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Parameterisation of Fire in LPX1 Vegetation Model Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Open Access Geosci. Model Dev. Discuss., 7, 931–1000, 2014 Geoscientific www.geosci-model-dev-discuss.net/7/931/2014/ doi:10.5194/gmdd-7-931-2014 Model Development GMDD Discussions © Author(s) 2014. CC Attribution 3.0 License. 7, 931–1000, 2014 This discussion paper is/has been under review for the journal Geoscientific Model Parameterisation of Development (GMD). Please refer to the corresponding final paper in GMD if available. fire in LPX1 vegetation model Improved simulation of fire-vegetation D. I. Kelley et al. interactions in the Land surface Processes and eXchanges dynamic Title Page global vegetation model (LPX-Mv1) Abstract Introduction Conclusions References 1 1,2 1,3 D. I. Kelley , S. P. Harrison , and I. C. Prentice Tables Figures 1Department of Biological Sciences, Macquarie University, North Ryde, NSW 2109, Australia 2 Geography & Environmental Sciences, School of Archaeology, Geography and J I Environmental Sciences (SAGES), University of Reading, Whiteknights, Reading, RG6 6AB, UK J I 3AXA Chair of Biosphere and Climate Impacts, Grantham Institute for Climate Change and Back Close Department of Life Sciences, Imperial College, Silwood Park Campus, Ascot SL5 7PY, UK Full Screen / Esc Received: 30 October 2013 – Accepted: 26 November 2013 – Published: 23 January 2014 Correspondence to: D. I. Kelley ([email protected]) Printer-friendly Version Published by Copernicus Publications on behalf of the European Geosciences Union. Interactive Discussion 931 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Abstract GMDD The Land surface Processes and eXchanges (LPX) model is a fire-enabled dynamic global vegetation model that performs well globally but has problems representing fire 7, 931–1000, 2014 regimes and vegetative mix in savannas. Here we focus on improving the fire module. 5 To improve the representation of ignitions, we introduced a treatment of lightning that Parameterisation of allows the fraction of ground strikes to vary spatially and seasonally, realistically parti- fire in LPX1 tions strike distribution between wet and dry days, and varies the number of dry-days vegetation model with strikes. Fuel availability and moisture content were improved by implementing de- composition rates specific to individual plant functional types and litter classes, and D. I. Kelley et al. 10 litter drying rates driven by atmospheric water content. To improve water extraction by grasses, we use realistic plant-specific treatments of deep roots. To improve fire re- sponses, we introduced adaptive bark thickness and post-fire resprouting for tropical Title Page and temperate broadleaf trees. All improvements are based on extensive analyses of Abstract Introduction relevant observational data sets. We test model performance for Australia, first evalu- 15 ating parameterisations separately and then measuring overall behaviour against stan- Conclusions References dard benchmarks. Changes to the lightning parameterisation produce a more realistic Tables Figures simulation of fires in southeastern and central Australia. Implementation of PFT-specific decomposition rates enhances performance in central Australia. Changes in fuel dry- ing improve fire in northern Australia, while changes in rooting depth produce a more J I 20 realistic simulation of fuel availability and structure in central and northern Australia. J I The introduction of adaptive bark thickness and resprouting produces more realistic fire regimes in savannas, including simulating biomass recovery rates consistent with Back Close observations. The new model (LPX-Mv1) improves Australian vegetation composition Full Screen / Esc by 33 % and burnt area by 19 % compared to LPX. Printer-friendly Version Interactive Discussion 932 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 1 Introduction GMDD The Land surface Processes and eXchanges (LPX) dynamic global vegetation model (DGVM) incorporates fire through a coupled fire module (Prentice et al., 2011) as fire 7, 931–1000, 2014 is a major agent in vegetation disturbance regimes (Bond and Van Wilgen, 1996) and 5 contributes to changes in interannual atmospheric carbon fluxes (Prentice et al., 2011; Parameterisation of van der Werf et al., 2008). LPX realistically simulates fire and vegetation cover glob- fire in LPX1 ally but performs relatively poorly in grassland and savanna ecosystems (Kelley et al., vegetation model 2013) – areas where fire is particularly important for maintaining vegetation diversity and ecosystem structure (e.g. Williams et al., 2002; Lehmann et al., 2008; Biganzoli D. I. Kelley et al. 10 et al., 2009). Specifically: – LPX produces sharp boundaries between areas of high burning and no burning Title Page in tropical and temperate regions. These sharp fire boundaries produce sharp boundaries between grasslands and forests. The unrealistically high fire-induced Abstract Introduction tree mortality prevents the development of transitions via more open forests and Conclusions References 15 woodlands. Tables Figures – LPX simulates too little fire in areas of high but seasonal rainfall because fuel takes an unrealistically long time to dry, and because LPX fails to produce open woody vegetation in these areas. J I – In arid areas, where fire is limited by fuel availability, LPX simulates too much Net J I 20 Primary Production (NPP) resulting in unrealistically high fuel loads and generat- Back Close ing more fire than observed. Full Screen / Esc To address these shortcomings in the version of LPX running at Macquarie University (here designated LPX-M), we re-parameterised lightning ignitions, fuel moisture, fuel Printer-friendly Version decomposition, plant adaptations to arid conditions via rooting depth, and woody plant 25 resistance to fire through bark thickness. In each case, the new parameterisation was Interactive Discussion developed based on extensive data analysis. We tested each parameterisation sepa- rately, and then all parametrisations combined, using a comprehensive benchmarking 933 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | system (Kelley et al., 2013) which assesses model performance against observations of key vegetation and fire processes. We then included a new treatment of woody plant GMDD recovery after fire through resprouting – a behavioural trait that increases post-fire 7, 931–1000, 2014 competitiveness compared to non-resprouters in fire-prone areas (Clarke et al., 2013) 5 – and tested the impact of introducing this new component on model performance. Parameterisation of fire in LPX1 2 LPX model description vegetation model LPX is a Plant Functional Type (PFT) based model. Nine PFTs are distinguished by D. I. Kelley et al. a combination of life form (tree, grass) and leaf type (broad, needle), phenology (ev- ergreen, deciduous) and climate range (tropical, temperate, boreal) for trees and pho- 10 tosynthetic pathway (C3,C4) for grasses. PFTs are represented by a set of parame- Title Page ters. Each PFT that occurs within a gridcell is represented by an “average” plant, and ecosystem-level behaviour is calculated by multiplying the simulated properties of this Abstract Introduction average plant by the simulated number of individuals in the PFT in that gridcell. PFT- Conclusions References specific properties (e.g. establishment, mortality and growth) are updated annually, but 15 water and carbon-exchange processes are simulated on shorter timesteps. Tables Figures LPX incorporates a process-based fire scheme (Fig. 1) run on a daily timestep (Prentice et al., 2011). Ignition rates are derived from a monthly lightning climatology, J I interpolated to the daily timestep. The number of lighting strikes that reach the ground (cloud-to-ground: CG) is specified as 20 % of the total number of strikes (Thonicke J I 20 et al., 2010). The CG lightning is split into dry (CGdry) and wet strikes based on the Back Close fraction of wetdays in the month (Pwet): Full Screen / Esc β CGdry = CG · (1 − Pwet) (1) Printer-friendly Version where β is a parameter tuned to 0.00001. “Wet” lightning is not considered to be an 25 ignition source (Prentice et al., 2011). Lightning is finally scaled down by 85 % to al- Interactive Discussion low for discontinuous current strikes. Numerical precision limits of the compiled code means the function described by Eq. (1) effectively removes all strikes in months with 934 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | more than two wet days in LPX. Monthly “dry” lightning is distributed evenly across all dry days. GMDD Fuel loads are generated from litter production and decay using the vegetation dy- 7, 931–1000, 2014 namics algorithms in LPJ (Sitch et al., 2003). LPX does not simulate competition be- 5 tween C3 and C4 grasses explicitly; in gridcells where C3 and C4 grasses co-exist, the total NPP is estimated as the potential NPP of each grass type in the absence of the Parameterisation of other type and this produces erroneously high NPP. This problem can be corrected by fire in LPX1 scaling the fractional projective cover (FPC) and Leaf Area Index (LAI) of each grass vegetation model PFT by the ratio of total simulated grass leaf mass of both PFTs to the leaf mass ex- D. I. Kelley et al. 10 pected if only one grass PFT was present (B. Stocker, personal communication, 2012) Fuel decomposition rate (k) depends on temperature and moisture, and is the same for all PFTs and fuel structure types:
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