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dc.contributor.authorGryspeerdt, E.
dc.contributor.authorMcCoy, D.T.
dc.contributor.authorCrosbie, E.
dc.contributor.authorMoore, R.H.
dc.contributor.authorNott, G.J.
dc.contributor.authorPainemal, D.
dc.contributor.authorSmall-Griswold, J.
dc.contributor.authorSorooshian, A.
dc.contributor.authorZiemba, L.
dc.date.accessioned2022-08-01T20:17:19Z
dc.date.available2022-08-01T20:17:19Z
dc.date.issued2022
dc.identifier.citationGryspeerdt, E., McCoy, D. T., Crosbie, E., Moore, R. H., Nott, G. J., Painemal, D., Small-Griswold, J., Sorooshian, A., & Ziemba, L. (2022). The impact of sampling strategy on the cloud droplet number concentration estimated from satellite data. Atmospheric Measurement Techniques, 15(12), 3875–3892.
dc.identifier.issn1867-1381
dc.identifier.doi10.5194/amt-15-3875-2022
dc.identifier.urihttp://hdl.handle.net/10150/665477
dc.description.abstractCloud droplet number concentration (Nd) is of central importance to observation-based estimates of aerosol indirect effects, being used to quantify both the cloud sensitivity to aerosol and the base state of the cloud. However, the derivation of Nd from satellite data depends on a number of assumptions about the cloud and the accuracy of the retrievals of the cloud properties from which it is derived, making it prone to systematic biases. A number of sampling strategies have been proposed to address these biases by selecting the most accurate Nd retrievals in the satellite data. This work compares the impact of these strategies on the accuracy of the satellite retrieved Nd, using a selection of in situ measurements. In stratocumulus regions, the MODIS Nd retrieval is able to achieve a high precision (r2 of 0.5-0.8). This is lower in other cloud regimes but can be increased by appropriate sampling choices. Although the Nd sampling can have significant effects on the Nd climatology, it produces only a 20% variation in the implied radiative forcing from aerosol-cloud interactions, with the choice of aerosol proxy driving the overall uncertainty. The results are summarised into recommendations for using MODIS Nd products and appropriate sampling. © 2022 Edward Gryspeerdt et al.
dc.language.isoen
dc.publisherCopernicus GmbH
dc.rightsCopyright © Author(s) 2022. This work is distributed under the Creative Commons Attribution 4.0 License.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.titleThe impact of sampling strategy on the cloud droplet number concentration estimated from satellite data
dc.typeArticle
dc.typetext
dc.contributor.departmentDepartment of Chemical And Environmental Engineering, University of Arizona
dc.identifier.journalAtmospheric Measurement Techniques
dc.description.noteOpen access journal
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
dc.eprint.versionFinal published version
dc.source.journaltitleAtmospheric Measurement Techniques
refterms.dateFOA2022-08-01T20:17:19Z


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Copyright © Author(s) 2022. This work is distributed under the Creative Commons Attribution 4.0 License.
Except where otherwise noted, this item's license is described as Copyright © Author(s) 2022. This work is distributed under the Creative Commons Attribution 4.0 License.