TY - JOUR
T1 - Implementation and evaluation of a new methane model within a dynamic global vegetation model
T2 - LPJ-WHyMe v1.3.1
AU - Wania, R.
AU - Ross, I.
AU - Prentice, I. C.
PY - 2010
Y1 - 2010
N2 - For the first time, a model that simulates methane emissions from northern peatlands is incorporated directly into a dynamic global vegetation model. The model, LPJ-WHyMe (LPJ Wetland Hydrology and Methane), was previously modified in order to simulate peatland hydrology, permafrost dynamics and peatland vegetation. LPJ-WHyMe simulates methane emissions using a mechanistic approach, although the use of some empirical relationships and parameters is unavoidable. The model simulates methane production, three pathways of methane transport (diffusion, plant-mediated transport and ebullition) and methane oxidation. A sensitivity test was conducted to identify the most important factors influencing methane emissions, followed by a parameter fitting exercise to find the best combination of parameter values for individual sites and over all sites. A comparison of model results to observations from seven sites resulted in normalised root mean square errors (NRMSE) of 0.40 to 1.15 when using the best site parameter combinations and 0.68 to 1.42 when using the best overall parameter combination.
AB - For the first time, a model that simulates methane emissions from northern peatlands is incorporated directly into a dynamic global vegetation model. The model, LPJ-WHyMe (LPJ Wetland Hydrology and Methane), was previously modified in order to simulate peatland hydrology, permafrost dynamics and peatland vegetation. LPJ-WHyMe simulates methane emissions using a mechanistic approach, although the use of some empirical relationships and parameters is unavoidable. The model simulates methane production, three pathways of methane transport (diffusion, plant-mediated transport and ebullition) and methane oxidation. A sensitivity test was conducted to identify the most important factors influencing methane emissions, followed by a parameter fitting exercise to find the best combination of parameter values for individual sites and over all sites. A comparison of model results to observations from seven sites resulted in normalised root mean square errors (NRMSE) of 0.40 to 1.15 when using the best site parameter combinations and 0.68 to 1.42 when using the best overall parameter combination.
UR - http://www.scopus.com/inward/record.url?scp=78649238511&partnerID=8YFLogxK
U2 - 10.5194/gmd-3-565-2010
DO - 10.5194/gmd-3-565-2010
M3 - Article
AN - SCOPUS:78649238511
SN - 1991-959X
VL - 3
SP - 565
EP - 584
JO - Geoscientific Model Development
JF - Geoscientific Model Development
IS - 2
ER -