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Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0

The Goddard Earth Observing System composition forecast (GEOS‐CF) system is a high‐resolution (0.25°) global constituent prediction system from NASA's Global Modeling and Assimilation Office (GMAO). GEOS‐CF offers a new tool for atmospheric chemistry research, with the goal to supplement NASA&#...

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Autores principales: Keller, Christoph A., Knowland, K. Emma, Duncan, Bryan N., Liu, Junhua, Anderson, Daniel C., Das, Sampa, Lucchesi, Robert A., Lundgren, Elizabeth W., Nicely, Julie M., Nielsen, Eric, Ott, Lesley E., Saunders, Emily, Strode, Sarah A., Wales, Pamela A., Jacob, Daniel J., Pawson, Steven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8244029/
https://www.ncbi.nlm.nih.gov/pubmed/34221240
http://dx.doi.org/10.1029/2020MS002413
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author Keller, Christoph A.
Knowland, K. Emma
Duncan, Bryan N.
Liu, Junhua
Anderson, Daniel C.
Das, Sampa
Lucchesi, Robert A.
Lundgren, Elizabeth W.
Nicely, Julie M.
Nielsen, Eric
Ott, Lesley E.
Saunders, Emily
Strode, Sarah A.
Wales, Pamela A.
Jacob, Daniel J.
Pawson, Steven
author_facet Keller, Christoph A.
Knowland, K. Emma
Duncan, Bryan N.
Liu, Junhua
Anderson, Daniel C.
Das, Sampa
Lucchesi, Robert A.
Lundgren, Elizabeth W.
Nicely, Julie M.
Nielsen, Eric
Ott, Lesley E.
Saunders, Emily
Strode, Sarah A.
Wales, Pamela A.
Jacob, Daniel J.
Pawson, Steven
author_sort Keller, Christoph A.
collection PubMed
description The Goddard Earth Observing System composition forecast (GEOS‐CF) system is a high‐resolution (0.25°) global constituent prediction system from NASA's Global Modeling and Assimilation Office (GMAO). GEOS‐CF offers a new tool for atmospheric chemistry research, with the goal to supplement NASA's broad range of space‐based and in‐situ observations. GEOS‐CF expands on the GEOS weather and aerosol modeling system by introducing the GEOS‐Chem chemistry module to provide hindcasts and 5‐days forecasts of atmospheric constituents including ozone (O(3)), carbon monoxide (CO), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), and fine particulate matter (PM(2.5)). The chemistry module integrated in GEOS‐CF is identical to the offline GEOS‐Chem model and readily benefits from the innovations provided by the GEOS‐Chem community. Evaluation of GEOS‐CF against satellite, ozonesonde and surface observations for years 2018–2019 show realistic simulated concentrations of O(3), NO(2), and CO, with normalized mean biases of −0.1 to 0.3, normalized root mean square errors between 0.1–0.4, and correlations between 0.3–0.8. Comparisons against surface observations highlight the successful representation of air pollutants in many regions of the world and during all seasons, yet also highlight current limitations, such as a global high bias in SO(2) and an overprediction of summertime O(3) over the Southeast United States. GEOS‐CF v1.0 generally overestimates aerosols by 20%–50% due to known issues in GEOS‐Chem v12.0.1 that have been addressed in later versions. The 5‐days forecasts have skill scores comparable to the 1‐day hindcast. Model skills can be improved significantly by applying a bias‐correction to the surface model output using a machine‐learning approach.
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spelling pubmed-82440292021-07-02 Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0 Keller, Christoph A. Knowland, K. Emma Duncan, Bryan N. Liu, Junhua Anderson, Daniel C. Das, Sampa Lucchesi, Robert A. Lundgren, Elizabeth W. Nicely, Julie M. Nielsen, Eric Ott, Lesley E. Saunders, Emily Strode, Sarah A. Wales, Pamela A. Jacob, Daniel J. Pawson, Steven J Adv Model Earth Syst Research Article The Goddard Earth Observing System composition forecast (GEOS‐CF) system is a high‐resolution (0.25°) global constituent prediction system from NASA's Global Modeling and Assimilation Office (GMAO). GEOS‐CF offers a new tool for atmospheric chemistry research, with the goal to supplement NASA's broad range of space‐based and in‐situ observations. GEOS‐CF expands on the GEOS weather and aerosol modeling system by introducing the GEOS‐Chem chemistry module to provide hindcasts and 5‐days forecasts of atmospheric constituents including ozone (O(3)), carbon monoxide (CO), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), and fine particulate matter (PM(2.5)). The chemistry module integrated in GEOS‐CF is identical to the offline GEOS‐Chem model and readily benefits from the innovations provided by the GEOS‐Chem community. Evaluation of GEOS‐CF against satellite, ozonesonde and surface observations for years 2018–2019 show realistic simulated concentrations of O(3), NO(2), and CO, with normalized mean biases of −0.1 to 0.3, normalized root mean square errors between 0.1–0.4, and correlations between 0.3–0.8. Comparisons against surface observations highlight the successful representation of air pollutants in many regions of the world and during all seasons, yet also highlight current limitations, such as a global high bias in SO(2) and an overprediction of summertime O(3) over the Southeast United States. GEOS‐CF v1.0 generally overestimates aerosols by 20%–50% due to known issues in GEOS‐Chem v12.0.1 that have been addressed in later versions. The 5‐days forecasts have skill scores comparable to the 1‐day hindcast. Model skills can be improved significantly by applying a bias‐correction to the surface model output using a machine‐learning approach. John Wiley and Sons Inc. 2021-04-07 2021-04 /pmc/articles/PMC8244029/ /pubmed/34221240 http://dx.doi.org/10.1029/2020MS002413 Text en © 2021. The Authors. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Research Article
Keller, Christoph A.
Knowland, K. Emma
Duncan, Bryan N.
Liu, Junhua
Anderson, Daniel C.
Das, Sampa
Lucchesi, Robert A.
Lundgren, Elizabeth W.
Nicely, Julie M.
Nielsen, Eric
Ott, Lesley E.
Saunders, Emily
Strode, Sarah A.
Wales, Pamela A.
Jacob, Daniel J.
Pawson, Steven
Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0
title Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0
title_full Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0
title_fullStr Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0
title_full_unstemmed Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0
title_short Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0
title_sort description of the nasa geos composition forecast modeling system geos‐cf v1.0
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8244029/
https://www.ncbi.nlm.nih.gov/pubmed/34221240
http://dx.doi.org/10.1029/2020MS002413
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