Current state of the global operational aerosol multi‐model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP)

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 ov...

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Published in:Quarterly Journal of the Royal Meteorological Society
Main Authors: Xian, Peng, Reid, Jeffrey S., Hyer, Edward J., Sampson, Charles R., Rubin, Juli I., Ades, Melanie, Asencio, Nicole, Basart, Sara, Benedetti, Angela, Bhattacharjee, Partha S., Brooks, Malcolm E., Colarco, Peter R., da Silva, Arlindo M., Eck, Tom F., Guth, Jonathan, Jorba, Oriol, Kouznetsov, Rostislav, Kipling, Zak, Sofiev, Mikhail, Perez Garcia‐Pando, Carlos, Pradhan, Yaswant, Tanaka, Taichu, Wang, Jun, Westphal, Douglas L., Yumimoto, Keiya, Zhang, Jianglong
Other Authors: Office of Naval Research, Academy of Finland, Centre National de la Recherche Scientifique, Department for Environment, Food and Rural Affairs, Met Office, National Aeronautics and Space Administration, Ministry of the Environment, European Commission
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2019
Subjects:
Online Access:http://dx.doi.org/10.1002/qj.3497
https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.3497
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spelling crwiley:10.1002/qj.3497 2024-06-23T07:44:59+00:00 Current state of the global operational aerosol multi‐model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP) Xian, Peng Reid, Jeffrey S. Hyer, Edward J. Sampson, Charles R. Rubin, Juli I. Ades, Melanie Asencio, Nicole Basart, Sara Benedetti, Angela Bhattacharjee, Partha S. Brooks, Malcolm E. Colarco, Peter R. da Silva, Arlindo M. Eck, Tom F. Guth, Jonathan Jorba, Oriol Kouznetsov, Rostislav Kipling, Zak Sofiev, Mikhail Perez Garcia‐Pando, Carlos Pradhan, Yaswant Tanaka, Taichu Wang, Jun Westphal, Douglas L. Yumimoto, Keiya Zhang, Jianglong Office of Naval Research Academy of Finland Centre National de la Recherche Scientifique Department for Environment, Food and Rural Affairs Met Office National Aeronautics and Space Administration Ministry of the Environment European Commission 2019 http://dx.doi.org/10.1002/qj.3497 https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.3497 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/qj.3497 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.3497 en eng Wiley http://creativecommons.org/licenses/by-nc/4.0/ http://creativecommons.org/licenses/by-nc/4.0/ Quarterly Journal of the Royal Meteorological Society volume 145, issue S1, page 176-209 ISSN 0035-9009 1477-870X journal-article 2019 crwiley https://doi.org/10.1002/qj.3497 2024-06-06T04:22:22Z 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. Article in Journal/Newspaper Aerosol Robotic Network Wiley Online Library Quarterly Journal of the Royal Meteorological Society 145 S1 176 209
institution Open Polar
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language English
description 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.
author2 Office of Naval Research
Academy of Finland
Centre National de la Recherche Scientifique
Department for Environment, Food and Rural Affairs
Met Office
National Aeronautics and Space Administration
Ministry of the Environment
European Commission
format Article in Journal/Newspaper
author Xian, Peng
Reid, Jeffrey S.
Hyer, Edward J.
Sampson, Charles R.
Rubin, Juli I.
Ades, Melanie
Asencio, Nicole
Basart, Sara
Benedetti, Angela
Bhattacharjee, Partha S.
Brooks, Malcolm E.
Colarco, Peter R.
da Silva, Arlindo M.
Eck, Tom F.
Guth, Jonathan
Jorba, Oriol
Kouznetsov, Rostislav
Kipling, Zak
Sofiev, Mikhail
Perez Garcia‐Pando, Carlos
Pradhan, Yaswant
Tanaka, Taichu
Wang, Jun
Westphal, Douglas L.
Yumimoto, Keiya
Zhang, Jianglong
spellingShingle Xian, Peng
Reid, Jeffrey S.
Hyer, Edward J.
Sampson, Charles R.
Rubin, Juli I.
Ades, Melanie
Asencio, Nicole
Basart, Sara
Benedetti, Angela
Bhattacharjee, Partha S.
Brooks, Malcolm E.
Colarco, Peter R.
da Silva, Arlindo M.
Eck, Tom F.
Guth, Jonathan
Jorba, Oriol
Kouznetsov, Rostislav
Kipling, Zak
Sofiev, Mikhail
Perez Garcia‐Pando, Carlos
Pradhan, Yaswant
Tanaka, Taichu
Wang, Jun
Westphal, Douglas L.
Yumimoto, Keiya
Zhang, Jianglong
Current state of the global operational aerosol multi‐model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP)
author_facet Xian, Peng
Reid, Jeffrey S.
Hyer, Edward J.
Sampson, Charles R.
Rubin, Juli I.
Ades, Melanie
Asencio, Nicole
Basart, Sara
Benedetti, Angela
Bhattacharjee, Partha S.
Brooks, Malcolm E.
Colarco, Peter R.
da Silva, Arlindo M.
Eck, Tom F.
Guth, Jonathan
Jorba, Oriol
Kouznetsov, Rostislav
Kipling, Zak
Sofiev, Mikhail
Perez Garcia‐Pando, Carlos
Pradhan, Yaswant
Tanaka, Taichu
Wang, Jun
Westphal, Douglas L.
Yumimoto, Keiya
Zhang, Jianglong
author_sort Xian, Peng
title Current state of the global operational aerosol multi‐model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP)
title_short Current state of the global operational aerosol multi‐model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP)
title_full Current state of the global operational aerosol multi‐model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP)
title_fullStr Current state of the global operational aerosol multi‐model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP)
title_full_unstemmed Current state of the global operational aerosol multi‐model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP)
title_sort current state of the global operational aerosol multi‐model ensemble: an update from the international cooperative for aerosol prediction (icap)
publisher Wiley
publishDate 2019
url http://dx.doi.org/10.1002/qj.3497
https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.3497
https://onlinelibrary.wiley.com/doi/full-xml/10.1002/qj.3497
https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.3497
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source Quarterly Journal of the Royal Meteorological Society
volume 145, issue S1, page 176-209
ISSN 0035-9009 1477-870X
op_rights http://creativecommons.org/licenses/by-nc/4.0/
http://creativecommons.org/licenses/by-nc/4.0/
op_doi https://doi.org/10.1002/qj.3497
container_title Quarterly Journal of the Royal Meteorological Society
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container_issue S1
container_start_page 176
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