ALBERT

Description: We describe a method of evaluating systematic errors in measurements of total column dry-air mole fractions of CO2 (XCO2) from space, and we illustrate the method by applying it to the v2.8 Atmospheric CO2 Observations from Space retrievals of the Greenhouse Gases Observing Satellite (ACOS-GOSAT) measurements over land. The approach exploits the lack of large gradients in XCO2 south of 25° S to identify large-scale offsets and other biases in the ACOS-GOSAT data with several retrieval parameters and errors in instrument calibration. We demonstrate the effectiveness of the method by comparing the ACOS-GOSAT data in the Northern Hemisphere with ground truth provided by the Total Carbon Column Observing Network (TCCON). We use the observed correlation between free-tropospheric potential temperature and XCO2 in the Northern Hemisphere to define a dynamically informed coincidence criterion between the ground-based TCCON measurements and the ACOS-GOSAT measurements. We illustrate that this approach provides larger sample sizes, hence giving a more robust comparison than one that simply uses time, latitude and longitude criteria. Our results show that the agreement with the TCCON data improves after accounting for the systematic errors, but that extrapolation to conditions found outside the region south of 25° S may be problematic (e.g., high airmasses, large surface pressure biases, M-gain, measurements made over ocean). A preliminary evaluation of the improved v2.9 ACOS-GOSAT data is also discussed.

Description: We analyse the carbon monoxide (CO), ethane (C2H6) and hydrogen cyanide (HCN) partial columns (from the ground to 12 km) derived from measurements by ground-based solar Fourier Transform Spectroscopy at Lauder, New Zealand (45° S, 170° E), and at Arrival Heights, Antarctica (78° S, 167° E), from 1997 to 2009. Significant negative trends are calculated for all species at both locations, based on the daily-mean observed time series, namely CO (−0.94 ± 0.47% yr−1), C2H6 (−2.37 ± 1.18% yr−1) and HCN (−0.93 ± 0.47% yr−1) at Lauder and CO (−0.92 ± 0.46% yr−1), C2H6 (−2.82 ± 1.37% yr−1) and HCN (−1.41 ± 0.71% yr−1) at Arrival Heights. The uncertainties reflect the 95% confidence limits. However, the magnitudes of the trends are influenced by the anomaly associated with the 1997–1998 El Niño Southern Oscillation event at the beginning of the time series reported. We calculate trends for each month from 1997 to 2009 and find negative trends for all months. The largest monthly trends of CO and C2H6 at Lauder, and to a lesser degree at Arrival Heights, occur during austral spring during the Southern Hemisphere tropical and subtropical biomass burning period. For HCN, the largest monthly trends occur in July and August at Lauder and around November at Arrival Heights. The correlations between CO and C2H6 and between CO and HCN at Lauder in September to November, when the biomass burning maximizes, are significantly larger that those in other seasons. A tropospheric chemistry-climate model is used to simulate CO, C2H6, and HCN partial columns for the period of 1997–2009, using interannually varying biomass burning emissions from GFED3 and annually periodic but seasonally varying emissions from both biogenic and anthropogenic sources. The model-simulated partial columns of these species compare well with the measured partial columns and the model accurately reproduces seasonal cycles of all three species at both locations. However, while the model satisfactorily captures both the seasonality and trends in HCN, it is not able to reproduce the negative trends in either C2H6 or CO. A further simulation assuming a 35% decline of C2H6 and a 26% decline of CO emissions from the industrial sources from 1997 to 2009 largely captures the observed trends of C2H6 and CO partial columns at both locations. Here we attribute trends in HCN exclusively to changes in biomass burning and thereby isolate the influence of anthropogenic emissions as responsible for the long-term decline in CO and C2H6. This analysis shows that biomass burning emissions are the main factors in controlling the interannual and seasonal variations of these species. We also demonstrate contributions of biomass burning emission from different southern tropical and sub-tropical regions to seasonal and interannual variations of CO at Lauder; it shows that long-range transport of biomass burning emissions from southern Africa and South America have consistently larger year-to-year contributions to the background seasonality of CO at Lauder than those from other regions (e.g. Australia and South-East Asia). However, large interannual anomalies are triggered by variations in biomass burning emissions associated with large-scale El Niño Southern Oscillation and prolonged biomass burning events, e.g. the Australian bush fires.

Description: We describe a method of evaluating systematic errors in measurements of total column dry-air mole fractions of CO2 (XCO2) from space, and we illustrate the method by applying the method to the Atmospheric CO2 Observations from Space retrievals of the Greenhouse Gases Observing Satellite (ACOS-GOSAT) v2.8 data. The approach exploits the lack of large gradients in XCO2 south of 25° S to identify large-scale offsets and other biases in the ACOS-GOSAT data with several retrieval parameters and errors in instrument calibration. We demonstrate the effectiveness of the method by comparing the ACOS-GOSAT data in the Northern Hemisphere with ground truth provided by the Total Carbon Column Observing Network (TCCON). We use the correlation between free-tropospheric temperature and XCO2 in the Northern Hemisphere to define a dynamically informed coincidence criterion between the ground-based TCCON measurements and the ACOS-GOSAT measurements. We illustrate that this approach provides larger sample sizes, hence giving a more robust comparison than one that simply uses time, latitude and longitude criteria. Our results show that the agreement with the TCCON data improves after accounting for the systematic errors.

Description: We investigate factors that drive the variability in total column CO2 at the Total Carbon Column Observing Network sites in the Southern Hemisphere using CarbonTracker analysed fluxes tagged by process and by source region. We show that the terrestrial biosphere is the largest driver of variability in the Southern Hemisphere column CO2, however, it does not dominate in the same fashion as in the Northern Hemisphere. Local and hemispheric scale biomass burning can also play an important role, particularly at the tropical site, Darwin. The magnitude of seasonal variability in the column-average dry-air mole fraction of CO2, XCO2, is also much smaller in the Southern Hemisphere and comparable in magnitude to the annual increase. Comparison of measurements to the model simulations highlights that there is some discrepancy between the two timeseries, especially in the early part of the Darwin data record. We show that this mismatch is most likely due to erroneously estimated local fluxes in the Australian tropical region, which are associated with enhanced photosynthesis caused by early rainfall during the tropical monsoon season.

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

Description: We analyse the carbon monoxide (CO), ethane (C2H6) and hydrogen cyanide (HCN) partial columns (from the ground to 12 km) derived from measurements by ground-based solar Fourier Transform Spectroscopy at Lauder, New Zealand (45° S, 170° E) and at Arrival Heights, Antarctica (78° S, 167° E) from 1997 to 2009. Significant negative trends are calculated for all species at both locations: CO (−0.90 ± 0.31% yr−1) and C2H6 (−3.10 ± 1.07% yr−1) at Arrival Heights and CO (−0.87 ± 0.30% yr−1), C2H6 (−2.70 ± 0.94% yr−1) and HCN (−0.93 ± 0.32% yr−1) at Lauder. The uncertainties reflect the 95% confidence limits. The dominant seasonal trends of CO and C2H6 at Lauder, and to a lesser degree at Arrival Heights, occur in austral spring when the correlations between CO and C2H6 and between CO and HCN maximize. Tropospheric columns of all three species are characterised by minima in March–June and maxima from August to November; this season is the southern-hemisphere tropical and sub-tropical biomass burning period. A tropospheric chemistry-climate model is used to simulate CO and C2H6 columns for the period of 1997–2009 using interannually varying biomass burning emissions; the model simulated tropospheric columns of CO and C2H6 compare well with the measured partial columns of both species. However, the model does not re-produce the significant negative trends of observed CO and C2H6 partial columns at both locations. Weak negative trends are calculated from model data. The model sensitivity calculations indicate that long-range transport of biomass burning emissions from Southern Africa and South America dominate the seasonal cycles of CO and C2H6 at both Lauder and Arrival Heights. Interannual variability of these compounds at both locations is largely triggered by variations in biomass burning emissions associated with large-scale El Nino Southern Oscillation and prolonged biomass burning events, e.g. the Australian bush fires.

Description: Here, we report preliminary estimates of the column averaged carbon dioxide (CO2) dry air mole fraction, XCO2, retrieved from spectra recorded over land by the Greenhouse gases Observing Satellite, GOSAT (nicknamed "Ibuki"), using retrieval methods originally developed for the NASA Orbiting Carbon Observatory (OCO) mission. After screening for clouds and other known error sources, these retrievals reproduce much of the expected structure in the global XCO2 field, including its variation with latitude and season. However, low yields of retrieved XCO2 over persistently cloudy areas and ice covered surfaces at high latitudes limit the coverage of some geographic regions, even on seasonal time scales. Comparisons of early GOSAT XCO2 retrievals with XCO2 estimates from the Total Carbon Column Observing Network (TCCON) revealed a global, −2% (7–8 parts per million, ppm, with respect to dry air) XCO2 bias and 2 to 3 times more variance in the GOSAT retrievals. About half of the global XCO2 bias is associated with a systematic, 1% overestimate in the retrieved air mass, first identified as a global +10 hPa bias in the retrieved surface pressure. This error has been attributed to errors in the O2 A-band absorption cross sections. Much of the remaining bias and spurious variance in the GOSAT XCO2 retrievals has been traced to uncertainties in the instrument's calibration, oversimplified methods for generating O2 and CO2 absorption cross sections, and other subtle errors in the implementation of the retrieval algorithm. Many of these deficiencies have been addressed in the most recent version (Build 2.9) of the retrieval algorithm, which produces negligible bias in XCO2 on global scales as well as a ~30% reduction in variance. Comparisons with TCCON measurements indicate that regional scale biases remain, but these could be reduced by applying empirical corrections like those described by Wunch et al. (2011b). We recommend that such corrections be applied before these data are used in source sink inversion studies to minimize spurious fluxes associated with known biases. These and other lessons learned from the analysis of GOSAT data are expected to accelerate the delivery of high quality data products from the Orbiting Carbon Observatory-2 (OCO-2), once that satellite is successfully launched and inserted into orbit.

Description: The TCCON (Total Carbon Column Observing Network) FTIR (Fourier transform infrared) network provides highly accurate observations of greenhouse gas column-averaged dry-air mole fractions. As an important component of TCCON quality assurance, sealed cells filled with approximately 5 mbar of HCl are used for instrumental line shape (ILS) monitoring at all TCCON sites. Here, we introduce a calibration procedure for the HCl cells which employs a refillable, pressure-monitored reference cell filled with C2H2. Using this method, we identify variations of HCl purity between the TCCON cells as a non-negligible disturbance. The new calibration procedure introduced here assigns effective pressure values to each individual cell to account for additional broadening of the HCl lines. This approach will improve the consistency of the network by significantly reducing possible station-to-station biases due to inconsistent ILS results from different HCl cells. We demonstrate that the proposed method is accurate enough to turn the ILS uncertainty into an error source of secondary importance from the viewpoint of network consistency.

Description: The Total Carbon Column Observing Network (TCCON) has been established to provide ground-based remote sensing measurements of the column-averaged dry air mole fractions (DMF) of key greenhouse gases. To ensure network-wide consistency, biases between Fourier transform spectrometers at different sites have to be well controlled. Errors in interferogram sampling can introduce significant biases in retrievals. In this study we investigate a two-step scheme to correct these errors. In the first step the laser sampling error (LSE) is estimated by determining the sampling shift which minimises the magnitude of the signal intensity in selected, fully absorbed regions of the solar spectrum. The LSE is estimated for every day with measurements which meet certain selection criteria to derive the site-specific time series of the LSEs. In the second step, this sequence of LSEs is used to resample all the interferograms acquired at the site, and hence correct the sampling errors. Measurements acquired at the Izaña and Lauder TCCON sites are used to demonstrate the method. At both sites the sampling error histories show changes in LSE due to instrument interventions (e.g. realignment). Estimated LSEs are in good agreement with sampling errors inferred from the ratio of primary and ghost spectral signatures in optically bandpass-limited tungsten lamp spectra acquired at Lauder. The original time series of Xair and XCO2 (XY: column-averaged DMF of the target gas Y) at both sites show discrepancies of 0.2–0.5% due to changes in the LSE associated with instrument interventions or changes in the measurement sample rate. After resampling, discrepancies are reduced to 0.1% or less at Lauder and 0.2% at Izaña. In the latter case, coincident changes in interferometer alignment may also have contributed to the residual difference. In the future the proposed method will be used to correct historical spectra at all TCCON sites.

Description: Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water), long-term tropospheric water vapour isotopologue data records are provided for ten globally distributed ground-based mid-infrared remote sensing stations of the NDACC (Network for the Detection of Atmospheric Composition Change). We present a new method allowing for an extensive and straightforward characterisation of the complex nature of such isotopologue remote sensing datasets. We demonstrate that the MUSICA humidity profiles are representative for most of the troposphere with a vertical resolution ranging from about 2 km (in the lower troposphere) to 8 km (in the upper troposphere) and with an estimated precision of better than 10%. We find that the sensitivity with respect to the isotopologue composition is limited to the lower and middle troposphere, whereby we estimate a precision of about 30‰ for the ratio between the two isotopologues HD16O and H216O. The measurement noise, the applied atmospheric temperature profiles, the uncertainty in the spectral baseline, and the cross-dependence on humidity are the leading error sources. We introduce an a posteriori correction method of the cross-dependence on humidity, and we recommend applying it to isotopologue ratio remote sensing datasets in general. In addition, we present mid-infrared CO2 retrievals and use them for demonstrating the MUSICA network-wide data consistency. In order to indicate the potential of long-term isotopologue remote sensing data if provided with a well-documented quality, we present a climatology and compare it to simulations of an isotope incorporated AGCM (Atmospheric General Circulation Model). We identify differences in the multi-year mean and seasonal cycles that significantly exceed the estimated errors, thereby indicating deficits in the modeled atmospheric water cycle.