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| Titel |
Statistical properties of aerosol-cloud-precipitation interactions in South America |
| VerfasserIn |
T. A. Jones, S. A. Christopher |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 10, no. 5 ; Nr. 10, no. 5 (2010-03-05), S.2287-2305 |
| Datensatznummer |
250008170
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| Publikation (Nr.) |
 copernicus.org/acp-10-2287-2010.pdf |
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| Zusammenfassung |
Given the complex interaction between aerosol, cloud, and atmospheric
properties, it is difficult to extract their individual effects to observed
rainfall amount. This research uses principle component analysis (PCA) that
combines Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol and
cloud products, NCEP Reanalysis atmospheric products, and rainrate estimates
from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR)
to assess if aerosols affect warm rain processes. Data collected during
September 2006 over the Amazon basin in South America during the
biomass-burning season are used. The goal of this research is to combine
these observations into a smaller number of variables through PCA with each
new variable having a unique physical interpretation. In particular, we are
concerned with PC variables whose weightings include aerosol optical
thickness (AOT), as these may be an indicator of aerosol indirect effects.
If they are indeed occurring, then PC values that include AOT should change
as a function of rainrate.
To emphasize the advantage of PCA, changes in aerosol, cloud, and
atmospheric observations are compared to rainrate. Comparing no-rain, rain,
and heavy rain only (>5 mm h−1) samples, we find that cloud
thicknesses, humidity, and upward motion are all greater during rain and
heavy rain conditions. However, no statistically significant difference in
AOT exists between each sample, indicating that atmospheric conditions are
more important to rainfall than aerosol concentrations as expected. If
aerosols are affecting warm process clouds, it would be expected that
stratiform precipitation would decrease as a function increasing aerosol
concentration through either Twomey and/or semi-direct effects. PCA extracts
the latter signal in a variable labeled PC2, which explains 15% of the
total variance and is second in importance the variable (PC1) containing the
broad atmospheric conditions. PC2 contains weightings showing that AOT is
inversely proportional to low-level humidity and cloud optical thickness.
Increasing AOT is also positively correlated with increasing low-level
instability due to aerosol absorption. The nature of these weightings is
strongly suggestive that PC2 is an indicator of the semi-direct effect with
larger values associated with lower rainfall rates. PC weightings consistent
with the Twomey effect (an anti-correlation between AOT and cloud droplet
effective radius) are only present in higher order PC variables that explain
less than 1% of the total variance, and do not vary significantly as a
function of rainrate. If the Twomey effect is occurring, it is highly
non-linear and/or being overshadowed by other processes. Using the raw
variables alone, these determinations could not be made; thus, we are able
to show the advantage of using advanced statistical techniques such as PCA
for analysis of aerosols impacts on precipitation in South America. |
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