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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
Sprache Englisch
ISSN 1680-7316
Digitales Dokument URL
Erschienen In: Atmospheric Chemistry and Physics ; 14, no. 9 ; Nr. 14, no. 9 (2014-05-05), S.4397-4407
Datensatznummer 250118679
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/acp-14-4397-2014.pdf
 
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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