Thorsten Warneke

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

Tropical methane emissions: A revised view from SCIAMACHY onboard ENVISAT

Methane retrievals from near-infrared spectra recorded by the SCIAMACHY instrument onboard ENVISAT hitherto suggested unexpectedly large tropical emissions. Even though recent studies confirm substantial tropical emissions, there were indications for an unresolved error in the satellite retrievals. Here we identify a retrieval error related to inaccuracies in water vapor spectroscopic parameters, causing a substantial overestimation of methane correlated with high water vapor abundances. We report on the overall implications of an update in water spectroscopy on methane retrievals with special focus on the tropics where the impact is largest. The new retrievals are applied in a four-dimensional variational (4D-VAR) data assimilation system to derive a first estimate of the impact on tropical CH_4 sources. Compared to inversions based on previous SCIAMACHY retrievals, annual tropical emission estimates are reduced from 260 to about 201 Tg CH_4 but still remain higher than previously anticipated.

Dynamic Processes Governing Lower-Tropospheric HDO/H2O Ratios as Observed from Space and Ground

Cycling Around Water vapor is the most important greenhouse gas, and clouds are one of the most important components of climate, but the global hydrological cycle is still poorly-enough understood that the atmospheric cycling of water and cloud formation are inadequately represented in global climate models. As the transformation from liquid into vapor tends to deplete water of the isotope deuterium, Frankenburg et al. (p. 1374) were able to use satellite measurements of global “heavy” water abundances to provide a deeper understanding of atmospheric water dynamics. Tropospheric distributions of light and heavy water reveal previously unrecognized features of atmospheric circulation. The hydrological cycle and its response to environmental variability such as temperature changes is of prime importance for climate reconstruction and prediction. We retrieved deuterated water/water (HDO/H2O) abundances using spaceborne absorption spectroscopy, providing an almost global perspective on the near-surface distribution of water vapor isotopologs. We observed an unexpectedly high HDO/H2O seasonality in the inner Sahel region, pointing to a strong isotopic depletion in the subsiding branch of the Hadley circulation and its misrepresentation in general circulation models. An extension of the analysis at high latitudes using ground-based observations of δD¯ and a model study shows that dynamic processes can entirely compensate for temperature effects on the isotopic composition of precipitation.

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.

Side by side measurements of CO2 by ground-based Fourier transform spectrometry (FTS)

High resolution solar absorption Fourier transform spectrometry (FTS) is the most precise ground-based remote sensing technique to measure the total column of atmospheric carbon dioxide. For carbon cycle studies as well as for the calibration and validation of spaceborne sensors the instrumental comparability of FTS systems is of critical importance. Retrievals from colocated measurements by two identically constructed FTS systems have been compared for the first time. Under clear sky conditions a precision for the retrieved xCO2 better than ˜0.1% is demonstrated and the instruments agree within ˜0.07%. An important factor in achieving such good comparability of the xCO2 is an accurate sampling of the internal reference laser. A periodic laser mis-sampling leads to ghosts (artificial spectral lines), which are mirrored images from original spectral lines. These ghosts can interfere with the spectral range of interest. The influence of the laser mis-sampling on the retrieved xCO2 and xO2 in the near-IR has been quantified. For a typical misalignment, the ratio of the ghost intensity compared to the intensity of the original spectral line is about 0.18% and in this case the retrieved xCO2 is wrong by 0.26% (1 ppm) and the retrieved xO2 is wrong by 0.2%.

Precise methane absorption measurements in the 1.64 μm spectral region for the MERLIN mission

In this article we describe a high-precision laboratory measurement targeting the R(6) manifold of the 2ν3 band of 12CH4. Accurate physical models of this absorption spectrum will be required by the Franco-German, Methane Remote Sensing LIDAR (MERLIN) space mission for retrievals of atmospheric methane. The analysis uses the Hartmann-Tran profile for modeling line shape and also includes line-mixing effects. To this end, six high-resolution and high signal-to-noise absorption spectra of air-broadened methane were recorded using a frequency-stabilized cavity ring-down spectroscopy apparatus. Sample conditions corresponded to room temperature and spanned total sample pressures of 40 hPa - 1013 hPa with methane molar fractions between 1 μmol mol-1 and 12 μmol mol-1. All spectroscopic model parameters were simultaneously adjusted in a multispectrum nonlinear least-squares fit to the six measured spectra. Comparison of the fitted model to the measured spectra reveals the ability to calculate the room-temperature, methane absorption coefficient to better than 0.1% at the on-line position of the MERLIN mission. This is the first time that such fidelity has been reached in modeling methane absorption in the investigated spectral region, fulfilling the accuracy requirements of the MERLIN mission. We also found excellent agreement when comparing the present results with measurements obtained over different pressure conditions and using other laboratory techniques. Finally, we also evaluated the impact of these new spectral parameters on atmospheric transmissions spectra calculations.

The impact of disturbed peatlands on river outgassing in Southeast Asia

River outgassing has proven to be an integral part of the carbon cycle. In Southeast Asia, river outgassing quantities are uncertain due to lack of measured data. Here we investigate six rivers in Indonesia and Malaysia, during five expeditions. CO2 fluxes from Southeast Asian rivers amount to 66.9±15.7 Tg C per year, of which Indonesia releases 53.9±12.4 Tg C per year. Malaysian rivers emit 6.2±1.6 Tg C per year. These moderate values show that Southeast Asia is not the river outgassing hotspot as would be expected from the carbon-enriched peat soils. This is due to the relatively short residence time of dissolved organic carbon (DOC) in the river, as the peatlands, being the primary source of DOC, are located near the coast. Limitation of bacterial production, due to low pH, oxygen depletion or the refractory nature of DOC, potentially also contributes to moderate CO2 fluxes as this decelerates decomposition.

CH4 concentrations over the Amazon from GOSAT consistent with in situ vertical profile data

We thank JAXA and NIES for providing access and support for GOSAT data. We thank the NERC and FAPESP for their joint funding of the Amazonian Carbon Observatory Project (NERC Reference: NE/J016284/1). A. Webb is funded by the UK Natural Environment Research Council (NERC). H. Bosch and R. Parker are supported by the NERC National Centre for Earth Observation (NCEO) and the ESA Climate Change Initiative (GHG-CCI). Parker is also funded via an ESA Living Planet Fellowship. M. Gloor was financially supported by the NERC consortium grant AMAZONICA (NE/F005806/1) which we also thank for providing access to additional aircraft profiles. We thank BADC for providing ECMWF data. Research at the University of Edinburgh is funded by the NERC grant NE/J016195/1. P. Palmer acknowledges his Royal Society Wolfson Research Merit Award. The University of Leicester GOSAT data are freely available through the ESA GHG-CCI website (www.esa-ghg-cci.org). ACO data will be made available through the British Atmospheric Data Centre (BADC) (www.badc.nerc.ac.uk/data/), and AMAZONICA data are available upon request by L. V. Gatti (lvgatti@gmail.com). ECMWF ERA-Interim data are available through the ECMWF website (http://apps.ecmwf.int/datasets/). Access to the MACC-II data can be requested from the ECMWF MARS data server (experiment ID g4om, www.ecmwf.int/en/forecasts/datasets). Paramaribo-FTS data are available upon request from T. Warneke (warneke@iup.physik.uni-bremen.de). GEOS-Chem model and metadata are freely available upon request by P. Palmer (pip@ed.ac.uk). TOMCAT model output can be requested from M. Chipperfield (M.Chipperfield@leeds.ac.uk), who acknowledges his Royal Society Wolfson Research Merit award. This research used the SPECTRE and ALICE High Performance Computing Facilities at the University of Leicester. The TOMCAT model was run on the Archer national supercomputer. We thank CEDA for use of the JASMIN supercomputer system on which we run the NAME model.

Near-Infrared Lunar Absorption Spectroscopy for the Retrieval of Column Averaged CO2 and CH4

High resolution Fourier-Transform InfraRed (FTIR) absorption spectroscopic measurements are used to retrieve trace gas abundances in the atmosphere at a number of sites throughout the world. Typically, the sun is used as an infrared light source above the atmosphere of the Earth, however, at polar sites, such as our measurement site at Spitsbergen, sunlight is not available during polar night (October–March). Instead, the moon can be used as a substitute infrared light source. In this article we present a proof of concept for the usage of a thermoelectrically cooled InGaAs (Indium-Gallium-Arsenide) near infrared detector to measure the column averaged trace gas abundances by lunar absorption spectroscopy based on trial measurements made in Bremen. These measurements demonstrate the potential of using lunar measurements for retrieval of atmospheric columns of CO2 and CH4. The resulting data can be used to fill a crucial gap in the seasonal cycle at polar sites.