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| Titel |
Relationship between Amazon biomass burning aerosols and rainfall over the La Plata Basin |
| VerfasserIn |
G. Camponogara, M. A. F. Silva Dias, G. G. Carrio |
| 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 ; 14, no. 9 ; Nr. 14, no. 9 (2014-05-05), S.4397-4407 |
| Datensatznummer |
250118679
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| Publikation (Nr.) |
 copernicus.org/acp-14-4397-2014.pdf |
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| Zusammenfassung |
| High aerosol loads are discharged into the atmosphere by biomass burning in
the Amazon and central Brazil during the dry season. These particles can
interact with clouds as cloud condensation nuclei (CCN) changing cloud
microphysics and radiative properties and, thereby, affecting the radiative
budget of the region. Furthermore, the biomass burning aerosols can be
transported by the low-level jet (LLJ) to the La Plata Basin, where many
mesoscale convective systems (MCS) are observed during spring and summer.
This work proposes to investigate whether the aerosols from biomass burning
may affect the MCS in terms of rainfall over the La Plata Basin during
spring. Aerosol effects are very difficult to isolate because convective
clouds are very sensitive to small environment disturbances; for that reason,
detailed analyses using different techniques are used. The binplot,
2-D histograms and combined empirical orthogonal function (EOF)
methods are used to identify certain environmental conditions with the
possible effects of aerosol loading. Reanalysis 2, TRMM-3B42 and AERONET data
are used from 1999 up to 2012 during September–December. The results show
that there are two patterns associated with rainfall–aerosol interaction in
the La Plata Basin: one in which the dynamic conditions are more important
than aerosols to generation of rain; and a second one where the aerosol
particles have a more important role in rain formation, acting mainly to
suppress rainfall over the La Plata Basin. However, these results need
further investigation to strengthen conclusions, especially because there
are limitations and uncertainties in the methodology and data set used. |
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