Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

Continuous CO2/CH4/CO measurements (2012–2014) at Beromünster tall tower station in Switzerland

The understanding of the continental carbon budget is essential to predict future climate change. In order to quantify CO₂ and CH₄ fluxes at the regional scale, a measurement system was installed at the former radio tower in Beromünster as part of the Swiss greenhouse gas monitoring network (CarboCount CH). We have been measuring the mixing ratios of CO₂, CH₄ and CO on this tower with sample inlets at 12.5, 44.6, 71.5, 131.6 and 212.5 m above ground level using a cavity ring down spectroscopy (CRDS) analyzer. The first 2-year (December 2012–December 2014) continuous atmospheric record was analyzed for seasonal and diurnal variations and interspecies correlations. In addition, storage fluxes were calculated from the hourly profiles along the tower. The atmospheric growth rates from 2013 to 2014 determined from this 2-year data set were 1.78 ppm yr⁻¹, 9.66 ppb yr⁻¹ and and -1.27 ppb yr⁻¹ for CO₂, CH₄ and CO, respectively. After detrending, clear seasonal cycles were detected for CO₂ and CO, whereas CH₄ showed a stable baseline suggesting a net balance between sources and sinks over the course of the year. CO and CO₂ were strongly correlated (r² > 0.75) in winter (DJF), but almost uncorrelated in summer. In winter, anthropogenic emissions dominate the biospheric CO₂ fluxes and the variations in mixing ratios are large due to reduced vertical mixing. The diurnal variations of all species showed distinct cycles in spring and summer, with the lowest sampling level showing the most pronounced diurnal amplitudes. The storage flux estimates exhibited reasonable diurnal shapes for CO₂, but underestimated the strength of the surface sinks during daytime. This seems plausible, keeping in mind that we were only able to calculate the storage fluxes along the profile of the tower but not the flux into or out of this profile, since no Eddy covariance flux measurements were taken at the top of the tower.

CH4, CO, and H2O spectroscopy for the Sentinel-5 Precursor mission: an assessment with the Total Carbon Column Observing Network measurements

The TROPOspheric Monitoring Instrument (TROPOMI) will be part of ESA's Sentinel-5 Precursor (S5P) satellite platform scheduled for launch in 2015. TROPOMI will monitor methane and carbon monoxide concentrations in the Earth's atmosphere by measuring spectra of back-scattered sunlight in the short-wave infrared (SWIR). S5P will be the first satellite mission to rely uniquely on the spectral window at 4190–4340 cm−1 (2.3 μm) to retrieve CH4 and CO. In this study, we investigated if the absorption features of the three relevant molecules CH4, CO, and H2O are adequately known. To this end, we retrieved total columns of CH4, CO, and H2O from absorption spectra measured by two ground-based Fourier transform spectrometers that are part of the Total Carbon Column Observing Network (TCCON). The retrieval results from the 4190–4340 cm−1 range at the TROPOMI resolution (0.45 cm−1) were then compared to the CH4 results obtained from the 6000 cm−1 region, and the CO results obtained from the 4190–4340 cm−1 region at the higher TCCON resolution (0.02 cm−1). For TROPOMI-like settings, we were able to reproduce the CH4 columns to an accuracy of 0.3% apart from a constant bias of 1%. The CO retrieval accuracy was, through interference, systematically influenced by the shortcomings of the CH4 and H2O spectroscopy. In contrast to CH4, the CO column error also varied significantly with atmospheric H2O content. Unaddressed, this would introduce seasonal and latitudinal biases to the CO columns retrieved from TROPOMI measurements. We therefore recommend further effort from the spectroscopic community to be directed at the H2O and CH4 spectroscopy in the 4190–4340 cm−1 region.

Divalent metal-ion transporter DMT1 mediates both H+ -coupled Fe2+ transport and uncoupled fluxes

The H(+) -coupled divalent metal-ion transporter DMT1 serves as both the primary entry point for iron into the body (intestinal brush-border uptake) and the route by which transferrin-associated iron is mobilized from endosomes to cytosol in erythroid precursors and other cells. Elucidating the molecular mechanisms of DMT1 will therefore increase our understanding of iron metabolism and the etiology of iron overload disorders. We expressed wild type and mutant DMT1 in Xenopus oocytes and monitored metal-ion uptake, currents and intracellular pH. DMT1 was activated in the presence of an inwardly directed H(+) electrochemical gradient. At low extracellular pH (pH(o)), H(+) binding preceded binding of Fe(2+) and its simultaneous translocation. However, DMT1 did not behave like a typical ion-coupled transporter at higher pH(o), and at pH(o) 7.4 we observed Fe(2+) transport that was not associated with H(+) influx. His(272) --> Ala substitution uncoupled the Fe(2+) and H(+) fluxes. At low pH(o), H272A mediated H(+) uniport that was inhibited by Fe(2+). Meanwhile H272A-mediated Fe(2+) transport was independent of pH(o). Our data indicate (i) that H(+) coupling in DMT1 serves to increase affinity for Fe(2+) and provide a thermodynamic driving force for Fe(2+) transport and (ii) that His-272 is critical in transducing the effects of H(+) coupling. Notably, our data also indicate that DMT1 can mediate facilitative Fe(2+) transport in the absence of a H(+) gradient. Since plasma membrane expression of DMT1 is upregulated in liver of hemochromatosis patients, this H(+) -uncoupled facilitative Fe(2+) transport via DMT1 can account for the uptake of nontransferrin-bound plasma iron characteristic of iron overload disorders.

Time- and dose-related regional fluxes of tissue-type plasminogen activator in anesthetized endotoxemic pigs

BACKGROUND: Acute endotoxinemia elicits an early fibrinolytic response. This study analyzes the effects of the dose and duration of endotoxin infusion on arterial levels of tissue-type plasminogen activator (tPA) and pulmonary, mesenteric and hepatic plasma tPA fluxes. METHODS: Pigs were randomized to receive an acute, high-dose (for 6 h, n=13, high ETX) or a prolonged, low-dose (for 18 h, n=18, low ETX) infusion of endotoxin or saline vehicle alone (for 18 h, n=14, control). All animals were fluid resuscitated to maintain a normodynamic circulation. Systemic and regional blood flows were measured and arterial, pulmonary arterial, portal and hepatic venous blood samples were analyzed to calculate regional net fluxes of tPA. Plasma tumor necrosis factor (TNF-alpha) levels were analyzed. RESULTS: Mesenteric tPA release and hepatic uptake increased maximally at 1.5 h in ETX groups related to dose. Maximal mesenteric tPA release [high ETX 612 (138-1185) microg/min/kg, low ETX 72 (32-94) microg/min/kg, median+/-interquartile range] and hepatic tPA uptake [high ETX -1549 (-1134 to -2194) microg/min/kg, low ETX -153 (-105 to -307) microg/min/kg] correlated to TNF-alpha levels. Regional tPA fluxes returned to baseline levels at 6 h in both ETX groups and also remained low during sustained low ETX. No changes were observed in control animals. CONCLUSIONS: Endotoxemia induces an early increase in mesenteric tPA release and hepatic tPA uptake related to the severity of endotoxemia. The time patterns of changes in mesenteric and hepatic tPA fluxes are similar in acute high-dose endotoxemia and sustained low-dose endotoxemia.

Tree phenology and carbon dioxide fluxes - use of digital photography for process-based interpretation at the ecosystem scale

Vegetation phenology is an important indicator of climate change and climate variability and it is strongly connected to biospheric–atmospheric gas exchange. We aimed to evaluate the applicability of phenological information derived from digital imagery for the interpretation of CO2 exchange measurements. For the years 2005–2007 we analyzed seasonal phenological development of 2 temperate mixed forests using tower-based imagery from standard RGB cameras. Phenological information was jointly analyzed with gross primary productivity (GPP) derived from net ecosystem exchange data. Automated image analysis provided reliable information on vegetation developmental stages of beech and ash trees covering all seasons. A phenological index derived from image color values was strongly correlated with GPP, with a significant mean time lag of several days for ash trees and several weeks for beech trees in early summer (May to mid-July). Leaf emergence dates for the dominant tree species partly explained temporal behaviour of spring GPP but were also masked by local meteorological conditions. We conclude that digital cameras at flux measurement sites not only provide an objective measure of the physiological state of a forest canopy at high temporal and spatial resolutions, but also complement CO2 and water exchange measurements, improving our knowledge of ecosystem processes.