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AMT | Articles | Volume 13, issue 2
Atmos. Meas. Tech., 13, 373–404, 2020
https://doi.org/10.5194/amt-13-373-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 13, 373–404, 2020
https://doi.org/10.5194/amt-13-373-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 03 Feb 2020

Research article | 03 Feb 2020

A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing

Andrew M. Sayer et al.

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Cited articles

Ahn, C., Torres, O., and Jethva, H.: Assessment of OMI near‐UV aerosol optical depth over land, J. Geophys. Res.-Atmos., 119, 2457–2473, https://doi.org/10.1002/2013JD020188, 2013. a
Baum, B. A., Menzel, W. P., Frey, R. A., Tobin, D. C., Holz, R. E., Ackerman, S. A., Heidinger, A. K., and Yang, P.: MODIS Cloud-Top Property Refinements for Collection 6, J. Appl. Meteorol. Clim., 51, 1145–1163, https://doi.org/10.1175/JAMC-D-11-0203.1, 2012. a
Benedetti, A., Morcrette, J.‐J., Boucher, O., Dethof, A., Engelen, R. J., Fisher, M., Flentje, H., Huneeus, N., Jones, L., Kaiser, J. W., Kinne, S., Mangold, A., Razinger, M., Simmons, A. J., and Suttie, M.: Aerosol analysis and forecast in the European Centre for Medium‐Range Weather Forecasts Integrated Forecast System: 2. Data assimilation, J. Geophys. Res., 114, D13205, https://doi.org/10.1029/2008JD011115, 2009. a
Benedetti, A., Reid, J. S., Knippertz, P., Marsham, J. H., Di Giuseppe, F., Rémy, S., Basart, S., Boucher, O., Brooks, I. M., Menut, L., Mona, L., Laj, P., Pappalardo, G., Wiedensohler, A., Baklanov, A., Brooks, M., Colarco, P. R., Cuevas, E., da Silva, A., Escribano, J., Flemming, J., Huneeus, N., Jorba, O., Kazadzis, S., Kinne, S., Popp, T., Quinn, P. K., Sekiyama, T. T., Tanaka, T., and Terradellas, E.: Status and future of numerical atmospheric aerosol prediction with a focus on data requirements, Atmos. Chem. Phys., 18, 10615–10643, https://doi.org/10.5194/acp-18-10615-2018, 2018. a
Bevan, S. L., North, P. R. J., Los, S. O., and Grey, W. M. F.: A global dataset of atmospheric aerosol optical depth and surface reflectance from AATSR, Remote Sens. Environ., 116, 199–210, https://doi.org/10.1016/j.rse.2011.05.024, 2012. a
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Short summary
Satellite measurements of the Earth are routinely processed to estimate useful quantities; one example is the amount of atmospheric aerosols (which are particles such as mineral dust, smoke, volcanic ash, or sea spray). As with all measurements and inferred quantities, there is some degree of uncertainty in this process. There are various methods to estimate these uncertainties. A related question is the following: how reliable are these estimates? This paper presents a method to assess them.
Satellite measurements of the Earth are routinely processed to estimate useful quantities; one...
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