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Convection strongly influences the distribution of atmospheric trace gases. General circulation models (GCMs) use convective mass fluxes calculated by parameterizations to transport gases, but the results are difficult to compare with trace gas observations because of difference in scale. The high resolution of cloud-resolving models (CRMs) facilitates direct comparison with aircraft observations. Averaged over a sufficient area, CRM results yield a validated product directly comparable to output from a single global model grid column. This study presents comparisons of vertical profiles of convective mass flux and trace gas mixing ratios derived from CRM and single column model (SCM) simulations of storms observed during three field campaigns. In all three cases, SCM simulations underpredicted convective mass flux relative to CRM simulations. As a result, the SCM simulations produced lower trace gas mixing ratios in the upper troposphere in two of the three storms than did the CRM simulations. The impact of parameter sensitivity in the moist physics schemes employed in the SCM has also been examined. Statistical techniques identified the most significant parameters influencing convective transport. Convective mass fluxes are shown to be strongly dependent on chosen parameter values. Results show that altered parameter settings can substantially improve the comparison between SCM and CRM convective mass flux. Upper tropospheric trace gas mixing ratios were also improved in two storms. In the remaining storm, the SCM representation of C[O.sub.2] was not improved because of differences in entrainment and detrainment levels in the CRM and SCM simulations.

Cities, currently covering only a very small portion (< 3 %) of the world's land surface, directly release to the atmosphere about 44% of global energy-related CO2, and are associated with 71-76% of CO2 emissions from global final energy use. Although many cities have set voluntary climate plans, their CO2 emissions are not evaluated by Monitoring, Reporting and Verification (MRV) procedures that play a key role for market- or policy-based mitigation actions. Here we propose a monitoring tool that could support the development of such procedures at the city scale. It is based on an atmospheric inversion method that exploits inventory data and continuous atmospheric CO2 concentration measurements from a network of stations within and around cities to estimate city CO2 emissions. We examine the cost-effectiveness and the performance of such a tool. The instruments presently used to measure CO2 concentrations at research stations are expensive. However, cheaper sensors are currently developed and should be useable for the monitoring of CO2 emissions from a megacity in the near-term. Our assessment of the inversion method is thus based on the use of several types of hypothetical networks, with a range of numbers of sensors sampling at 25ma.g.l. The study case for this assessment is the monitoring of the emissions of the Paris metropolitan area (12 million inhabitants and 11.4 TgC emitted in 2010) during the month of January 2011. The performance of the inversion is evaluated in terms of uncertainties in the estimates of total and sectoral CO2 emissions. These uncertainties are compared to a notional ambitious target to diagnose annual total city emissions with an uncertainty of 5% (2-sigma). We find that, with 10 stations only, which is the typical size of current pilot networks that are deployed in some cities, the uncertainty for the 1-month total city CO2 emissions is significantly reduced by the inversion by 42% but still corresponds to an annual uncertainty that is two times larger than the target of 5%. By extending the network from 10 to 70 stations, the inversion can meet this requirement. As for major sectoral CO2 emissions, the uncertainties in the inverted emissions using 70 stations are reduced significantly over that obtained using 10 stations by 32% for commercial and residential buildings, by 33% for road transport and by 18% for the production of energy by power plants, respectively. With 70 stations, the uncertainties from the inversion become of 15% 2-sigma annual uncertainty for dispersed building emissions, and 18% for emissions from road transport and energy production. The inversion performance could be further improved by optimal design of station locations and/or by assimilating additional atmospheric measurements of species that are co-emitted with CO2 by fossil fuel combustion processes with a specific signature from each sector, such as carbon monoxide (CO). Atmospheric inversions based on continuous CO2 measurements from a large number of cheap sensors can thus de liver a valuable quantification tool for the monitoring and/or the verification of city CO2 emissions (baseline) and CO2 emission reductions (commitments). [ABSTRACT FROM AUTHOR]

We propose a new approach to estimate urban emission ratios that takes advantage of the enhanced local urban signal in the atmosphere at low wind speed. We apply it to estimate monthly ratios between CO2, CO and some VOCs from several atmospheric concentration measurement datasets acquired in the centre of Paris between 2010 and 2014. We find that this approach is little sensitive to the regional background level definition and that, in the case of Paris, it samples all days (weekdays and weekends) and all hours of the day evenly. A large seasonal variability of the ΔCO/ΔCO2 ratio in Paris is shown, with a difference of around 60% between the extreme values and a strong anti-correlation (r² = 0.75) with atmospheric temperature. The comparison of the ratios obtained for two short measurement campaigns conducted in two different districts and two different periods (fall and winter) shows differences ranging from -120 to +63%. A comparison with a highly resolved regional emission inventory suggests some spatial variations of the ratio within the city, although most of these differences seem to be rather driven by the seasonal variability. [ABSTRACT FROM AUTHOR]

Atmospheric concentration measurements are used to adjust the daily to monthly budget of fossil fuel CO2 emissions of the Paris urban area from the prior estimates established by the Airparif local air quality agency. Five atmospheric monitoring sites are available, including one at the top of the Eiffel Tower. The atmospheric inversion is based on a Bayesian approach, and relies on an atmospheric transport model with a spatial resolution of 2 km with boundary conditions from a global coarse grid transport model. The inversion adjusts prior knowledge about the anthropogenic and biogenic CO2 fluxes from the Airparif inventory and an ecosystem model, respectively, with corrections at a temporal resolution of 6 h, while keeping the spatial distribution from the emission inventory. These corrections are based on assumptions regarding the temporal autocorrelation of prior emissions uncertainties within the daily cycle, and from day to day. The comparison of the measurements against the atmospheric transport simulation driven by the a priori CO2 surface fluxes shows significant differences upwind of the Paris urban area, which suggests a large and uncertain contribution from distant sources and sinks to the CO2 concentration variability. This contribution advocates that the inversion should aim at minimising model-data misfits in upwind-downwind gradients rather than misfits in mole fractions at individual sites. Another conclusion of the direct model-measurement comparison is that the CO2 variability at the top of the Eiffel Tower is large and poorly represented by the model for most wind speeds and directions. The model's inability to reproduce the CO2 variability at the heart of the city makes such measurements ill-suited for the inversion. This and the need to constrain the budgets for the whole city suggests the assimilation of upwind-downwind mole fraction gradients between sites at the edge of the urban area only. The inversion significantly improves the agreement between measured and modelled concentration gradients. Realistic emissions are retrieved for two 30-day periods and suggest a significant overestimate by the AirParif inventory. Similar inversions over longer periods are necessary for a proper evaluation of the optimised CO2 emissions against independent data. [ABSTRACT FROM AUTHOR]

Measurements of CO2, CO, NOx and selected Volatile Organic Compounds (VOCs) concentrations have been performed continuously during ten days in the Guy Môquet tunnel in Thiais, in a peri-urban area about 15 km south from the centre of Paris, between 28 September and 8 October 2012. This dataset is used here to identify the characteristics of traffic-emitted CO2 by evaluating its ratios to co-emitted species, for the first time in the Paris region. High coefficients of determination (r² > 0.7) are observed between CO2 and some compounds which are characteristic of the traffic source (CO, NOx, benzene, xylenes and acetylene). Weak correlations (r ² < 0.2) are found with species such as propane, n-butane, i-butane, that are associated with fuel evaporation, an insignificant source for CO2. To better characterize the traffic signal, we focus only on species that are well correlated with CO2 and rush hour periods characterized by the highest traffic-related concentrations. To those concentrations, we remove the nighttime averaged weekday concentration obtained for each species that we infer to be the most appropriate background signal for our study. Then, we calculate observed Δspecies/ΔCO2 ratios that we compare with the ones provided by the 2010 bottom-up high resolved regional emission inventory from Airparif, the association in charge of monitoring the air quality in Île-de-France, focusing on local emission data for the specific road of the tunnel. We find an excellent agreement (2%) between the local inventory emission CO/CO2 ratio with our observed ΔCO/ΔCO2 ratio. Former tunnel experiments carried out elsewhere in the world provided observed ΔCO/ΔCO2 ratios that differ from 49% to 592% to ours. This variability can be related to technological improvement of vehicles, differences in driving conditions and fleet compositions. We also find a satisfactory agreement with the Airparif inventory for n-propylbenzene, n-pentane and xylenes to CO2 ratios. For most of the other species, the ratios obtained from the local emission inventory overestimate the observed ratios to CO2, by 36% to more than 300%. However, the emission ratios of NOx, o-xylene and i-pentane are underestimated by 39% to 79%. One main cause of such high differences between the inventory and our observations is likely the obsolete feature of the VOCs speciation matrix of the inventory that was not updated since 1998, although law regulations on some VOCs occurred since that time. Our study bears important consequences for the characterisation of the urban CO2 plume and for atmospheric inverse modelling of urban CO2 emissions that are discussed in the conclusion. [ABSTRACT FROM AUTHOR]

Measurements of the mole fraction of the CO2 and its isotopes were performed in Paris during the MEGAPOLI winter campaign (January-February 2010). Radiocarbon (14CO2) measurements were used to identify the relative contributions of 77% CO2 from fossil fuel consumption (CO2ff from liquid and gas combustion) and 23% from biospheric CO2 (CO2 from the use of biofuels and from human and plant respiration: CO2bio). These percentages correspond to average mole fractions of 26.4 ppm and 8.2 ppm for CO2ff and CO2bio, respectively. The 13CO2 analysis indicated that gas and liquid fuel contributed 70% and 30 %, respectively, of the CO2 emission from fossil fuel use. Continuous measurements of CO and NOx and the ratios ...CO CO2ff and ...NOx CO2ff derived from radiocarbon measurements during four days make it possible to estimate the fossil fuel CO2 contribution over the entire campaign. The ratios ...CO CO2ff and ...NOx CO2ff are functions of air mass origin and exhibited daily ranges of 7.9 to 14.5 ppbppm-1 and 1.1 to 4.3 ppbppm-1, respectively. These ratios are consistent with different emission inventories given the uncertainties of the different approaches. By using both tracers to derive the fossil fuel CO2, we observed similar diurnal cycles with two maxima during rush hour traffic. [ABSTRACT FROM AUTHOR]

Accurate simulation of the spatial and temporal variability of tracer mixing ratios over urban areas is a challenging and interesting task needed to be performed in order to utilise CO² measurements in an atmospheric inverse framework and to better estimate regional CO² fluxes. This study investigates the ability of a high-resolution model to simulate meteorological and CO² fields around Paris agglomeration during the March field campaign of the CO²- MEGAPARIS project. The mesoscale atmospheric model Meso-NH, running at 2 km horizontal resolution, is coupled with the Town Energy Balance (TEB) urban canopy scheme and with the Interactions between Soil, Biosphere and Atmosphere CO²-reactive (ISBA-A-gs) surface scheme, allowing a full interaction of CO² modelling between the surface and the atmosphere. Statistical scores show a good representation of the urban heat island (UHI) with stronger urban-rural contrasts on temperature at night than during the day by up to 7°C. Boundary layer heights (BLH) have been evaluated on urban, suburban and rural sites during the campaign, and also on a suburban site over 1 yr. The diurnal cycles of the BLH are well captured, especially the onset time of the BLH increase and its growth rate in the morning, which are essential for tall tower CO² observatories. The main discrepancy is a small negative bias over urban and suburban sites during nighttime (respectively 45m and 5 m), leading to a few overestimations of nocturnal CO² mixing ratios at suburban sites and a bias of +5 ppm. The diurnal CO² cycle is generally well captured for all the sites. At the Eiffel tower, the observed spikes of CO² maxima occur every morning exactly at the time at which the atmospheric boundary layer (ABL) growth reaches the measurement height. At suburban ground stations, CO² measurements exhibit maxima at the beginning and at the end of each night, when the ABL is fully contracted, with a strong spatio-temporal variability. A sensitivity test without urban parameterisation removes the UHI and underpredicts nighttime BLH over urban and suburban sites, leading to large overestimation of nocturnal CO² mixing ratio at the suburban sites (bias of +17 ppm). The agreement between observation and prediction for BLH and CO² concentrations and urban-rural increments, both day and night, demonstrates the potential of using the urban mesoscale system in the context of inverse modelling. [ABSTRACT FROM AUTHOR]

Measurements of the mole fraction of the CO2 and its isotopes were performed in Paris during the MEGAPOLI winter campaign (January--February 2010). Radiocarbon (14CO2) measurements were used to identify the relative contributions of 77% CO2 from fossil fuel consumption (CO2ff from liquid and gas combustion) and 23% from biospheric CO2 (CO2 from the use of biofuels and from human and plant respiration: CO2bio). These percentages correspond to average mole fractions of 26.4 ppm and 8.2 ppm for CO2ff and CO2bio, respectively. The 13CO2 analysis indicated that gas and liquid fuel contributed 70% and 30 %, respectively, of the CO2 emission from fossil fuel use. Continuous measurements of CO and NOx and the ratios CO/CO2ff and NOx/CO2ff derived from radiocarbon measurements during four days make it possible to estimate the fossil fuel CO2 contribution over the entire campaign. The ratios CO/CO2ff and NOx/CO2ff are functions of air mass origin and exhibited daily ranges of 7.9 to 14.5 ppbppm-1 and 1.1 to 4.3 ppbppm-1, respectively. These ratios are sufficiently consistent with different emission inventories given the uncertainties of the different approaches. [ABSTRACT FROM AUTHOR]

Accurate simulation of the spatial and temporal variability of tracer mixing ratios over urban areas is challenging, but essential in order to utilize CO2 measurements in an atmospheric inverse framework to better estimate regional CO2 fluxes. This study investigates the ability of a high-resolution model to simulate meteorological and CO2 fields around Paris agglomeration, during the March field campaign of the CO2-MEGAPARIS project. The mesoscale atmospheric model Meso-NH, running at 2 km horizontal resolution, is coupled with the Town-Energy Balance (TEB) urban canopy scheme and with the Interactions between Soil, Biosphere and Atmosphere CO2-reactive (ISBA-A-gs) surface scheme, allowing a full interaction of CO2 between the surface and the atmosphere. Statistical scores show a good representation of the Urban Heat Island (UHI) and urban-rural contrasts. Boundary layer heights (BLH) at urban, sub-urban and rural sites are well captured, especially the onset time of the BLH increase and its growth rate in the morning, that are essential for tall tower CO2 observatories. Only nocturnal BLH at sub-urban sites are slightly underestimated a few nights, with a bias less than 50m. At Eiffel tower, the observed spikes of CO2 maxima occur every morning exactly at the time at which the Atmospheric Boundary Layer (ABL) growth reaches the measurement height. The timing of the CO2 cycle is well captured by the model, with only small biases on CO2 concentrations, mainly linked to the misrepresentation of anthropogenic emissions, as the Eiffel site is at the heart of traffic emission sources. At suburban ground stations, CO2 measurements exhibit maxima at the beginning and at the end of each night, when the ABL is fully contracted, with a very strong spatio-emporal variability. The CO2 cycle at these sites is generally well reproduced by the model, even if some biases on the nocturnal maxima appear in the Paris plume parly due to small errors on the vertical transport, or in the vicinity of airports due to small errors on the horizontal transport (wind direction). A sensitivity test without urban parameterisation removes UHI and underpredicts nighttime BLH over urban and sub-urban sites, leading to large overestimation of nocturnal CO2 concentration at the sub-urban sites. The agreement of daytime and nighttime BLH and CO2 predictions of the reference simulation over Paris agglomeration demonstrates the potential of using the meso-scale system on urban and sub-urban area in the context of inverse modelling. [ABSTRACT FROM AUTHOR]

Our ability to predict future climate change relies on our understanding of current and future CO2 fluxes, particularly on a regional scale (100-1000 km). CO2 regional sources and sinks are still poorly understood. Inverse transport modeling, a method often used to quantify these fluxes, relies on atmospheric CO2 measurements. One of the main challenges for the transport models used in the inversions is to properly reproduce CO2 vertical gradients between the boundary layer and the free troposphere, as these gradients impact on the partitioning of the calculated fluxes between the different model regions. Vertical CO2 profiles are very well suited to assess the performances of the models. In this paper, we conduct a comparison between observed and modeled CO 2 profiles recorded during two CAATER campaigns that occurred in May 2001 and October 2002 over Western Europe, as described in a companion paper. We test different combinations between a global transport model (LMDZt), a mesoscale transport model (CHIMERE), and different sets of biospheric fluxes, all chosen with a diurnal cycle (CASA, SiB2 and ORCHIDEE). The vertical profile comparison shows that: 1) in most cases the influence of the biospheric flux is small but sometimes not negligible, ORCHIDEE giving the best results in the present study; 2) LMDZt is most of the time too diffuse, as it simulates a too high boundary layer height; 3) CHIMERE better reproduces the observed gradients between the boundary layer and the free troposphere, but is sometimes too variable and gives rise to incoherent structures. We conclude there is a need for more vertical profiles to conduct further studies to improve the parameterization of vertical transport in the models used for CO 2 flux inversions. Furthermore, we use a modeling method to quantify CO 2 fluxes at the regional scale from a chosen observing point, coupling influence functions from the transport model LMDZt (that works quite well at the synoptic scale) with information on the space-time distribution of fluxes. This modeling method is compared to a dual tracer method (the so-called Radon method) for a case study on 25 May 2001 during which simultaneous well-correlated in situ CO2 and Radon 222 measurements have been collected. Both methods give a similar result: a flux within the Radon 222 method uncertainty (35%), that is an atmospheric CO2 sink of -4.2 -2 -1 to -4.4 gCm-1 day-1 . We have estimated the uncertainty of the modeling method to be at least 33% on average, and even more for specific individual events. This method allows the determination of the area that contributed to the CO 2 observed concentration. In our case, the observation point located at 1700ma.s.l. in the north of France, is influenced by an area of 1500x700 km² that covers the Benelux region, part of Germany and western Poland. Furthermore, this method allows deconvolution between the different contributing fluxes. In this case study, the biospheric sink contributes 73% of the total flux, fossil fuel emissions for 27%, the oceanic flux being negligible. However, the uncertainties of the influence function method need to be better assessed. This could be possible by applying it to other cases where the calculated fluxes can be checked independently, for example at tall towers where simultaneous CO2 and Radon 222 measurements can be conducted. The use of optimized fluxes (from atmospheric inversions) and of mesoscale models for atmospheric transport may also significantly reduce the uncertainties. [ABSTRACT FROM AUTHOR]

Atmospheric air borne measurements of CO2 are very well suited for estimating the time-varying distribution of carbon sources and sinks at the regional scale due to the large geographical area covered over a short time. We present here an analysis of two cross-European airborne campaigns carried out on 23-26 May 2001 (CAATER-1) and 2-3 October 2002 (CAATER-2) over Western Europe. The area covered during CAATER-1 and CAATER-2 was 4° W to 14° E long; 44° N to 52° N 1° at and 1° E to 17° E long; 46° N to 52° N lat respectively. High precision in situ CO2, CO and Radon 222 measurements were recorded. Flask samples were collected during both campaigns to cross-validate the in situ data. During CAATER-1 and CAATER-2, the mean CO2concentration was 370.1±4.0 (1-δ standard deviation) ppm and 371.7±5.0 (1-δ) ppm respectively. A HYSPLIT back-trajectories analysis shows that during CAATER 1, northwesterly winds prevailed. In the planetary boundary layer (PBL) air masses became contaminated over Benelux and Western Germany by emissions from these highly urbanized areas, reaching about 380 ppm. Air masses passing over rural areas were depleted in CO2 because of the photosynthesis activity of the vegetation, with observations as low as 355 ppm. During CAATER-2, the back-trajectory analysis showed that air masses were distributed among the 4 sectors. Airmasses were enriched in CO2 and CO over anthropogenic emission spots in Germany but also in Poland, as these countries have part of the most CO2-emitting coal-based plants in Europe. Simultaneous measurements of in situ CO2 and CO combined with back-trajectories helped us to distinguish between fossil fuel emissions and other CO2 sources. The ΔCO/ΔCO2 ratios (R²=0.33 to 0.88, slopes=2.42 to 10.37), calculated for anthropogenic-influenced air masses over different countries/regions matched national inventories quite well, showing that airborne measurements can help to identify the origin of fossil fuel emissions in the PBL even when distanced by several days/hundreds of kms from their sources. We have compared airborne CO2 observations to nearby ground station measurements and thereby, confirmed that measurements taken in the lower few meters of the PBL (low-level ground stations) are representative of the local scale, while those located in the free troposphere (FT) (moutain stations) are representative of atmospheric CO2 regionally on a scale of a few hundred kilometers. Stations located several 100 km away from each other differ from a few ppm in their measurements indicating the existence of a gradient within the free troposphere. Observations at stations located on top of small mountains may match the airborne data if the sampled air comes from the FT rather than coming up from the valley. Finally, the analysis of the CO2 vertical variability conducted on the 14 profiles recorded in each campaign shows a variability at least 5 to 8 times higher in the PBL (the 1-δ standard deviation associated to the CO2mean of all profiles within the PBL is 4.0 ppm and 5.7 ppm for CAATER-1 and CAATER-2, respectively) than in the FT (within the FT, 1-δ is 0.5 ppm and 1.1 ppm for CAATER-1 and CAATER-2, respectively). The CO 2 jump between the PBL and the FT equals 3.7 ppm for the first campaign and -0.3 ppm for the second campaign. A very striking zonal CO2 gradient of about 11 ppm was observed in the mid-PBL during CAATER-2, with higher concentrations in the west than in the east. This gradient may originate from differences in atmospheric mixing, ground emission rates or Autumn's earlier start in the west. More airborne campaigns are currently under analysis in the framework of the CARBOEUROPE-IP project to better assess the likelihood of these different hypotheses. In a companion paper (Xueref-Remy et al., 2011, Part 2), a comparison of vertical profiles from observations and several modeling frameworks was conducted for both campaigns. [ABSTRACT FROM AUTHOR]

The article presents a study which compares the backscatter profiles of ground-based light detection and ranging (LIDAR) sensors and in-situ radiosounding in determining boundary-layer (BL) structure. The instruments investigated in the study are highlighted which include a Leosphere ALS300 lidar and two ceilometers, Visala CL31 and Jenoptik CHM15K. The findings of the intercomparisons are expressed in mean bias, mean correlation coefficients and consistency.

Atmospheric airborne measurements of CO2 are very well-suited to estimate the time varying distribution of carbon sources and sinks at the regional scale. We present here an analysis of two cross-European airborne campaigns that have been carried out on 23-26 May 2001 (CAATER 1) and 2-3 October 2002 (CAATER 2) over Western Europe. The area covered during CAATER 1 (respectively CAATER 2) was comprised between longitude 4°W to 14° E and latitude 44° N to 52° N (respectively longitude 1° E to 17° E and latitude 46° N to 52° N). High precision in-situ CO2, CO and Radon 222 measurements have been recorded. Flasks samples have been collected during both cam paigns to cross-validate the in-situ data. During CAATER 1 (respectively CAATER 2), the mean CO2 concentration was 370.1±4 ppm (respectively 371.7±5 ppm). A HYSPLIT backtrajectories analysis shows that during CAATER 1, dominant winds were blowing from the north-west. In the planetary boundary layer (PBL) airmasses got contaminated over Benelux and Western Germany by pollution from these high urbanized areas, reaching about 380 ppm. Air masses passing over rural areas are depleted in CO2 because of the photosynthesis activity of the land cover vegetation, as low as 355 ppm. During CAATER 2, the backtrajectory analysis shows that airmasses were distributed among the 4 sectors. Airmasses got enriched in CO2 and CO when passing above polluted spots in Germany but also in Poland, as these countries are known to hold part of the most polluting plants based on coal consumption, the so-called "dirty thirty" from WWF. Simultaneous measurements of in-situ CO2 and CO combined to backtrajectories helped us to discriminate the role of fossil fuel emissions from over CO2 sources. The ΔCO/ΔCO2 ratios (R²=0.33 to 0.88, slopes=2.42 to 10.37), calculated for polluted airmasses originating from different countries/regions, matched quite well national inventories, showing that the airborne measurements can help to identify the role of fossil fuel sources even several days/hundreds of kms further in the PBL. CO2 observations have been compared to surrounding ground stations measurements, confirming that the stations located near the ground (ex. CBW, WES, HUN) are representative of the local scale, while those located in the free troposphere (FT) are representative of atmospheric CO2 on a regional scale of a few hundred kilometers (ex. CMN).… [ABSTRACT FROM AUTHOR]

Our ability to predict future climate change relies on our understanding of current and future CO2 fluxes, particularly at the scale of regions (100-1000 km). Nowadays, CO2 regional sources and sinks are still poorly known. Inverse transport modeling, a method often used to quantify these fluxes, relies on atmospheric CO2 measurements. One of the main challenge for the transport models used in the inversions is to reproduce properly CO2 vertical gradients between the boundary layer and the free troposphere, as these gradients impact on the partitioning ot the calculated fluxes between the different model regions. Vertical CO2 profiles are very well suited to assess the performances of the models. In this paper, we conduct a comparison between observed and modeled CO2 profiles recorded during two CAATER campaigns that occurred in May 2001 and October 2002 over western Europe, and that we have described in a companion paper. We test different combinations between a global transport model (LMDZt), a mesoscale transport model (CHIMERE), and different sets of biospheric fluxes, those latter all chosen to have a diurnal cycle (CASA, SiB2 and ORCHIDEE). The vertical profile comparison shows that: (1) in most cases the influence of the biospheric flux is small but sometimes not negligeable, ORCHIDEE giving the best results in the present study; (2) LMDZt is most of the time too diffusive, as it simulates a too high boundary layer height; (3) CHIMERE reproduces better the observed gradients between the boundary layer and the free troposphere, but is sometimes too variable and gives rise to incoherent structures. We conclude there is a need for more vertical profiles to conduct further studies that will help to improve the parameterization of vertical transport in the models used for CO2 flux inversions. Furthermore, we use a modeling method to quantify CO2 fluxes at the regional scale from any observing point, coupling influence functions from the transport model LMDZt (that works quite well at the synoptic scale) with information on the space-time distribution of fluxes. This modeling method is compared to a dual tracer method (the so-called Radon method) for a case study on 25 May 2001 during which simultaneous well-correlated in-situ CO2 and Radon 222 measurements have been collected. Both methods give a similar flux within the Radon 222 method uncertainty (35%), that is an atmospheric CO2 sink of -4.2 to -4.4 gCm-2 day-1. We have estimated the uncertainty of the modeling method to be at least 33% when considering averages, even much more on individual events. This method allows the determination of the area that contributed to the CO2 observed concentration. In our case, the observation point located at 1700ma.s.l. in the North of France, is influenced by an area of 1500×700 km² that covers the Benelux region, part of Germany and western Poland. Furthermore, this method allows deconvolution between the different contributing fluxes. In this case study, the biospheric sink contributes for 73% of the total flux, fossil fuel emissions for 27%, the oceanic flux being negligeable. However, the uncertainties of the influence function method must be better assessed. This could be possible by applying it to other cases where the calculated fluxes can be checked independantly, for example at tall towers where simultaneous CO2 and Radon 222 measurements can be conducted. The use of optimized fluxes (from atmospheric inversions) and of mesoscale models for atmospheric transport may also significantly reduce the uncertainties. [ABSTRACT FROM AUTHOR]

We analysed gross primary productivity (GPP), total ecosystem respiration (TER) and the resulting net ecosystem exchange (NEE) of carbon dioxide (CO 2 ) by the terrestrial biosphere during the summer of 2018 through observed changes across the Integrated Carbon Observation System (ICOS) network, through biosphere and inverse modelling, and through remote sensing. Highly correlated yet independently-derived reductions in productivity from sun-induced fluorescence, vegetative near-infrared reflectance, and GPP simulated by the Simple Biosphere model version 4 (SiB4) suggest a 130-340 TgC GPP reduction in July-August-September (JAS) of 2018. This occurs over an area of 1.6 × 10 6 km 2 with anomalously low precipitation in northwestern and central Europe. In this drought-affected area, reduced GPP, TER, NEE and soil moisture at ICOS ecosystem sites are reproduced satisfactorily by the SiB4 model. We found that, in contrast to the preceding 5 years, low soil moisture is the main stress factor across the affected area. SiB4's NEE reduction by 57 TgC for JAS coincides with anomalously high atmospheric CO 2 observations in 2018, and this is closely matched by the NEE anomaly derived by CarbonTracker Europe (52 to 83 TgC). Increased NEE during the spring (May-June) of 2018 (SiB4 -52 TgC; CTE -46 to -55 TgC) largely offset this loss, as ecosystems took advantage of favourable growth conditions. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

During the summer of 2018, a widespread drought developed over Northern and Central Europe. The increase in temperature and the reduction of soil moisture have influenced carbon dioxide (CO 2 ) exchange between the atmosphere and terrestrial ecosystems in various ways, such as a reduction of photosynthesis, changes in ecosystem respiration, or allowing more frequent fires. In this study, we characterize the resulting perturbation of the atmospheric CO 2 seasonal cycles. 2018 has a good coverage of European regions affected by drought, allowing the investigation of how ecosystem flux anomalies impacted spatial CO 2 gradients between stations. This density of stations is unprecedented compared to previous drought events in 2003 and 2015, particularly thanks to the deployment of the Integrated Carbon Observation System (ICOS) network of atmospheric greenhouse gas monitoring stations in recent years. Seasonal CO 2 cycles from 48 European stations were available for 2017 and 2018. Earlier data were retrieved for comparison from international databases or national networks. Here, we show that the usual summer minimum in CO 2 due to the surface carbon uptake was reduced by 1.4 ppm in 2018 for the 10 stations located in the area most affected by the temperature anomaly, mostly in Northern Europe. Notwithstanding, the CO 2 transition phases before and after July were slower in 2018 compared to 2017, suggesting an extension of the growing season, with either continued CO 2 uptake by photosynthesis and/or a reduction in respiration driven by the depletion of substrate for respiration inherited from the previous months due to the drought. For stations with sufficiently long time series, the CO 2 anomaly observed in 2018 was compared to previous European droughts in 2003 and 2015. Considering the areas most affected by the temperature anomalies, we found a higher CO 2 anomaly in 2003 (+3 ppm averaged over 4 sites), and a smaller anomaly in 2015 (+1 ppm averaged over 11 sites) compared to 2018. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.