The effect of optimization and the nesting domain on carbon flux analyses in Asia using a carbon tracking system based on the ensemble Kalman filter

To estimate the surface carbon flux in Asia and investigate the effect of the nesting domain on carbon flux analyses in Asia, two experiments with different nesting domains were conducted using the CarbonTracker developed by the National Oceanic and Atmospheric Administration. CarbonTracker is an inverse modeling system that uses an ensemble Kalman filter (EnKF) to estimate surface carbon fluxes from surface CO₂ observations. One experiment was conducted with a nesting domain centered in Asia and the other with a nesting domain centered in North America. Both experiments analyzed the surface carbon fluxes in Asia from 2001 to 2006. The results showed that prior surface carbon fluxes were underestimated in Asia compared with the optimized fluxes. The optimized biosphere fluxes of the two experiments exhibited roughly similar spatial patterns but different magnitudes. Weekly cumulative optimized fluxes showed more diverse patterns than the prior fluxes, indicating that more detailed flux analyses were conducted during the optimization. The nesting domain in Asia produced a detailed estimate of the surface carbon fluxes in Asia and exhibited better agreement with the CO₂ observations. Finally, the simulated background atmospheric CO₂ concentrations in the experiment with the nesting domain in Asia were more consistent with the observed CO₂ concentrations than those in the experiment with the nesting domain in North America. The results of this study suggest that surface carbon fluxes in Asia can be estimated more accurately using an EnKF when the nesting domain is centered in Asian regions.     

Accounting for CO<Subscript>2</Subscript> variability over East Asia with a regional joint inversion system and its preliminary evaluation

A regional surface carbon dioxide (CO₂) flux inversion system, the Tan-Tracker-Region, was developed by incorporating an assimilation scheme into the Community Multiscale Air Quality (CMAQ) regional chemical transport model to resolve fine-scale CO₂ variability over East Asia. The proper orthogonal decomposition-based ensemble four-dimensional variational data assimilation approach (POD-4DVar) is the core algorithm for the joint assimilation framework, and simultaneous assimilations of CO₂ concentrations and surface CO₂ fluxes are applied to help reduce the uncertainty in initial CO₂ concentrations. A persistence dynamical model was developed to describe the evolution of the surface CO₂ fluxes and help avoid the “signal-to-noise” problem; thus, CO₂ fluxes could be estimated as a whole at the model grid scale, with better use of observation information. The performance of the regional inversion system was evaluated through a group of single-observation-based observing system simulation experiments (OSSEs). The results of the experiments suggest that a reliable performance of Tan-Tracker-Region is dependent on certain assimilation parameter choices, for example, an optimized window length of approximately 3 h, an ensemble size of approximately 100, and a covariance localization radius of approximately 320 km. This is probably due to the strong diurnal variation and spatial heterogeneity in the fine-scale CMAQ simulation, which could affect the performance of the regional inversion system. In addition, because all observations can be artificially obtained in OSSEs, the performance of Tan-Tracker-Region was further evaluated through different densities of the artificial observation network in different CO₂ flux situations. The results indicate that more observation sites would be useful to systematically improve the estimation of CO₂ concentration and flux in large areas over the model domain. The work presented here forms a foundation for future research in which a thorough estimation of CO₂ flux variability over East Asia could be performed with the regional inversion system.     

Accounting for CO_2 Variability over East Asia with a Regional Joint Inversion System and Its Preliminary Evaluation

A regional surface carbon dioxide(CO_2) flux inversion system, the Tan-Tracker-Region, was developed by incorporating an assimilation scheme into the Community Multiscale Air Quality(CMAQ) regional chemical transport model to resolve fine-scale CO_2 variability over East Asia. The proper orthogonal decomposition-based ensemble four-dimensional variational data assimilation approach(POD-4 DVar) is the core algorithm for the joint assimilation framework, and simultaneous assimilations of CO_2 concentrations and surface CO_2 fluxes are applied to help reduce the uncertainty in initial CO_2 concentrations. A persistence dynamical model was developed to describe the evolution of the surface CO_2 fluxes and help avoid the "signal-to-noise" problem; thus, CO_2 fluxes could be estimated as a whole at the model grid scale, with better use of observation information. The performance of the regional inversion system was evaluated through a group of single-observation-based observing system simulation experiments(OSSEs). The results of the experiments suggest that a reliable performance of Tan-Tracker-Region is dependent on certain assimilation parameter choices, for example, an optimized window length of approximately 3 h, an ensemble size of approximately 100, and a covariance localization radius of approximately 320 km. This is probably due to the strong diurnal variation and spatial heterogeneity in the fine-scale CMAQ simulation, which could affect the performance of the regional inversion system. In addition, because all observations can be artificially obtained in OSSEs, the performance of Tan-Tracker-Region was further evaluated through different densities of the artificial observation network in different CO_2 flux situations. The results indicate that more observation sites would be useful to systematically improve the estimation of CO_2 concentration and flux in large areas over the model domain. The work presented here forms a foundation for future research in which a thorough estimation of CO_2 flux variability over East Asia could be performed with the regional inversion system.     

Simulation of Non-Homogeneous CO<Subscript>2</Subscript> and Its Impact on Regional Temperature in East Asia

Carbon dioxide (CO₂) is an important greenhouse gas that influences regional climate through disturbing the earth’s energy balance. The CO₂ concentrations are usually prescribed homogenously in most climate models and the spatiotemporal variations of CO₂ are neglected. To address this issue, a regional climate model (RegCM4) is modified to investigate the non-homogeneous distribution of CO₂ and its effects on regional longwave radiation flux and temperature in East Asia. One-year simulation is performed with prescribed surface CO₂ fluxes that include fossil fuel emission, biomass burning, air–sea exchange, and terrestrial biosphere flux. Two numerical experiments (one using constant prescribed CO₂ concentrations in the radiation scheme and the other using the simulated CO₂ concentrations that are spatially non-homogeneous) are conducted to assess the impact of non-homogeneous CO₂ on the regional longwave radiation flux and temperature. Comparison of CO₂ concentrations from the model with the observations from the GLOBALVIEW-CO₂ network suggests that the model can well capture the spatiotemporal patterns of CO₂ concentrations. Generally, high CO₂ mixing ratios appear in the heavily industrialized eastern China in cold seasons, which probably relates to intensive human activities. The accommodation of non-homogeneous CO₂ concentrations in the radiative transfer scheme leads to an annual mean change of–0.12 W m^–2 in total sky surface upward longwave flux in East Asia. The experiment with non-homogeneous CO₂ tends to yield a warmer lower troposphere. Surface temperature exhibits a maximum difference in summertime, ranging from–4.18 K to 3.88 K, when compared to its homogeneous counterpart. Our results indicate that the spatial and temporal distributions of CO₂ have a considerable impact on regional longwave radiation flux and temperature, and should be taken into account in future climate modeling.     

Estimates of Large-Scale Fluxes in High Latitudes from Terrestrial Biosphere Models and an Inversion of Atmospheric CO2 Measurements

It is important to improve estimates of large-scale carbon fluxes over the boreal forest because the responses of this biome to global change may influence the dynamics of atmospheric carbon dioxide in ways that may influence the magnitude of climate change. Two methods currently being used to estimate these fluxes are process-based modeling by terrestrial biosphere models (TBMs), and atmospheric inversions in which fluxes are derived from a set of observations on atmospheric CO₂ concentrations via an atmospheric transport model. Inversions do not reveal information about processes and therefore do not allow for predictions of future fluxes, while the process-based flux estimates are not necessarily consistent with atmospheric observations of CO₂. In this study we combine the two methods by using the fluxes from four TBMs as a priori fluxes for an atmospheric Bayesian Synthesis Inversion. By doing so we learn about both approaches. The results from the inversion indicate where the results of the TBMs disagree with the atmospheric observations of CO₂, and where the results of the inversion are poorly constrained by atmospheric data, the process-based estimates determine the flux results. The analysis indicates that the TBMs are modeling the spring uptake of CO₂ too early, and that the inversion shows large uncertainty and more dependence on the initial conditions over Europe and Boreal Asia than Boreal North America. This uncertainty is related to the scarcity of data over the continents, and as this problem is not likely to be solved in the near future, TBMs will need to be developed and improved, as they are likely the best option for understanding the impact of climate variability in these regions.     

Energy Balance Closure Using Eddy Covariance Above Two Different Land Surfaces and Implications for CO<Subscript>2</Subscript> Flux Measurements

Components of the surface energy balance of a mature boreal jack pine forest and a jack pine clearcut were analysed to determine the causes of the imbalance that is commonly observed in micrometeorological measurements. At the clearcut site (HJP02), a significant portion of the imbalance was caused by: (i) the overestimation of net radiation (R _n ) due to the inclusion of the tower in the field of view of the downward facing radiometers, and (ii) the underestimation of the latent heat flux (λE) due to the damping of high frequency fluctuations in the water vapour mixing ratio by the sample tube of the closed-path infrared gas analyzer. Loss of low-frequency covariance induced by insufficient averaging time as well as systematic advection of fluxes away from the eddy-covariance (EC) tower were discounted as significant issues. Spatial and temporal distributions of the total surface-layer heat flux (T), i.e. the sum of sensible heat flux (H) and λE, were well behaved and differences between the relative magnitudes of the turbulent fluxes for several investigated energy balance closure (C) classes were observed. Therefore, it can be assumed that micrometeorological processes that affected all turbulent fluxes similarly did not cause the variation in C. Turbulent fluxes measured at the clearcut site should not be forced to close the energy balance. However, at the mature forest site (OJP), loss of low-frequency covariance contributed significantly to the systematic imbalance when a 30-min averaging time was used, but the application of averaging times that were long enough to capture all of the low-frequency covariance was inadequate to resolve all of the high-frequency covariance. Although we found qualitative similarity between T and the net ecosystem exchange (NEE) of carbon dioxide (CO₂), forcing T to closure while retaining the Bowen ratio and applying the same factor to CO₂ fluxes (F _C ) cannot be generally recommended since it remains uncertain to what extent long wavelength contributions affect the relationship between T, F _C and C.     

A simulation study for the global carbon cycle,including man's impact on the biosphere

The simulation model accounts for four major compartments in the global carbon cycle: atmosphere, ocean, terrestrial biosphere and fossil carbon reservoir. The ocean is further compartmentalized into a high and a low latitude surface layer, and into 10 deep sea strata. The oceanic carbon fluxes are caused by massflow of descending and upwelling water, by precipitation of organic material and by diffusion exchange.The biosphere is horizontally subdivided into six ecosystems and vertically into leaves, branches, stemwood, roots, litter, young humus and stable soil carbon. Deforestation, slash and burn agriculture, rangeland burning and shifts in land use have been included. The atmosphere is treated as one well mixed reservoir. Fossil fuel consumption is simulated with historic data, and with IIASA scenario's for the future. Using the low IIASA scenario an atmospheric CO₂ concentration of 431 ppmv is simulated for 2030 AD. A sensitivity analysis shows the importance of different parameters and of human behaviour. Notwithstanding the large size of the biosphere fluxes, the atmospheric CO₂ concentration in the next century will be predominantly determined by the growth rate of fossil fuel consumption.     

Interpreting CO<Subscript>2</Subscript> Fluxes Over a Suburban Lawn: The Influence of Traffic Emissions

Turf-grass lawns are ubiquitous in the United States. However direct measurements of land–atmosphere fluxes using the eddy-covariance method above lawn ecosystems are challenging due to the typically small dimensions of lawns and the heterogeneity of land use in an urbanised landscape. Given their typically small patch sizes, there is the potential that CO₂ fluxes measured above turf-grass lawns may be influenced by nearby CO₂ sources such as passing traffic. In this study, we report on two years of eddy-covariance flux measurements above a 1.5 ha turf-grass lawn in which we assess the contribution of nearby traffic emissions to the measured CO₂ flux. We use winter data when the vegetation was dormant to develop an empirical estimate of the traffic effect on the measured CO₂ fluxes, based on a parametrised version of a three-dimensional Lagrangian footprint model and continuous traffic count data. The CO₂ budget of the ecosystem was adjusted by 135gCm⁻² in 2007 and by 134gCm⁻² in 2008 to determine the natural flux, even though the road crossed the footprint only at its far edge. We show that bottom-up flux estimates based on CO₂ emission factors of the passing vehicles, combined with the crosswind-integrated footprint at the distance of the road, agreed very well with the empirical estimate of the traffic contribution that we derived from the eddy-covariance measurements. The approach we developed may be useful for other sites where investigators plan to make eddy-covariance measurements on small patches within heterogeneous landscapes where there are significant contrasts in flux rates. However, we caution that the modelling approach is empirical and will need to be adapted individually to each site.     

CO<Subscript>2</Subscript> dynamics on the shelf of the East Siberian Sea

Expedition data obtained in the coastal-shelf zone of the East Siberian Sea in September 2003, 2004, and 2008 are generalized. Studies of carbonate system in water and CO₂ fluxes between ocean and atmosphere in this region confirmed that it was reasonable to divide the water area studied into two biogeochemical provinces and that the ecosystem of its coastal part is mainly of a heterotrophic nature. In different years, the extent of water supersaturation in carbon dioxide in the East Siberian Sea and the area of the CO₂ release significantly changed. Geographic localization of the atmosphere action centers over the Arctic and their intensity were main determining factors; that told both on the formation of a basic character of the atmospheric and hydrological processes and on the dynamics of the CO₂ exchange between water and air.     

The Simulation of the Opposing Fluxes of Latent Heat and CO<Subscript>2</Subscript> over Various Land-Use Types: Coupling a Gas Exchange Model to a Mesoscale Atmospheric Model

A mesoscale meteorological model (FOOT3DK) is coupled with a gas exchange model to simulate surface fluxes of CO₂ and H₂O under field conditions. The gas exchange model consists of a C3 single leaf photosynthesis sub-model and an extended big leaf (sun/shade) sub-model that divides the canopy into sunlit and shaded fractions. Simulated CO₂ fluxes of the stand-alone version of the gas exchange model correspond well to eddy-covariance measurements at a test site in a rural area in the west of Germany. The coupled FOOT3DK/gas exchange model is validated for the diurnal cycle at singular grid points, and delivers realistic fluxes with respect to their order of magnitude and to the general daily course. Compared to the Jarvis-based big leaf scheme, simulations of latent heat fluxes with a photosynthesis-based scheme for stomatal conductance are more realistic. As expected, flux averages are strongly influenced by the underlying land cover. While the simulated net ecosystem exchange is highly correlated with leaf area index, this correlation is much weaker for the latent heat flux. Photosynthetic CO₂ uptake is associated with transpirational water loss via the stomata, and the resulting opposing surface fluxes of CO₂ and H₂O are reproduced with the model approach. Over vegetated surfaces it is shown that the coupling of a photosynthesis-based gas exchange model with the land-surface scheme of a mesoscale model results in more realistic simulated latent heat fluxes.     

The First Global Carbon Dioxide Flux Map Derived from TanSat Measurements

Space-borne measurements of atmospheric greenhouse gas concentrations provide global observation constraints for top-down estimates of surface carbon flux.Here,the first estimates of the global distribution of carbon surface fluxes inferred from dry-air CO_2 column (XCO_2) measurements by the Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite (Tan Sat) are presented.An ensemble transform Kalman filter (ETKF) data assimilation system coupled with the GEOS-Chem global chemistry transport model is used to optimally fit model simulations with the Tan Sat XCO_2 observations,which were retrieved using the Institute of Atmospheric Physics Carbon dioxide retrieval Algorithm for Satellite remote sensing (IAPCAS).High posterior error reduction (30%–50%) compared with a priori fluxes indicates that assimilating satellite XCO_2 measurements provides highly effective constraints on global carbon flux estimation.Their impacts are also highlighted by significant spatiotemporal shifts in flux patterns over regions critical to the global carbon budget,such as tropical South America and China.An integrated global land carbon net flux of 6.71±0.76 Gt C yr~(-1) over12 months (May 2017–April 2018) is estimated from the Tan Sat XCO_2 data,which is generally consistent with other inversions based on satellite data,such as the JAXA GOSAT and NASA OCO-2 XCO_2 retrievals.However,discrepancies were found in some regional flux estimates,particularly over the Southern Hemisphere,where there may still be uncorrected bias between satellite measurements due to the lack of independent reference observations.The results of this study provide the groundwork for further studies using current or future Tan Sat XCO_2 data together with other surfacebased and space-borne measurements to quantify biosphere–atmosphere carbon exchange.     

Assimilating Best Track Minimum Sea Level Pressure Data Together with Doppler Radar Data Using an Ensemble Kalman Filter for Hurricane Ike (2008) at a Cloud-Resolving Resolution

Extending an earlier study, the best track minimum sea level pressure (MSLP) data are assimilated for landfalling Hurricane Ike (2008) using an ensemble Kalman filter (EnKF), in addition to data from two coastal ground-based Doppler radars, at a 4-km grid spacing. Treated as a sea level pressure observation, the MSLP assimilation by the EnKF enhances the hurricane warm core structure and results in a stronger and deeper analyzed vortex than that in the GFS (Global Forecast System) analysis; it also improves the subsequent 18-h hurricane intensity and track forecasts. With a 2-h total assimilation window length, the assimilation of MSLP data interpolated to 10-min intervals results in more balanced analyses with smaller subsequent forecast error growth and better intensity and track forecasts than when the data are assimilated every 60 minutes. Radar data are always assimilated at 10-min intervals. For both intensity and track forecasts, assimilating MSLP only outperforms assimilating radar reflectivity (Z) only. For intensity forecast, assimilating MSLP at 10-min intervals outperforms radar radial wind (Vr) data (assimilated at 10-min intervals), but assimilating MSLP at 60-min intervals fails to beat Vr data. For track forecast, MSLP assimilation has a slightly (noticeably) larger positive impact than Vr(Z) data. When Vr or Z is combined with MSLP, both intensity and track forecasts are improved more than the assimilation of individual observation type. When the total assimilation window length is reduced to 1h or less, the assimilation of MSLP alone even at 10-min intervals produces poorer 18-h intensity forecasts than assimilating Vr only, indicating that many assimilation cycles are needed to establish balanced analyses when MSLP data alone are assimilated; this is due to the very limited pieces of information that MSLP data provide.     

The influence of geometry on recirculation and CO2 transport over forested hills

Flow distortion over a forested hill is asymmetric, forming a recirculation region on the lee slope that increases the complexity in understanding atmosphere–biosphere interaction. To understand the complexity, we examine the effect of the geometry of forested hills on recirculation formation, structure, and related CO₂ transport by performing numerical simulations over double-forested hills. The ratio (0.8) of hill height (H) to half length (L) is a threshold value of flow patterns in the recirculation region: below 0.8, sporadic reversed flow occurs; at 0.8, one vortex is formed; and above 0.8, a pair of counter-rotating vortices is formed. The depth of recirculation increases with increasing H/L. The contribution of advection to the CO₂ budget is non-negligible and topographic-dependent. Vertical advection is opposite in sign to horizontal advection but cannot exactly offset in magnitude. Height-integrated advection shows significant variation in fluxes across hills. Gentle slopes can cause larger advection error. However, the relative importance of advection to CO₂ budget is slope-independent.     

土壤水分条件对内蒙古典型草原水汽和二氧化碳通量的影响研究

本文基于2007年和2008年生长季内蒙古羊草和大针茅草原湍流观测资料,分析了两种典型草原下垫面生长季的不同土壤水分条件下水汽和二氧化碳通量交换特征及其控制因子。主要结果如下:（1）在植被生长峰值期,日尺度上,干旱条件下土壤湿度是潜热通量的主要控制因子,而土壤水分条件较好时潜热通量主要受净辐射控制。（2）与大针茅草原相比,羊草草原叶面积指数较大,水分条件较好时,其潜热通量平均值更大,CO₂吸收能力更强,吸收CO₂更多;但在土壤水分胁迫出现时,羊草草原叶面的气孔闭合度急剧增加,大针茅草原的潜热通量、和CO₂吸收反而更大,表现出更为耐旱的植被特性。（3）地表导度可以用来解释土壤水分条件对羊草和大针茅草原碳水通量的影响。     

Coupling Ensemble Kalman Filter with Four-dimensional Variational Data Assimilation

This study examines the performance of coupling the deterministic four-dimensional variational assimilation system (4DVAR) with an ensemble Kalman filter (EnKF) to produce a superior hybrid approach for data assimilation. The coupled assimilation scheme (E4DVAR) benefits from using the state-dependent uncertainty provided by EnKF while taking advantage of 4DVAR in preventing filter divergence: the 4DVAR analysis produces posterior maximum likelihood solutions through minimization of a cost function about which the ensemble perturbations are transformed, and the resulting ensemble analysis can be propagated forward both for the next assimilation cycle and as a basis for ensemble forecasting. The feasibility and effectiveness of this coupled approach are demonstrated in an idealized model with simulated observations. It is found that the E4DVAR is capable of outperforming both 4DVAR and the EnKF under both perfect- and imperfect-model scenarios. The performance of the coupled scheme is also less sensitive to either the ensemble size or the assimilation window length than those for standard EnKF or 4DVAR implementations.     

Estimates of anthropogenic CO<Subscript>2</Subscript> uptake in a global ocean model

A global ocean general circulation model (L30T63) is employed to study the uptake and distribution of anthropogenic CO₂ in the ocean. A subgrid-scale mixing scheme called GM90 is used in the model. There are two main GM90 parameters including isopycnal diffusivity and skew (thickness) diffusivity. Sensitivities of the ocean circulation and the redistribution of dissolved anthropogenic CO₂ to these two parameters are examined. Two runs estimate the global oceanic anthropogenic CO₂ uptake to be 1.64 and 1.73 Pg C yr^-1 for the 1990s, and that the global ocean contained 86.8 and 92.7 Pg C of anthropogenic CO₂ at the end of 1994, respectively. Both the total inventory and uptake from our model are smaller than the data-based estimates. In this presentation, the vertical distributions of anthropogenic CO₂ at three meridional sections are discussed and compared with the available data-based estimates. The inventory in the individual basins is also calculated. Use of large isopycnal diffusivity can generally improve the simulated results, including the exchange flux, the vertical distribution patterns, inventory, storage, etc. In terms of comparison of the vertical distributions and column inventory, we find that the total inventory in the Pacific Ocean obtained from our model is in good agreement with the data-based estimate, but a large difference exists in the Atlantic Ocean, particularly in the South Atlantic. The main reasons are weak vertical mixing and that our model generates small exchange fluxes of anthropogenic CO₂ in the Southern Ocean. Improvement in the simulation of the vertical transport and sea ice in the Southern Ocean is important in future work.     

Terrestrial vegetation dynamics and global climate controls

Monthly data from the moderate resolution imaging spectroradiometer (MODIS) and its predecessor satellite sensors was used to reconstruct vegetation dynamics in response to climate patterns over the period 1983–2005. Results suggest that plant growth over extensive land areas of southern Africa and Central Asia were the most closely coupled of any major land area to El Niño–southern oscillation (ENSO) effects on regional climate. Others land areas strongly tied to recent ENSO climate effects were in northern Canada, Alaska, western US, northern Mexico, northern Argentina, and Australia. Localized variations in precipitation were the most common controllers of monthly values for the fraction absorbed of photosynthetically active radiation (FPAR) over these regions. In addition to the areas cited above, seasonal FPAR values from MODIS were closely coupled to rainfall patterns in grassland and cropland areas of the northern and central US. Historical associations between global vegetation FPAR and atmospheric carbon dioxide (CO₂) anomalies suggest that the terrestrial biosphere can contribute major fluxes of CO₂ during major drought events, such as those triggered by 1997–1998 El Niño event.     

Consequences of Uncertainties in CO<Subscript>2</Subscript> Density for Estimating Net Ecosystem CO<Subscript>2</Subscript> Exchange by Open-path Eddy Covariance

Errors in the estimation of CO₂ surface exchange by open-path eddy covariance, introduced during the removal of density terms [Webb et al. Quart J Roy Meteorol Soc 106:85–100, (1980) - WPL], can happen both because of errors in energy fluxes [Liu et al. Boundary-Layer Meteorol 120:65–85, (2006)] but also because of inaccuracies in other terms included in the density corrections, most notably due to measurements of absolute CO₂ density (ρ _c ). Equations are derived to examine the propagation of all errors through the WPL algorithm. For an open-path eddy covariance system operating in the Sierra de Gádor in south-east Spain, examples are presented of the inability of an unattended, open-path infrared gas analyzer (IRGA) to reliably report ρ _c and the need for additional instrumentation to determine calibration corrections. A sensitivity analysis shows that relatively large and systematic errors in net ecosystem exchange (NEE) can result from uncertainties in ρ _c in a semi-arid climate with large sensible heat fluxes (H _s ) and (wet) mineral deposition. When ρ_c is underestimated by 5% due to lens contamination, this implies a 13% overestimation of monthly CO₂ uptake.     

Future Expansion Of Agriculture and Pasture Acts to Amplify Atmospheric CO<Subscript>2</Subscript> Levels in Response to Fossil-Fuel and Land-Use Change Emissions

The expansion of crop and pastures to the detriment of forests results in an increase in atmospheric CO₂. The first obvious cause is the loss of forest biomass and soil carbon during and after conversion. The second, generally ignored cause, is the reduction of the residence time of carbon when, for example, forests or grasslands are converted to cultivated land. This decreases the sink capacity of the global terrestrial biosphere, and thereby may amplify the atmospheric CO₂ rise due to fossil and land-use carbon release. For the IPCC A2 future scenario, characterized by high fossil and high land-use emissions, we show that the land-use amplifier effect adds 61 ppm extra CO₂ in the atmosphere by 2100 as compared to former treatment of land-use processes in carbon models. Investigating the individual contribution of each of the six land-use transitions (forest &#x02194; crop, forest &#x02194; pasture, grassland crop) to the amplifier effect indicates that the clearing of forest and grasslands to arable lands explains most of the CO₂ amplification. The amplification effect is 50% higher than in a previous analysis by the same authors which considered neither the deforestation of pastures nor the ploughing of grasslands. Such an amplification effect is further examined in sensitivity tests where the net primary productivity is considered independent of the atmospheric CO₂. We also show that the land-use changes, which have already occurred in the recent past, have a strong inertia at releasing CO₂, and will contribute to about 1/3 of the amplification effect by 2100. These results suggest that there is an additional atmospheric benefit of preserving pristine ecosystems with high turnover times.