On observational and modelling strategies targeted at regional carbon exchange over continents

Estimating carbon exchange at regional scales is paramount to understanding feedbacks between climate and the carbon cycle, but also to verifying climate change mitigation such as emission reductions and strategies compensating for emissions such as carbon sequestration. This paper discusses evidence for a number of important shortcomings of current generation modelling frameworks designed to provide regional scale budgets from atmospheric observations. Current top-down and bottom-up approaches targeted at deriving consistent regional scale carbon exchange estimates for biospheric and anthropogenic sources and sinks are hampered by a number of issues: we show that top-down constraints using point measurements made from tall towers, although sensitive to larger spatial scales, are however influenced by local areas much more strongly than previously thought. On the other hand, classical bottom-up approaches using process information collected at the local scale, such as from eddy covariance data, need up-scaling and validation on larger scales. We therefore argue for a combination of both approaches, implicitly providing the important local scale information for the top-down constraint, and providing the atmospheric constraint for up-scaling of flux measurements. Combining these data streams necessitates quantifying their respective representation errors, which are discussed. The impact of these findings on future network design is highlighted, and some recommendations are given

Vertical mixing in atmospheric tracer transport models: error characterization and propagation

International audienceImperfect representation of vertical mixing near the surface in atmospheric transport models leads to uncertainties in modelled tracer mixing ratios. When using the atmosphere as an integrator to derive surface-atmosphere exchange from mixing ratio observations made in the atmospheric boundary layer, this uncertainty has to be quantified and taken into account. A comparison between radiosonde-derived mixed layer heights and mixed layer heights derived from ECMWF meteorological data during May?June 2005 in Europe revealed random discrepancies of about 40% for the daytime with insignificant bias errors, and much larger values approaching 100% for nocturnal mixed layers with bias errors also exceeding 50%. The Stochastic Time Inverted Lagrangian Transport (STILT) model was used to propagate this uncertainty into CO2 mixing ratio uncertainties, accounting for spatial and temporal error covariance. Average values of 3 ppm were found for the 2 month period, indicating that this represents a large fraction of the overall uncertainty. A pseudo data experiment shows that the error propagation with STILT avoids biases in flux retrievals when applied in inversions. The results indicate that transport models driven by current generation data assimilation for meteorological fields is by far not sufficient for inversions of continental mixing ratio data. As a solution we suggest the use of better, higher resolution atmospheric models, and a modification of the overall sampling strategy

Detecting regional variability in sources and sinks of carbon dioxide: a synthesis

The current paper reviews the experimental setup of the CarboEurope Experimental Strategy (CERES) campaigns with the aim of providing an overview of the instrumentation used, the data-set and associated modelling. It then assesses progress in the field of regional observation and modelling of carbon fluxes, bringing the papers of this special issue into a somewhat broader context of analysis. <br><br> Instrumental progress has been obtained in the field of remotely monitoring from tall towers and the experimental planning. Flux measurements from aircraft are now capable, within some constraints, to provide regular regional observations of fluxes of CO<sub>2</sub>, latent and sensible heat. <br><br> Considerable effort still needs to be put into calibrating the surface schemes of models, as they have direct impact on the input of energy, moisture and carbon fluxes in the boundary layer. Overall, the mesoscale models appear to be capable of simulating the large scale dynamics of the region, but in the fine detail, like the precise horizontal and vertical CO<sub>2</sub> field differences between the models still exist. These errors translate directly into transport uncertainty, when the forward simulations are used in inverse mode. Quantification of this uncertainty, including that of inadequate boundary layer height modelling, still remains a major challenge for state of the art mesoscale models. Progress in inverse models has been slow, but has shown that it is possible to estimate some of the errors involved, and that using the combination of observations. Overall, the capability to produce regional, high-resolution estimates of carbon exchange, exist in potential, but the routine application will require considerable effort, both in the experimental as in the modelling domain

Model studies of the meteorology and chemical composition of the troposphere over the North Atlantic during August 18-30, 1993

A mesoscale chemistry transport model driven by meteorological data from a numerical weather prediction model is used to calculate ozone, carbon monoxide, oxides of nitrogen, and other chemical species over the North Atlantic for a 13-days period (August 18-30, 1993). The model has a circumpolar grid so that the boundary condition problems are minimized, and the influence of North American emissions on the chemical composition of the troposphere over the North Atlantic and Europe is calculated. During the first part of the period there is a zonal flow across the North Atlantic in the free troposphere; later, there is a strong north-south as well as vertical component in the advection field. The variability in the concentrations of ozone in the free troposphere is mainly caused by dynamical processes, while the chemical modification is small over an integration time of less than two weeks. A continental plume off the North American continent extending 2000 km or more into the North Atlantic is identified toward the end of the calculation period. There is then a maximum in the concentration of ozone around 1 km above the sea surface, with a much lower concentration in the marine boundary layer close to the ocean surface. Measurements from the U.K. Meteorological Office Hercules C-130 in the free troposphere off the Atlantic Provinces, across the Atlantic Ocean, and around the Azores together with ozone soundings from the Azores, Bermuda, and Iceland were used for model comparison. The calculations indicate that in the free troposphere the initial conditions as well as the upper boundary conditions are important for ozone distribution. In the upper troposphere the net change in the chemical formation rate of ozone due to a change in the NOx concentration is quite independent of the absolute value of the ozone concentration itself and, consequently, the choice of boundary conditions for ozone is not so important in this context, In the lower troposphere the change in the net chemical formation rate of ozone, which follows from a change in the concentration of NOx, shows a marked dependence on the concentration of ozone

What can tracer observations in the continental boundary layer tell us about surface-atmosphere fluxes?

International audienceWe analyze the potential for inferring spatially resolved surface fluxes from atmospheric tracer observations within the mixed layer, such as from monitoring towers, using a receptor oriented transport model (Stochastic Time-Inverted Lagrangian Transport model ? STILT) coupled to a simple biosphere in which CO2 fluxes are represented as functional responses to environmental drivers (radiation and temperature). Transport and biospheric fluxes are coupled on a dynamic grid using a polar projection with high horizontal resolution (~20 km) in near field, and low resolution far away (as coarse as 2000 km), reducing the number of surface pixels without significant loss of information. To test the system, and to evaluate the errors associated with the retrieval of fluxes from atmospheric observations, a pseudo data experiment was performed. A large number of realizations of measurements (pseudo data) and a priori fluxes were generated, and for each case spatially resolved fluxes were retrieved. Results indicate strong potential for high resolution retrievals based on a network of tall towers, subject to the requirement of correctly specifying the a priori uncertainty covariance, especially the off diagonal elements that control spatial correlations. False assumptions about the degree to which the uncertainties in the a priori fluxes are spatially correlated may lead to a strong underestimation of uncertainties in the retrieved fluxes, or, equivalently, to biased retrievals. The framework presented here, however, allows a conservative choice of the off diagonal elements that avoids biasing the retrievals

Strategies for measurement of atmospheric column means of carbon dioxide from aircraft using discrete sampling

[1] Automated flask sampling aboard small charter aircraft has been proposed as a low-cost, reliable method to greatly increase the density of measurements of CO2 mixing ratios in continental regions in order to provide data for assessment of global and regional CO2 budgets. We use data from the CO2 Budget and Rectification-Airborne 2000 campaign over North America to study the feasibility of using discrete ( flask) sampling to determine column mean CO2 in the lowest 4 km of the atmosphere. To simulate flask sampling, data were selected from profiles of CO2 measured continuously with an onboard ( in situ) analyzer. We find that midday column means can be determined without bias relative to true column means measured by the in situ analyzer to within 0.15 and better than 0.10 ppm by using 10 and 20 instantaneously collected flask samples, respectively. More precise results can be obtained by using a flask sampling strategy that linearly integrates over portions of the air column. Using less than 8 - 10 flasks can lead to significant sampling bias for some common profile shapes. Sampling prior to the breakup of the nocturnal stable layer will generally lead to large sampling bias because of the inability of aircraft to probe large CO2 gradients that often exist very close to the ground at night and during the early morning

Emission ratio and isotopic signatures of molecular hydrogen emissions from tropical biomass burning

In this study, we identify a biomass-burning signal in molecular hydrogen (H₂) over the Amazonian tropical rainforest. To quantify this signal, we measure the mixing ratios of H₂ and several other species as well as the H₂ isotopic composition in air samples that were collected in the BARCA (Balanço Atmosférico Regional de Carbono na Amazônia) aircraft campaign during the dry season. We derive a relative H₂ emission ratio with respect to carbon monoxide (CO) of 0.31 ± 0.04 ppb ppb⁻¹ and an isotopic source signature of −280 ± 41‰ in the air masses influenced by tropical biomass burning. In order to retrieve a clear source signal that is not influenced by the soil uptake of H₂, we exclude samples from the atmospheric boundary layer. This procedure is supported by data from a global chemistry transport model. The ΔH₂ / ΔCO emission ratio is significantly lower than some earlier estimates for the tropical rainforest. In addition, our results confirm the lower values of the previously conflicting estimates of the H₂ isotopic source signature from biomass burning. These values for the emission ratio and isotopic source signatures of H₂ from tropical biomass burning can be used in future bottom-up and top-down approaches aiming to constrain the strength of the biomass-burning source for H₂. Hitherto, these two quantities relied only on combustion experiments or on statistical relations, since no direct signal had been obtained from in-situ observations

Mesoscale covariance of transport and CO2 fluxes: Evidence from observations and simulations using the WRF-VPRM coupled atmosphere-biosphere model

We developed a modeling system which combines a mesoscale meteorological model, the Weather Research and Forecasting (WRF) model, with a diagnostic biospheric model, the Vegetation Photosynthesis and Respiration (VPRM). The WRF-VPRM modeling system was designed to realistically simulate high-resolution atmospheric CO₂ concentration fields. In the system, WRF takes into account anthropogenic and biospheric CO₂ fluxes and realistic initial and boundary conditions for CO₂ from a global model. The system uses several “tagged” tracers for CO₂ fields from different sources. VPRM uses meteorological fields from WRF and high-resolution satellite indices to simulate biospheric CO₂ fluxes with realistic spatiotemporal patterns. Here we present results from the application of the model for interpretation of measurements made within the CarboEurope Regional Experiment Strategy (CERES). Simulated fields of meteorological variables and CO₂ were compared against ground-based and airborne observations. In particular, the characterization by aircraft measurements turned out to be crucial for the model evaluation. The comparison revealed that the model is able to capture the main observed features in the CO₂ distribution reasonably well. The simulations showed that daytime CO₂ measurements made at coastal stations can be strongly affected by land breeze and subsequent sea breeze transport of CO₂ respired from the vegetation during the previous night, which can lead to wrong estimates when such data are used in inverse studies. The results also show that WRF-VPRM is an effective modeling tool for addressing the near-field variability of CO₂ fluxes and concentrations for observing stations around the globe