons.org/publicdomain/mark/1.0/ | |
dc.title | Current state of the global operational aerosol multi-model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP) | |
dc.type | Text | |
dcterms.creator | https://orcid.org/0000-0001-9801-1610 |
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