Christian Frankenberg

Inverse modeling of global and regional CH4 emissions using SCIAMACHY satellite retrievals

Methane retrievals from the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) instrument onboard ENVISAT provide important information on atmospheric CH_4 sources, particularly in tropical regions which are poorly monitored by in situ surface observations. Recently, Frankenberg et al. (2008a, 2008b) reported a major revision of SCIAMACHY retrievals due to an update of spectroscopic parameters of water vapor and CH_4. Here, we analyze the impact of this revision on global and regional CH_4 emissions estimates in 2004, using the TM5-4DVAR inverse modeling system. Inversions based on the revised SCIAMACHY retrievals yield ∼20% lower tropical emissions compared to the previous retrievals. The new retrievals improve significantly the consistency between observed and assimilated column average mixing ratios and the agreement with independent validation data. Furthermore, the considerable latitudinal and seasonal bias correction of the previous SCIAMACHY retrievals, derived in the TM5-4DVAR system by simultaneously assimilating high-accuracy surface measurements, is reduced by a factor of ∼3. The inversions result in significant changes in the spatial patterns of emissions and their seasonality compared to the bottom-up inventories. Sensitivity tests were done to analyze the robustness of retrieved emissions, revealing some dependence on the applied a priori emission inventories and OH fields. Furthermore, we performed a detailed validation of simulated CH_4 mixing ratios using NOAA ship and aircraft profile samples, as well as stratospheric balloon samples, showing overall good agreement. We use the new SCIAMACHY retrievals for a regional analysis of CH_4 emissions from South America, Africa, and Asia, exploiting the zooming capability of the TM5 model. This allows a more detailed analysis of spatial emission patterns and better comparison with aircraft profiles and independent regional emission estimates available for South America. Large CH_4 emissions are attributed to various wetland regions in tropical South America and Africa, seasonally varying and opposite in phase with CH_4 emissions from biomass burning. India, China and South East Asia are characterized by pronounced emissions from rice paddies peaking in the third quarter of the year, in addition to further anthropogenic emissions throughout the year.

New global observations of the terrestrial carbon cycle from GOSAT: patterns of plant fluorescence with gross primary productivity

Our ability to close the Earths carbon budget and predict feedbacks in a warming climate depends critically on knowing where, when and how carbon dioxide is exchanged between the land and atmosphere. Terrestrial gross primary production (GPP) constitutes the largest flux component in the global carbon budget, however significant uncertainties remain in GPP estimates and its seasonality. Empirically, we show that global spaceborne observations of solar induced chlorophyll fluorescence – occurring during photosynthesis – exhibit a strong linear correlation with GPP. We found that the fluorescence emission even without any additional climatic or model information has the same or better predictive skill in estimating GPP as those derived from traditional remotely-sensed vegetation indices using ancillary data and model assumptions. In boreal summer the generally strong linear correlation between fluorescence and GPP models weakens, attributable to discrepancies in savannas/croplands (18–48% higher fluorescence-based GPP derived by simple linear scaling), and high-latitude needleleaf forests (28–32% lower fluorescence). Our results demonstrate that retrievals of chlorophyll fluorescence provide direct global observational constraints for GPP and open an entirely new viewpoint on the global carbon cycle. We anticipate that global fluorescence data in combination with consolidated plant physiological fluorescence models will be a step-change in carbon cycle research and enable an unprecedented robustness in the understanding of the current and future carbon cycle.

Satellite chartography of atmospheric methane from SCIAMACHY on board ENVISAT: 2. Evaluation based on inverse model simulations

We extend the analysis of a global CH_4 data set retrieved from SCIAMACHY (Frankenberg et al., 2006) by making a detailed comparison with inverse TM5 model simulations for 2003 that are optimized versus high accuracy CH_4 surface measurements from the NOAA ESRL network. The comparison of column averaged mixing ratios over remote continental and oceanic regions shows that major features of the atmospheric CH_4 distribution are consistent between SCIAMACHY observations and model simulations. However, the analysis suggests that SCIAMACHY CH_4 retrievals may have some bias that depends on latitude and season (up to ∼30 ppb). Large enhancements of column averaged CH_4 mixing ratios (∼50–100 ppb) are observed and modeled over India, Southeast Asia, and the tropical regions of South America, and Africa. We present a detailed comparison of observed spatial patterns and their seasonal evolution with TM5 1° × 1° zoom simulations over these regions. Application of a new wetland inventory leads to a significant improvement in the agreement between SCIAMACHY retrievals and model simulations over the Amazon basin during the first half of the year. Furthermore, we present an initial coupled inversion that simultaneously uses the surface and satellite observations and that allows the inverse system to compensate for the potential systematic bias. The results suggest significantly greater tropical emissions compared to either the a priori estimates or the inversion based on the surface measurements only. Emissions from rice paddies in India and Southeast Asia are relatively well constrained by the SCIAMACHY data and are slightly reduced by the inversion.

Large-Scale Controls of Methanogenesis Inferred from Methane and Gravity Spaceborne Data

Measuring Methanogenesis After carbon dioxide, methane is the second most important greenhouse gas, and an important species in terms of its role in atmospheric chemistry. The sources and sinks of methane, particularly the natural ones, are too poorly quantified, however, even to explain why the decades-long, steady increase of its concentration in the atmosphere was interrupted between 1999 and 2006. Bloom et al. (p. 322) use a combination of satellite data, which indicate water table depth and surface temperature, and atmospheric methane concentrations to determine the location and strength of methane emissions from wetlands, the largest natural global source. The constraints placed on these sources should help to improve predictions of how climate change will affect wet-land emissions of methane. Satellite measurements allow the strength of wetland emissions of methane to be determined. Wetlands are the largest individual source of methane (CH4), but the magnitude and distribution of this source are poorly understood on continental scales. We isolated the wetland and rice paddy contributions to spaceborne CH4 measurements over 2003–2005 using satellite observations of gravity anomalies, a proxy for water-table depth Γ, and surface temperature analyses TS. We find that tropical and higher-latitude CH4 variations are largely described by Γ and TS variations, respectively. Our work suggests that tropical wetlands contribute 52 to 58% of global emissions, with the remainder coming from the extra-tropics, 2% of which is from Arctic latitudes. We estimate a 7% rise in wetland CH4 emissions over 2003–2007, due to warming of mid-latitude and Arctic wetland regions, which we find is consistent with recent changes in atmospheric CH4.

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.

Global column‐averaged methane mixing ratios from 2003 to 2009 as derived from SCIAMACHY: Trends and variability

After a decade of stable or slightly decreasing global methane concentrations, ground-based in situ data show that CH_4 began increasing again in 2007 and that this increase continued through 2009. So far, space-based retrievals sensitive to the lower troposphere in the time period under consideration have not been available. Here we report a long-term data set of column-averaged methane mixing ratios retrieved from spectra of the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) instrument onboard Envisat. The retrieval quality after 2005 was severely affected by degrading detector pixels within the methane 2ν_3 absorption band. We identified the most crucial problems in SCIAMACHY detector degradation and overcame the problem by applying a strict pixel mask as well as a new dark current characterization. Even though retrieval precision after the end of 2005 is invariably degraded, consistent methane retrievals from 2003 through 2009 are now possible. Regional time series in the Sahara, Australia, tropical Africa, South America, and Asia show the methane increase in 2007–2009, but we cannot yet draw a firm conclusion concerning the origin of the increase. Tropical Africa even seems to exhibit a negative anomaly in 2006, but an impact from changes in SCIAMACHY detector degradation cannot be excluded yet. Over Assakrem, Algeria, we observed strong similarities between SCIAMACHY measurements and ground-based data in deseasonalized time series. We further show long-term SCIAMACHY xCH_4 averages at high spatial resolution that provide further insight into methane variations on regional scales. The Red Basin in China exhibits, on average, the highest methane abundance worldwide, while other localized features such as the Sudd wetlands in southern Sudan can also be identified in SCIAMACHY xCH_4 averages.

Constraining global methane emissions and uptake by ecosystems

Natural methane (CH 4) emissions from wet ecosystems are an important part of today’s global CH 4 budget. Climate affects the exchange of CH 4 between ecosystems and the atmosphere by influencing CH 4 production, oxidation, and transport in the soil. The net CH 4 exchange depends on ecosystem hydrology, soil and vegetation characteristics. Here, the LPJ-WHyMe global dynamical vegetation model is used to simulate global net CH 4 emissions for different ecosystems: northern peatlands (45 –90 N), naturally inundated wetlands (60 ◦ S–45 N), rice agriculture and wet mineral soils. Mineral soils are a potential CH 4 sink, but can also be a source with the direction of the net exchange depending on soil moisture content. The geographical and seasonal distributions are evaluated against multi-dimensional atmospheric inversions for 2003–2005, using two independent four-dimensional variational assimilation systems. The atmospheric inversions are constrained by the atmospheric CH4 observations of the SCIAMACHY satellite instrument and global surface networks. Compared to LPJ-WHyMe the inversions result in a significant reduction in the emissions from northern peatlands and suggest that LPJ-WHyMe maximum annual emissions peak about one month late. The Correspondence to: R. Spahni (spahni@climate.unibe.ch) inversions do not put strong constraints on the division of sources between inundated wetlands and wet mineral soils in the tropics. Based on the inversion results we diagnose model parameters in LPJ-WHyMe and simulate the surface exchange of CH4 over the period 1990–2008. Over the whole period we infer an increase of global ecosystem CH 4 emissions of+1.11 Tg CH4 yr−1, not considering potential additional changes in wetland extent. The increase in simulated CH4 emissions is attributed to enhanced soil respiration resulting from the observed rise in land temperature and in atmospheric carbon dioxide that were used as input. The longterm decline of the atmospheric CH 4 growth rate from 1990 to 2006 cannot be fully explained with the simulated ecosystem emissions. However, these emissions show an increasing trend of+3.62 Tg CH4 yr−1 over 2005–2008 which can partly explain the renewed increase in atmospheric CH 4 conentration during recent years.

Space-based observations of megacity carbon dioxide

Urban areas now house more than half the worlds population, and are estimated to contribute over 70% of global energy-related CO_2 emissions. Many cities have emission reduction policies in place, but lack objective, observation-based methods for verifying their outcomes. Here we demonstrate the potential of satellite-borne instruments to provide accurate global monitoring of megacity CO_2 emissions using GOSAT observations of column averaged CO_2 dry air mole fraction (X_(CO_2)) collected over Los Angeles and Mumbai. By differencing observations over the megacity with those in nearby background, we observe robust, statistically significant X_(CO_2) enhancements of 3.2 ± 1.5 ppm for Los Angeles and 2.4 ± 1.2 ppm for Mumbai, and find these enhancements can be exploited to track anthropogenic emission trends over time. We estimate that X_(CO_2) changes as small as 0.7 ppm in Los Angeles, corresponding to a 22% change in emissions, could be detected with GOSAT at the 95% confidence level.

Atmospheric constraints on global emissions of methane from plants

We investigate whether a recently proposed large source of CH_4 from vegetation can be reconciled with atmospheric measurements. Atmospheric transport model simulations with and without vegetation emissions are compared with background CH_4, δ^(13)C-CH_4 and satellite measurements. For present–day CH_4 we derive an upper limit to the newly discovered source of 125 Tg CH_4 yr^(−1). Analysis of preindustrial CH_4, however, points to 85 Tg CH_4 yr^(−1) as a more plausible limit. Model calculations with and without vegetation emissions show strikingly similar results at background surface monitoring sites, indicating that these measurements are rather insensitive to CH_4 from plants. Simulations with 125 Tg CH_4 yr^(−1) vegetation emissions can explain up to 50% of the previously reported unexpectedly high CH_4 column abundances over tropical forests observed by SCIAMACHY. Our results confirm the potential importance of vegetation emissions, and call for further research.