Abstract. Most forests of the world are recovering from a past disturbance. It is well known that forest disturbances profoundly affect carbon stocks and fluxes in forest ecosystems, yet it has been a great challenge to assess disturbance impacts in estimates of forest carbon budgets. Net sequestration or loss of CO 2 by forests after disturbance follows a predictable pattern with forest recovery. Forest age, which is related to time since disturbance, is a useful surrogate variable for analyses of the impact of disturbance on forest carbon. In this study, we compiled the first continental forest age map of North America by combining forest inventory data, historical fire data, optical satellite data and the dataset from NASA's Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) project. A companion map of the standard deviations for age estimates was developed for quantifying uncertainty. We discuss the significance of the disturbance legacy from the past, as represented by current forest age structure in different regions of the US and Canada, by analyzing the causes of disturbances from land management and nature over centuries and at various scales. We also show how such information can be used with inventory data for analyzing carbon management opportunities. By combining geographic information about forest age with estimated C dynamics by forest type, it is possible to conduct a simple but powerful analysis of the net CO 2 uptake by forests, and the potential for increasing (or decreasing) this rate as a result of direct human intervention in the disturbance/age status. Finally, we describe how the forest age data can be used in large-scale carbon modeling, both for land-based biogeochemistry models and atmosphere-based inversion models, in order to improve the spatial accuracy of carbon cycle simulations.

Abstract. The use of global three-dimensional (3-D) models with satellite observations of CO 2 in inverse modeling studies is an area of growing importance for understanding Earth's carbon cycle. Here we use the GEOS-Chem model (version 8-02-01) CO 2 mode with multiple modifications in order to assess their impact on CO 2 forward simulations. Modifications include CO 2 surface emissions from shipping (∼ 0.19 Pg C yr −1 ), 3-D spatially-distributed emissions from aviation (∼0.16 Pg C yr −1 ), and 3-D chemical production of CO 2 (∼1.05 Pg C yr −1 ). Although CO 2 chemical production from the oxidation of CO, CH 4 and other carbon gases is recognized as an important contribution to global CO 2 , it is typically accounted for by conversion from its precursors at the surface rather than in the free troposphere. We base our model 3-D spatial distribution of CO 2 chemical production on monthly-averaged loss rates of CO (a key precursor and intermediate in the oxidation of organic carbon) and apply an associated surface correction for inventories that have counted emissions of CO 2 precursors as CO 2 . We also explore the benefit of assimilating satellite observations of CO into GEOS-Chem to obtain an observation-based estimate of the CO 2 chemical source. The CO assimilationCorrespondence to: R. Nassar (ray.nassar@ec.gc.ca) corrects for an underestimate of atmospheric CO abundances in the model, resulting in increases of as much as 24% in the chemical source during May-June 2006, and increasing the global annual estimate of CO 2 chemical production from 1.05 to 1.18 Pg C. Comparisons of model CO 2 with measurements are carried out in order to investigate the spatial and temporal distributions that result when these new sources are added. Inclusion of CO 2 emissions from shipping and aviation are shown to increase the global CO 2 latitudinal gradient by just over 0.10 ppm (∼3%), while the inclusion of CO 2 chemical production (and the surface correction) is shown to decrease the latitudinal gradient by about 0.40 ppm (∼10%) with a complex spatial structure generally resulting in decreased CO 2 over land and increased CO 2 over the oceans. Since these CO 2 emissions are omitted or misrepresented in most inverse modeling work to date, their implementation in forward simulations should lead to improved inverse modeling estimates of terrestrial biospheric fluxes.

Abstract. The net surface exchange of CO 2 for the years 2002-2007 is inferred from 12 181 atmospheric CO 2 concentration data with a time-dependent Bayesian synthesis inversion scheme. Monthly CO 2 fluxes are optimized for 30 regions of the North America and 20 regions for the rest of the globe. Although there have been many previous multiyear inversion studies, the reliability of atmospheric inversion techniques has not yet been systematically evaluated for quantifying regional interannual variability in the carbon cycle. In this study, the global interannual variability of the CO 2 flux is found to be dominated by terrestrial ecosystems, particularly by tropical land, and the variations of regional terrestrial carbon fluxes are closely related to climate variations. These interannual variations are mostly caused by abnormal meteorological conditions in a few months in the year or part of a growing season and cannot be well represented using annual means, suggesting that we should pay attention to finer temporal climate variations in ecosystem modeling. We find that, excluding fossil fuel and biomass burning emissions, terrestrial ecosystems and oceans absorb an average of 3.63 ± 0.49 and 1.94 ± 0.41 Pg C yr −1 , respectively. The terrestrial uptake is mainly in northern land while the tropical and southern lands contribute 0.62 ± 0.47, and 0.67 ± 0.34 Pg C yr −1 to the sink, respectively. In North America, terrestrial ecosystems absorb 0.89 ± 0.18 Pg C yr −1 on average with a strong flux density found in the south-east of the continent.

The evapotranspiration (ET) from all Canadian landmass in 1996 is estimated at daily steps and 1 km resolution using a process model named boreal ecosystem productivity simulator (BEPS). The model is driven by remotely sensed leaf area index and land cover maps as well as soil water holding capacity and daily meteorological data. All the major ET components are considered: transpiration from vegetation, evaporation of canopy‐intercepted rainfall, evaporation from soil, sublimation of snow in winter and in permafrost and glacier areas, and sublimation of canopy‐intercepted snow. In forested areas the transpiration from both the overstory and understory vegetation is modeled separately. The Penman‐Monteith method was applied to sunlit and shaded leaf groups individually in modeling the canopy‐level transpiration, a methodological improvement necessary for forest canopies with considerable foliage clumping. The modeled ET map displays pronounced east‐west and north‐south gradients as well as detailed variations with cover types and vegetation density. It is estimated that for a relative wet year of 1996, the total ET from all Canada's landmass (excluding inland waters) was 2037 km3. If compared with the total precipitation of 5351 km3 based on the data from a medium range meteorological forecast model, the ratio of ET to precipitation was 38%. The ET averaged over Canadian land surface was 228 mm/yr in 1996, partitioned into transpiration of 102 mm yr−1 and evaporation and sublimation of 126 mm yr−1. Forested areas contributed the largest fraction of the total national ET at 59%. Averaged for all cover types, transpiration accounted for 45% of the total ET, while in forested areas, transpiration contributed 51% of ET. Modeled results of daily ET are compared with eddy covariance measurements at three forested sites with a r2 value of 0.61 and a root mean square error of 0.7 mm/day.

Abstract. We infer CO 2 surface fluxes using satellite observations of mid-tropospheric CO 2 from the Tropospheric Emission Spectrometer (TES) and measurements of CO 2 from surface flasks in a time-independent inversion analysis based on the GEOS-Chem model. Using TES CO 2 observations over oceans, spanning 40 • S-40 • N, we find that the horizontal and vertical coverage of the TES and flask data are complementary. This complementarity is demonstrated by combining the datasets in a joint inversion, which provides better constraints than from either dataset alone, when a posteriori CO 2 distributions are evaluated against independent ship and aircraft CO 2 data. In particular, the joint inversion offers improved constraints in the tropics where surface measurements are sparse, such as the tropical forests of South America. Aggregating the annual surface-to-atmosphere fluxes from the joint inversion for the year 2006 yields −1.13±0.21 Pg C for the global ocean, −2.77±0.20 Pg C for the global land biosphere and −3.90±0.29 Pg C for the total global natural flux (defined as the sum of all biospheric, oceanic, and biomass burning contributions but excluding CO 2 emissions from fossil fuel combustion). These global ocean and global land fluxes are shown to be near the median of the broad range of values from other inversion resultsCorrespondence to: R. Nassar (ray.nassar@ec.gc.ca) for 2006. To achieve these results, a bias in TES CO 2 in the Southern Hemisphere was assessed and corrected using aircraft flask data, and we demonstrate that our results have low sensitivity to variations in the bias correction approach. Overall, this analysis suggests that future carbon data assimilation systems can benefit by integrating in situ and satellite observations of CO 2 and that the vertical information provided by satellite observations of mid-tropospheric CO 2 combined with measurements of surface CO 2 , provides an important additional constraint for flux inversions.