On the spatio-temporal representativeness of observations

Nick Schutgens*, Svetlana Tsyro, Edward Gryspeerdt, Daisuke Goto, Natalie Weigum, Michael Schulz, Philip Stier

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review


The discontinuous spatio-temporal sampling of observations has an impact when using them to construct climatologies or evaluate models. Here we provide estimates of this so-called representation error for a range of timescales and length scales (semi-annually down to sub-daily, 300 to 50 km) and show that even after substantial averaging of data significant representation errors may remain, larger than typical measurement errors. Our study considers a variety of observations: ground-site or in situ remote sensing (PM2. 5, black carbon mass or number concentrations), satellite remote sensing with imagers or lidar (extinction). We show that observational coverage (a measure of how dense the spatio-temporal sampling of the observations is) is not an effective metric to limit representation errors. Different strategies to construct monthly gridded satellite L3 data are assessed and temporal averaging of spatially aggregated observations (super-observations) is found to be the best, although it still allows for significant representation errors. However, temporal collocation of data (possible when observations are compared to model data or other observations), combined with temporal averaging, can be very effective at reducing representation errors. We also show that ground-based and wide-swath imager satellite remote sensing data give rise to similar representation errors, although their observational sampling is different. Finally, emission sources and orography can lead to representation errors that are very hard to reduce, even with substantial temporal averaging.

Original languageEnglish
Pages (from-to)9761-9780
Number of pages20
JournalAtmospheric Chemistry and Physics
Issue number16
Publication statusPublished - 21 Aug 2017


Acknowledgements. This work was supported by the Natural Environmental Research Council grant no. NE/J024252/1 (GASSP: Global Aerosol Synthesis And Science Project). Edward Gryspeerdt acknowledges funding from the European Research Council under the EU Seventh Framework Programme FP7-306284 (“QUAERERE”). Daisuke Goto was supported by the Global Environment Research Fund S-12 of the Ministry of the Environment (MOE), Japan; the Grant-in-Aid for Young Scientist B (grant number 26740010) of the Ministry of Education, Culture, Sports and Science and Technology (MEXT), Japan; and KAK- ENHI/Innovative Areas (grant number 24110002) of MEXT, Japan. Philip Stier and Nick Schutgens acknowledge funding from the European Research Council under the EU Seventh Framework Programme (FP7/2007-2013) and ERC grant agreement FP7-280025 (ACCLAIM: Aerosol effects on Convective CLouds And clIMate). Michael Schulz and Svetlana Tsyro acknowledge funding from the Norwegian Research Council under the KLIMAFORSK project “AeroCom-P3”. Their work was supported by EMEP under UN-ECE.

FundersFunder number
Natural Environmental Research CouncilNE/J024252/1
Horizon 2020 Framework Programme654109
Seventh Framework Programme306284, 280025
Natural Environment Research CouncilNE/J022624/1, NE/L01355X/1
European Research CouncilFP7-280025
Japan Society for the Promotion of Science17H04711
Ministry of Education, Culture, Sports, Science and Technology24110002
Seventh Framework Programme
Norges forskningsråd
Ministry of the Environment, Government of Japan26740010


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