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

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

The importance of transport model uncertainties for the estimation of CO2 sources and sinks using satellite measurements

This study presents a synthetic model intercomparison to investigate the importance of transport model errors for estimating the sources and sinks of CO2 using satellite measurements. The experiments were designed for testing the potential performance of the proposed CO2 lidar A-SCOPE, but also apply to other space borne missions that monitor total column CO2. The participating transport models IFS, LMDZ, TM3, and TM5 were run in forward and inverse mode using common a priori CO2 fluxes and initial concentrations. Forward simulations of column averaged CO2 (xCO2) mixing ratios vary between the models by s=0.5 ppm over the continents and s=0.27 ppm over the oceans. Despite the fact that the models agree on average on the sub-ppm level, these modest differences nevertheless lead to significant discrepancies in the inverted fluxes of 0.1 PgC/yr per 106 km2 over land and 0.03 PgC/yr per 106 km2 over the ocean. These transport model induced flux uncertainties exceed the target requirement that was formulated for the A-SCOPE mission of 0.02 PgC/yr per 106 km2, and could also limit the overall performance of other CO2 missions such as GOSAT. A variable, but overall encouraging agreement is found in comparison with FTS measurements at Park Falls, Darwin, Spitsbergen, and Bremen, although systematic differences are found exceeding the 0.5 ppm level. Because of this, our estimate of the impact of transport model uncerainty is likely to be conservative. It is concluded that to make use of the remote sensing technique for quantifying the sources and sinks of CO2 not only requires highly accurate satellite instruments, but also puts stringent requirements on the performance of atmospheric transport models. Improving the accuracy of these models should receive high priority, which calls for a closer collaboration between experts in atmospheric dynamics and tracer transpor

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

Understanding greenhouse gas (GHG) column concentrations in Munich using WRF

To address ambitious goals of carbon neutrality set at national and city scales, a number of atmospheric networks have been deployed to monitor greenhouse gas (GHG) concentrations in and around cities. To convert these measurements into estimates of emissions from cities, atmospheric models are used to simulate the transport of various tracer gases and help interpret these measurements. We set up a modelling framework using the Weather Research and Forecasting (WRF) model applied at a high spatial resolution (up to 400 m) to simulate the atmospheric transport of GHGs and interpret the observations provided by the Munich Urban Carbon Column Network (MUCCnet). Building on previous analyses using similar measurements performed within a campaign for the city of Berlin and its surroundings (Zhao et al., 2019), our modelling framework has been improved regarding the initialization of tagged tracers, model settings, and input data. To assess the model performance, we validate the modelled output against two local weather stations and observed column GHG concentrations provided by MUCCnet from 1 to 30 August 2018. The modelled wind matches well with the measurements from the weather stations, with wind speeds slightly overestimated. The measured slant column concentrations of GHGs and their variability are generally reproduced by the model, with a bias in CO2 of around 3.7 ppm that can be attributed to the initial and boundary conditions used. The differential column method (DCM) has been applied to cancel out the influence from the background concentrations of CO2. We optimize its application by selecting suitable days on which the assumption of the DCM holds true: a relatively uniform air mass travels over the city, passing from an upwind site to a downwind site. In particular, the Stochastic Time-Inverted Lagrangian Transport model (STILT) is used here and driven by our WRF modelled meteorological fields to obtain footprints (i.e., the potential areas of influence for signals observed at specific points), further used for interpreting measurement results. Combining these footprints with knowledge of local emission sources, we find evidence of CH4 sources near Munich that are missing or underestimated in the emission inventory used. This demonstrates the potential of this data-model framework to constrain local sources and improve emission inventories

CO2 budgeting at the regional scale using a Lagrangian experimental strategy and meso-scale modeling

An atmospheric Lagrangian experiment for regional CO2 budgeting with aircraft measurements took place during the CarboEurope Regional Experiment Strategy campaign (CERES) in south-west France, in June 2005. The atmospheric CO2 aircraft measurements taken upstream and downstream of an active and homogeneous pine forest revealed a CO2 depletion in the same air mass, using a Lagrangian strategy. This field experiment was analyzed with a meteorological meso-scale model interactively coupled with a surface scheme, with plant assimilation, ecosystem respiration, anthropogenic CO2 emissions and sea fluxes. First, the model was carefully validated against observations made close to the surface and in the atmospheric boundary layer. Then, the carbon budget was evaluated using the numerous CERES observations, by upscaling the surface fluxes observations, and using the modeling results, in order to estimate the relative contribution of each physical process. A good agreement is found between the two methods which use the same vegetation map: the estimation of the regional CO2 surface flux by the Eulerian meso-scale model budget is close to the budget deduced from the upscaling of the observed surface fluxes, and found a budget between −9.4 and −12.1μmol.m−2.s−1, depending on the size of the considered area. Nevertheless, the associated uncertainties are rather large for the upscaling method and reach 50%. A third method, using Lagrangian observations of CO2 estimates a regional CO2 budget a few different and more scattered, (−16.8μmol.m−2.s−1 for the small sub-domain and −8.6μmol.m−2.s−1 for the larger one). For this budgeting method, we estimate a mean of 31% error, mainly arising from the time of integration between the two measurements of the Lagrangian experiment. The paper describes in details the three methods to assess the regional CO2 budget and the associated error

Femtosecond laser ablation of cemented carbides: properties and tribological applications

Laser ablation with fs laser pulses was performed in air on cobalt cemented tungsten carbide by means of a Ti : sapphire laser (800nm, 100fs). Small and moderate fluences (2, 5, 10J/cm2) and up to 5×104 pulses per irradiated spot were used to drill holes with aspect ratios up to 10. Cross-section cuts from laser-irradiated samples were produced and they were analysed with optical microscopy and SEM. EDX analyses were carried out on selected zones. Quasi-cylindrical holes were found for 2J/cm2, whereas for 5 and 10J/cm2 irregular shapes (lobes, bottoms wider than hole entrances) were found to occur after a given number of incident pulses. Layers with modified structure were evidenced at pore walls. SEM revealed a denser structure, while EDX analyses showed uniform and almost similar contents of W, C, and Co in these layers. As a direct application, patterning of coated WC-Co was carried out with 2J/cm2 and 100 pulses per pore. The resulted surfaces were tribologically tested and these tests revealed an improved friction and wear behaviou