Employing MODIS Cloud Regimes to Find Signals of Aerosol-Cloud-Precipitation Interactions

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20150018350.pdf (7.28 MB)

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https://ntrs.nasa.gov/citations/20150018350

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http://hdl.handle.net/11603/40170

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UMBC GESTAR II

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Author/Creator ORCID

https://orcid.org/0000-0003-4389-4393

Date

2015-05-18

Type of Work

posters
conference papers and proceedings
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Citation of Original Publication

Cho, Nayeong, Lazaros Oraiopoulos, Dongmin Lee, and Daeho Jin. “Employing MODIS Cloud Regimes to Find Signals of Aerosol-Cloud-Precipitation Interactions.” MODIS/VIIRS 2015 Science Team Meeting, May 18, 2015. https://ntrs.nasa.gov/citations/20150018350.

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This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
Public Domain

Subjects

Meteorology And Climatology

Abstract

• A Cloud Regime (CR) approach is used to study aerosol-cloud-precipitation relationships. • 10 years of MODIS Terra-Aqua C5.1 daily joint (2D) histograms of Cloud Top pressure (CTP) vs Cloud Optical Thickness (COT) and Cloud Effective Radius (CER, liquid and ice phase) vs COT are used to derived global CRs using clustering analysis. • We composite CR properties, namely COT, CTP, Cloud Fraction (CF), and CER, as well as TRMM precipitation. • The AI (= AOD x Ångström exponent) parameter from MODIS, thought to correlate better with CCN than AOD, is used to examine relationships between aerosols and clouds. • The seasonal AI distribution for each 1°x1° gridcell is broken into vigintiles (5% increments). High and low AI are defined as the highest and lowest AI quartile, respectively. • TRMM Multi satellite Precipitation Analysis TMPA-3B42 rainfall is composited for each CR, and separately for each AI vigintile.