The global rate of fossil fuel combustion continues to rise, but the amount of CO₂ accumulating in the atmosphere has not increased accordingly (Tans et al., 1990; Conway et al., 1994; Wofsy, 2001).  The causes for this discrepancy are widely debated (Houghton, 2003).  In particular, the location and drivers for the interannual variability of atmospheric CO₂ are highly uncertain.  Here we examine links between global atmospheric CO₂ growth rate (CGR) and the climate anomalies of biomes based on ten years (1986-1995) of global climate data and accompanying satellite data sets.  Our results show that four biomes, the tropical rainforest, tropical savanna, C₄ grassland and boreal forest, and their responses to climate anomalies, are the major climate-sensitive CO₂ sinks/sources that control the CGR.  The nature and magnitude by which these biomes respond to climate anomalies are generally not the same.  However, one common influence did emerge from our analysis; the extremely high CGR that was observed for the one extreme El Niño year was caused by the response of the tropical biomes (rainforest, savanna and C₄ grassland) to temperature.

The forests of Siberia represent one of the last natural frontiers in the world. Nearly 65% of Siberia's forests grow in areas with permafrost and Larch forests are dominated here. According to our estimates, carbon stocks in the soils of permafrost forest and tundra ecosystems of Yakutia amount to 17 Gt (altogether 126 Mha of forest area and 37 Mha of tundra).  It is about 25% of total carbon stock in forest soils of the Russian Federation. This carbon has been accumulated during centuries, and rapid climate change may release its huge amount for relatively short period, thus enhancing rather source than sink role of Russia. The total stock of terrestrial phytomass carbon of forests, tundra and meadows of Yakutia is 2.2-4.5 Gt C, including 0.053 Gt C of tundra and meadows.

A long-term observation of CO₂ exchange was conducted above a broadleaved deciduous forest in Sapporo, northern Japan. The CO₂ exchange was measured using the eddy covariance method with closed-path gas analyzer and we obtained net ecosystem production (NEP). We estimated a carbon budget using a simple empirical model. In this model, ecosystem respiration (RE) and gross primary production (GPP) were parameterized by soil temperature and photosynthetically active radiation (PAR) respectively. The annual NEP derived from an equation “NEP = GPP -RE” ranged from 237 to 431 g C m^-2 year^-1 for 4 years (2000 - 2003).

The objective of this study is to provide improved estimation of the area extent for major mire types within West Siberia (WS) and determine the spatial variability of NPP and biomass in relation to macro/micro landscape and site position within the bioclimatic division. Our approach relies upon scaling up available field survey and literature data to provide wetland net primary production (NPP) and biomass inventory maps for West Siberia. Both, satellite images and aerial photography classifications have been used to extrapolate site data into a regional inventory map (1:2.5M scale). Total NPP of wetlands is estimated as 530.5 TgDM (teragram/megaton dry matter)yr^-1, or 624.4 TgDM/yr when woody parts are included. Lowest NPP has been assigned to wetlands at the northern part of Taiga zone (4.5-6.2 tonDM)/ha/yr^-1). Wetlands in Tundra, Forested tundra and southern parts of Taiga zone show considerably higher NPP values. Minimum of living biomass storage was found in middle and southern taiga subzones. It is also increased to the north and south within West Siberian territory.

In this study, we developed an integrated modeling system to simulate dynamics of a stable carbon isotope of CO₂, moisture, energy, and momentum between boreal ecosystems and the atmosphere as well as their diffusion processes through the whole convective boundary layer (CBL), using remotely sensed surface parameters to characterize the surface heterogeneity, and the marine boundary layer matrix data to represent the CBL top condition. Model validation and primary results in boreal ecosystems were presented in this paper.

Our research goal is to assess the regional vegetation dynamics in the Iberian Peninsula (IP). For this purpose, estimations of net ecosystem production (NEP) from a productivity ecosystem model, the Carnegie Ames Stanford Approach (CASA) model [Potter et al., 1993], were compared with local CO₂ flux measurements. The CASA calibration process aimed the tuning of efficiency scalars directly related to net primary productivity and soil respiration calculations: maximum light use efficiency (ε*) and temperature effect on soil fluxes (Q₁₀), respectively. Local weather station data was used for climatic inputs, as well as remotely sensed leaf area index (LAI) and fraction of photosynthetically active radiation (FPAR) from the MODIS TERRA sensor. Firstly, NEP calculations were performed at different temporal resolutions, ranging from monthly to daily time steps, in order to assess the impact of temporal scales on productivity estimates. Both the calibration and validation procedures showed significant confidence, although the main processes behind vegetation carbon fluxes were best simulated at temporal scales ranging from 8 days to monthly. The impact of spatial scale was also analyzed on the NEP estimates. It was found that results accuracy was influenced by the data spatial resolution, and, furthermore, by the tree cover percentage of the aggregated cells. A correction method was implemented and a reduction of the spatial aggregation error up to 10% was obtained. The long term NEP analysis for the IP indicates statistically significant positive trends mainly related to solar radiation positive trends. A less significant negative trend was also found with a strong spatial autocorrelation behavior.

Progress in determining CO₂ sources, sinks, and their response to environmental forcing will rely on utilization of more extensive and intensive CO₂ and related observations including those from satellite remote sensing.  Full exploitation of new observations will require new modeling and analysis techniques, especially those that can use information at finer spatial and temporal scales than has traditionally been employed in “top-down” carbon flux studies.  We report on a modeling effort to reduce uncertainty in carbon cycle processes that create the so-called missing terrestrial sink of atmospheric CO₂ using transport fields derived from NASA’s GEOS-4 meteorological assimilation analyses.  Our overall objective is to improve characterization of CO₂ source/sink processes globally with improved formulations for atmospheric transport, terrestrial uptake and release, biomass and fossil fuel burning, and observational data analysis.  We show results from an advanced biosphere model (SiB3) constrained by remote sensing data and coupled to the global transport model to produce distributions of CO₂ fluxes and concentrations that are consistent with actual meteorological variability.  Use of analyzed meteorological data allows comparison to observations on a wide range of temporal and spatial scales.  Here we compare with local-to-global data for hourly to annual CO₂ simulation.  The results will help to prepare for the use of satellite CO₂ and other data in a multi-disciplinary carbon data assimilation system for analysis and prediction of carbon cycle changes and carbon/climate interactions.

We report modeling experiments with a new global dynamic land model (LM3V), to reconstruct possible causes of the terrestrial carbon sources and sinks over the past century.  The model is unique, in that it is capable of representing the global history of land use, including the management of secondary forests (those forests that have re-grown at least once following harvest). Several published carbon inventories attribute the majority of the carbon sink caused by land use in the temperate zone to the management of secondary forests.

A spatially-distributed model of net ecosystem production (NEP) was run over western Oregon for the period 2001-2003 at the 1 km spatial resolution and daily temporal resolution.  Inputs included MODIS-based FPAR, Landsat-based land cover and disturbance history, and distributed meteorology. Resulting NEP showed sensitivity to 1) areas of recent disturbance, such as a large forest fire in 2002, 2) areas of intensive management for timber production, 3) topographically-driven climatic gradients, and 4) interannual variation in climate. Validation measurements included a network of field plots and a chronosequence study.