Cooperative Air Sampling Network Research Articles

Validation of revised methane and nitrous oxide profiles from MIPAS–ENVISAT

Abstract. Improved versions of CH4 and N2O profiles derived at the Institute of Meteorology and Climate Research and Instituto de Astrofísica de Andalucía (CSIC) from spectra measured by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) have become available. For the MIPAS full-resolution period (2002–2004) these are V5H_CH4_21 and V5H_N2O_21 and for the reduced-resolution period (2005–2012) these are V5R_CH4_224, V5R_CH4_225, V5R_N2O_224 and V5R_N2O_225. Here, we compare CH4 profiles to those measured by the Fourier Transform Spectrometer on board of the Atmospheric Chemistry Experiment (ACE-FTS), the HALogen Occultation Experiment (HALOE) and the Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY), to the Global Cooperative Air Sampling Network (GCASN) surface data. We find the MIPAS CH4 profiles below 25 km to be typically higher of the order of 0.1 ppmv for both measurement periods. N2O profiles are compared to those measured by ACE-FTS, the Microwave Limb Sounder on board of the Aura satellite (Aura-MLS) and the Sub-millimetre Radiometer on board of the Odin satellite (Odin-SMR) as well as to the Halocarbons and other Atmospheric Trace Species Group (HATS) surface data. The mixing ratios of the satellite instruments agree well with each other for the full-resolution period. For the reduced-resolution period, MIPAS produces similar values as Odin-SMR, but higher values than ACE-FTS and HATS. Below 27 km, the MIPAS profiles show higher mixing ratios than Aura-MLS, and lower values between 27 and 41 km. Cross-comparisons between the two MIPAS measurement periods show that they generally agree quite well, but, especially for CH4, the reduced-resolution period seems to produce slightly higher mixing ratios than the full-resolution data.

Inverse modelling of CH<sub>4</sub> emissions for 2010–2011 using different satellite retrieval products from GOSAT and SCIAMACHY

Abstract. At the beginning of 2009 new space-borne observations of dry-air column-averaged mole fractions of atmospheric methane (XCH4) became available from the Thermal And Near infrared Sensor for carbon Observations–Fourier Transform Spectrometer (TANSO-FTS) instrument on board the Greenhouse Gases Observing SATellite (GOSAT). Until April 2012 concurrent {methane (CH4) retrievals} were provided by the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) instrument on board the ENVironmental SATellite (ENVISAT). The GOSAT and SCIAMACHY XCH4 retrievals can be compared during the period of overlap. We estimate monthly average CH4 emissions between January 2010 and December 2011, using the TM5-4DVAR inverse modelling system. In addition to satellite data, high-accuracy measurements from the Cooperative Air Sampling Network of the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA ESRL) are used, providing strong constraints on the remote surface atmosphere. We discuss five inversion scenarios that make use of different GOSAT and SCIAMACHY XCH4 retrieval products, including two sets of GOSAT proxy retrievals processed independently by the Netherlands Institute for Space Research (SRON)/Karlsruhe Institute of Technology (KIT), and the University of Leicester (UL), and the RemoTeC "Full-Physics" (FP) XCH4 retrievals available from SRON/KIT. The GOSAT-based inversions show significant reductions in the root mean square (rms) difference between retrieved and modelled XCH4, and require much smaller bias corrections compared to the inversion using SCIAMACHY retrievals, reflecting the higher precision and relative accuracy of the GOSAT XCH4. Despite the large differences between the GOSAT and SCIAMACHY retrievals, 2-year average emission maps show overall good agreement among all satellite-based inversions, with consistent flux adjustment patterns, particularly across equatorial Africa and North America. Over North America, the satellite inversions result in a significant redistribution of CH4 emissions from North-East to South-Central United States. This result is consistent with recent independent studies suggesting a systematic underestimation of CH4 emissions from North American fossil fuel sources in bottom-up inventories, likely related to natural gas production facilities. Furthermore, all four satellite inversions yield lower CH4 fluxes across the Congo basin compared to the NOAA-only scenario, but higher emissions across tropical East Africa. The GOSAT and SCIAMACHY inversions show similar performance when validated against independent shipboard and aircraft observations, and XCH4 retrievals available from the Total Carbon Column Observing Network (TCCON).

Reconstruction of Northern Hemisphere 1950–2010 atmospheric non-methane hydrocarbons

Abstract. The short-chain non-methane hydrocarbons (NMHC) are mostly emitted into the atmosphere by anthropogenic processes. Recent studies have pointed out a tight linkage between the atmospheric mole fractions of the NMHC ethane and the atmospheric growth rate of methane. Consequently, atmospheric NMHC are valuable indicators for tracking changes in anthropogenic emissions, photochemical ozone production, and greenhouse gases. This study investigates the 1950–2010 Northern Hemisphere atmospheric C2–C5 NMHC ethane, propane, i-butane, n-butane, i-pentane, and n-pentane by (a) reconstructing atmospheric mole fractions of these trace gases using firn air extracted from three boreholes in 2008 and 2009 at the North Greenland Eemian Ice Drilling (NEEM) site and applying state-of-the-art models of trace gas transport in firn, and by (b) considering eight years of ambient NMHC monitoring data from five Arctic sites within the NOAA Global Monitoring Division (GMD) Cooperative Air Sampling Network. Results indicate that these NMHC increased by ~40–120% after 1950, peaked around 1980 (with the exception of ethane, which peaked approximately 10 yr earlier), and have since dramatically decreased to be now back close to 1950 levels. The earlier peak time of ethane vs. the C3–C5 NMHC suggests that different processes and emissions mitigation measures contributed to the decline in these NMHC. The 60 yr record also illustrates notable increases in the ratios of the isomeric iso-/n-butane and iso-/n-pentane ratios. Comparison of the reconstructed NMHC histories with 1950–2000 volatile organic compounds (VOC) emissions data and with other recently published ethane trend analyses from ambient air Pacific transect data showed (a) better agreement with North America and Western Europe emissions than with total Northern Hemisphere emissions data, and (b) better agreement with other Greenland firn air data NMHC history reconstructions than with the Pacific region trends. These analyses emphasize that for NMHC, having atmospheric lifetimes on the order of < 2 months, the Greenland firn air records are primarily a representation of Western Europe and North America emission histories.

On the parallelization of atmospheric inversions of CO<sub>2</sub> surface fluxes within a variational framework

Abstract. The variational formulation of Bayes' theorem allows inferring CO2 sources and sinks from atmospheric concentrations at much higher time–space resolution than the ensemble or analytical approaches. However, it usually exhibits limited scalable parallelism. This limitation hinders global atmospheric inversions operated on decadal time scales and regional ones with kilometric spatial scales because of the computational cost of the underlying transport model that has to be run at each iteration of the variational minimization. Here, we introduce a physical parallelization (PP) of variational atmospheric inversions. In the PP, the inversion still manages a single physically and statistically consistent window, but the transport model is run in parallel overlapping sub-segments in order to massively reduce the computation wall-clock time of the inversion. For global inversions, a simplification of transport modelling is described to connect the output of all segments. We demonstrate the performance of the approach on a global inversion for CO2 with a 32 yr inversion window (1979–2010) with atmospheric measurements from 81 sites of the NOAA global cooperative air sampling network. In this case, we show that the duration of the inversion is reduced by a seven-fold factor (from months to days), while still processing the three decades consistently and with improved numerical stability.

Interannual variability in the oxygen isotopes of atmospheric CO2 driven by El Niño

The stable isotope ratios of atmospheric CO(2) ((18)O/(16)O and (13)C/(12)C) have been monitored since 1977 to improve our understanding of the global carbon cycle, because biosphere-atmosphere exchange fluxes affect the different atomic masses in a measurable way. Interpreting the (18)O/(16)O variability has proved difficult, however, because oxygen isotopes in CO(2) are influenced by both the carbon cycle and the water cycle. Previous attention focused on the decreasing (18)O/(16)O ratio in the 1990s, observed by the global Cooperative Air Sampling Network of the US National Oceanic and Atmospheric Administration Earth System Research Laboratory. This decrease was attributed variously to a number of processes including an increase in Northern Hemisphere soil respiration; a global increase in C(4) crops at the expense of C(3) forests; and environmental conditions, such as atmospheric turbulence and solar radiation, that affect CO(2) exchange between leaves and the atmosphere. Here we present 30 years' worth of data on (18)O/(16)O in CO(2) from the Scripps Institution of Oceanography global flask network and show that the interannual variability is strongly related to the El Niño/Southern Oscillation. We suggest that the redistribution of moisture and rainfall in the tropics during an El Niño increases the (18)O/(16)O ratio of precipitation and plant water, and that this signal is then passed on to atmospheric CO(2) by biosphere-atmosphere gas exchange. We show how the decay time of the El Niño anomaly in this data set can be useful in constraining global gross primary production. Our analysis shows a rapid recovery from El Niño events, implying a shorter cycling time of CO(2) with respect to the terrestrial biosphere and oceans than previously estimated. Our analysis suggests that current estimates of global gross primary production, of 120 petagrams of carbon per year, may be too low, and that a best guess of 150-175 petagrams of carbon per year better reflects the observed rapid cycling of CO(2). Although still tentative, such a revision would present a new benchmark by which to evaluate global biospheric carbon cycling models.

Observed and simulated global distribution and budget of atmospheric C<sub>2</sub>-C<sub>5</sub> alkanes

Abstract. The primary sources and atmospheric chemistry of C2-C5 alkanes were incorporated into the atmospheric chemistry general circulation model EMAC. Model output is compared with new observations from the NOAA/ESRL GMD Cooperative Air Sampling Network. Based on the global coverage of the data, two different anthropogenic emission datasets for C4-C5 alkanes, widely used in the modelling community, are evaluated. We show that the model reproduces the main atmospheric features of the C2-C5 alkanes (e.g., seasonality). While the simulated values for ethane and propane are within a 20% range of the measurements, larger deviations are found for the other tracers. According to the analysis, an oceanic source of butanes and pentanes larger than the current estimates would be necessary to match the observations at some coastal stations. Finally the effect of C2-C5 alkanes on the concentration of acetone and acetaldehyde are assessed. Their chemical sources are largely controlled by the reaction with OH, while the reactions with NO3 and Cl contribute only to a little extent. The total amount of acetone produced by propane, i-butane and i-pentane oxidation is 11.2 Tg/yr, 4.3 Tg/yr, and 5.8 Tg/yr, respectively. Moreover, 18.1, 3.1, 3.4, 1.4 and 4.8 Tg/yr of acetaldehyde are formed by the oxidation of ethane, propane, n-butane, n-pentane and i-pentane, respectively.

Assimilation of SCIAMACHY total column CO observations: Global and regional analysis of data impact

Carbon monoxide (CO) total column observations from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) on board Envisat‐1 are assimilated into the Global Modeling and Assimilation Office constituent assimilation system for the period 1 April to 20 December 2004. The impact of the assimilation on CO distribution is evaluated using independent surface flask observations from the National Oceanic and Atmospheric Administration (NOAA)/ESRL global cooperative air sampling network and Measurement of Ozone and Water Vapor by Airbus In‐Service Aircraft (MOZAIC) in situ CO profiles. Assimilation of SCIAMACHY data improves agreement of CO assimilation with both of these data sets on both global and regional scales compared to the free‐running model. Regional comparisons with MOZAIC profiles made in western Europe, the northeastern United States, and the Arabian Peninsula show improvements at all three locations in the free troposphere and into the boundary layer over Arabia and the northeastern United States. Comparisons with NOAA Earth System Research Laboratory data improve at about two thirds of the surface observation sites. The systematic model errors related to the uncertainty of CO surface sources and the chemistry of CO losses are investigated through experiments with increased surface CO emissions over the Arabian Peninsula and/or globally reduced hydroxyl radical (OH) concentrations. Both model changes decrease mean CO errors at all altitudes in comparison to MOZAIC data over Dubai and Abu Dhabi. In contrast, errors in the assimilated CO are reduced by the increased emissions for pressures ≥800 hPa and by the reduced OH for pressures ≤600 hPa. Our analysis suggests that CO emissions over Dubai in 2004 are more than double those in the 1998 emissions inventory.

Technical Note: Adapting a fixed-lag Kalman smoother to a geostatistical atmospheric inversion framework

Abstract. Inverse modeling methods are now commonly used for estimating surface fluxes of carbon dioxide, using atmospheric mass fraction measurements combined with a numerical atmospheric transport model. The geostatistical approach to flux estimation takes advantage of the spatial and/or temporal correlation in fluxes and does not require prior flux estimates. In this work, a previously-developed, computationally-efficient, fixed-lag Kalman smoother is adapted for application with a geostatistical approach to atmospheric inversions. This method makes it feasible to perform multi-year geostatistical inversions, at fine resolutions, and with large amounts of data. The new method is applied to the recovery of global gridscale carbon dioxide fluxes for 1997 to 2001 using pseudodata representative of a subset of the NOAA-ESRL Cooperative Air Sampling Network.

Global monthly averaged CO2 fluxes recovered using a geostatistical inverse modeling approach: 1. Results using atmospheric measurements

This study presents monthly CO2 fluxes from 1997 to 2001 at a 3.75° latitude × 5° longitude resolution, inferred using a geostatistical inverse modeling approach. The approach focuses on quantifying the information content of measurements from the NOAA‐ESRL cooperative air sampling network with regard to the global CO2 budget at different spatial and temporal scales. The geostatistical approach avoids the use of explicit prior flux estimates that have formed the basis of previous synthesis Bayesian inversions and does not prescribe spatial patterns of flux for large, aggregated regions. Instead, the method relies strongly on the atmospheric measurements and the inferred spatial autocorrelation of the fluxes to estimate sources and sinks and their associated uncertainties at the resolution of the atmospheric transport model. Results show that grid‐scale estimates exhibit high uncertainty and relatively little small‐scale variability, but generally reflect reasonable fluxes in areas that are relatively well constrained by measurements. The aggregated continental‐scale fluxes are better constrained, and estimates are consistent with results from previous synthesis Bayesian inversion studies for many regions. Observed differences at the continental scale are primarily attributable to the choice of a priori assumptions in the current work relative to those in other synthesis Bayesian studies. Overall, the results indicate that the geostatistical inverse modeling approach is able to estimate global fluxes using the limited atmospheric measurement network without relying on assumptions about a priori estimates of the flux distribution. As such, the method provides a means of isolating the information content of the atmospheric measurements, and thus serves as a valuable tool for reconciling top‐down and bottom‐up estimates of CO2 flux variability.

Sampling, storage, and analysis of C 2–C 7 non-methane hydrocarbons from the US National Oceanic and Atmospheric Administration Cooperative Air Sampling Network glass flasks

An analytical technique was developed to analyze light non-methane hydrocarbons (NMHC), including ethane, propane, iso-butane, n-butane, iso-pentane, n-pentane, n-hexane, isoprene, benzene and toluene from whole air samples collected in 2.5 l-glass flasks used by the National Oceanic and Atmospheric Administration, Earth System Research Laboratory, Global Monitoring Division (NOAA ESRL GMD, Boulder, CO, USA) Cooperative Air Sampling Network. This method relies on utilizing the remaining air in these flasks (which is at below-ambient pressure at this stage) after the completion of all routine greenhouse gas measurements from these samples. NMHC in sample aliquots extracted from the flasks were preconcentrated with a custom-made, cryogen-free inlet system and analyzed by gas chromatography (GC) with flame ionization detection (FID). C 2–C 7 NMHC, depending on their ambient air mixing ratios, could be measured with accuracy and repeatability errors of generally ≤10–20%. Larger deviations were found for ethene and propene. Hexane was systematically overestimated due to a chromatographic co-elution problem. Saturated NMHC showed less than 5% changes in their mixing ratios in glass flask samples that were stored for up to 1 year. In the same experiment ethene and propene increased at ∼30% yr −1. A series of blank experiments showed negligible contamination from the sampling process and from storage (<10 pptv yr −1) of samples in these glass flasks. Results from flask NMHC analyses were compared to in-situ NMHC measurements at the Global Atmospheric Watch station in Hohenpeissenberg, Germany. This 9-months side-by-side comparison showed good agreement between both methods. More than 94% of all data comparisons for C 2–C 5 alkanes, isoprene, benzene and toluene fell within the combined accuracy and precision objectives of the World Meteorological Organization Global Atmosphere Watch (WMO-GAW) for NMHC measurements.

Examining injection properties of boreal forest fires using surface and satellite measurements of CO transport

Boreal forest fires are highly variable in space and time and also have variable vertical injection properties. We compared a University of Maryland Chemistry and Transport Model (UMD‐CTM) simulation of boreal forest fire CO in the summer of 2000 to surface observations from the NOAA Cooperative Air Sampling Network and satellite observations of CO from the Measurement of Pollutants in the Troposphere (MOPITT) instrument to investigate the sensitivity of these measurements to injection height and to evaluate the bulk injection properties of the boreal fire source. Our results show that emissions at the surface produce more than twice the signal in surface CO measurements compared with emissions injected into the upper troposphere. Surface injection yielded the best agreement with surface observations, but high‐altitude injection resulted in very small variations at the surface, and so the statistical comparison with surface observations was inconclusive. Because of the vertical sensitivity of MOPITT, estimated total CO burden north of 30°N was 10% higher for upper tropospheric injection of boreal forest fire CO compared to surface release. We used a contrast filter to select the MOPITT retrievals most sensitive to boreal forest fire injection height and found that the best agreement between simulation results and MOPITT observations was obtained with midtropospheric injection of emissions and with pressure‐weighted distribution of emissions through the tropospheric column. Appendix A uses CTM output to examine quantitatively the bias and errors in calculations of total column CO and total CO burden using MOPITT CO retrievals.

Effects of source temporal resolution on transport simulations of boreal fire emissions

The quality of temporal information from daily burned area inputs was evaluated using a transport and chemistry experiment. Carbon monoxide emissions from boreal forest fires were estimated using burned area inputs with daily resolution. Averaging of emissions data to create 30‐day aggregate data reduced the variance by 80%, indicating a substantial loss of information. Data from Russia, Canada, and Alaska were tested for periodicity to uncover systematic gaps in daily data. Some evidence of periodicity was found in data from Alaska, where temporal information came from fire mapping by the Alaskan Fire Service. Autocorrelation decayed rapidly and nearly monotonically for Canada and Russia, where temporal information came from Advanced Very High Resolution Radiometer (AVHRR) satellite observations. Daily data as well as 7‐day and 30‐day aggregates were used as input to the University of Maryland Atmospheric Chemistry and Transport Model, and output was compared with CO observations from the Cooperative Air Sampling Network (CASN); continuous measurements from Mace Head, Ireland; and total column CO retrievals from the Measurement of Pollution in the Troposphere (MOPITT) instrument. CASN flask measurements showed no sensitivity to high‐frequency variability in the source, indicating the effectiveness of the filtering protocol at ensuring only well‐mixed air masses are sampled in this data set. Differences between daily and 7‐day simulations were too small for quantitative comparison in any of the data. For cases where the differences were substantial, simulations using daily and 7‐day average sources agreed better with observations than 30‐day average sources.

Maximum likelihood estimation of covariance parameters for Bayesian atmospheric trace gas surface flux inversions

This paper introduces a Maximum Likelihood (ML) approach for estimating the statistical parameters required for the covariance matrices used in the solution of Bayesian inverse problems aimed at estimating surface fluxes of atmospheric trace gases. The method offers an objective methodology for populating the covariance matrices required in Bayesian inversions, thereby resulting in better estimates of the uncertainty associated with derived fluxes and minimizing the risk of inversions being biased by unrealistic covariance parameters. In addition, a method is presented for estimating the uncertainty associated with these covariance parameters. The ML method is demonstrated using a typical inversion setup with 22 flux regions and 75 observation stations from the National Oceanic and Atmospheric Administration‐Climate Monitoring and Diagnostics Laboratory (NOAA‐CMDL) Cooperative Air Sampling Network with available monthly averaged carbon dioxide data. Flux regions and observation locations are binned according to various characteristics, and the variances of the model‐data mismatch and of the errors associated with the a priori flux distribution are estimated from the available data.

Simultaneous mass balance inverse modeling of methane and carbon monoxide

We perform a simultaneous mass‐balance inversion of atmospheric methane (CH4) and carbon monoxide (CO) using measurements from the NOAA/CMDL Cooperative Air Sampling Network and a model of tropospheric transport and background chemistry over the period 1990–2000. Our method has a spatial resolution of a semihemisphere and a temporal resolution of 1 month. The deduced CO sources show relatively low interannual variability except around the major biomass burning event in 1997–1998, when we calculate an anomalous emission between July 1997 and December 1998 of 270 Tg(CO). This is enough to suppress the modeled global air mass weighted hydroxyl radical (OH) concentration during this time by 2.2%, and account for 75% of the observed increase in CH4 mixing ratios during 1998. We compare our implied CH4/CO emissions factors with published biomass burning emissions factors, suggesting that the remainder of the increase in CH4 observed in 1998 is due to anomalously high biomass burning emissions, with CH4 emissions from wetlands showing a small negative anomaly in 1998.

Mass balance inverse modelling of methane in the 1990s using a Chemistry Transport Model

Abstract. A mass balance inverse modelling procedure is applied with a time-dependent methane concentration boundary condition and a chemical transport model to relate observed changes in the surface distribution of methane mixing ratios during the 1990s to changes in its surface sources. The model reproduces essential features of the global methane cycle, such as the latitudinal distribution and seasonal cycle of fluxes, without using a priori knowledge of methane fluxes. A detailed description of the temporal and spatial variability of the fluxes diagnosed by the inverse procedure is presented, and compared with previously hypothesised changes in the methane budget, and previous inverse modelling studies. The sensitivity of the inverse results to the forcing data supplied by surface measurements of methane from the NOAA CMDL cooperative air sampling network is also examined. This work serves as an important starting point for future inverse modelling work examining changes in both the source and sink terms in the methane budget together.

The seasonal cycle of N2O

We have carried out an empirical study of the seasonal cycle of nitrous oxide (N2O) using the data archived by the National Oceanic and Atmospheric Administration – Climate Monitoring and Diagnostics Laboratory (NOAA‐CMDL) Global Cooperative Air Sampling Network from 1977 to 2000. In order to isolate the seasonal cycle, we first detrended the data using least square polynomial fits. The remaining variability was averaged to extract the seasonal cycle, which has an amplitude of about 0.8 ppbv. The statistical significance of the seasonal signal was established using the multitaper method and Welch's method for power spectrum analysis.

Development of analytical methods and measurements of 13C/12C in atmospheric CH4 from the NOAA Climate Monitoring and Diagnostics Laboratory Global Air Sampling Network

We describe the development of an automated gas chromatography‐isotope ratio mass spectrometry (GC‐IRMS) system capable of measuring the carbon isotopic composition of atmospheric methane (δ13CH4) with a precision of better than 0.1‰. The system requires 200 mL of air and completes a single analysis in 15 min. The combination of small sample size, fast analysis time, and high precision has allowed us to measure background variations in atmospheric δ13CH4 through the NOAA Climate Monitoring and Diagnostics Laboratory Cooperative Air Sampling Network. We then present a record of δ13CH4 obtained from six surface sites of the network between January 1998 and December 1999. The sites are Barrow, Alaska (71°N); Niwot Ridge, Colorado (40°N); Mauna Loa, Hawaii (20°N); American Samoa (14°S); Cape Grim, Tasmania (41°S); and the South Pole (90°S). For the years 1998 and 1999, the globally averaged surface δ13C value was −47.1‰, and the average difference between Barrow and the South Pole was 0.6‰. Consistent seasonal variations were seen only in the Northern Hemisphere, especially at Barrow, where the average amplitude was 0.5‰. Seasonal variations in 1998, however, were evident at all sites, the cause of which is unknown. We also use a two‐box model to examine the extent to which annual average δ13C and CH4 mole fraction measurements can constrain broad categories of source emissions. We find that the biggest sources of error are not the atmospheric δ13C measurements but instead the radiocarbon‐derived fossil fuel emission estimates, rate coefficients for methane destruction, and isotopic ratios of source emissions.

The sensitivity of tropospheric methane to the interannual variability in stratospheric ozone

The dominant processes affecting the concentration of tropospheric methane on interannual timescales are the biospheric and anthropogenic sources and changes in the abundance of the hydroxyl radical caused by the changes in the UV flux which result from changes in stratospheric ozone abundance. We have carried out an empirical study of the sensitivity of the methane to fluctuations in ozone column abundance. This analysis was carried out using monthly mean surface methane concentrations measured by the National Oceanic and Atmospheric Administration – Climate Monitoring and Diagnostics Laboratory (NOAA-CMDL) Global Cooperative Air Sampling Network from 1983 to 1998 and ozone column abundances obtained by the Total Ozone Mapping Spectrometer (TOMS) and the EP TOMS instruments over the same time period. We focused on interannual variability with periods between 15 and 60 months, in which interval the dominant ozone fluctuation is the quasi-biennial oscillation (QBO), with a period of approximately 29 months. In order to isolate the response of methane to ozone from the effects of variability in the sources and transport of methane, we restricted our analysis to data at mid-latitudes in the southern hemisphere. A statistical study shows that the sensitivity factor α≡−d(ln[CH4])/d(ln[O3])=−0.038±0.009. The response of CH4 lags approximately 6 months behind the forcing by O3. A simple model was used to interpret the empirical results. Our results confirm that any mechanism that affects stratospheric ozone impacts the oxidizing potential of the troposphere. CH4 fluctuations provide a quantitative measure of this important effect linking the upper and the lower atmosphere.

Measurements of CO and O3 at Shemya, Alaska

In situ measurements of surface CO were conducted from June 1994 to May 1995, and surface ozone was measured from February to May, 1995, at Shemya, Alaska (52o44'N, 174o06'E) using nondispersive infrared‐gas filter correlation (GFC) and UV absorption spectroscopy, respectively. Over the same period, air samples were collected in flasks for analysis of CO and other trace gases as part of the NOAA‐CMDL cooperative air sampling network. We compared the continuous GFC measurements with the National Oceanic and Atmospheric Administration Climate Monitoring and Diagnostics Laboratory (NOAA‐CMDL) flask data. Over this 1‐year period, CO mixing ratios varied between 60 and 250 parts per billion by volume (ppbv). Within this range, the comparison between the two measurements is quite good, with an overall R2 of 0.953 and an average difference of 3.1%. A seasonal cycle is apparent in the CO data, with a springtime maximum and a summer minimum. Synoptic influences on the data include transport from the lower‐latitude Pacific, bringing air with very low CO mixing ratios to Shemya, and, occasionally, transport from industrial areas in east Asia, including northern China, Japan, and eastern Russia. A scatterplot of CO versus O3 using all the data shows essentially no relationship at this remote site. This result implies that the primary sources and sinks for these trace gases are different at this location. However, during a few 12‐ to 48‐hour periods in fall and late spring, enhancements in CO or in both CO and O3 were observed. During these periods, isentropic back trajectories indicate transport from the west and southwest. However, the trajectories are often difficult to interpret due to looping and are of short duration due to impact at the surface. These complexities are associated with the presence of cyclonic systems in the region. The local meteorological data suggest that the enhanced concentrations occurred around the time when these cyclonic systems passed near the sampling site. Synoptic surface pressure maps indicate that these cyclonic systems formed or crossed industrial regions in east Asia and passed near Shemya on their way to the Bering Sea. This process suggests a role for transport of anthropogenic pollutants by cyclonic systems moving northward along the western edge of the Pacific Ocean.

Extension and integration of atmospheric carbon dioxide data into a globally consistent measurement record

Atmospheric transport models are used to constrain sources and sinks of carbon dioxide by requiring that the modeled spatial and temporal concentration patterns are consistent with the observations. Serious obstacles to this approach are the sparsity of sampling sites and the lack of temporal continuity among observations at different locations. A procedure is presented that attempts to extend the knowledge gained during a limited period of measurements beyond the period itself resulting in records containing measurement data and extrapolated and interpolated values. From limited measurements we can define trace gas climatologies that describe average seasonal cycles, trends, and changes in trends at individual sampling sites. A comparison of the site climatologies with a reference defined over a much longer period of time constitutes the framework used in the development of the data extension procedure. Two extension methods are described. The benchmark trend method uses a deseasonalized long‐term trend from a single site as a reference to individual site climatologies. The latitude reference method utilizes measurements from many sites in constructing a reference to the climatologies. Both methods are evaluated and the advantages and limitations of each are discussed. Data extension is not based on any atmospheric models but entirely on the data themselves. The methods described here are relatively straightforward and reproducible and result in extended records that are model independent. The cooperative air sampling network maintained by the National Oceanic and Atmospheric Administration Climate Monitoring and Diagnostics Laboratory in Boulder, Colorado, provides a test bed for the development of the data extension method; we intend to integrate and extend CO2 measurement records from other laboratories providing a globally consistent atmospheric CO2 database to the modeling community.