The impact of sampling strategy on the cloud droplet number concentration estimated from satellite data
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Cloud 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.
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.
Date Issued
2022-07-01
Date Acceptance
2022-04-06
Citation
Atmospheric Measurement Techniques, 2022, 15 (12), pp.3875-3892
ISSN
1867-1381
Publisher
Copernicus Publications
Start Page
3875
End Page
3892
Journal / Book Title
Atmospheric Measurement Techniques
Volume
15
Issue
12
Copyright Statement
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
License URL
Identifier
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000819425100001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
Subjects
Science & Technology
Physical Sciences
Meteorology & Atmospheric Sciences
VERTICAL PHOTON TRANSPORT
LIQUID WATER PATH
AEROSOL INFLUENCE
MICROPHYSICAL PROPERTIES
RADIATIVE PROPERTIES
STRATIFORM CLOUDS
EFFECTIVE RADIUS
MODIS
MODEL
PARAMETERIZATION
Publication Status
Published
Date Publish Online
2022-07-01