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An Evaluation of the Liquid Cloud Droplet Effective Radius Derived from MODIS, Airborne Remote Sensing, and in Situ Measurements from CAMP2ExThe cloud drop effective radius (Re) of the drop size distribution derived from passive satellite sensors is a key variable used in climate research. Validation of these satellite products has often taken place under stratiform cloud conditions that favor the assumption of cloud horizontal homogeneity used by the retrieval techniques. However, many studies have noted concerns with respect to significant biases in retrieved Re arising from cloud heterogeneity, for example, in cumulus cloud fields. Here, we examine data collected during the 2019 “Cloud, Aerosol and Monsoon Processes Philippines Experiment” (CAMP2Ex), which, in part, targeted the objective of providing the first detailed evaluation of Re retrieved across multiple platforms and techniques in a cumulus and congestus cloud region. Our evaluation consists of cross-comparisons of Re between the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite, the Research Scanning Polarimeter (RSP) onboard the NASA P-3 aircraft, and in situ measurements from both the NASA P-3 and Learjet aircraft that are all taken in close spatiotemporal proximity to the same cloud fields. A particular advantage of our approach lies in the capability of the RSP to retrieve Re using a bi-spectral MODIS approach and a polarimetric approach, which allows for the evaluation of bi-spectral and polarimetric Re retrievals from an airborne perspective using the same samples.

Averaged over all P-3 flight segments examined here for warm clouds, the RSP polarimetric method, the in situ method, and the bias-adjusted MODIS method of Fu et al. (2019) show a comparable median (mean ± standard deviation) for the Re samples of 9.6 (10.2 ± 4.0) µm, 11.0 (13.6 ± 11.3) µm, and 10.4 (10.8 ± 3.8) µm, respectively. These values are far lower than the values of 15.1 (16.2 ± 5.5) µm and 17.2 (17.7 ± 5.7) µm from the bi-spectral retrievals of RSP and MODIS, respectively. Similar results are observed when Re is segregated by cloud-top height and in detailed case studies. The clouds sampled during CAMP2Ex consist of mostly small (mean transect length ∼ 1.4 km) and low clouds (mean cloud-top height ∼ 1 km), which had more numerous small clouds than the trade wind cumuli sampled in past field campaigns such as Rain in Shallow Cumulus over the Ocean (RICO) and the Indian Ocean Experiment (INDOEX). The overestimates of Re from the RSP bi-spectral technique compared with the polarimetric technique increased as cloud size and cloud optical depth decreased. Drizzle, cloud-top bumpiness, and solar zenith angle, however, are not closely correlated with the overestimate of bi-spectral Re. For shallow clouds that dominated the liquid cloud cover for the CAMP2Ex region and period, we show that 3-D radiative transfer and cloud heterogeneity, particularly for the optically thin and small clouds, appear to be the leading cause of the large positive biases in bi-spectral retrievals. Because this bias varies with the underlying structure of the cloud field, caution continues to be warranted in studies that use bi-spectral Re retrievals in cumulus cloud fields.
Document ID
20220009928
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Dongwei Fu
(University of Illinois at Urbana Champaign Urbana, Illinois, United States)
Larry Di Girolamo
(University of Illinois at Urbana Champaign Urbana, Illinois, United States)
Robert M Rauber
(University of Illinois at Urbana Champaign Urbana, Illinois, United States)
Greg M McFarquhar ORCID
(University of Oklahoma Norman, Oklahoma, United States)
Stephen W Nesbitt ORCID
(University of Illinois at Urbana Champaign Urbana, Illinois, United States)
Jesse Loveridge
(University of Illinois at Urbana Champaign Urbana, Illinois, United States)
Yulan Hong
(University of Illinois at Urbana Champaign Urbana, Illinois, United States)
Bastiaan Van Diedenhoven
(Columbia University New York, New York, United States)
Brian Cairns
(Goddard Institute for Space Studies New York, New York, United States)
Mikhail D Alexandrov
(Columbia University New York, New York, United States)
Paul Lawson
(Stratton Park Engineering Company (United States) Boulder, Colorado, United States)
Sarah Woods
(Stratton Park Engineering Company (United States) Boulder, Colorado, United States)
Simone Tanelli
(Jet Propulsion Lab La Cañada Flintridge, California, United States)
Sebastian Schmidt
(University of Colorado Boulder Boulder, Colorado, United States)
Chris Hostetler
(Langley Research Center Hampton, Virginia, United States)
Amy Jo Scarino
(Science Systems & Applications, Inc. Hampton, VA, USA)
Date Acquired
June 27, 2022
Publication Date
June 27, 2022
Publication Information
Publication: Atmospheric Chemistry and Physics
Publisher: Copernicus Publications
Volume: 22
Issue: 12
Issue Publication Date: June 27, 2022
ISSN: 1680-7316
e-ISSN: 1680-7324
Subject Category
Meteorology And Climatology
Funding Number(s)
CONTRACT_GRANT: 80NSSC18K0144
CONTRACT_GRANT: 80NSSC18K0150
CONTRACT_GRANT: 80NSSC18K0146
CONTRACT_GRANT: 80NSSC21K1449
WBS: 281945.02.20.03.51
CONTRACT_GRANT: 80NSSC22M0054
CONTRACT_GRANT: NNL16AA05C
Distribution Limits
Public
Copyright
Public Use Permitted.
Technical Review
External Peer Committee
Keywords
Cloud microphysics
retrieved cloud droplet sizes
satellite remote sensing
airborne remote sensing
cumulus clouds
water cycle
energy cycle
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