|
Titel |
A model for global biomass burning in preindustrial time: LPJ-LMfire (v1.0) |
VerfasserIn |
M. Pfeiffer, A. Spessa, J. O. Kaplan |
Medientyp |
Artikel
|
Sprache |
Englisch
|
ISSN |
1991-959X
|
Digitales Dokument |
URL |
Erschienen |
In: Geoscientific Model Development ; 6, no. 3 ; Nr. 6, no. 3 (2013-05-17), S.643-685 |
Datensatznummer |
250017817
|
Publikation (Nr.) |
copernicus.org/gmd-6-643-2013.pdf |
|
|
|
Zusammenfassung |
Fire is the primary disturbance factor in many terrestrial ecosystems.
Wildfire alters vegetation structure and composition, affects carbon storage
and biogeochemical cycling, and results in the release of climatically
relevant trace gases including CO2, CO, CH4,
NOx, and aerosols. One way of assessing the impacts of global
wildfire on centennial to multi-millennial timescales is to use process-based
fire models linked to dynamic global vegetation models (DGVMs). Here we
present an update to the LPJ-DGVM and a new fire module based on SPITFIRE
that includes several improvements to the way in which fire occurrence,
behaviour, and the effects of fire on vegetation are simulated. The new
LPJ-LMfire model includes explicit calculation of natural ignitions, the
representation of multi-day burning and coalescence of fires, and the
calculation of rates of spread in different vegetation types. We describe a
new representation of anthropogenic biomass burning under preindustrial
conditions that distinguishes the different relationships between humans and
fire among hunter-gatherers, pastoralists, and farmers. We evaluate our model
simulations against remote-sensing-based estimates of burned area at regional
and global scale. While wildfire in much of the modern world is largely
influenced by anthropogenic suppression and ignitions, in those parts of the
world where natural fire is still the dominant process (e.g. in remote areas
of the boreal forest and subarctic), our results demonstrate a significant
improvement in simulated burned area over the original SPITFIRE. The new fire
model we present here is particularly suited for the investigation of
climate–human–fire relationships on multi-millennial timescales prior to
the Industrial Revolution. |
|
|
Teil von |
|
|
|
|
|
|