The importance of temporal collocation for the evaluation of aerosol models with observations
This is the final version of the article. Available from European Geosciences Union (EGU) and Copernicus Publications via the DOI in this record. It is often implicitly assumed that over suitably long periods the mean of observations and models should be comparable, even if they have different tempo...
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Online Access: | http://hdl.handle.net/10871/31971 https://doi.org/10.5194/acp-16-1065-2016 |
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ftunivexeter:oai:ore.exeter.ac.uk:10871/31971 2024-09-15T17:35:17+00:00 The importance of temporal collocation for the evaluation of aerosol models with observations Schutgens, NAJ Partridge, DG Stier, P 2016 http://hdl.handle.net/10871/31971 https://doi.org/10.5194/acp-16-1065-2016 en eng European Geosciences Union (EGU) and Copernicus Publications Vol. 16, pp. 1065 - 1079 https://doi.org/10.5194/acp-16-1065-2016 http://hdl.handle.net/10871/31971 Atmospheric Chemistry and Physics © The Author(s). Open Access. This article is distributed under the terms of the Creative Commons Attribution Attribution 3.0 License (https://creativecommons.org/licenses/by-nc-nd/3.0/), which permits non-commercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. temporal collocation aerosol models Article 2016 ftunivexeter https://doi.org/10.5194/acp-16-1065-2016 2024-07-29T03:24:16Z This is the final version of the article. Available from European Geosciences Union (EGU) and Copernicus Publications via the DOI in this record. It is often implicitly assumed that over suitably long periods the mean of observations and models should be comparable, even if they have different temporal sampling. We assess the errors incurred due to ignoring temporal sampling and show that they are of similar magnitude as (but smaller than) actual model errors (20–60 %). Using temporal sampling from remote-sensing data sets, the satellite imager MODIS (MODerate resolution Imaging Spectroradiometer) and the ground-based sun photometer network AERONET (AErosol Robotic NETwork), and three different global aerosol models, we compare annual and monthly averages of full model data to sampled model data. Our results show that sampling errors as large as 100 % in AOT (aerosol optical thickness), 0.4 in AE (Ångström Exponent) and 0.05 in SSA (single scattering albedo) are possible. Even in daily averages, sampling errors can be significant. Moreover these sampling errors are often correlated over long distances giving rise to artificial contrasts between pristine and polluted events and regions. Additionally, we provide evidence that suggests that models will underestimate these errors. To prevent sampling errors, model data should be temporally collocated to the observations before any analysis is made. We also discuss how this work has consequences for in situ measurements (e.g. aircraft campaigns or surface measurements) in model evaluation. Although this study is framed in the context of model evaluation, it has a clear and direct relevance to climatologies derived from observational data sets. This work was supported by the Natural Environmental Research Council grant nr NE/J024252/1 (Global Aerosol Synthesis And Science Project). Computational resources for the ECHAM-HAM runs were made available by Deutsches Klimarechenzentrum (DKRZ) through support from the Bundesministerium für Bildung und Forschung (BMBF). ... Article in Journal/Newspaper Aerosol Robotic Network University of Exeter: Open Research Exeter (ORE) Atmospheric Chemistry and Physics 16 2 1065 1079 |
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University of Exeter: Open Research Exeter (ORE) |
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ftunivexeter |
language |
English |
topic |
temporal collocation aerosol models |
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temporal collocation aerosol models Schutgens, NAJ Partridge, DG Stier, P The importance of temporal collocation for the evaluation of aerosol models with observations |
topic_facet |
temporal collocation aerosol models |
description |
This is the final version of the article. Available from European Geosciences Union (EGU) and Copernicus Publications via the DOI in this record. It is often implicitly assumed that over suitably long periods the mean of observations and models should be comparable, even if they have different temporal sampling. We assess the errors incurred due to ignoring temporal sampling and show that they are of similar magnitude as (but smaller than) actual model errors (20–60 %). Using temporal sampling from remote-sensing data sets, the satellite imager MODIS (MODerate resolution Imaging Spectroradiometer) and the ground-based sun photometer network AERONET (AErosol Robotic NETwork), and three different global aerosol models, we compare annual and monthly averages of full model data to sampled model data. Our results show that sampling errors as large as 100 % in AOT (aerosol optical thickness), 0.4 in AE (Ångström Exponent) and 0.05 in SSA (single scattering albedo) are possible. Even in daily averages, sampling errors can be significant. Moreover these sampling errors are often correlated over long distances giving rise to artificial contrasts between pristine and polluted events and regions. Additionally, we provide evidence that suggests that models will underestimate these errors. To prevent sampling errors, model data should be temporally collocated to the observations before any analysis is made. We also discuss how this work has consequences for in situ measurements (e.g. aircraft campaigns or surface measurements) in model evaluation. Although this study is framed in the context of model evaluation, it has a clear and direct relevance to climatologies derived from observational data sets. This work was supported by the Natural Environmental Research Council grant nr NE/J024252/1 (Global Aerosol Synthesis And Science Project). Computational resources for the ECHAM-HAM runs were made available by Deutsches Klimarechenzentrum (DKRZ) through support from the Bundesministerium für Bildung und Forschung (BMBF). ... |
format |
Article in Journal/Newspaper |
author |
Schutgens, NAJ Partridge, DG Stier, P |
author_facet |
Schutgens, NAJ Partridge, DG Stier, P |
author_sort |
Schutgens, NAJ |
title |
The importance of temporal collocation for the evaluation of aerosol models with observations |
title_short |
The importance of temporal collocation for the evaluation of aerosol models with observations |
title_full |
The importance of temporal collocation for the evaluation of aerosol models with observations |
title_fullStr |
The importance of temporal collocation for the evaluation of aerosol models with observations |
title_full_unstemmed |
The importance of temporal collocation for the evaluation of aerosol models with observations |
title_sort |
importance of temporal collocation for the evaluation of aerosol models with observations |
publisher |
European Geosciences Union (EGU) and Copernicus Publications |
publishDate |
2016 |
url |
http://hdl.handle.net/10871/31971 https://doi.org/10.5194/acp-16-1065-2016 |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_relation |
Vol. 16, pp. 1065 - 1079 https://doi.org/10.5194/acp-16-1065-2016 http://hdl.handle.net/10871/31971 Atmospheric Chemistry and Physics |
op_rights |
© The Author(s). Open Access. This article is distributed under the terms of the Creative Commons Attribution Attribution 3.0 License (https://creativecommons.org/licenses/by-nc-nd/3.0/), which permits non-commercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
op_doi |
https://doi.org/10.5194/acp-16-1065-2016 |
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Atmospheric Chemistry and Physics |
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16 |
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1065 |
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