This paper documents a global Bayesian variational inversion of CO₂ surface fluxes during the period 1988–2008. Weekly fluxes are estimated on a 3.75° × 2.5° (longitude-latitude) grid throughout the 21 years. The assimilated observations include 128 station records from three large data sets of surface CO₂ mixing ratio measurements. A Monte Carlo approach rigorously quantifies the theoretical uncertainty of the inverted fluxes at various space and time scales, which is particularly important for proper interpretation of the inverted fluxes. Fluxes are evaluated indirectly against two independent CO₂ vertical profile data sets constructed from aircraft measurements in the boundary layer and in the free troposphere. The skill of the inversion is evaluated by the improvement brought over a simple benchmark flux estimation based on the observed atmospheric growth rate. Our error analysis indicates that the carbon budget from the inversion should be more accurate than the a priori carbon budget by 20% to 60% for terrestrial fluxes aggregated at the scale of subcontinental regions in the Northern Hemisphere and over a year, but the inversion cannot clearly distinguish between the regional carbon budgets within a continent. On the basis of the independent observations, the inversion is seen to improve the fluxes compared to the benchmark: the atmospheric simulation of CO₂ with the Bayesian inversion method is better by about 1 ppm than the benchmark in the free troposphere, despite possible systematic transport errors. The inversion achieves this improvement by changing the regional fluxes over land at the seasonal and at the interannual time scales.

We use eddy covariance measurements of net ecosystem productivity (NEP) from 21 FLUXNET sites (153 site-years of data) to investigate relationships between phenology and productivity (in terms of both NEP and gross ecosystem photosynthesis, GEP) in temperate and boreal forests. Results are used to evaluate the plausibility of four different conceptual models. Phenological indicators were derived from the eddy covariance time series, and from remote sensing and models. We examine spatial patterns (across sites) and temporal patterns (across years); an important conclusion is that it is likely that neither of these accurately represents how productivity will respond to future phenological shifts resulting from ongoing climate change. In spring and autumn, increased GEP resulting from an ‘extra’ day tends to be offset by concurrent, but smaller, increases in ecosystem respiration, and thus the effect on NEP is still positive. Spring productivity anomalies appear to have carry-over effects that translate to productivity anomalies in the following autumn, but it is not clear that these result directly from phenological anomalies. Finally, the productivity of evergreen needleleaf forests is less sensitive to phenology than is productivity of deciduous broadleaf forests. This has implications for how climate change may drive shifts in competition within mixed-species stands.

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. These calibrations are compared with similar observations made in 2004 and 2006. The results indicate that a single, global calibration factor for each gas accurately captures the TCCON total column data within error.

Although China has surpassed the United States as the world's largest carbon dioxide emitter, in situ measurements of atmospheric CO₂ have been sparse in China. This paper analyzes hourly CO₂ and its correlation with CO at Miyun, a rural site near Beijing, over a period of 51 months (Dec 2004 through Feb 2009). The CO₂-CO correlation analysis evaluated separately for each hour of the day provides useful information with statistical significance even in the growing season. We found that the intercept, representing the initial condition imposed by global distribution of CO₂ with influence of photosynthesis and respiration, exhibits diurnal cycles differing by season. The background CO₂ (CO_2,b) derived from Miyun observations is comparable to CO₂ observed at a Mongolian background station to the northwest. Annual growth of overall mean CO₂ at Miyun is estimated at 2.7 ppm yr⁻¹ while that of CO_2,b is only 1.7 ppm yr⁻¹ similar to the mean growth rate at northern mid-latitude background stations. This suggests a relatively faster increase in the regional CO₂ sources in China than the global average, consistent with bottom-up studies of CO₂ emissions. For air masses with trajectories through the northern China boundary layer, mean winter CO₂/CO correlation slopes (dCO₂/dCO) increased by 2.8 ± 0.9 ppmv/ppmv or 11% from 2005–2006 to 2007–2008, with CO₂ increasing by 1.8 ppmv. The increase in dCO₂/dCO indicates improvement in overall combustion efficiency over northern China after winter 2007, attributed to pollution reduction measures associated with the 2008 Beijing Olympics. The observed CO₂/CO ratio at Miyun is 25% higher than the bottom-up CO₂/CO emission ratio, suggesting a contribution of respired CO₂ from urban residents as well as agricultural soils and livestock in the observations and uncertainty in the emission estimates.

Refractory black carbon (rBC) aerosol loadings and mass size distributions have been quantified during the HIPPO campaign above the remote Pacific from 80N to 67S. Over 100 vertical profiles of rBC loadings, extending from ∼0.3 to ∼14 km were obtained with a Single‐ Particle Soot Photometer (SP2) during a two‐week period in January 2009. The dataset provides a striking, and previously unobtainable, pole‐to‐pole snapshot of rBC mass loadings. rBC vertical concentration profiles reveal significant dependences on latitude, while associated rBC mass size distributions were highly uniform. The vertical profiles averaged in five latitude zones were compared to an ensemble of AEROCOM model fields. The model ensemble spread in each zone was over an order of magnitude, while the model average over‐predicted rBC concentrations overall by a factor five. The comparisons suggest that rBC removal in global models may need to be evaluated separately in different latitude regions and perhaps enhanced.

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 with observations, while nitrous oxide emissions are significantly low, by a factor 2.5–3 in the peak emissions time period found to be February through May.

Rates for large-scale vertical transport of air in the Tropical Tropopause Layer (TTL) were determined using high-resolution, in situ observations of CO₂ concentrations in the tropical upper troposphere and lower stratosphere during the NASA Tropical Composition, Cloud and Climate Coupling (TC4) campaign in August 2007. Upward movement of trace gases in the deep tropics was notably slower in TC4 than during the Costa Rica AURA Validation Experiment (CR-AVE), in January 2006. Transport rates in the TTL were combined with in situ measurements of chlorinated and brominated organic compounds from whole air samples to determine chemical loss rates for reactive chemical species, providing empirical vertical profiles for 24-h mean concentrations of hydroxyl radicals (OH) and chlorine atoms in the TTL. The analysis shows that important short-lived species such as CHCl₃, CH₂Cl₂, and CH₂Br₂ have longer chemical lifetimes than the time for transit of the TTL, implying that these species, which are not included in most models, could readily reach the stratosphere and make significant contributions of chlorine and/or bromine to stratospheric loading.

An automated Fourier Transform Spectroscopic (FTS) solar observatory was established in Darwin, Australia in August 2005. The laboratory is part of the Total Carbon Column Observing Network, and measures atmospheric column abundances of CO₂ and O₂ and other gases. Measured CO₂ columns were calibrated against integrated aircraft profiles obtained during the TWP-ICE campaign in January–February 2006, and show good agreement with calibrations for a similar instrument in Park Falls, Wisconsin. A clear-sky low airmass relative precision of 0.1% is demonstrated in the CO₂ and O₂ retrieved column-averaged volume mixing ratios. The 1% negative bias in the FTS X_CO2 relative to the World Meteorological Organization (WMO) calibrated in situ scale is within the uncertainties of the NIR spectroscopy and analysis.

The Tropical Composition, Cloud and Climate Coupling Experiment (TC4), was based in Costa Rica and Panama during July and August 2007. The NASA ER-2, DC-8, and WB-57F aircraft flew 26 science flights during TC4. The ER-2 employed 11 instruments as a remote sampling platform and satellite surrogate. The WB-57F used 25 instruments for in situ chemical and microphysical sampling in the tropical tropopause layer (TTL). The DC-8 used 25 instruments to sample boundary layer properties, as well as the radiation, chemistry, and microphysics of the TTL. TC4 also had numerous sonde launches, two ground-based radars, and a ground-based chemical and microphysical sampling site. The major goal of TC4 was to better understand the role that the TTL plays in the Earth's climate and atmospheric chemistry by combining in situ and remotely sensed data from the ground, balloons, and aircraft with data from NASA satellites. Significant progress was made in understanding the microphysical and radiative properties of anvils and thin cirrus. Numerous measurements were made of the humidity and chemistry of the tropical atmosphere from the boundary layer to the lower stratosphere. Insight was also gained into convective transport between the ground and the TTL, and into transport mechanisms across the TTL. New methods were refined and extended to all the NASA aircraft for real-time location relative to meteorological features. The ability to change flight patterns in response to aircraft observations relayed to the ground allowed the three aircraft to target phenomena of interest in an efficient, well-coordinated manner.

From 2000 until January 2010 vertical profiles were collected above eastern Amazonia to help determine regional-scale (∼10⁵–10⁶ km²) fluxes of carbon cycle-related greenhouse gases. Samples were collected aboard light aircraft between the surface and 4.3 km and a column integration technique was used to determine the CO₂ flux. Measured CO₂ profiles were differenced from the CO₂ background determined from measurements in the tropical Atlantic. The observed annual flux between the coast and measurement sites was 0.40 ± 0.27 gC m⁻² d⁻¹ (90% confidence interval using a bootstrap analysis). The wet season (January–June) mean flux was 0.44 ± 0.38 gC m⁻² d⁻¹ (positive fluxes defined as a source to the atmosphere) and the dry season mean flux was 0.35 ± 0.17 gC m⁻² d⁻¹ (July–December). The observed flux variability is high, principally in the wet season. The influence of biomass burning has been removed using co-measured CO, and revealed the presence of a significant dry season sink. The annual mean vegetation flux, after the biomass burning correction, was 0.02 ± 0.27 gC m⁻² d⁻¹, and a clear sink was observed between August and November of −0.70 ± 0.21 gC m⁻² d⁻¹ where for all of the dry season it was −0.24 ± 0.17 gC m⁻² d⁻¹.

Soil carbon dioxide efflux (soil respiration, SR) was measured with eight autochambers at two locations along a wetland to upland slope at Harvard Forest over a 4 year period, 2003–2007. SR was consistently higher in the upland plots than at the wetland margin during the late summer/early fall. Seasonal and diel hystereses with respect to soil temperatures were of sufficient magnitude to prevent quantification of the influence of soil moisture, although apparent short-term responses of SR to precipitation occurred. Calculations of annual cumulative SR illustrated a decreasing trend in SR over the 5 year period, which were correlated with decreasing springtime mean soil temperatures. Spring soil temperatures decreased despite rising air temperatures over the same period, possibly as an effect of earlier leaf expansion and shading. The synchronous decrease in spring soil temperatures and SR during regional warming of air temperatures may represent a negative feedback on a warming climate by reducing CO₂ production from soils. SR reached a maximum later in the year than total ecosystem respiration (ER) measured at a nearby eddy covariance flux tower, and the seasonality of their temperature response patterns were roughly opposite. SR, particularly in the upland, exceeded ER in the late summer/early fall in each year, suggesting that areas of lower efflux such as the wetland may be significant in the flux tower footprint or that long-term bias in either estimate may create a mismatch. Annual estimates of ER decreased over the same period and were highly correlated with SR.

We examine seasonal variations of carbon monoxide (CO), ozone (O3), and their relationships observed over the course of 3 yr (2005–2007) at Miyun, a rural site 100 km north of Beijing. Monthly mean afternoon mixing ratios of CO have broad maxima in winter and a secondary peak in June. Monthly mean afternoon O3 shows a clear seasonal pattern with a major peak in June (85 ppb), a secondary peak in September (65 ppb) and minimum in winter (50–55 ppb). The seasonal cycles of O3 and CO are associated with seasonal changes in dominant synoptic pattern. Substantial interannual variability is found for CO which is attributed to the interannual variability of meteorology and emissions from biomass burning. The seasonality and magnitude of background CO and O3 derived at Miyun are consistent with observations at upwind remote continental sites. The O3–CO correlation slope is about 0.07 ppb ppb−1 on average in summer, significantly lower than the typical slope of 0.3 ppb ppb−1 reported for developed countries. The O3–CO correlation slope shows large gradients for different types of air masses (0.133 ± 0.017 ppb ppb−1 in aged urban pollution plumes and 0.047 ± 0.008 ppb ppb−1 in biomass burning plumes), suggesting that the conventional method of direct scaling the mean O3–CO slope by CO emissions to deduce O3 production rate is subject to large uncertainties if applied for China.

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.

We assess the significance of high-frequency variability of environmental parameters (sunlight, precipitation, temperature) for the structure and function of terrestrial ecosystems under current and future climate. We examine the influence of hourly, daily, and monthly variance using the Ecosystem Demography model version 2 in conjunction with the long-term record of carbon fluxes measured at Harvard Forest. We find that fluctuations of sunlight and precipitation are strongly and nonlinearly coupled to ecosystem function, with effects that accumulate through annual and decadal timescales. Increasing variability in sunlight and precipitation leads to lower rates of carbon sequestration and favors broad-leaved deciduous trees over conifers. Temperature variability has only minor impacts by comparison. We also find that projected changes in sunlight and precipitation variability have important implications for carbon storage and ecosystem structure and composition. Based on Intergovernmental Panel on Climate Change model estimates for changes in high-frequency meteorological variability over the next 100 years, we expect that terrestrial ecosystems will be affected by changes in variability almost as much as by changes in mean climate. We conclude that terrestrial ecosystems are highly sensitive to high-frequency meteorological variability, and that accurate knowledge of the statistics of this variability is essential for realistic predictions of ecosystem structure and functioning.

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.

Gross primary production (GPP) defined as the overall rate of fixation of carbon through the process of vegetation photosynthesis is important for carbon cycle and climate change research. Three models, the Vegetation Photosynthesis Model (VPM), the Temperature and Greenness (TG) model and the Vegetation Index (VI) model have been compared for the estimation of GPP in Harvard Forest from 2003 to 2006 using climate variables acquired by eddy covariance (EC) measurements and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images. All these models provide more reliable estimates of GPP than that of MODIS GPP product. High Pearsons correlation coefficients r equal to 0.94, 0.92 and 0.90 are observed for the VPM, the TG and the VI model, respectively. Relationships between GPP and land surface temperature (LST, R²=0.72), and vapor pressure deficit (VPD, R²=0.45) indicate that climate variables are important for GPP estimation. Due to proper characterization of temperature, water stress and leaf age by three scalars, VPM best follows the seasonal variations of GPP. By incorporation of the MODIS surface reflectance and LST product, the TG model is the most suitable choice for areas without prior knowledge as it is based entirely on remote sensing observations. Results from the VI model demonstrate the possibility of using a single vegetation index for light use efficiency (LUE) estimation in deciduous forest that is of high spatial heterogeneity. The validation and comparison of models will be helpful in development of future GPP models using combinations of climate variables and/or remote sensing observations.

The quantification of carbon fluxes between the terrestrial biosphere and the atmosphere is of scientific importance and also relevant to climate-policy making. Eddy covariance flux towers provide continuous measurements of ecosystem-level exchange of carbon dioxide spanning diurnal, synoptic, seasonal, and interannual time scales. However, these measurements only represent the fluxes at the scale of the tower footprint. Here we used remotely sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to upscale gross primary productivity (GPP) data from eddy covariance flux towers to the continental scale. We first combined GPP and MODIS data for 42 AmeriFlux towers encompassing a wide range of ecosystem and climate types to develop a predictive GPP model using a regression tree approach. The predictive model was trained using observed GPP over the period 2000–2004, and was validated using observed GPP over the period 2005–2006 and leave-one-out cross-validation. Our model predicted GPP fairly well at the site level. We then used the model to estimate GPP for each 1 km × 1 km cell across the U.S. for each 8-day interval over the period from February 2000 to December 2006 using MODIS data. Our GPP estimates provide a spatially and temporally continuous measure of gross primary production for the U.S. that is a highly constrained by eddy covariance flux data. Our study demonstrated that our empirical approach is effective for upscaling eddy flux GPP data to the continental scale and producing continuous GPP estimates across multiple biomes. With these estimates, we then examined the patterns, magnitude, and interannual variability of GPP. We estimated a gross carbon uptake between 6.91 and 7.33 Pg C yr^− 1 for the conterminous U.S. Drought, fires, and hurricanes reduced annual GPP at regional scales and could have a significant impact on the U.S. net ecosystem carbon exchange. The sources of the interannual variability of U.S. GPP were dominated by these extreme climate events and disturbances.

The Stratosphere–Troposphere Analyses of Regional Transport 2008 (START08) experiment investigated a number of important processes in the extratropical upper troposphere and lower stratosphere (UTLS) using the National Science Foundation (NSF)–NCAR Gulfstream V (GV) research aircraft. The main objective was to examine the chemical structure of the extratropical UTLS in relation to dynamical processes spanning a range of scales. The campaign was conducted during April–June 2008 from Broomfield, Colorado. A total of 18 research flights sampled an extensive geographical region of North America (25°–65°N, 80°–120°W) and a wide range of meteorological conditions. The airborne in situ instruments measured a comprehensive suite of chemical constituents and microphysical variables from the boundary layer to the lower stratosphere, with flights specifically designed to target key transport processes in the extratropical UTLS. The flights successfully investigated stratosphere–troposphere exchange (STE) processes, including the intrusion of tropospheric air into the stratosphere in association with the secondary tropopause and the intrusion of stratospheric air deep into the troposphere. The flights also sampled the influence of convective transport and lightning on the upper troposphere as well as the distribution of gravity waves associated with multiple sources, including fronts and topography. The aircraft observations are complemented by satellite observations and modeling. The measurements will be used to improve the representation of UTLS chemical gradients and transport in Chemistry–Climate models (CCMs). This article provides an overview of the experiment design and selected observational highlights.