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This study investigates the use of total column CH4 (XCH4) retrievals from the SCIAMACHY satellite in- strument for quantifying large-scale emissions of methane. A unique data set from SCIAMACHY is available span- ning almost a decade of measurements, covering a period when the global CH4 growth rate showed a marked transition from stable to increasing mixing ratios. The TM5 4DVAR in- verse modelling system has been used to infer CH4 emissions from a combination of satellite and surface measurements for the period 2003–2010. In contrast to earlier inverse mod- elling studies, the SCIAMACHY retrievals have been cor- rected for systematic errors using the TCCON network of ground-based Fourier transform spectrometers. The aim is to further investigate the role of bias correction of satellite data in inversions. Methods for bias correction are discussed, and the sensitivity of the optimized emissions to alternative bias correction functions is quantified. It is found that the use of SCIAMACHY retrievals in TM5 4DVAR increases the esti- mated inter-annual variability of large-scale fluxes by 22 % compared with the use of only surface observations. The dif- ference in global methane emissions between 2-year periods before and after July 2006 is estimated at 27–35 Tg yr−1. The use of SCIAMACHY retrievals causes a shift in the emis- sions from the extra-tropics to the tropics of 50±25 Tg yr−1. The large uncertainty in this value arises from the uncertainty in the bias correction functions. Using measurements from the HIPPO and BARCA aircraft campaigns, we show that systematic errors in the SCIAMACHY measurements are a main factor limiting the performance of the inversions. To further constrain tropical emissions of methane using current and future satellite missions, extended validation capabilities in the tropics are of critical importance., JRC.H.2-Air and Climate

Traditional techniques for measuring the mole fractions of greenhouse gases in the well-mixed atmosphere have required dry sample gas streams (dew point < −25 °C) to achieve the inter-laboratory compatibility goals set forth by the Global Atmosphere Watch programme of the World Meteorological Organisation (WMO/GAW) for carbon dioxide (±0.1 ppm in the Northern Hemisphere and ±0.05 ppm in the Southern Hemisphere) and methane (±2 ppb). Drying the sample gas to low levels of water vapour can be expensive, time-consuming, and/or problematic, especially at remote sites where access is difficult. Recent advances in optical measurement techniques, in particular cavity ring down spectroscopy, have led to the development of greenhouse gas analysers capable of simultaneous measurements of carbon dioxide, methane and water vapour. Unlike many older technologies, which can suffer from significant uncorrected interference from water vapour, these instruments permit accurate and precise greenhouse gas measurements that can meet the WMO/GAW inter-laboratory compatibility goals (WMO, 2011a) without drying the sample gas. In this paper, we present laboratory methodology for empirically deriving the water vapour correction factors, and we summarise a series of in-situ validation experiments comparing the measurements in humid gas streams to well-characterised dry-gas measurements. By using the manufacturer-supplied correction factors, the dry-mole fraction measurements have been demonstrated to be well within the GAW compatibility goals up to a water vapour concentration of at least 1%. By determining the correction factors for individual instruments once at the start of life, this water vapour concentration range can be extended to at least 2% over the life of the instrument, and if the correction factors are determined periodically over time, the evidence suggests that this range can be extended up to and even above 4% water vapour concentrations.

Airborne observations of greenhouse gases are a very useful reference for validation of satellite-based column-averaged dry air mole fraction data. However, since the aircraft data are available only up to about 9–13 km altitude, these profiles do not fully represent the depth of the atmosphere observed by satellites and therefore need to be extended synthetically into the stratosphere. In the near future, observations of CO2 and CH4 made from passenger aircraft are expected to be available through the In-Service Aircraft for a Global Observing System (IAGOS) project. In this study, we analyse three different data sources that are available for the stratospheric extension of aircraft profiles by comparing the error introduced by each of them into the total column and provide recommendations regarding the best approach. First, we analyse CH4 fields from two different models of atmospheric composition – the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System for Composition (C-IFS) and the TOMCAT/SLIMCAT 3-D chemical transport model. Secondly, we consider scenarios that simulate the effect of using CH4 climatologies such as those based on balloons or satellite limb soundings. Thirdly, we assess the impact of using a-priori profiles used in the satellite retrievals for the stratospheric part of the total column. We find that the models considered in this study have a better estimation of the stratospheric CH4 as compared to the climatology-based data and the satellite a-priori profiles. Both the C-IFS and TOMCAT models have a bias of about −9 ppb at the locations where tropospheric vertical profiles will be measured by IAGOS. The C-IFS model, however, has a lower random error (6.5 ppb) than TOMCAT (12.8 ppb). These values are well within the minimum desired accuracy and precision of satellite total column XCH4 retrievals (10 ppb and 34 ppb, respectively). In comparison, the a-priori profile from the University of Leicester Greenhouse Gases Observing Satellite (GOSAT) Proxy XCH4 retrieval and climatology-based data introduce larger random errors in the total column, being limited in spatial coverage and temporal variability. Furthermore, we find that the bias in the models varies with latitude and season. Therefore, applying appropriate bias correction to the model fields before using them for profile extension is expected to further decrease the error contributed by the stratospheric part of the profile to the total column.

Optimized biogenic carbon fluxes for Europe were estimated from high resolution regional scale inversions, utilizing atmospheric CO2 measurements at 16 stations for the year 2007. Additional sensitivity tests with different data-driven error structures were performed. As the atmospheric network is rather sparse and consequently contains large spatial gaps, we use a priori biospheric fluxes to further constrain the inversions. The biospheric fluxes were simulated by the Vegetation Photosynthesis and Respiration Model (VPRM) at a resolution of 0.1° and optimized against Eddy covariance data. Overall we estimate an a priori uncertainty of 0.54 GtC y−1 related to the poor spatial representation between the biospheric model and the ecosystem sites. The sink estimated from the atmospheric inversions for the area of Europe (as represented in the model domain) ranges between 0.23 and 0.38 GtC y−1 (0.30 and 0.49 GtC y−1 up-scaled to geographical Europe). This is within the range of posterior flux uncertainty estimates of previous studies using ground based observations.

Atmospheric inversions are widely used in the optimization of surface carbon fluxes at regional scale using information from atmospheric CO2 dry mole fractions. In many studies the prior flux uncertainty applied to the inversion schemes does not reflect directly the true flux uncertainties but it is used in such a way to regularize the inverse problem. Here, we aim to implement an inversion scheme using the Jena inversion system and applying a prior flux error structure derived from a model – data residual analysis using high spatial and temporal resolution over a full year period in the European domain. We analyzed the performance of the inversion system with a synthetic experiment, where the flux constraint is derived following the same residual analysis but applied to the model-model mismatch. The synthetic study showed a quite good agreement between posterior and “true” fluxes at European/Country and annual/monthly scales. Posterior monthly and country aggregated fluxes improved their correlation coefficient with the “known truth” by 7 % compared to the prior estimates when compared to the reference, with a mean correlation of 0.92. Respectively, the ratio of the standard deviation between posterior/reference and prior/reference was also reduced by 33 % with a mean value of 1.15. We identified temporal and spatial scales where the inversion system maximizes the derived information; monthly temporal scales at around 200 km spatial resolution seem to maximize the information gain.

Gobal methane emissions were estimated for 2000–2012 using the CarbonTracker Europe-CH4 (CTE-CH4) data assimilation system. In CTE-CH4, the anthropogenic and biosphere emissions of CH4 are simultaneously constrained by global atmospheric in-situ methane mole fraction observations. We use three configurations developed in Tsuruta et al. (2016) to assess the sensitivity of the CH4 flux estimates to (a) the number of unknown flux scaling factors to be optimized which in turn depends on the choice of underlying land-ecosystem map, and (b) on the parametrization of vertical mixing in the 30 atmospheric transport model TM5. The posterior emission estimates were evaluated by comparing simulations to surface in-situ observation sites, to profile observations made by aircraft, to dry air total column-averaged mole fractions (XCH4) observations from the Total Carbon Column Observing Network (TCCON), and to XCH4 retrievals from the Greenhouse gases Observing SATellite (GOSAT). Our estimated posterior mean global total emissions during 2000–2012 are 516 ± 51 Tg CH4 yr−1, and emission estimates during 2007–2012 are 18 Tg CH4 yr−1 greater than those from 2001–2006, mainly driven by an 35 increase in emissions from the south America temperate region, the Asia temperate region and Asia tropics. The sensitivity of the flux estimates to the underlying ecosystem map was large for the Asia temperate region and Australia, but not significant in the northern latitude regions, i.e. the north American boreal region, the north American temperate region and Europe. Instead, the posterior estimates for the northern latitude regions show larger sensitivity to the choice of convection scheme in TM5. The Gregory et al. (2000) mixing scheme with faster interhemispheric exchange leads to higher estimated CH4 emissions at northern latitudes, and lower emissions in southern latitudes, compared to the estimates using Tiedtke (1989) convection scheme. Our evaluation with non-assimilated observations showed that posterior mole fractions were better matched with the 5 observations when Gregory et al. (2000) convection scheme was used.

Megacities are major sources of anthropogenic fossil fuel CO2 emissions. The spatial extents of these large urban systems cover areas of 10,000 km2 or more with complex topography and changing landscapes. We present a high-resolution land-atmosphere modelling system for urban CO2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO2 emission product, Hestia-LA, to simulate atmospheric CO2 concentrations across the LA megacity at spatial resolutions as fine as ~ 1 km. We evaluated multiple WRF configurations, selecting one that minimized errors in wind speed, wind direction, and boundary layer height as validated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate- (4-km) and high- (1.3-km) resolution simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved PBL heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3-km resolution) fossil fuel CO2 emission products to evaluate the impact of the spatial resolution of the CO2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO2 concentrations. We find that high spatial resolution in the fossil fuel CO2 emissions is more important than in the atmospheric model to capture CO2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO2 fields to qualitatively evaluate greenhouse gas measurements over the LA megacity. Spatial correlations in the atmospheric CO2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO2 emissions monitoring in the LA megacity requires FFCO2 emissions modelling with ~ 1 km resolution since coarser resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.

Currently 52 % of the world's population resides in urban areas and as a consequence, approximately 70 % of fossil fuel emissions of CO2 arise from cities. This fact in combination with large uncertainties associated with quantifying urban emissions due to lack of appropriate measurements makes it crucial to obtain new measurements useful to identify and quantify urban emissions. This is required, for example, for the assessment of emission mitigation strategies and their effectiveness. Here we investigate the potential of a satellite mission like Carbon Monitoring Satellite (CarbonSat), proposed to the European Space Agency (ESA) – to retrieve the city emissions globally, taking into account a realistic description of the expected retrieval errors, the spatiotemporal distribution of CO2 fluxes, and atmospheric transport. To achieve this we use (i) a high-resolution modeling framework consisting of the Weather Research Forecasting model with a greenhouse gas module (WRF-GHG), which is used to simulate the atmospheric observations of column averaged CO2 dry air mole fractions (XCO2), and (ii) a Bayesian inversion method to derive anthropogenic CO2 emissions and their errors from the CarbonSat XCO2 observations. We focus our analysis on Berlin in Germany using CarbonSat's cloud-free overpasses for one reference year. The dense (wide swath) CarbonSat simulated observations with high-spatial resolution (approx. 2 km × 2 km) permits one to map the city CO2 emission plume with a peak enhancement of typically 0.8–1.35 ppm relative to the background. By performing a Bayesian inversion, it is shown that the random error (RE) of the retrieved Berlin CO2 emission for a single overpass is typically less than 8 to 10 MtCO2 yr−1 (about 15 to 20 % of the total city emission). The range of systematic errors (SE) of the retrieved fluxes due to various sources of error (measurement, modeling, and inventories) is also quantified. Depending on the assumptions made, the SE is less than about 6 to 10 MtCO2 yr−1 for most cases. We find that in particular systematic modeling-related errors can be quite high during the summer months due to substantial XCO2 variations caused by biogenic CO2 fluxes at and around the target region. When making the extreme worst-case assumption that biospheric XCO2 variations cannot be modeled at all (which is overly pessimistic), the SE of the retrieved emission is found to be larger than 10 MtCO2 yr−1 for about half of the sufficiently cloud-free overpasses, and for some of the overpasses we found that SE may even be on the order of magnitude of the anthropogenic emission. This indicates that biogenic XCO2 variations cannot be neglected but must be considered during forward and/or inverse modeling. Overall, we conclude that CarbonSat is well suited to obtain city-scale CO2 emissions as needed to enhance our current understanding of anthropogenic carbon fluxes and that CarbonSat or CarbonSat-like satellites should be an important component of a future global carbon emission monitoring system.

Records of trace gas composition of the atmosphere originating from mountain stations are difficult to interpret in terms of continental gas balances due to complex topography and local wind patterns. Kasprowy Wierch station, located in the High Tatra Mountains, Poland, provides datasets to European GHG databases and can be used for regional and continental balances of trace gases in Earth's atmosphere. Although it suffers from strong influence of local valley winds, the concentration record obtained at Kasprowy Wierch contains also a discernible fraction of methane (up to 100 ppb) emitted mainly by large regional source of this gas (Silesian Coal Basin) located ca. 150 km north-west of Kasprowy Wierch. Comparison of GOSAT satellite CH_4 record in the pixel including High Tatras at the level of 850 hPa with the data obtained at Kasprowy Wierch mountain station revealed surprisingly good correlation, even for relatively short time intervals.

A new technique for the satellite remote sensing of greenhouse gases in the atmosphere via the absorption of short-wave infrared laser signals transmitted between counter-rotating satellites in low Earth orbit has recently been proposed; this would enable the acquisition of a long-term, stable, global set of altitude-resolved concentration measurements. We present the first ground-based experimental demonstration of this new infrared-laser occultation method, in which the atmospheric absorption of CO2 near 2.1 μm was measured over a ~144 km path length between two peaks in the Canary Islands (at an altitude of ~2.4 km), using relatively low power diode lasers (~4 to 10 mW). The retrieved CO2 volume mixing ratio of 400 ppm (±15 ppm) is consistent within experimental uncertainty with simultaneously recorded in situ validation measurements. We conclude that the new method has a sound basis for monitoring CO2 in the free atmosphere; other greenhouse gases such as methane, nitrous oxide and water vapour can be monitored in the same way.

We report results from our atmospheric flask sampling network for three European sites: Lutjewad in the Netherlands, Mace Head in Ireland and the North Sea F3 platform. The air samples from these stations are analyzed for their CO2 and O2 concentrations. In this paper we present the CO2 and O2 data series from these sites between 1998 and 2009, as well as the atmospheric potential oxygen (APO). The seasonal pattern and long term trends agree to a large extent between our three measurement locations. We however find a changing gradient between Mace Head and Lutjewad, both for CO2 and O2. To explain the potential contribution of fossil fuel emissions to this changing gradient we use an atmospheric transport model in combination with CO2 emission data and information on the fossil fuel mix per region. Using the APO trend from Mace Head we obtain an estimate for the global oceanic CO2 uptake of 1.8 ± 0.8 PgC/year.

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 σ=0.5 ppm over the continents and σ=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 transport.

This paper describes the coupling between a mesoscale numerical weather prediction model, the Weather Research and Forecasting (WRF) model, and a Lagrangian Particle Dispersion Model, the Stochastic Time-Inverted Lagrangian Transport (STILT) model. The primary motivation for developing this coupled model has been to reduce transport errors in continental-scale top–down estimates of terrestrial greenhouse gas fluxes. Examples of the model’s application are shown here for backward trajectory computations originating at CO2 measurement sites in North America. Owing to its unique features, including meteorological realism and large support base, good mass conservation properties, and a realistic treatment of convection within STILT, the WRF–STILT model offers an attractive tool for a wide range of applications, including inverse flux estimates, flight planning, satellite validation, emergency response and source attribution, air quality, and planetary exploration.

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 −12.1 μmol.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, (−16.8 μmol.m−2.s−1 for the small sub-domain and −8.6 μmol.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 errors.

Atmospheric CO2 modeling in interaction with the surface fluxes, at the regional scale is developed within the frame of the European project CarboEurope-IP and its Regional Experiment component. In this context, five meso-scale meteorological models at 2 km resolution participate in an intercomparison exercise. Using a common experimental protocol that imposes a large number of rules, two days of the CarboEurope Regional Experiment Strategy (CERES) campaign are simulated. A systematic evaluation of the models is done in confrontation with the observations, using statistical tools and direct comparisons. Thus, temperature and relative humidity at 2 m, wind direction, surface energy and CO2 fluxes, vertical profiles of potential temperature as well as in-situ CO2 concentrations comparisons between observations and simulations are examined. These comparisons reveal a cold bias in the simulated temperature at 2 m, the latent heat flux is often underestimated. Nevertheless, the CO2 concentrations heterogeneities are well captured by most of the models. This intercomparison exercise shows also the models ability to represent the meteorology and carbon cycling at the synoptic and regional scale in the boundary layer, but also points out some of the major shortcomings of the models.

Utilising a fleet of commercial airliners, MOZAIC/IAGOS provides atmospheric composition data on a regular basis that are widely used for modelling applications. Due to the specific operational context of the platforms, such observations are collected close to international airports and hence in an environment characterised by high anthropogenic emissions. This provides opportunities for assessing emission inventories of major metropolitan areas around the world, but also challenges in representing the observations in typical chemical transport models. We assess here the contribution of different sources of error to overall model–data mismatch using the example of MOZAIC/IAGOS carbon monoxide (CO) profiles collected over the European regional domain in a time window of 5 yr (2006–2011). The different sources of error addressed in the present study are: 1) mismatch in modelled and observed mixed layer height; 2) bias in emission fluxes and 3) spatial representation error (related to unresolved spatial variations in emissions). The modelling framework combines a regional Lagrangian transport model (STILT) with EDGARv4.3 emission inventory and lateral boundary conditions from the MACC reanalysis. The representation error was derived by coupling STILT with emission fluxes aggregated to different spatial resolutions. We also use the MACC reanalysis to assess uncertainty related to uncertainty sources 2) and 3). We treat the random and the bias components of the uncertainty separately and found that 1) and 3) have a comparable impact on the random component for both models, while 2) is far less important. On the other hand, the bias component shows comparable impacts from each source of uncertainty, despite both models being affected by a low bias of a factor of 2–2.5 in the emission fluxes. In addition, we suggested methods to correct for biases in emission fluxes and in mixing heights. Lastly, the evaluation of the spatial representation error against model–data mismatch between MOZAIC/IAGOS observations and the MACC reanalysis revealed that the representation error accounts for roughly 15–20% of the model–data mismatch uncertainty. Keywords: airborne observations, IAGOS, carbon monoxide, representation error, model–data mismatch (Published: 5 November 2015) Citation: Tellus B 2015, 67, 28292, http://dx.doi.org/10.3402/tellusb.v67.28292

This paper describes a tunable diode laser-based dual-channel photoacoustic (PA) humidity measuring system primarily designed for aircraft-based environment research. It is calibrated for total pressure and water vapor (WV) volume mixing ratios (VMRs) possible during airborne applications. WV VMR is calculated by using pressure-dependent calibration curves and a cubic spline interpolation method. Coverage of the entire atmospheric humidity concentration range that might be encountered during airborne measurements is facilitated by applying an automated sensitivity mode switching algorithm. The calibrated PA system was validated through laboratory and airborne intercomparisons, which proved that the repeatability, the estimated accuracy and the response time of the system are 0.5 ppmV or 0.5% of the actual reading (whichever value is the greater), 5% of the actual reading within the VMR range of 1–12 000 ppmV and 2 s, respectively. The upper detection limit of the system is theoretically about 85 000 ppmV, limited only by condensation of water vapor on the walls of the 318 K heated PA cells and inlet lines, and was experimentally verified up to 20 000 ppmV. The unique advantage of the presented system is its applicability for simultaneous water vapor and total water volume mixing ratio measurements.

A case study of aircraft measurements in the vicinity of a warm front over the North Sea is presented. Measurements of ozone, carbon monoxide and meteorological parameters were recorded at several altitudes behind a dissipating warm front by the U.K. Met. Office's C130 aircraft, operated by the Meteorological Research Flight on 3rd October 1997. The aim of the study was to investigate the composition of the warm conveyor belt (WCB), the main air flow associated with mid-latitude cyclones, which has the potential to transport boundary layer air containing ozone and its precursors into the free troposphere.Three distinct air masses were identified by changes in the parameters measured. Trajectory analyses together with synoptic charts showed that these air masses corresponded to a WCB and air ahead and behind it, and that the WCB consisted of marine air from the boundary layer and lower free-troposphere. The WCB was clearly identifiable as a distinct chemical air mass that retained its integrity even after the warm front began to dissipate; it contained lower ozone than the surrounding free tropospheric air due to its remote marine origin.

Surface carbon dioxide concentrations were measured using a non-dispersive infrared carbon dioxide sensor at Lampang Rajabhat University from April to May 2013 and at the University of the Philippines-Diliman campus starting September 2013. Factors influencing the variations in these measurements were determined using multiple linear regression and a Lagrangian transport model. Air temperature and sea level pressure were the dominant meteorological factors that affect the CO2 variations. However, these factors are not enough. Surface CO2 flux and transboundary transport needs to be considered as well.

During the fall 1997 North Atlantic Regional Experiment (NARE 97), two separate intercomparisons of aircraft-based carbon monoxide measurement instrumentation were conducted. On September 2, CO measurements were simultaneously made aboard the National Oceanic and Atmospheric Administration (NOAA) WP-3 by vacuum ultraviolet (VUV) fluorescence and by tunable diode laser absorption spectroscopy (TDLAS), On September 18, an intercomparison flight was conducted between two separate instruments, both employing the VUV fluorescence method, on the NOAA WP-3 and the U,K. Meteorological Office C-130 Hercules. The results indicate that both of the VUV fluorescence instruments and the TDLAS system are capable of measuring ambient CO accurately and precisely with no apparent interferences in 5 s. The accuracy of the measurements, based upon three independent calibration systems, is indicated by the agreement to within 11% with systematic offsets of less than 1 ppbv. In addition, one of the groups participated in the Measurement of Air Pollution From Satellite (MAPS) intercomparison [Novelli ef at., 1998] with a different measurement technique but very similar calibration system, and agreed with the accepted analysis to within 5%. The precision of the measurements is indicated by the variability of the ratio of simultaneous measurements from the separate instruments, This variability is consistent with the estimated precisions of 1.5 ppbv and 2.2 ppbv for the 5 s average results of the C-130 and the WP-3 instruments, respectively, and indicates a precision of approximately 3.6% for the TDLAS instrument. The excellent agreement of the instruments in both intercomparisons demonstrates that significant interferences in the measurements are absent in air masses that ranged from 7 km in the midtroposphere to boundary layer conditions including subtropical marine air and continental outflow with embedded urban plumes. The intercomparison of the two VUV instruments that differed widely in their design indicates that the VUV fluorescence technique for CO measurements is not particularly sensitive to the details of its implementation. These intercomparisons help to establish the reliability of ambient CO measurements by the VUV fluorescence technique.

Climatologies of tropospheric NOx (NO + NO2) and NOy (total reactive nitrogen: NOx + N03 + 2 × N2O5 + HNO2 + HNO3 + HNO4 + ClONO2 + PAN (peroxyacetylnitrate) + other organic ni trates) have been compiled from data previously published and, in most cases, publicly archived. Emphasis has been on non-urban measurements, including rural and remote ground sites, as well as aircraft data. Although the distribution of data is sparse, a compilation in this manner can begin to provide an understanding of the spatial and temporal distributions of these reactive nitrogen species. The cleanest measurements in the boundary layer are in Alaska, northern Canada and the eastern Pacific, with median NO mixing ratios below 10 pptv, NOx below 50 pptv, and NOy below 300 pptv. The highest NO values (greater than 1 ppbv) were found in eastern North America and Europe, with correspondingly high NOy (∼ 5 ppbv). A significantly narrower range of concentrations is seen in the free troposphere, particularly at 3–6 km, with NO typically about 10 pptv in the boreal summer. NO increases with altitude to ∼ 100 pptv at 9–12 km, whereas NOy does not show a trend with altitude, but varies between 100 and 1000 pptv. Decreasing mixing ratios eastward of the Asian and North American continents are seen in all three species at all altitudes. Model-generated climatologies of NOx and NOy from six chemical transport models are also presented and are compared with observations in the boundary layer and the middle troposphere for summer and winter. These comparisons test our understanding of the chemical and transport processes responsible for these species distributions. Although the model results show differences between them, and disagreement with observations, none are systematically different for all seasons and altitudes. Some of the differences between the observations and model results may likely be attributed to the specific meteorological conditions at the time that measurements were made differing from the model meteorology, which is either climatological flow from GCMs or actual meteorology for an arbitrary year. Differences in emission inventories, and convection and washout schemes in the models will also affect the calculated NOα and NOy distributions.

Amazon forests exert a major influence on the global carbon cycle, but quantifying the impact is complicated by diverse landscapes and sparse data. Here we examine seasonal carbon balance in southern Amazonia using new measurements of column-averaged dry air mole fraction of CO2 (XCO2) and solar induced chlorophyll fluorescence (SIF) from the Greenhouse Gases Observing Satellite (GOSAT) from July 2009 to December 2010. SIF, which reflects gross primary production (GPP), is used to disentangle the photosynthetic component of land-atmosphere carbon exchange. We find that tropical transitional forests in southern Amazonia exhibit a pattern of low XCO2 during the wet season and high XCO2 in the dry season that is robust to retrieval methodology and with seasonal amplitude double that of cerrado ecosystems to the east (4 ppm versus 2 ppm), including enhanced dilution of 2.5 ppm in the wet season. Concomitant measurements of SIF, which are inversely correlated with XCO2 in southern Amazonia (r =0.53, p

Common transport models use the mixing height (MH) to determine turbulent coefficients and to obtain tracer concentrations in the planetary boundary layer (PBL). We conducted a pseudo data experiment to elucidate the impact of assimilating MHs to improve CO2 transport within the Stochastic Time-Inverted Lagrangian Transport model (STILT). Transport of CO2 was simulated for August 2006 with a receptor located at Bialystok, Poland. STILT was driven by meteorology obtained from the Weather Research and Forecasting (WRF) model, using the Yonsei University (YSU) and Mellor-Yamada-Janjic (MYJ) PBL parameterizations, which differ substantially in the produced MHs. To quantify model-data mismatch in CO2 to errors in vertical mixing, we defined the WRF-YSU simulation as known truth. Pseudo MH observations were sampled from WRF-YSU at locations of real radiosonde stations. These point observations were interpolated in space-time to the entire WRF domain using kriging with an external drift, which combines observed and modeled MHs to create a "best guess" MH field. We prescribed MHs in STILT driven by WRF-MYJ winds with the best guess to study the impact on CO 2 concentrations. Differences in CO2 between the STILT simulations were on the order of 0-1 and 1-10 ppm on average (i.e., bias), with standard deviations of 1-3 and 4-14 ppm (random error) during day (12 UTC) and nighttime (0 UTC), respectively. These were reduced when using STILT with the best guess (50%-80% of the bias, 10%-20% of the random error). Simulated CO2 concentrations and MHs were also compared to measurements made at the Bialystok tall tower. © 2012. American Geophysical Union. All Rights Reserved. (Less)

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.

[1] Tropical regions, especially the Amazon region, account for large emissions of methane (CH_4). Here, we present CH_4 observations from two airborne campaigns conducted within the BARCA (Balanco Atmosferico Regional de Carbono na Amazonia) project in the Amazon basin in November 2008 (end of the dry season) and May 2009 (end of the wet season). We performed continuous measurements of CH_4 onboard an aircraft for the first time in the Amazon region, covering the whole Amazon basin with over 150 vertical profiles between altitudes of 500 m and 4000 m. The observations support the finding of previous ground-based, airborne, and satellite measurements that the Amazon basin is a large source of atmospheric CH_4. Isotope analysis verified that the majority of emissions can be attributed to CH_4 emissions from wetlands, while urban CH_4 emissions could be also traced back to biogenic origin. A comparison of five TM5 based global CH_4 inversions with the observations clearly indicates that the inversions using SCIAMACHY observations represent the BARCA observations best. The calculated CH_4 flux estimate obtained from the mismatch between observations and TM5-modeled CH_4 fields ranges from 36 to 43 mg m^(−2) d^(−1) for the Amazon lowland region.

COMMENTARY Common but differentiated IBI Prize Essay LETTERS I BOOKS I POLICY FORUM I EDUCATION FORUM I PERSPECTIVES LETTERS edited by Jennifer Sills Iconic CO 2 Time Series at Risk THE STEADY RISE IN ATMOSPHERIC LONG- lived greenhouse gas concentrations is the main driver of contemporary climate change. The Mauna Loa CO 2 time series (1, 2), started by C. D. Keeling in 1958 and maintained today by the Scripps Institution of Oceanography and the Earth System Research Laboratory (ESRL) of NOAA, is iconic evidence of the effect of human- caused fossil fuel and land-use change emis- sions on the atmospheric increase of CO 2 . The continuity of such records depends criti- cally on having stable funding, which is chal- lenging to maintain in the context of 3- to 4-year research grant funding cycles (3), and LEAH R. GERBER Faculty of Ecology, Evolution, and Environmental Sciences, School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA. E-mail: leah.gerber@asu.edu References 1. Associated Press, The New York Times, 6 July 2012, p. A7 (www.nytimes.com/2012/07/06/ world/europe/south-korea-whaling-plan-criticized.html). 2. S. Herman, Voice of America, 24 July 2012 (www.voanews.com/content/south-korea-still- considering-resumption-of-whaling/1444081.html). 3. L. R. Gerber, L. Morissette, K. Kaschner, D. Pauly, Science 323, 880 (2009). 4. R. Black, BBC News, 5 July 2012 (www.bbc.co.uk/news/science-environment-18719512). is currently threatened by the fi nancial crisis. The ESRL Global Monitoring Division maintains a network of about 100 surface and aircraft sites worldwide at which whole air samples are collected approximately every week for analysis of CO 2 , CH 4 , CO, halocar- bons, and many other chemical species (4). This is complemented by high-frequency measurements at the Mauna Loa, Barrow, American Samoa, and South Pole obser- vatories, and about 10 North American tall towers. The success of the NOAA program has inspired similar efforts in Europe (5), China (6), India (7), and Brazil (8), with the United Nations World Meteorological Orga- nization providing guidance and precision requirements through the Global Atmosphere Watch program (9), but no funding. 31 AUGUST 2012 Downloaded from www.sciencemag.org on August 17, 2015 AT THE RECENT INTERNATIONAL WHALING COMMISSION’S ANNUAL meeting in Panama, South Korean offi cials announced their plan to initiate a “scientifi c whaling” program (1). This announcement came as a surprise given the general sentiment that the global demand for whale meat is declining. After weeks of international outcry, on 17 July, South Korea reversed their decision to hunt whales for research, but the issue is not dead (2). South Korea claimed that the goal of the scientifi c whaling pro- gram is to study the types and amounts of fi sh whales eat, given confl ict with fi sher- ies. Yet, it is well established in the scien- tifi c literature that there are many ways to study whale diet without killing them (3). Decades of fruitless negotiation between pro- and anti-whaling nations suggests a broken system, wrought with loopholes that allow unsustainable whal- ing to continue. Within this broken system, there is no incentive to reduce whaling, as the recent announcement by South Korea shows. Whaling groups are unwilling to compromise by allowing a sustainable harvest of whales, so unsustainable (scientifi c) whaling continues. To ensure a future of both whales and whalers, we must har- ness the passion and value that people place on living whales, with- out telling people what to do or force one set of values on others. We need novel, out-of-the-box approaches to effective management and conservation of whales. We must compromise to ensure reduc- tions in whales being killed, better oversight of countries that har- vest them, and limited whaling that does not threaten the persis- tence of whales. For those who believe that whaling is unethical, I challenge you to put forward alternative ideas to a global moratorium that fosters the “loophole” of scientifi c whaling. With new plans to develop scientifi c whaling programs (4), the current global moratorium is clearly bro- ken. Scientists, conservation advocates, resource managers, and the public must work together to develop new approaches to ensure the persistence of whales in our oceans. The data collected by NOAA and its worldwide partners have been used not only to demonstrate the unassailable rise of atmo- spheric greenhouse gas concentrations, but also to infer the magnitudes, locations, and times of surface-atmosphere exchange of those gases based on small concentration gradients between sites (10). Important fi nd- ings from analysis of these records include the detection of a signifi cant terrestrial car- bon sink at northern mid-latitudes (11) and subsequent research aimed at identifying the mechanisms by which that sink must operate. Long-term, high-quality, atmospheric mea- surements are crucial for quantifying trends in greenhouse gas fl uxes and attributing them to fossil fuel emissions, changes in land-use and management, or the response of natural VOL 337 SCIENCE www.sciencemag.org Published by AAAS CREDIT: LEAH GERBER/ ARIZONA STATE UNIVERSITY The Scientifi c Whaling Loophole

[1] Lagrangian models (LMs) track the movement of fluid parcels in their moving frame of reference. As such, scientists using LMs are forced, in a way, to imagine themselves moving with the parcel and experiencing the effects of advection, turbulence, and changes in the parcel's environment. LMs have advanced in sophistication over recent decades, allowing them to be used increasingly for both scientific and societal purposes. For example, it is common practice now for researchers around the world to apply LMs to examine a wide spectrum of geophysical phenomena. Atmospheric chemists can track intercontinental transport of pollution plumes [Stohl et al., 2002] or airborne radioactivity [Wotawa et al., 2006]. By running LMs backward in time [Flesch et al., 1995; Lin et al., 2003], instrumentalists can establish the source regions of observed atmospheric species with high computational efficiency [Ryall et al., 2001]. Therefore, LMs are being used increasingly to quantify sources and sinks of greenhouse gases by combining simulations with observations in an inverse modeling framework [Trusilova et al., 2010]. Such “top-down” emissions estimation is receiving growing acceptance as an independent tool to test the veracity of emissions inventories and to verify adherence to treaties.

S. Houweling1,2, M. Krol1,2,3, P. Bergamaschi4, C. Frankenberg5, E. J. Dlugokencky6, I. Morino7, J. Notholt8, V. Sherlock9, D. Wunch10, V. Beck11, C. Gerbig11, H. Chen12,13, E. A. Kort14, T. Rockmann2, and I. Aben1 1SRON Netherlands Institute for Space Research, Utrecht, the Netherlands 2Institute for Marine and Atmospheric Research (IMAU), Utrecht University, Utrecht, the Netherlands 3Department of Meteorology and Air Quality (MAQ), Wageningen University and Research Centre, Wageningen, the Netherlands 4European Commission Joint Research Centre, Institute for Environment and Sustainability, Ispra (Va), Italy 5Jet Propulsion Laboratory, Pasadena, CA, USA 6NOAA Earth System Research Laboratory, Global Monitoring Division, Boulder, CO, USA 7Center for Global Environmental Research, National Institute for Environmental Studies (NIES) Onogawa 16-2, Tsukuba, Ibaraki 305-8506, Japan 8Institute of Environmental Physics, University of Bremen, Bremen, Germany 9National Institute of Water and Atmospheric Research (NIWA), P.O. Box 14-901, Wellington, New Zealand 10Caltech, Pasadena, CA, USA 11Max Planck Institute for Biogeochemistry, Jena, Germany 12Center for Isotope Research (CIO), University of Groningen, the Netherlands 13CIRES, University of Colorado, Boulder, CO, USA 14Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, Ann Arbor, MI, USA

A Bayesian inversion approach was used to retrieve temporally and spatially resolved N2O fluxes for western and central Europe using in-situ atmospheric observations from the tall tower site at Ochsenkopf, Germany (50°01´ N, 11°48´ E). For atmospheric transport, the STILT (Stochastic Time-Inverted Lagrangian Transport) model was employed, which was driven with ECMWF analysis and short term forecast fields. The influence of temporal aggregation error, as well as the choice of spatial and temporal correlation scale length, on the retrieval was investigated using a synthetic dataset consisting of mixing ratios generated for the Ochsenkopf site. We found that if the aggregation error is ignored, then a significant bias error in the retrieved fluxes ensues. However, by estimating this error and projecting it into the observation space, it was possible to avoid bias errors in the retrieved fluxes. Using the real observations from the Ochsenkopf site, N2O fluxes were retrieved every 7 days for 2007 at 2 by 2 degrees spatial resolution. Emissions of N2O were strongest during the summer and autumn months, with peak emissions in August and September, while the regions of Benelux and northern United Kingdom had the strongest annual mean emissions.

We report results from our atmospheric flask sampling network for three European sites: Lutjewad in the Netherlands, Mace Head in Ireland and the North Sea F3 platform. The air samples from these stations are primarily being analyzed for their CO2 and O2 concentrations. In this paper we present the CO2 and O2 data series from these sites between 1998 and 2009, as well as the atmospheric potential oxygen (APO). The seasonal pattern and long term trends agree to a large extent between our three measurement locations. We however find an increasing gradient between Mace Head and Lutjewad, both for CO2 and O2. As Lutjewad is influenced by local fluctuations in the fossil fuel sources, we use an atmospheric transport model in combination with CO2 emission data and information on the fossil fuel mix per region and category in order to correct the tracer APO for a residual fossil fuel component. For Lutjewad this correction differs significantly from the global average. Using the APO trend from Mace Head we obtain an estimate for the global oceanic CO2 uptake of 1.8 ± 0.8 PgC/year.

The first ground-based remote sensing measurements of the column averaged volume mixing ratio of CO2 (XCO2) in tropical South America have been obtained at Paramaribo, Suriname (5.8° N, 55.2° W). The remote sensing observations are complemented by surface air-samples collected at the site, analyzed for CO2 and 13CO2. The surface in-situ measurements are strongly influenced by local sources. From the isotopic composition of the air samples the local source component is suggested to be dominated by the terrestrial biosphere. Using δ13C from the NOAA/ESRL stations Ascension Is. (ASC), 7.9° S, 14.4° W, and Ragged Point (RPB), 13.2° N, 59.4° W, the data has been corrected for the local source component. Due to the migration of the Intertropical Convergence Zone (ITCZ) over the measurement site the sampled air masses belong to the Northern or Southern Hemisphere depending on the time of the year. Comparison to analyzed CO2 fields based on TM3 model simulations using optimized fluxes indicate agreement for the seasonality in XCO2 as well as for the corrected CO2 mixing ratios at the surface for the long dry season, when Paramaribo belongs to the Southern Hemisphere. A slightly worse agreement during the short dry season is attributed to a larger representation error during this time of the year. Overall the comparison indicates that the TM3 model is capable to simulate the seasonal variation of surface concentrations as well as column densities of CO2 correctly at Paramaribo. It has been also shown that the column measurements currently performed at Paramaribo have a limited precision and lack the link to the in situ measurements. Solutions for future improvements have been suggested.

Total column concentrations and volume mixing ratio profiles of methane have been retrieved from ground-based solar absorption FTIR spectra in the near-infrared recorded in Paramaribo (Suriname). The methane FTIR observations are compared with TM5 model simulations and satellite observations from SCIAMACHY, and represent the first validation of SCIAMACHY retrievals in the tropics using ground-based remote sensing techniques. Apart from local biomass burning features, our methane FTIR observations agree well with the SCIAMACHY retrievals and TM5 model simulations.

The Total Carbon Column Observing Network (TCCON) produces precise measurements of the column average dry-air mole fractions of CO2, CO, CH4, N2O and H2O at a variety of sites worldwide. These observations rely on spectroscopic parameters that are not known with sufficient accuracy to compute total columns that can be used in combination with in situ measurements. The TCCON must therefore be calibrated to World Meteorological Organization (WMO) in situ trace gas measurement scales. We present a calibration of TCCON data using WMO-scale instrumentation aboard aircraft that measured profiles over four TCCON stations during 2008 and 2009. The aircraft campaigns are the Stratosphere-Troposphere Analyses of Regional Transport 2008 (START-08), which included a profile over the Park Falls site, the HIAPER Pole-to-Pole Observations (HIPPO-1) campaign, which included profiles over the Lamont and Lauder sites, a series of Learjet profiles over the Lamont site, and a Beechcraft King Air profile over the Tsukuba site. These calibrations are compared with similar observations made during the INTEX-NA (2004), COBRA-ME (2004) and TWP-ICE (2006) campaigns. A single, global calibration factor for each gas accurately captures the TCCON total column data within error.

High-accuracy continuous measurements of greenhouse gases (CO2 and CH4) during the BARCA (Balanço Atmosférico Regional de Carbono na Amazônia) phase B campaign in Brazil in May 2009 were accomplished using a newly available analyzer based on the cavity ring-down spectroscopy (CRDS) technique. This analyzer was flown without a drying system or any in-flight calibration gases. Water vapor corrections associated with dilution and pressure-broadening effects for CO2 and CH4 were derived from laboratory experiments employing measurements of water vapor by the CRDS analyzer. Before the campaign, the stability of the analyzer was assessed by laboratory tests under simulated flight conditions. During the campaign, a comparison of CO2 measurements between the CRDS analyzer and a nondispersive infrared (NDIR) analyzer on board the same aircraft showed a mean difference of 0.22±0.09 ppm for all flights over the Amazon rain forest. At the end of the campaign, CO2 concentrations of the synthetic calibration gases used by the NDIR analyzer were determined by the CRDS analyzer. After correcting for the isotope and the pressure-broadening effects that resulted from changes of the composition of synthetic vs. ambient air, and applying those concentrations as calibrated values of the calibration gases to reprocess the CO2 measurements made by the NDIR, the mean difference between the CRDS and the NDIR during BARCA was reduced to 0.05±0.09 ppm, with the mean standard deviation of 0.23±0.05 ppm. The results clearly show that the CRDS is sufficiently stable to be used in flight without drying the air or calibrating in flight and the water corrections are fully adequate for high-accuracy continuous airborne measurements of CO2 and CH4.

Total column concentrations of methane have been retrieved from ground-based solar absorption FTIR spectra in the near-infrared recorded in Paramaribo (Suriname). The methane FTIR observations are compared with TM5 model simulations and satellite observations from SCIAMACHY, and represent the first validation of SCIAMACHY retrievals in the inner tropics using ground-based remote sensing techniques. Apart from local biomass burning features, our methane FTIR observations agree well with TM5 model simulations. The comparison of the direct measured CH4/CO2 ratios by FTIR and satellite reveals that the satellite can hardly detect methane emissions of tropical biomass burning due to the used retrieval method.

Methane and nitrous oxide are potent greenhouse gases whose atmospheric abundances have increased significantly in the past 200 years, together accounting for approximately half of the radiative forcing associated with increasing concentrations of carbon dioxide. In order to understand the factors causing increase of these gases globally, we need to determine their emission rates at regional to continental scales. We directly link atmospheric observations with surface emissions using a Lagrangian Particle Dispersion Model, and then determine emission rates by optimizing prior emissions estimates. We use measurements from NOAA's tall tower and aircraft program in 2004, The Stochastic Time-Inverted Lagrangian Transport model (STILT) driven by meteorological fields from a customized version of the Weather Research and Forecasting (WRF) model, and EDGAR32FT2000 and Global Emissions Inventory Activity (GEIA) as prior emission estimates. In the US and Canada, methane emission rates are found to be consistent wi...

This paper describes a numerical interpretation of the April 2007, CarboEurope Regional Experiment Strategy (CERES) campaign, devoted to the study of the CO2 cycle at the regional scale. Four consecutive clear sky days with intensive observations of CO2 concentration, fluxes at the surface and in the boundary layer have been simulated with the Meso-NH mesoscale model, coupled to ISBA-A-gs land surface model. The main result of this paper is to show how aircraft observations of CO2 concentration have been used to identify surface model errors and to calibrate the CO2 driving component of the surface model. In fact, the comparisons between modelled and observed CO2 concentrations within the Atmospheric Boundary Layer (ABL) allow to calibrate and correct not only the parameterization of respired CO2 fluxes by the ecosystem but also the Leaf Area Index (LAI) of the dominating land cover. After this calibration, the paper describes systematic comparisons of the model outputs with numerous data collected during the CERES campaign, in April 2007. For instance, the originality of this paper is the spatial integration of the comparisons. In fact, the aircraft observations of CO2 concentration and fluxes and energy fluxes are used for the model validation from the local to the regional scale. As a conclusion, the CO2 budgeting approach from the mesoscale model shows that the winter croplands are assimilating more CO2 than the pine forest, at this stage of the year and this case study.

This paper describes a numerical interpretation of the April 2007, CarboEurope Regional Experiment Strategy (CERES) campaign, devoted to the study of the CO2 cycle at the regional scale. Four consecutive clear sky days with intensive observations of CO2 concentration, fluxes at the surface and in the boundary layer have been simulated with the Meso-NH mesoscale model, coupled to ISBA-A-gs land surface model. The main result of this paper is to show how aircraft observations of CO2 concentration have been used to identify surface model errors and to calibrate the CO2 driving component of the surface model. In fact, the comparisons between modelled and observed CO2 concentrations within the Atmospheric Boundary Layer (ABL) allow to calibrate and correct not only the parameterization of respired CO2 fluxes by the ecosystem but also the Leaf Area Index (LAI) of the dominating land cover. After this calibration, the paper describes systematic comparisons of the model outputs with numerous data collected during the CERES campaign, in April 2007. For instance, the originality of this paper is the spatial integration of the comparisons. In fact, the aircraft observations of CO2 concentration and fluxes and energy fluxes are used for the model validation from the local This paper describes a numerical interpretation of the April 2007, CarboEurope Regional Experiment Strategy (CERES) campaign, devoted to the study of the CO2 cycle at the regional scale. Four consecutive clear sky days with intensive observations of CO2 concentration, fluxes at the surface and in the boundary layer have been simulated with the Meso-NH mesoscale model, coupled to ISBA-A-gs land surface model. The main result of this paper is to show how aircraft observations of CO2 concentration have been used to identify surface model errors and to calibrate the CO2 driving component of the surface model. In fact, the comparisons between modelled and observed CO2 concentrations within the Atmospheric Boundary Layer (ABL) allow to calibrate and correct not only the parameterization of respired CO2 fluxes by the ecosystem but also the Leaf Area Index (LAI) of the dominating land cover. After this calibration, the paper describes systematic comparisons of the model outputs with numerous data collected during the CERES campaign, in April 2007. For instance, the originality of this paper is the spatial integration of the comparisons. In fact, the aircraft observations of CO2 concentration and fluxes and energy fluxes are used for the model validation from the local This paper describes a numerical interpretation of the April 2007, CarboEurope Regional Experiment Strategy (CERES) campaign, devoted to the study of the CO2 cycle at the regional scale. Four consecutive clear sky days with intensive observations of CO2 concentration, fluxes at the surface and in the boundary layer have been simulated with the Meso-NH mesoscale model, coupled to ISBA-A-gs land surface model. The main result of this paper is to show how aircraft observations of CO2 concentration have been used to identify surface model errors and to calibrate the CO2 driving component of the surface model. In fact, the comparisons between modelled and observed CO2 concentrations within the Atmospheric Boundary Layer (ABL) allow to calibrate and correct not only the parameterization of respired CO2 fluxes by the ecosystem but also the Leaf Area Index (LAI) of the dominating land cover. After this calibration, the paper describes systematic comparisons of the model outputs with numerous data collected during the CERES campaign, in April 2007. For instance, the originality of this paper is the spatial integration of the comparisons. In fact, the aircraft observations of CO2 concentration and fluxes and energy fluxes are used for the model validation from the local to the regional scale. As a conclusion, the CO2 budgeting approach from the mesoscale model shows that the winter croplands are assimilating more CO2 than the pine forest, at this stage of the year and this case study.

We present top-down emission constraints for two non-CO2 greenhouse gases in large areas of the U. S. and southern Canada during early summer. Collocated airborne measurements of methane and nitrous oxide acquired during the COBRA-NA campaign in May-June 2003, analyzed using a receptor-oriented Lagrangian particle dispersion model, provide robust validation of independent bottom-up emission estimates from the EDGAR and GEIA inventories. We find that the EDGAR CH4 emission rates are slightly low by a factor of 1.08 +/- 0.15 (2 sigma), while both EDGAR and GEIA N2O emissions are significantly too low, by factors of 2.62 +/- 0.50 and 3.05 +/- 0.61, respectively, for this region. Potential footprint bias may expand the statistically retrieved uncertainties. Seasonality of agricultural N2O emissions may help explain the discrepancy. Total anthropogenic U.S. and Canadian emissions would be 49 Tg CH4 and 4.3 Tg N2O annually, if these inventory scaling factors applied to all of North America. [References: 21]

[1] We present the Vegetation Photosynthesis and Respiration Model (VPRM), a satellite-based assimilation scheme that estimates hourly values of Net Ecosystem Exchange (NEE) of CO2 for 12 North American biomes using the Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI), derived from reflectance data of the Moderate Resolution Imaging Spectroradiometer (MODIS), plus high-resolution data for sunlight and air temperature. The motivation is to provide reliable, fine-grained first-guess fields of surface CO2 fluxes for application in inverse models at continental and smaller scales. An extremely simple mathematical structure, with minimal numbers of parameters, facilitates optimization using in situ data, with finesse provided by maximal infusion of observed NEE and environmental data from networks of eddy covariance towers across North America (AmeriFlux and Fluxnet Canada). Cross validation showed that the VPRM has strong prediction ability for hourly to monthly timescales for sites with similar vegetation. The VPRM also provides consistent partitioning of NEE into Gross Ecosystem Exchange (GEE, the light-dependent part of NEE) and ecosystem respiration (R, the light-independent part), half-saturation irradiance of ecosystem photosynthesis, and annual sum of NEE at all eddy flux sites for which it is optimized. The capability to provide reliable patterns of surface flux for fine-scale inversions is presently limited by the number of vegetation classes for which NEE can be constrained by the current network of eddy flux sites and by the accuracy of MODIS data and data for sunlight.

A framework has been developed that allows validating CO2 column averaged volume mixing ratios (VMRs) retrieved from ground-based solar absorption measurements using Fourier transform infrared spectrometry (FTS) against measurements made in-situ (such as from aircrafts and tall towers). Since in-situ measurements are done frequently and at high accuracy on the global calibration scale, linking this scale with FTS total column retrievals ultimately provides a calibration scale for remote sensing. FTS, tower and aircraft data were analyzed from measurements during the CarboEurope Regional Experiment Strategy (CERES) from May to June 2005 in Biscarrosse, France. Carbon dioxide VMRs from the MetAir Dimona aircraft, the TM3 global transport model and Observations of the Middle Stratosphere (OMS) balloon based experiments were combined and integrated to compare with the FTS measurements. The comparison allows for calibrating the retrieved carbon dioxide VMRs from the FTS. The Stochastic Time Inverted Lagrangian Transport (STILT) model was then utilized to identify differences in surface influence regions or footprints between the FTS and the aircraft CO2 concentrations. Additionally, the STILT model was used to compare carbon dioxide concentrations from a tall tower situated in close proximity to the FTS station. The STILT model was then modified to produce column concentrations of CO2 to facilitate comparison with the FTS data. These comparisons were additionally verified by using the Weather Research and Forecasting – Vegetation Photosynthesis and Respiration Model (WRF-VPRM). The differences between the model-tower and the model-FTS were then used to calculate an effective bias of approximately −2.5 ppm between the FTS and the tower. This bias is attributed to the scaling factor used in the FTS CO2 data, which was to a large extent derived from the aircraft measurements made within a 50 km distance from the FTS station: spatial heterogeneity of carbon dioxide in the coastal area caused a low bias in the FTS calibration. Using STILT for comparing remotely sensed CO2 data with tower measurements of carbon dioxide and quantifying this comparison by means of an effective bias, provided a framework or a "transfer standard" that allowed validating the FTS retrievals versus measurements made in-situ.

Imperfect 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 mixing heights and mixing 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 mixing 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 flux inversions employing transport models based on current generation meteorological products have misrepresented an important part of the model error structure likely leading to biases in the estimated mean and uncertainties. We strongly recommend including the solution presented in this work: better, higher resolution atmospheric models, a proper description of correlated random errors, and a modification of the overall sampling strategy.

The concentrations of CO2 and CH4 in the atmosphere are at the highest level they have been in the past 650,000 years. "The Continental-Scale Greenhouse Gas Balance of Europe", edited by A. Johannes Dolman, Annette Freibauer and Riccardo Valentini, highlights current results of research into the European greenhouse gases budget, including human-induced and biospheric sources and sinks. Much of this work is executed through the CarboEurope project, one of the world’s foremost research programs on continental-scale carbon cycle research.

The CarboEurope Regional Experiment Strategy (CERES) experiment took place in May and June 2005 in France and offers a comprehensive database on atmospheric CO2 and boundary layer processes at the regional scale. One "golden" day of CERES is interpreted with the mesoscale atmospheric model Meso-NH coupled on-line 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. The rapid diurnal cycle of carbon coupled with water and energy fluxes is parameterized including, e.g., plant assimilation, respiration, anthropogenic emissions, and sea fluxes. During the analyzed day, frequent vertical profiles and aircraft transects revealed high spatial and temporal variabilities of CO2 concentrations within the boundary layer at the regional scale: a 10-ppm gradient of CO2-mixing ratio is observed during the day by the aircraft measurements. The Meso-NH model proved able to simulate very well the CO2 concentration variability as well as the spatial and temporal evolution of the surface fluxes and the boundary layer in the domain. The model is used to explain the CO2 variability as a result of two complementary processes: (1) the regional heterogeneity of CO2 surface fluxes related to the land cover (e.g., winter crops versus a pine forest) and (2) the variability of mesoscale circulation across the boundary layer: development of the sea breeze in the western part of the domain and dominating wind flow in the eastern part of the domain. Copyright 2007 by the American Geologiclal Union.

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. Copyright 2007 by the American Geophysical Union.