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Preprints
https://doi.org/10.5194/acp-2019-767
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2019-767
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 23 Sep 2019

Submitted as: research article | 23 Sep 2019

Review status
A revised version of this preprint was accepted for the journal ACP and is expected to appear here in due course.

Site representativity of AERONET and GAW remotely sensed AOT and AAOT observations

Nick A. J. Schutgens Nick A. J. Schutgens
  • Department of Earth Science, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands

Abstract. Remote sensing observations from the AERONET and GAW networks are intermittent in time and have a limited field-of-view. A global high-resolution simulation (GEOS5 Nature Run) is used to conduct an Observing System Simulation Experiment (OSSE) for AERONET and GAW observations of AOT and AAOT and estimate the spatio-temporal representativity of individual sites for larger areas (from 0.5° to 4° in size).

G5NR and the OSSE are evaluated and shown to have sufficient skill, although daily AAOT variability is significantly underestimated while the frequency of AAOT observations is over-estimated (both resulting in an under-estimation of temporal representativity errors in AAOT).

Yearly representation errors are provided for a host of scenarios: varying grid-box size, temporal collocation protocols, and site altitudes are explored. Monthly representation errors are shown to correlate strongly throughout the year, with a pronounced annual cycle. The collocation protocol for AEROCOM model evaluation (using daily data) is shown to be sub-optimal and the use of hourly data advocated instead. A previous subjective ranking of site spatial representativity (Kinne et al., 2013) is analysed and a new objective ranking proposed. Several sites are shown to have yearly representation errors in excess of 40 %.

Lastly, a recent suggestion by Wang et al. (2018) that AERONET observations of AAOT suffer a positive representation bias of 30 % globally is analysed and evidence is provided that this bias is likely an overestimate (the current paper finds 4 %) due methodological choices.

Nick A. J. Schutgens

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Nick A. J. Schutgens

Nick A. J. Schutgens

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Latest update: 30 May 2020
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Short summary
Aerosols are tiny particles in the air that affect human health and climate. To study these particles, measurement networks across the world are used. Each site, however, can only observe the air directly above it, so how representative is this measurement for the wider environment? The sites of a well-known remote sensing network (AERONET) are examined, and ranked according to their representativity. This should benefit researchers using this measurement network.
Aerosols are tiny particles in the air that affect human health and climate. To study these...
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