Simulating the Black Saturday 2009 smoke plume with an interactive composition-climate model: sensitivity to emissions amount, timing and injection height.
J Geophys Res Atmos
; 121(8): 4296-4316, 2016 Apr 27.
Article
em En
| MEDLINE
| ID: mdl-32747872
ABSTRACT
We simulated the high-altitude smoke plume from the early February 2009 Black Saturday bushfires in southeastern Australia using the NASA GISS ModelE2. To the best of our knowledge, this is the first single-plume analysis of biomass burning emissions injected directly into the upper-troposphere/lower stratosphere (UTLS) using a full-complexity composition-climate model. We compared simulated carbon monoxide (CO) to a new Aura TES/MLS joint CO retrieval, focusing on the plume's initial transport eastward, anticyclonic circulation to the north of New Zealand, westward transport in the lower stratospheric easterlies, and arrival over Africa at the end of February. Our goal was to determine the sensitivity of the simulated plume to prescribed injection height, emissions amount and emissions timing from different sources for a full complexity model when compared to Aura. The most realistic plumes were obtained using injection heights in the UTLS, including one drawn from ground-based radar data. A six-hour emissions pulse or emissions tied to independent estimates of hourly fire behavior produced a more realistic plume in the lower stratosphere compared to the same emissions amount being released evenly over 12 or 24-hours. Simulated CO in the plume was highly sensitive to the differences between emissions amounts estimated from the Global Fire Emissions Database and from detailed, ground-based estimates of fire growth. The emissions amount determined not only the CO concentration of the plume, but the proportion of the plume that entered the stratosphere. We speculate that this is due to either or both non-linear CO loss with a weakened OH sink, or plume self-lofting driven by shortwave absorption of the co-emitted aerosols.
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01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Diagnostic_studies
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article