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...
Published in: | Quarterly Journal of the Royal Meteorological Society |
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Online Access: | 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 |
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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 |
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Wiley Online Library |
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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 |
container_volume |
145 |
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S1 |
container_start_page |
176 |
op_container_end_page |
209 |
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1802644109692764160 |