Integrating peatlands and permafrost into a dynamic global vegetation model: 1. Evaluation and sensitivity of physical land surface processes

Abstract

[1] Northern peatlands and permafrost soils are associated with large carbon stocks. Rising temperatures are likely to affect the carbon balance in high-latitude ecosystems, but to what degree is uncertain. We have enhanced the Lund-Potsdam-Jena (LPJ) dynamic global vegetation model by introducing processes necessary to simulate permafrost dynamics, peatland hydrology, and peatland vegetation. The new version, LPJ-WHy v1.2, was used to study soil temperature, active layer depth, permafrost distribution, and water table position. Modeled soil temperatures agreed well with observations, apart from a Siberian site where the soil is insulated by an extensive shrub layer. Water table positions were generally in the range of observations, with some exceptions. Simulated active layer depth showed a mean absolute error of 44 cm when compared to observations, but the error was reduced to 25 cm when the soil type for seven sites was manually corrected to mirror local conditions. A sensitivity test, in which temperature and precipitation were varied independently, showed that soil temperatures and active layer depths increased more under higher temperatures when precipitation was increased at the same time. The sensitivity experiment suggested persisting wet conditions in peatlands even under temperature increases of up to 9°C as long as annual precipitation is allowed to increase with temperature to the extent indicated by climate model experiments.

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

“…LPJ-Bern is a subsequent development of the Lund-PotsdamJena dynamic global vegetation model Joos et al, 2004;Gerber et al, 2003) that combines processbased, large-scale representations of terrestrial vegetation dynamics, soil hydrology (Gerten et al, 2004;Wania et al, 2009a), human induced land use changes (Strassmann et al, 2008;Stocker et al, 2011), permafrost and peatland establishment (Wania et al, 2009a,b) and simulation of biogeochemical trace gas emissions, such as CH 4 (Wania et al, 2010;Spahni et al, 2011;Zürcher et al, 2013). LPJ-Bern uses a different ebullition mechanism for CH 4 emissions from peatlands, which includes variations in partial pressure of CO 2 .…”

“…Methane emissions for peatlands north of 35 • N were simulated using LPJ-WHyMe (Wania et al, 2009a(Wania et al, ,b, 2010Spahni et al, 2011). Location and fractional cover of peatlands are taken from NCSCD (Tarnocai et al, 2007(Tarnocai et al, , 2009.…”

“…The simple scheme of Kaplan (2002) used threshold values of slope and soil moisture content to define wetland areas, with the soil moisture calculated by an equilibrium vegetation model (BIOME4); an approach adopted by other models (Shindell et al, 2004;Weber et al, 2010;Avis et al, 2011). Later schemes used land cover datasets to outline peatland regions (Wania et al, 2009a(Wania et al, , 2010Spahni et al, 2011), and/or satellite-derived inundation datasets to prescribe wetlands either directly (Hodson et al, 2011;Ringeval et al, 2010), or indirectly Riley et al, 2011). Other wetland distribution schemes use internally calculated water table positions or soil moisture thresholds to locate wetlands .…”

Modelling Tundra Vegetation Response to Recent Arctic Warming

“…Compared with the standard version of the model (Smith et al 2001;Hickler et al 2012), the Arctic version includes differentiated representations of processes operating in upland and peatland ecosystems of the tundra and taiga biomes, as well as PFTs characteristic of Arctic ecosystems: evergreen and deciduous shrubs, forbs, graminoids and bryophytes. The model includes an improved description of soil freezing processes (affecting water available to plants), based on Wania et al (2009).…”

WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia

“…Among the participating models (Table 2) were those of the WETCHIMP study Wania et al, 2013) that contributed CH 4 emissions estimates: CLM4Me (Riley et al, 2011), DLEM (Tian et al, 2010(Tian et al, , 2011a(Tian et al, , b, 2012, IAP-RAS (Mokhov et al, 2007;Eliseev et al, 2008), LPJ-Bern (Spahni et al, 2011, LPJWHyMe (Wania et al, 2009a(Wania et al, , b, 2010, LPJ-WSL (Hodson et al, 2011), ORCHIDEE (Ringeval et al, 2010), SDGVM (Hopcroft et al, 2011), and UW-VIC (denoted by "UW-VIC (GIEMS)"; Bohn et al, 2013). In addition, we analyzed several other models.…”