Effect of Data Assimilation Parameters on The Optimized Surface CO<Subscript>2</Subscript> Flux in Asia

In this study, CarbonTracker, an inverse modeling system based on the ensemble Kalman filter, was used to evaluate the effects of data assimilation parameters (assimilation window length and ensemble size) on the estimation of surface CO₂ fluxes in Asia. Several experiments with different parameters were conducted, and the results were verified using CO₂ concentration observations. The assimilation window lengths tested were 3, 5, 7, and 10 weeks, and the ensemble sizes were 100, 150, and 300. Therefore, a total of 12 experiments using combinations of these parameters were conducted. The experimental period was from January 2006 to December 2009. Differences between the optimized surface CO₂ fluxes of the experiments were largest in the Eurasian Boreal (EB) area, followed by Eurasian Temperate (ET) and Tropical Asia (TA), and were larger in boreal summer than in boreal winter. The effect of ensemble size on the optimized biosphere flux is larger than the effect of the assimilation window length in Asia, but the importance of them varies in specific regions in Asia. The optimized biosphere flux was more sensitive to the assimilation window length in EB, whereas it was sensitive to the ensemble size as well as the assimilation window length in ET. The larger the ensemble size and the shorter the assimilation window length, the larger the uncertainty (i.e., spread of ensemble) of optimized surface CO₂ fluxes. The 10-week assimilation window and 300 ensemble size were the optimal configuration for CarbonTracker in the Asian region based on several verifications using CO₂ concentration measurements.     

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.     

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.     

Factors influencing anthropogenic carbon dioxide uptake in the North Atlantic in models of the ocean carbon cycle

The uptake and storage of anthropogenic carbon in the North Atlantic is investigated using different configurations of ocean general circulation/carbon cycle models. We investigate how different representations of the ocean physics in the models, which represent the range of models currently in use, affect the evolution of CO₂ uptake in the North Atlantic. The buffer effect of the ocean carbon system would be expected to reduce ocean CO₂ uptake as the ocean absorbs increasing amounts of CO₂. We find that the strength of the buffer effect is very dependent on the model ocean state, as it affects both the magnitude and timing of the changes in uptake. The timescale over which uptake of CO₂ in the North Atlantic drops to below preindustrial levels is particularly sensitive to the ocean state which sets the degree of buffering; it is less sensitive to the choice of atmospheric CO₂ forcing scenario. Neglecting physical climate change effects, North Atlantic CO₂ uptake drops below preindustrial levels between 50 and 300 years after stabilisation of atmospheric CO₂ in different model configurations. Storage of anthropogenic carbon in the North Atlantic varies much less among the different model configurations, as differences in ocean transport of dissolved inorganic carbon and uptake of CO₂ compensate each other. This supports the idea that measured inventories of anthropogenic carbon in the real ocean cannot be used to constrain the surface uptake. Including physical climate change effects reduces anthropogenic CO₂ uptake and storage in the North Atlantic further, due to the combined effects of surface warming, increased freshwater input, and a slowdown of the meridional overturning circulation. The timescale over which North Atlantic CO₂ uptake drops to below preindustrial levels is reduced by about one-third, leading to an estimate of this timescale for the real world of about 50 years after the stabilisation of atmospheric CO₂. In the climate change experiment, a shallowing of the mixed layer depths in the North Atlantic results in a significant reduction in primary production, reducing the potential role for biology in drawing down anthropogenic CO₂.     

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.     

Dissimilarity of Scalar Transport in the Convective Boundary Layer in Inhomogeneous Landscapes

A land-surface model (LSM) is coupled with a large-eddy simulation (LES) model to investigate the vegetation-atmosphere exchange of heat, water vapour, and carbon dioxide (CO₂) in heterogeneous landscapes. The dissimilarity of scalar transport in the lower convective boundary layer is quantified in several ways: eddy diffusivity, spatial structure of the scalar fields, and spatial and temporal variations in the surface fluxes of these scalars. The results show that eddy diffusivities differ among the three scalars, by up to 10–12%, in the surface layer; the difference is partly attributed to the influence of top-down diffusion. The turbulence-organized structures of CO₂ bear more resemblance to those of water vapour than those of the potential temperature. The surface fluxes when coupled with the flow aloft show large spatial variations even with perfectly homogeneous surface conditions and constant solar radiation forcing across the horizontal simulation domain. In general, the surface sensible heat flux shows the greatest spatial and temporal variations, and the CO₂ flux the least. Furthermore, our results show that the one-dimensional land-surface model scheme underestimates the surface heat flux by 3–8% and overestimates the water vapour and CO₂ fluxes by 2–8% and 1–9%, respectively, as compared to the flux simulated with the coupled LES-LSM.     

Turbulent carbon exchange in very stable conditions

Turbulent fluxes obtained using the conventional eddy covariance approach result in erratic results with large time fluctuations in extremely stable conditions. This can limit efforts to estimate components of the nocturnal energy budget and respiratory CO₂ fluxes. Well-organized fluxes that show a clear dependence on turbulent intensity were obtained when multiresolution decomposition was used to estimate turbulent exchanges. CO₂, heat and water vapour fluxes were observed at a site in the eastern Amazon basin that had been cleared for agricultural purposes. Temporal scales of the carbon transfer were determined and shown to be similar to those of latent heat, but as much as three times larger than those of sensible heat. CO₂ eddy diffusivities at the temporal scales on which most of the vertical CO₂ exchange occurs are shown to be 50 times larger than the eddy diffusivity for heat. A process associated with the vertical scale of the scalar accumulation layer is suggested to explain these different scales and turbulent diffusivities of carbon and sensible heat transfer. For an appreciable range of turbulence intensities, the observed vertical turbulent carbon exchange is insufficient to account for the locally respired CO₂ estimated independently. Evidence that shallow drainage currents may account for this is given.     

Turbulent transport of carbon dioxide over a paddy field

Turbulent fluctuations in CO₂ concentrations over a paddy field are measured by a fastresponse device with an open sensing path. This IR device coupled with a sonic anemometer constitutes an eddy correlation instrument to measure CO₂ fluxes. Three experiments were conducted in the surface layer over paddy 90 cm high. The stability (z – d)/L ranged from -0.14 to 0.20, where L denotes the Monin-Obukhov length.CO₂ power spectra show the range of applicability of the -2/3 power law to be between f = 0.2 and f = 2, where f is the frequency normalized by wind speed and height. The cospectral estimate between CO₂ and vertical component of wind speed ranging from f = 0.005 to f = 2 shows a peak at about f = 0.15 under near-neutral stratification.Hourly means of CO₂ flux measured by the eddy correlation method increase with intensity of net radiation. The maximum value of downward flux of CO₂ rises to 0.6 mg cm^-2 hr^-1 over the paddy field at the stage of ear emergence.Some turbulence statistics relating to the CO₂ transport are evaluated: the correlation coefficient between CO₂ and vertical velocity is about -0.3, and that between CO₂ and humidity attains -0.7 ~ -0.8 under unstable stratification; nondimensional gradients _c for CO₂ and _m for wind speed are 0.89 and 0.99, respectively.     

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.     

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.     

太平洋海气CO2通量对气候事件的响应

应用一个嵌套了海洋生物地球化学循环的太平洋环流碳循环模式,分析了1960～2000年太平洋不同海区海气碳通量随时间的变化。模拟结果显示,赤道太平洋为大气CO₂的排放区,南、北太平洋(南、北纬15°至模式计算区域南、北边界)为吸收区。3个海区海气碳通量随时间均存在显著的波动,其中赤道太平洋海气碳通量年际波动最显著。3个海区海气碳通量年际波动对气候事件的响应并不一致,在El Niño年赤道太平洋冷舌的强度和总溶解无机碳(DIC)的浓度以及输出生产力均会受到上升流减弱的影响而降低,La Niña年这些海气碳通量控制要素的分布情况则正好相反,但在南北太平洋副热带以及高纬度海区,El Niño和La Niña对这些要素带来的影响却并不一定相反,对输出生产力的影响甚至是一致的。以海表温度(SST)为例考察海气碳通量与物理场之间的关系表明,在赤道太平洋上升流对DIC的影响是控制海气碳通量变化的主要因素,而在其他海区,尤其是副热带海区,由于垂直运动的年际变化较小,且生物生产力水平较低,SST的波动对海气碳通量年际变化的影响更加重要。     

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.     

锡林浩特草原CO2通量特征及其影响因素分析

利用锡林浩特国家气候观象台开路涡度相关系统、辐射土壤观测系统,测得的长期连续通量观测数据,对锡林浩特草原2009—2011年期间的CO₂通量观测特征进行了分析。结果表明:CO₂通量存在明显的年际、季节和日变化特征。3 a中NEE年际变率达到200 g·m^-2,季节变率最大达到460 g·m^-2,日变化幅度生长季最大达到0.25 mg·m^-2·s^-1。通过不同时间尺度碳通量与温度、水分、辐射等环境因子的分析,认为CO₂通量日变化主要受温度和光合有效辐射影响,而季节变化和年变化主要受降水和土壤含水量的影响。降水强度及时间分布是制约牧草CO₂吸收的关键因素,大于15%的土壤含水量有利于促进牧草生长。     

Impact of extreme CO2 levels on tropical climate: a CGCM study

A coupled general circulation model has been used to perform a set of experiments with high CO₂ concentration (2, 4, 16 times the present day mean value). The experiments have been analyzed to study the response of the climate system to strong radiative forcing in terms of the processes involved in the adjustment at the ocean–atmosphere interface. The analysis of the experiments revealed a non-linear response of the mean state of the atmosphere and ocean to the increase in the carbon dioxide concentration. In the 16 × CO₂ experiment the equilibrium at the ocean–atmosphere interface is characterized by an atmosphere with a shut off of the convective precipitation in the tropical Pacific sector, associated with air warmer than the ocean below. A cloud feedback mechanism is found to be involved in the increased stability of the troposphere. In this more stable condition the mean total precipitation is mainly due to large-scale moisture flux even in the tropics. In the equatorial Pacific Ocean the zonal temperature gradient of both surface and sub-surface waters is significantly smaller in the 16 × CO₂ experiment than in the control experiment. The thermocline slope and the zonal wind stress decrease as well. When the CO₂ concentration increases by about two and four times with respect to the control experiment there is an intensification of El Niño. On the other hand, in the experiment with 16 times the present-day value of CO₂, the Tropical Pacific variability weakens, suggesting the possibility of the establishment of permanent warm conditions that look like the peak of El Niño.     

Estimation of Turbulent Fluxes Using the Flux-Variance Method over an Alpine Meadow Surface in the Eastern Tibetan Plateau

The flux-variance similarity relation and the vertical transfer of scalars exhibit dissimilarity over different types of surfaces,resulting in different parameterization approaches of relative transport efficiency among scalars to estimate turbulent fluxes using the flux-variance method.We investigated these issues using eddycovariance measurements over an open,homogeneous and flat grassland in the eastern Tibetan Plateau in summer under intermediate hydrological conditions during rainy season.In unstable conditions,the temperature,water vapor,and CO2 followed the flux-variance similarity relation,but did not show in precisely the same way due to different roles(active or passive) of these scalars.Similarity constants of temperature,water vapor and CO2 were found to be 1.12,1.19 and 1.17,respectively.Heat transportation was more efficient than water vapor and CO2.Based on the estimated sensible heat flux,five parameterization methods of relative transport efficiency of heat to water vapor and CO2 were examined to estimate latent heat and CO2 fluxes.The strategy of local determination of flux-variance similarity relation is recommended for the estimation of latent heat and CO2 fluxes.This approach is better for representing the averaged relative transport efficiency,and technically easier to apply,compared to other more complex ones.     

Limitations of an eddy-correlation technique for the determination of the carbon dioxide and sensible heat fluxes

A modified infrared CO₂ gas analyzer, a small thermocouple assembly, a heated-thermocouple anemometer for horizontal wind, and a propeller-type vertical wind sensor were used to measure the eddy fluxes of heat and CO₂ above a corn crop. Experimental results of these fluxes are discussed. The main sources of errors of the eddy fluxes using these instruments were estimated:

1. Sensors with a time constant of 0.5 s appear to be fast enough to detect most of the vertical CO₂ transfer as long as the sensors are located at least one meter above the crop surface.
2. The deviation from steady-state conditions for 10-min periods was found to have a significant effect on the eddy flux estimates.
3. Temperature fluctuations of the air sample passing through the CO₂ infrared gas analyzer were found to be non-negligible but could be easily corrected.
4. A 1° misalignment of the vertical anemometer affected these eddy fluxes by less than 10% under all circumstances studied.

     

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.     

On the Significance of the Webb Correction to Fluxes

For establishing correct mass or energy balances at the Earth's surface, detailed and correct measurements of air constituent fluxes are needed. Flux measurements obtained from the eddy covariance technique have to pass several corrections of different relevance in order to give correct flux data. One of these corrections, the Webb correction, is analysed herein from latent heat flux and CO₂ flux data recorded during two field experiments. The significance of this correction for the latent heat flux data varies with the air humidity and the Bowen ratio. The correction changes the latent heat flux values only a little, but significantly (by 2 to 3%). For other air constituents (like CO₂), the Webb correction is much more important (20 to 30% of the flux).     

Forest-Air Fluxes Of Carbon, Water And Energy Over Non-Flat Terrain

A field study of surface-air exchange of carbon, water, and energy was conducted at a mid-latitude, mixed forest on non-flat terrain to investigate how to best interpret biological signals from the eddy flux data that may be subject to advective influences. It is shown that during periods of Southwest winds (sector with mild topography), the eddy fluxes are well-behaved in terms of energy balance closure, the existence of a constant flux layer, consistency with chamber observations and the expected abiotic controls on the fluxes. Advective influences are evident during periods with wind from a steep (15%) slope to the Northeast of the tower. These influences appear more severe on CO₂ flux, particularly in stable air, than on the energy fluxes. Large positive flux of CO₂ (> 23 mol m^-2 s^-1) occurs frequently at night. The annual sum of the carbon flux is positive, but the issue about whether the forest is a source of atmospheric carbon remains inconclusive.Attempts are made to assess vertical advectionusing the data collected on a single tower. Over the Southwestsector, vertical advection makes a statistically significant but small contribution to the 30-min energy imbalance and CO₂ flux variations. Contributions by horizontal advection may be larger but cannot be verified directly by the current experimental method.     

Probabilistic simulations of the impact of increasing leaf-level atmospheric carbon dioxide on the global land surface

Using a climate model with a sophisticated land surface scheme, simulations were conducted to explore the impact of increases in leaf-level carbon dioxide (CO₂) on evaporation, temperature and other land surface quantities. Fifty-one realizations were run, for each of four Januarys and four Julys for CO₂ concentrations at leaf-level of 280, 375, 500, 650, 840 and 1,000 ppmv. Atmospheric CO₂ concentration was held constant at 375 ppmv in all experiments. Statistically significant decreases in evaporation and increases in temperature occur in specific regions as leaf-level CO₂ is increased from 280 to 375 ppmv. These same areas expand geographically, and the magnitude of the changes increase as leaf-level CO₂ is increased further suggesting that changes are caused by the increase in leaf-level CO₂ and are not internal model variability. As leaf-level CO₂ is increased further, larger areas of the continental surface are affected by increasing amounts and a statistically significant change in precipitation is seen. The increase in leaf-level CO₂ from 280 ppmv to 375 ppmv causes statistically significant changes in the evaporation over 12% of continental surfaces in July. This increases to 25% at 500 ppmv, 35% at 650 ppmv, 41% at 840 ppmv and 47% at 1,000 ppmv. This affects temperature and rainfall by similar amounts, generally in coincident regions. An analysis of these results over key regions shows that the probability density functions of the latent heat flux and temperature are affected non-uniformly. There is a shift in the latent heat flux probability density function to lower values, mainly through the reduction in the upper tail of the distribution. The temperature probability density function shifts to higher values, mainly through an increase in the upper tail of the distribution indicating that the impact is focussed on extremes. Given that there are a suite of well evaluated land surface models that include the biogeochemical effects of increasing CO₂ we suggest that the inclusion of such a model should be a recommended component of climate models used in future assessment reports by the Intergovernmental Panel on Climate Change.