| 1. |
- Arneth, Almut, et al.
(författare)
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Climate-fire interactions and Savanna ecosystems : A dynamic vegetation modeling study for the African Continent
- 2010
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Ingår i: Ecosystem Function in Savannas : Measurement and Modeling at Landscape to Global Scales - Measurement and Modeling at Landscape to Global Scales. - : CRC Press. - 9781439804704 - 9781439804711 ; , s. 463-478
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Bokkapitel (refereegranskat)abstract
- Savannas are inherently “disturbed” ecosystems, but the regularly recurring disruptions play such a fundamental ecological role (Scholes and Archer, 1997) that “episodic events” rather than “disturbance” may the more apt terminology. From an atmospheric perspective, fire is the most significant of these episodic events. Fires shape community species composition; tree to grass ratio and nutrient redistribution; and biosphere-atmosphere exchange of trace gases, aerosols, momentum, and energy. Savannas’ estimated mean NPP of 7.2 ± 2.0 t C ha-1 year-1 amounts to nearly two thirds of tropical forest NPP (Grace et al., 2006); but remarkably little is known about Savanna net carbon balance, especially for the African continent (Williams et al., 2007). In the absence of transient changes in the fire regime, such as could be introduced by climate change or fire-driven changes in land cover, Savanna fires do not affect average annual net carbon uptake much, as the carbon released.
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| 2. |
- Hantson, Stijn, et al.
(författare)
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The status and challenge of global fire modelling
- 2016
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Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 13:11, s. 3359-3375
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Tidskriftsartikel (refereegranskat)abstract
- Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.
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| 3. |
- Rabin, Sam S., et al.
(författare)
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The Fire Modeling Intercomparison Project (FireMIP), phase 1 : Experimental and analytical protocols with detailed model descriptions
- 2017
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Ingår i: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 10:3, s. 1175-1197
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Tidskriftsartikel (refereegranskat)abstract
- The important role of fire in regulating vegetation community composition and contributions to emissions of greenhouse gases and aerosols make it a critical component of dynamic global vegetation models and Earth system models. Over 2 decades of development, a wide variety of model structures and mechanisms have been designed and incorporated into global fire models, which have been linked to different vegetation models. However, there has not yet been a systematic examination of how these different strategies contribute to model performance. Here we describe the structure of the first phase of the Fire Model Intercomparison Project (FireMIP), which for the first time seeks to systematically compare a number of models. By combining a standardized set of input data and model experiments with a rigorous comparison of model outputs to each other and to observations, we will improve the understanding of what drives vegetation fire, how it can best be simulated, and what new or improved observational data could allow better constraints on model behavior. In this paper, we introduce the fire models used in the first phase of FireMIP, the simulation protocols applied, and the benchmarking system used to evaluate the models. We have also created supplementary tables that describe, in thorough mathematical detail, the structure of each model.
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