GLOBAL NET CARBON EXCHANGE AND INTRAANNUAL ATMOSPHERIC CO2 CONCENTRATIONS PREDICTED BY AN ECOSYSTEM PROCESS MODEL AND 3-DIMENSIONAL ATMOSPHERIC TRANSPORT MODEL
Er. Hunt et al., GLOBAL NET CARBON EXCHANGE AND INTRAANNUAL ATMOSPHERIC CO2 CONCENTRATIONS PREDICTED BY AN ECOSYSTEM PROCESS MODEL AND 3-DIMENSIONAL ATMOSPHERIC TRANSPORT MODEL, Global biogeochemical cycles, 10(3), 1996, pp. 431-456
A generalized terrestrial ecosystem process model, BIOME-BGC (for BIOM
E BioGeoChemical Cycles), was used to simulate the global fluxes of CO
2 resulting from photosynthesis, autotrophic respiration, and heterotr
ophic respiration. Daily meteorological data for the year 1987, gridde
d to 1 degrees by 1 degrees, were used to drive the model simulations.
From the maximum value of the normalized difference vegetation index
(NDVI) for 1987, the leaf area index for each grid cell was computed.
Global NPP was estimated to be 52 Pg C, and global R(h) was estimated
to be 66 Pg C. Model predictions of the stable carbon isotopic ratio C
-13/C-12 for C-3 and C-4 vegetation were in accord with values publish
ed in the literature, suggesting that our computations of total net ph
otosynthesis, and thus NPP, are more reliable than R(h). For each grid
cell, daily R(h) was adjusted so that the annual total was equal to a
nnual NPP, and the resulting net carbon fluxes were used as inputs to
a three-dimensional atmospheric transport model (TM2) using wind data
from 1987. We compared the spatial and seasonal patterns of NPP with a
diagnostic NDVI model, where NPP was derived from biweekly NDVI data
and Rh was tuned to fit atmospheric CO2 observations from three northe
rn stations. To an encouraging degree, predictions from the BIOME-BGC
model agreed in phase and amplitude with observed atmospheric CO2 conc
entrations for 20 degrees to 55 degrees N, the zone in which the most
complete data on ecosystem processes and meteorological input data are
available. However, in the tropics and high northern latitudes, disag
reements between simulated and measured CO2 concentrations indicated a
reas where the model could be improved. We present here a methodology
by which terrestrial ecosystem models can be tested globally, not by c
omparisons to homogeneous-plot data, but by seasonal and spatial consi
stency with a diagnostic NDVI model and atmospheric CO2 observations.