Debra Wunch

The Total Carbon Column Observing Network

A global network of ground-based Fourier transform spectrometers has been founded to remotely measure column abundances of CO2, CO, CH4, N2O and other molecules that absorb in the near-infrared. These measurements are directly comparable with the near-infrared total column measurements from space-based instruments. With stringent requirements on the instrumentation, acquisition procedures, data processing and calibration, the Total Carbon Column Observing Network (TCCON) achieves an accuracy and precision in total column measurements that is unprecedented for remote-sensing observations (better than 0.25% for CO2). This has enabled carbon-cycle science investigations using the TCCON dataset, and allows the TCCON to provide a link between satellite measurements and the extensive ground-based in situ network.

Daily and 3‐hourly variability in global fire emissions and consequences for atmospheric model predictions of carbon monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003–2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top-down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.

Process-evaluation of tropospheric humidity simulated by general circulation models using water vapor isotopologues: 1. Comparison between models and observations

The goal of this study is to determine how H2O and HDO measurements in water vapor can be used to detect and diagnose biases in the representation of processes controlling tropospheric humidity in atmospheric general circulation models (GCMs). We analyze a large number of isotopic data sets (four satellite, sixteen ground-based remote-sensing, five surface in situ and three aircraft data sets) that are sensitive to different altitudes throughout the free troposphere. Despite significant differences between data sets, we identify some observed HDO/H2O characteristics that are robust across data sets and that can be used to evaluate models. We evaluate the isotopic GCM LMDZ, accounting for the effects of spatiotemporal sampling and instrument sensitivity. We find that LMDZ reproduces the spatial patterns in the lower and mid troposphere remarkably well. However, it underestimates the amplitude of seasonal variations in isotopic composition at all levels in the subtropics and in midlatitudes, and this bias is consistent across all data sets. LMDZ also underestimates the observed meridional isotopic gradient and the contrast between dry and convective tropical regions compared to satellite data sets. Comparison with six other isotope-enabled GCMs from the SWING2 project shows that biases exhibited by LMDZ are common to all models. The SWING2 GCMs show a very large spread in isotopic behavior that is not obviously related to that of humidity, suggesting water vapor isotopic measurements could be used to expose model shortcomings. In a companion paper, the isotopic differences between models are interpreted in terms of biases in the representation of processes controlling humidity. Copyright

Emissions of greenhouse gases from a North American megacity

Atmospheric column abundances of carbon dioxide (CO_2), carbon monoxide (CO), methane (CH_4) and nitrous oxide (N_2O) have been measured above the South Coast air basin (SCB), a densely populated urban region of Southern California, USA, which includes Los Angeles and the surrounding suburbs. Large diurnal variations in CO and CH_4 are observed which correlate well with those in CO_2. Weaker correlations are seen between N_2O and CO_2, with large uncertainties. We compute yearly SCB emissions of CO and CH_4 to be 1.4 ± 0.3 Tg CO and 0.6 ± 0.1 Tg CH_4. We compare our calculated emissions to the California Air Resources Board (CARB) and the Emission Database for Global Atmospheric Research (EDGAR) estimates. Our measurements confirm that urban emissions are a significant source of CH_4 and in fact may be substantially higher than currently estimated. If our emissions are typical of other urban centers, these findings suggest that urban emissions could contribute 7–15% to the global anthropogenic budget of methane.

Methane observations from the Greenhouse Gases Observing SATellite: comparison to ground-based TCCON data and model calculations

We report new short-wave infrared (SWIR) column retrievals of atmospheric methane (X_(CH4)) from the Japanese Greenhouse Gases Observing SATellite (GOSAT) and compare observed spatial and temporal variations with correlative ground-based measurements from the Total Carbon Column Observing Network (TCCON) and with the global 3-D GEOS-Chem chemistry transport model. GOSAT X_(CH4) retrievals are compared with daily TCCON observations at six sites between April 2009 and July 2010 (Bialystok, Park Falls, Lamont, Orleans, Darwin and Wollongong). GOSAT reproduces the site-dependent seasonal cycles as observed by TCCON with correlations typically between 0.5 and 0.7 with an estimated single-sounding precision between 0.4–0.8%. We find a latitudinal-dependent difference between the X_(CH4) retrievals from GOSAT and TCCON which ranges from 17.9 ppb at the most northerly site (Bialystok) to −14.6 ppb at the site with the lowest latitude (Darwin). We estimate that the mean smoothing error difference included in the GOSAT to TCCON comparisons can account for 15.7 to 17.4 ppb for the northerly sites and for 1.1 ppb at the lowest latitude site. The GOSAT X_(CH4) retrievals agree well with the GEOS-Chem model on annual (August 2009 – July 2010) and monthly timescales, capturing over 80% of the zonal variability. Differences between model and observed X_(CH4) are found over key source regions such as Southeast Asia and central Africa which will be further investigated using a formal inverse model analysis.

Retrieval of atmospheric CO2 with enhanced accuracy and precision from SCIAMACHY: validation with FTS measurements and comparison with model results

The Bremen Optimal Estimation differential optical absorption spectroscopy (DOAS) (BESD) algorithm for satellite based retrievals of XCO_2 (the column-average dry-air mole fraction of atmospheric CO_2) has been applied to Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) data. It uses measurements in the O_2-A absorption band to correct for scattering of undetected clouds and aerosols. Comparisons with precise and accurate ground-based Fourier transform spectrometer (FTS) measurements at four Total Carbon Column Observing Network (TCCON) sites have been used to quantify the quality of the new SCIAMACHY XCO_2 data set. Additionally, the results have been compared to NOAAs assimilation system CarbonTracker. The comparisons show that the new retrieval meets the expectations from earlier theoretical studies. We find no statistically significant regional XCO_2 biases between SCIAMACHY and the FTS instruments. However, the standard error of the systematic differences is in the range of 0.2 ppm and 0.8 ppm. The XCO_2 single-measurement precision of 2.5 ppm is similar to theoretical estimates driven by instrumental noise. There are no significant differences found for the year-to-year increase as well as for the average seasonal amplitude between SCIAMACHY XCO_2 and the collocated FTS measurements. Comparison of the year-to-year increase and also of the seasonal amplitude of CarbonTracker exhibit significant differences with the corresponding FTS values at Darwin. Here the differences between SCIAMACHY and CarbonTracker are larger than the standard error of the SCIAMACHY values. The difference of the seasonal amplitude exceeds the significance level of 2 standard errors. Therefore, our results suggest that SCIAMACHY may provide valuable additional information about XCO_2, at least in regions with a low density of in situ measurements.

Atmospheric carbon dioxide retrieved from the Greenhouse gases Observing SATellite (GOSAT): Comparison with ground-based TCCON observations and GEOS-Chem model calculations

We retrieved column-averaged dry air mole fractions of atmospheric carbon dioxide (X_CO_2) from backscattered short-wave infrared (SWIR) sunlight measured by the Japanese Greenhouse gases Observing SATellite (GOSAT). Over two years of X_CO_2 retrieved from GOSAT is compared with X_CO_2 inferred from collocated SWIR measurements by seven ground-based Total Carbon Column Observing Network (TCCON) stations. The average difference between GOSAT and TCCON X_CO_2 for individual TCCON sites ranges from −0.87 ppm to 0.77 ppm with a mean value of 0.1 ppm and standard deviation of 0.56 ppm. We find an average bias between all GOSAT and TCCON X_CO_2 retrievals of −0.20 ppm with a standard deviation of 2.26 ppm and a correlation coefficient of 0.75. One year of XCO2 was retrieved from GOSAT globally, which was compared to global 3-D GEOS-Chem chemistry transport model calculations. We find that the latitudinal gradient, seasonal cycles, and spatial variability of GOSAT and GEOS-Chem agree well in general with a correlation coefficient of 0.61. Regional differences between GEOS-Chem model calculations and GOSAT observations are typically less than 1 ppm except for the Sahara and central Asia where a mean difference between 2 to 3 ppm is observed, indicating regional biases in the GOSAT X_CO_2 retrievals unobserved by the current TCCON network. Using a bias correction scheme based on linear regression these regional biases are significantly reduced, approaching the required accuracy for surface flux inversions.

On the Sources of Methane to the Los Angeles Atmosphere

We use historical and new atmospheric trace gas observations to refine the estimated source of methane (CH(4)) emitted into Californias 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.

Four corners: The largest US methane anomaly viewed from space

Methane (CH4) is a potent greenhouse gas and ozone precursor. Quantifying methane emissions is critical for projecting and mitigating changes to climate and air quality. Here we present CH4 observations made from space combined with Earth-based remote sensing column measurements. Results indicate the largest anomalous CH4 levels viewable from space over the conterminous U.S. are located at the Four Corners region in the Southwest U.S. Emissions exceeding inventory estimates, totaling 0.59 Tg CH4/yr [0.50–0.67; 2σ], are necessary to bring high-resolution simulations and observations into agreement. This underestimated source approaches 10% of the EPA estimate of total U.S. CH4 emissions from natural gas. The persistence of this CH4 signal from 2003 onward indicates that the source is likely from established gas, coal, and coalbed methane mining and processing. This work demonstrates that space-based observations can identify anomalous CH4 emission source regions and quantify their emissions with the use of a transport model.

Global CO2 fluxes inferred from surface air-sample measurements and from TCCON retrievals of the CO2 total column

We present the first estimate of the global distribution of CO_2 surface fluxes from 14 stations of the Total Carbon Column Observing Network (TCCON). The evaluation of this inversion is based on 1) comparison with the fluxes from a classical inversion of surface air-sample-measurements, and 2) comparison of CO_2 mixing ratios calculated from the inverted fluxes with independent aircraft measurements made during the two years analyzed here, 2009 and 2010. The former test shows similar seasonal cycles in the northern hemisphere and consistent regional carbon budgets between inversions from the two datasets, even though the TCCON inversion appears to be less precise than the classical inversion. The latter test confirms that the TCCON inversion has improved the quality (i.e., reduced the uncertainty) of the surface fluxes compared to the assumed or prior fluxes. The consistency between the surface-air-sample-based and the TCCON-based inversions despite remaining flaws in transport models opens the possibility of increased accuracy and robustness of flux inversions based on the combination of both data sources and confirms the usefulness of space-borne monitoring of the CO_2 column.