Thermal infrared radiances from the Tropospheric Emission Spectrometer (TES) between 10 and 15 μm contain significant carbon dioxide (CO₂) information, however the CO₂ signal must be separated from radiative interference from temperature, surface and cloud parameters, water, and other trace gases. Validation requires data sources spanning the range of TES CO₂ sensitivity, which is approximately 2.5 to 12 km with peak sensitivity at about 5 km and the range of TES observations in latitude (40° S to 40° N) and time (2005–2011). We therefore characterize Tropospheric Emission Spectrometer (TES) CO₂ version 5 biases and errors through comparisons to ocean and land-based aircraft profiles and to the CarbonTracker assimilation system. We compare to ocean profiles from the first three Hiaper Pole-to-Pole Observations (HIPPO) campaigns between 40° S and 40° N with measurements between the surface and 14 km and find that TES CO₂ estimates capture the seasonal and latitudinal gradients observed by HIPPO CO₂ measurements. Actual errors range from 0.8–1.8 ppm, depending on the campaign and pressure level, and are approximately 1.6–2 times larger than the predicted errors. The bias of TES versus HIPPO is within 1 ppm for all pressures and datasets; however, several of the sub-tropical TES CO₂ estimates are lower than expected based on the calculated errors. Comparisons to land aircraft profiles from the United States Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) between 2005 and 2011 measured from the surface to 5 km to TES CO₂ show good agreement with an overall bias of −0.3 ppm to 0.1 ppm and standard deviations of 0.8 to 1.0 ppm at different pressure levels. Extending the SGP aircraft profiles above 5 km using AIRS or CONTRAIL measurements improves comparisons with TES. Comparisons to CarbonTracker (version CT2011) show a persistent spatially dependent bias pattern and comparisons to SGP show a time-dependent bias of −0.2 ppm yr⁻¹. We also find that the predicted sensitivity of the TES CO₂ estimates is too high, which results from using a multi-step retrieval for CO₂ and temperature. We find that the averaging kernel in the TES product corrected by a pressure-dependent factor accurately reflects the sensitivity of the TES CO₂ product.

Validation results are reported for the MOPITT (Measurements of Pollution in the Troposphere) “Version 5” (V5) product for tropospheric carbon monoxide (CO) and are compared to results for the “Version 4” product. The V5 retrieval algorithm introduces (1) a method for reducing retrieval bias drift associated with long-term instrumental degradation, (2) a more exact representation of the effects of random errors in the radiances and, for the first time, (3) the use of MOPITT's near-infrared (NIR) radiances to complement the thermal-infrared (TIR) radiances. Exploiting TIR and NIR radiances together facilitates retrievals of CO in the lowermost troposphere. V5 retrieval products based (1) solely on TIR measurements, (2) solely on NIR measurements and (3) on both TIR and NIR measurements are separately validated and analyzed. Actual retrieved CO profiles and total columns are compared with equivalent retrievals based on in situ measurements from (1) routine NOAA aircraft sampling mainly over North America and (2) the “HIAPER Pole to Pole Observations” (HIPPO) field campaign. Particular attention is focused on the long-term stability and geographical uniformity of the retrieval errors. Results for the retrieved total column clearly indicate reduced temporal bias drift in the V5 products compared to the V4 product, and do not exhibit a positive bias in the Southern Hemisphere, which is evident in the V4 product.

A recent National Research Council report highlighted the potential utility of atmospheric observations and models for detecting trends in concentrated emissions from localized regions, such as urban areas. The Salt Lake City (SLC), Utah, area was chosen for a pilot study to determine the feasibility of using ground-based sensors to identify trends in anthropogenic urban emissions over a range of time scales (from days to years). The Weather Research and Forecasting model (WRF) was combined with a Lagrangian particle dispersion model and an emission inventory to model carbon dioxide (CO₂) concentrations that can be compared with in situ measurements. An accurate representation of atmospheric transport requires a faithful modeling of the meteorological conditions. This study examines in detail the ability of different configurations of WRF to reproduce the observed local and mesoscale circulations, and the diurnal evolution of the planetary boundary layer (PBL) in the SLC area. Observations from the Vertical Transport and Mixing field experiment in 2000 were used to examine the sensitivity of WRF results to changes in the PBL parameterization and to the inclusion of an urban canopy model (UCM). Results show that for urban locations there is a clear benefit from parameterizing the urban canopy for simulation of the PBL and near-surface conditions, particularly for temperature evolution at night. Simulation of near-surface CO₂ concentrations for a 2-week period in October 2006 showed that running WRF at high resolution (1.33 km) and with a UCM also improves the simulation of observed increases in CO₂during the early evening.

Nitrous oxide (N₂O) is an important gas for climate and for stratospheric chemistry, with a lifetime exceeding 100 years. Global concentrations have increased steadily since the 18th century, apparently due to human-associated emissions, principally from the application of nitrogen fertilizers. However, quantitative studies of agricultural emissions at large spatial scales are lacking, inhibited by the difficulty of measuring small enhancements in atmospheric concentration. Here we derive regional emission rates for N₂O in the agricultural heartland of California based on analysis of in-situ airborne atmospheric observations collected using a new quantum cascade laser spectrometer. The data were obtained on board the NOAA WP-3 research aircraft during the CalNex (California Research at the Nexus of Air Quality and Climate Change) program in late spring 2010. We coupled the WRF (weather research and forecasting) model, a meso-scale meteorology model, with the STILT (stochastic time-inverted Lagrangian transport) model, a Lagrangian particle dispersion model, to link our in-situ airborne observations to surface emissions. We then used a variety of statistical methods to identify source areas and to optimize emission rates. Our results are consistent with the view that fertilizer application is the largest source of N₂O in the Central Valley. The spatial distribution of surface emissions, based on California land use and activity maps, was very different than indicated in the leading emission inventory (EDGAR 4.0). Our estimated total emission flux of N₂O for California in May and June was 3 – 4 times larger than the annual mean given for the state by EDGAR and other inventories, indicating a strong seasonal variation. We estimated the statewide total annual emissions of N₂O to be 0.042 ± 0.011 Tg N/year, roughly equivalent to inventory values if we account for seasonal variations using observations obtained in the midwestern United States. This state total N₂O emission is 20.5 Tg CO₂ equivalent (100 year global warming potential = 310 CO₂ eq/g N₂O), accounting for approximately 4% of the state total greenhouse gas emissions.

Monitoring the global distribution and long-term variations of CO₂ sources and sinks is required for characterizing the global carbon budget. Total column measurements are useful for estimating regional-scale fluxes; however, model transport remains a significant error source, particularly for quantifying local sources and sinks. To improve the capability of estimating regional fluxes, we estimate lower tropospheric CO₂ concentrations from ground-based near-infrared (NIR) measurements with space-based thermal infrared (TIR) measurements. The NIR measurements are obtained from the Total Carbon Column Observing Network (TCCON) of solar measurements, which provide an estimate of the total CO₂ column amount. Estimates of tropospheric CO₂ that are co-located with TCCON are obtained by assimilating Tropospheric Emission Spectrometer (TES) free tropospheric CO₂ estimates into the GEOS-Chem model. We find that quantifying lower tropospheric CO₂ by subtracting free tropospheric CO₂ estimates from total column estimates is a linear problem, because the calculated random uncertainties in total column and lower tropospheric estimates are consistent with actual uncertainties as compared to aircraft data. For the total column estimates, the random uncertainty is about 0.55 ppm with a bias of −5.66 ppm, consistent with previously published results. After accounting for the total column bias, the bias in the lower tropospheric CO₂ estimates is 0.26 ppm with a precision (one standard deviation) of 1.02 ppm. This precision is sufficient for capturing the winter to summer variability of approximately 12 ppm in the lower troposphere; double the variability of the total column. This work shows that a combination of NIR and TIR measurements can profile CO₂ with the precision and accuracy needed to quantify lower tropospheric CO₂ variability.

Large areas of Amazonian evergreen forest experience seasonal droughts extending for three or more months, yet show maximum rates of photosynthesis and evapotranspiration during dry intervals. This apparent resilience is belied by disproportionate mortality of the large trees in manipulations that reduce wet season rainfall, occurring after 2–3 years of treatment. The goal of this study is to characterize the mechanisms that produce these contrasting ecosystem responses. A mechanistic model is developed based on the ecohydrological framework of TIN (Triangulated Irregular Network)-based Real Time Integrated Basin Simulator + Vegetation Generator for Interactive Evolution (tRIBS+VEGGIE). The model is used to test the roles of deep roots and soil capillary flux to provide water to the forest during the dry season. Also examined is the importance of “root niche separation,” in which roots of overstory trees extend to depth, where during the dry season they use water stored from wet season precipitation, while roots of understory trees are concentrated in shallow layers that access dry season precipitation directly. Observational data from the Tapajós National Forest, Brazil, were used as meteorological forcing and provided comprehensive observational constraints on the model. Results strongly suggest that deep roots with root niche separation adaptations explain both the observed resilience during seasonal drought and the vulnerability of canopy-dominant trees to extended deficits of wet season rainfall. These mechanisms appear to provide an adaptive strategy that enhances productivity of the largest trees in the face of their disproportionate heat loads and water demand in the dry season. A sensitivity analysis exploring how wet season rainfall affects the stability of the rainforest system is presented.

Accurately estimating biogenic methane (CH₄) and nitrous oxide (N₂O) fluxes in terrestrial ecosystems is critical for resolving global budgets of these greenhouse gases (GHGs) and continuing to mitigate climate warming. Here, we assess contemporary biogenic CH₄ and N₂O budgets and probable climate-change-related impacts on CH₄ and N₂O emissions in terrestrial North America. Multi-approach estimations show that, during 1990-2010, biogenic CH₄ emissions ranged from 0.159 to 0.502 petagrams of carbon dioxide (CO₂) equivalents per year (Pg CO₂eq yr⁻¹, where 1 Pg = 1 × 10¹⁵ g) and N₂O emissions ranged from 0.802 to 1.016 Pg CO₂ eq yr⁻¹, which offset 47-166% of terrestrial CO₂ sequestration (0.915-2.040 Pg CO₂ eq yr⁻¹, as indicated elsewhere in this Special Issue). According to two future climate scenarios, CH₄ and N₂O emissions are projected to continue increasing by 137-151% and 157-227%, respectively, by the end of this century, as compared with levels during 2000-2010. Strategies to mitigate climate change must account for non-CO₂ GHG emissions, given their substantial warming potentials.

Airborne measurements of methane (CH4) and carbon dioxide (CO2) were taken over the rice growing region of California's Sacramento Valley in the late spring of 2010 and 2011. From these and ancillary measurements, we show that CH4 mixing ratios were higher in the planetary boundary layer above the Sacramento Valley during the rice growing season than they were before it, which we attribute to emissions from rice paddies. We derive daytime emission fluxes of CH4 between 0.6 and 2.0% of the CO2 taken up by photosynthesis on a per carbon, or mole to mole, basis. We also use a mixing model to determine an average CH 4/CO2 flux ratio of -0.6% for one day early in the growing season of 2010. We conclude the CH4/CO2 flux ratio estimates from a single rice field in a previous study are representative of rice fields in the Sacramento Valley. If generally true, the California Air Resources Board (CARB) greenhouse gas inventory emission rate of 2.7×10¹⁰g CH4/yr is approximately three times lower than the range of probable CH4 emissions (7.8-9.3×10 ¹⁰g CH4/yr) from rice cultivation derived in this study. We attribute this difference to decreased burning of the residual rice crop since 1991, which leads to an increase in CH4 emissions from rice paddies in succeeding years, but which is not accounted for in the CARB inventory. © 2012. American Geophysical Union. All Rights Reserved.

We describe a pragmatic approach for evaluating the spatial representativeness of flux tower measurements based on footprint climatology modeling analyses of land cover and remotely sensed vegetation indices. The approach was applied to the twelve flux sites of the Canadian Carbon Program (CCP) that include grassland, wetland, and temperate and boreal forests across an east–west continental gradient. The spatial variation within the footprint area was evaluated by examining the spatial structure of Normalized Difference Vegetation Index (NDVI) and land cover using geostatistical analyses of frequency distribution, variogram and window size. The results show that at most sites (i) the percentages of the target vegetation functional type (dominant land cover) observed by the CCP towers were higher than 60%; (ii) to some extent, most of the CCP sites presented anisotropically distributed patterns of NDVI in the 90% annual footprint climatology area; and (iii) the land surface heterogeneity within the flux footprint area differed among sites. Overall, the forest sites had larger fine-scale spatial variation than the grassland and wetland sites. The coniferous boreal forest sites had greater spatial variability than the two wetland sites and a coniferous temperate forest site. We conclude that the combination of footprint modeling, semivariogram and window size techniques, together with moderate spatial resolution remotely-sensed image data, is a pragmatic approach for assessing the spatial representativeness of flux tower measurements.

Tropical regions, especially the Amazon region, account for large emissions of methane (CH₄). Here, we present CH₄ observations from two airborne campaigns conducted within the BARCA (Balanço Atmosférico Regional de Carbono na Amazônia) 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 CH₄ 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 CH₄. Isotope analysis verified that the majority of emissions can be attributed to CH₄ emissions from wetlands, while urban CH₄ emissions could be also traced back to biogenic origin. A comparison of five TM5 based global CH₄ inversions with the observations clearly indicates that the inversions using SCIAMACHY observations represent the BARCA observations best. The calculated CH₄ flux estimate obtained from the mismatch between observations and TM5-modeled CH₄ fields ranges from 36 to 43 mg m⁻² d⁻¹ for the Amazon lowland region.

We use historical and new atmospheric trace gas observations to refine the estimated source of methane (CH(4)) emitted into California's South Coast Air Basin (the larger Los Angeles metropolitan region). Referenced to the California Air Resources Board (CARB) CO emissions inventory, total CH(4) emissions are 0.44 ± 0.15 Tg each year. To investigate the possible contribution of fossil fuel emissions, we use ambient air observations of methane (CH(4)), ethane (C(2)H(6)), and carbon monoxide (CO), together with measured C(2)H(6) to CH(4) enhancement ratios in the Los Angeles natural gas supply. The observed atmospheric C(2)H(6) to CH(4) ratio during the ARCTAS (2008) and CalNex (2010) aircraft campaigns is similar to the ratio of these gases in the natural gas supplied to the basin during both these campaigns. Thus, at the upper limit (assuming that the only major source of atmospheric C(2)H(6) is fugitive emissions from the natural gas infrastructure) these data are consistent with the attribution of most (0.39 ± 0.15 Tg yr(-1)) of the excess CH(4) in the basin to uncombusted losses from the natural gas system (approximately 2.5-6% of natural gas delivered to basin customers). However, there are other sources of C(2)H(6) in the region. In particular, emissions of C(2)H(6) (and CH(4)) from natural gas seeps as well as those associated with petroleum production, both of which are poorly known, will reduce the inferred contribution of the natural gas infrastructure to the total CH(4) emissions, potentially significantly. This study highlights both the value and challenges associated with the use of ethane as a tracer for fugitive emissions from the natural gas production and distribution system.

We present the results of airborne measurements of carbon monoxide (CO) and aerosol particle number concentration (CN) made during the Balanço Atmosférico Regional de Carbono na Amazônia (BARCA) program. The primary goal of BARCA is to address the question of basin-scale sources and sinks of CO₂ and other atmospheric carbon species, a central issue of the Large-scale Biosphere-Atmosphere (LBA) program. The experiment consisted of two aircraft campaigns during November–December 2008 (BARCA-A) and May–June 2009 (BARCA-B), which covered the altitude range from the surface up to about 4500 m, and spanned most of the Amazon Basin.

Based on meteorological analysis and measurements of the tracer, SF₆, we found that airmasses over the Amazon Basin during the late dry season (BARCA-A, November 2008) originated predominantly from the Southern Hemisphere, while during the late wet season (BARCA-B, May 2009) low-level airmasses were dominated by northern-hemispheric inflow and mid-tropospheric airmasses were of mixed origin. In BARCA-A we found strong influence of biomass burning emissions on the composition of the atmosphere over much of the Amazon Basin, with CO enhancements up to 300 ppb and CN concentrations approaching 10 000 cm⁻³; the highest values were in the southern part of the Basin at altitudes of 1–3 km. The ΔCN/ΔCO ratios were diagnostic for biomass burning emissions, and were lower in aged than in fresh smoke. Fresh emissions indicated CO/CO₂ and CN/CO emission ratios in good agreement with previous work, but our results also highlight the need to consider the residual smoldering combustion that takes place after the active flaming phase of deforestation fires.

During the late wet season, in contrast, there was little evidence for a significant presence of biomass smoke. Low CN concentrations (300–500 cm⁻³) prevailed basinwide, and CO mixing ratios were enhanced by only ~10 ppb above the mixing line between Northern and Southern Hemisphere air. There was no detectable trend in CO with distance from the coast, but there was a small enhancement of CO in the boundary layer suggesting diffuse biogenic sources from photochemical degradation of biogenic volatile organic compounds or direct biological emission.

Simulations of CO distributions during BARCA-A using a range of models yielded general agreement in spatial distribution and confirm the important contribution from biomass burning emissions, but the models evidence some systematic quantitative differences compared to observed CO concentrations. These mismatches appear to be related to problems with the accuracy of the global background fields, the role of vertical transport and biomass smoke injection height, the choice of model resolution, and reliability and temporal resolution of the emissions data base.

Accurately simulating gross primary productivity (GPP) in terrestrial ecosystem models is critical because errors in simulated GPP propagate through the model to introduce additional errors in simulated biomass and other fluxes. We evaluated simulated, daily average GPP from 26 models against estimated GPP at 39 eddy covariance flux tower sites across the United States and Canada. None of the models in this study match estimated GPP within observed uncertainty. On average, models overestimate GPP in winter, spring, and fall, and underestimate GPP in summer. Models overpredicted GPP under dry conditions and for temperatures below 0°C. Improvements in simulated soil moisture and ecosystem response to drought or humidity stress will improve simulated GPP under dry conditions. Adding a low-temperature response to shut down GPP for temperatures below 0°C will reduce the positive bias in winter, spring, and fall and improve simulated phenology. The negative bias in summer and poor overall performance resulted from mismatches between simulated and observed light use efficiency (LUE). Improving simulated GPP requires better leaf-to-canopy scaling and better values of model parameters that control the maximum potential GPP, such asε_max (LUE), V_cmax (unstressed Rubisco catalytic capacity) or J_max (the maximum electron transport rate).

International agreements to limit greenhouse gas emissions require verification to ensure that they are effective and fair. Verification based on direct observation of atmospheric greenhouse gas concentrations will be necessary to demonstrate that estimated emission reductions have been actualized in the atmosphere. Here we assess the capability of ground-based observations and a high-resolution (1.3 km) mesoscale atmospheric transport model to determine a change in greenhouse gas emissions over time from a metropolitan region. We test the method with observations from a network of CO₂ surface monitors in Salt Lake City. Many features of the CO₂ data were simulated with excellent fidelity, although data-model mismatches occurred on hourly timescales due to inadequate simulation of shallow circulations and the precise timing of boundary-layer stratification and destratification. Using two optimization procedures, monthly regional fluxes were constrained to sufficient precision to detect an increase or decrease in emissions of approximately 15% at the 95% confidence level. We argue that integrated column measurements of the urban dome of CO₂ from the ground and/or space are less sensitive than surface point measurements to the redistribution of emitted CO₂ by small-scale processes and thus may allow for more precise trend detection of emissions from urban regions.

We simulate nitrogen deposition over the US in 2006–2008 by using the GEOS-Chem global chemical transport model at 1/2°×2/3° horizontal resolution over North America and adjacent oceans. US emissions of NO_x and NH₃ in the model are 6.7 and 2.9 Tg N a⁻¹ respectively, including a 20% natural contribution for each. Ammonia emissions are a factor of 3 lower in winter than summer, providing a good match to US network observations of NH_x (≡NH₃ gas + ammonium aerosol) and ammonium wet deposition fluxes. Model comparisons to observed deposition fluxes and surface air concentrations of oxidized nitrogen species (NO_y) show overall good agreement but excessive wintertime HNO₃ production over the US Midwest and Northeast. This suggests a model overestimate N₂O₅ hydrolysis in aerosols, and a possible factor is inhibition by aerosol nitrate. Model results indicate a total nitrogen deposition flux of 6.5 Tg N a⁻¹ over the contiguous US, including 4.2 as NO_y and 2.3 as NH_x. Domestic anthropogenic, foreign anthropogenic, and natural sources contribute respectively 78%, 6%, and 16% of total nitrogen deposition over the contiguous US in the model. The domestic anthropogenic contribution generally exceeds 70% in the east and in populated areas of the west, and is typically 50–70% in remote areas of the west. Total nitrogen deposition in the model exceeds 10 kg N ha⁻¹ a⁻¹ over 35% of the contiguous US.

We have developed a mid-infrared continuous-wave quantum cascade laser direct-absorption spectrometer (QCLS) capable of high frequency (≥1 Hz) measurements of 12CH4 and 13CH4 isotopologues of methane (CH4) with in situ 1-s RMS ? precision of 1.5 ‰ and Allan-minimum precision of 0.2 ‰. We deployed this QCLS in a well-studied New Hampshire fen to compare measurements of CH4 isoflux by eddy covariance (EC) to Keeling regressions of data from automated flux chamber sampling. Mean CH4 fluxes of 6.5 ± 0.7 mg CH4 m-2 hr-1 over two days of EC sampling in July, 2009 were indistinguishable from mean autochamber CH4 fluxes (6.6 ± 0.8 mgCH4 m-2 hr-1) over the same period. Mean ? composition of emitted CH4 calculated using EC isoflux methods was -71 ± 8 ‰ (95% C.I.) while Keeling regressions of 332 chamber closing events over 8 days yielded a corresponding value of -64.5 ± 0.8 ‰. Ebullitive fluxes, representing ˜10% of total CH4 fluxes at this site, were on average 1.2 ‰ enriched in 13C compared to diffusive fluxes. CH4 isoflux time series have the potential to improve process-based understanding of methanogenesis, fully characterize source isotopic distributions, and serve as additional constraints for both regional and global CH4 modeling analysis.

Uncertainty in the future atmospheric burden of methane, a potent greenhouse gas1, represents an important challenge to the development of realistic climate projections. The Arctic is home to large reservoirs of methane, in the form of permafrost soils and methane hydrates2, which are vulnerable to destabilization in a warming climate. Furthermore, methane is produced in the surface ocean3 and the surface waters of the Arctic Ocean are supersaturated with respect to methane4,5. However, the fate of this oceanic methane is uncertain. Here, we use airborne observations of methane to assess methane efflux from the remote Arctic Ocean, up to latitudes of 82° north. We report layers of increased methane concentrations near the surface ocean, with little or no enhancement in carbon monoxide levels, indicative of a non-combustion source. We further show that high methane concentrations are restricted to areas over open leads and regions with fractional sea-ice cover. Based on the observed gradients in methane concentration, we estimate that sea–air fluxes amount to around 2 mg d−1 m−2, comparable to emissions seen on the Siberian shelf. We suggest that the surface waters of the Arctic Ocean represent a potentially important source of methane, which could prove sensitive to changes in sea-ice cover.

Uncertainty in the future atmospheric burden of methane, a potent greenhouse gas1, represents an important challenge to the development of realistic climate projections. The Arctic is home to large reservoirs of methane, in the form of permafrost soils and methane hydrates2, which are vulnerable to destabilization in a warming climate. Furthermore, methane is produced in the surface ocean3 and the surface waters of the Arctic Ocean are supersaturated with respect to methane4,5. However, the fate of this oceanic methane is uncertain. Here, we use airborne observations of methane to assess methane efflux from the remote Arctic Ocean, up to latitudes of 82° north. We report layers of increased methane concentrations near the surface ocean, with little or no enhancement in carbon monoxide levels, indicative of a non-combustion source. We further show that high methane concentrations are restricted to areas over open leads and regions with fractional sea-ice cover. Based on the observed gradients in methane concentration, we estimate that sea–air fluxes amount to around 2 mg d−1 m−2, comparable to emissions seen on the Siberian shelf. We suggest that the surface waters of the Arctic Ocean represent a potentially important source of methane, which could prove sensitive to changes in sea-ice cover.

This paper presents top-down constraints on the magnitude, spatial distribution, and seasonality of nitrous oxide (N₂O) emissions over the central United States. We analyze data from tall towers in 2004 and 2008 using a high resolution Lagrangian particle dispersion model paired with both geostatistical and Bayesian inversions. Our results indicate peak N₂O emissions in June with a strong seasonal cycle. The spatial distribution of sources closely mirrors data on fertilizer application with particularly large N₂O sources over the US Cornbelt. Existing inventories for N₂O predict emissions that differ substantially from the inverse model results in both seasonal cycle and magnitude. We estimate a total annual N₂O budget over the central US of 0.9–1.2 TgN/yr and an extrapolated budget for the entire US and Canada of 2.1–2.6 TgN/yr. By this estimate, the US and Canada account for 12–15% of the total global N₂O source or 32–39% of the global anthropogenic source as reported by the Intergovernmental Panel on Climate Change in 2007.

In the ‘Natural and anthropogenic climatic variation’ section of this Review, we incorrectly referred to the North Atlantic Oscillation as a contributor to the 2005 Amazonian droughts. We should instead have referred to the Atlantic Multidecadal Oscillation, which is an oceanic phenomenon related to anomalies in sea surface temperature in the tropical north Atlantic Ocean and can affect drought in the Amazon Basin. We thank L. Aragao for drawing this error to our attention. This has been corrected in the PDF and HTML versions online.