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Atmospheric transport models are often used to simulate the distribution of greenhouse gases (GHGs). This can be in the context of forward modeling of tracer transport using surface–atmosphere fluxes or flux estimation through inverse modeling, whereby atmospheric tracer measurements are used in combination with simulated transport. In both of these contexts, transport errors can bias the results and should therefore be minimized. Here, we analyze transport uncertainties in the commonly used Weather Research and Forecasting (WRF) model coupled with the greenhouse gas module (WRF-GHG), enabling passive tracer transport simulation of CO2 and CH4. As a mesoscale numerical weather prediction model, WRF's transport is constrained by global meteorological fields via initialization and at the lateral boundaries of the domain of interest. These global fields were generated by assimilating various meteorological data to increase the accuracy of modeled fields. However, in limited-domain models like WRF, the winds in the center of the domain can deviate considerably from these driving fields. As the accuracy of the wind speed and direction is critical to the prediction of tracer transport, maintaining a close link to the observations across the simulation domain is desired. On the other hand, a link that is too close to the global meteorological fields can degrade performance at smaller spatial scales that are better represented by the mesoscale model. In this work, we evaluated the performance of strategies for keeping WRF's meteorology compatible with meteorological observations. To avoid the complexity of assimilating meteorological observations directly, two main strategies of coupling WRF-GHG with ERA5 meteorological reanalysis data were tested over a 2-month-long simulation over the European domain: (a) restarting the model daily with fresh initial conditions (ICs) from ERA5 and (b) nudging the atmospheric winds, temperatures, and moisture to those of ERA5 continuously throughout the simulation period, using WRF's built-in four-dimensional data assimilation (FDDA) in grid-nudging mode. Meteorological variables and simulated mole fractions of CO2 and CH4 were compared against observations to assess the performance of the different strategies. We also compared planetary boundary layer height (PBLH) with radiosonde-derived estimates. Either nudging or daily restarts similarly improved the meteorology and GHG transport in our simulations, with a small advantage of using both methods in combination. However, notable differences in soil moisture were found that accumulated over the course of the simulation when not using frequent restarts. The soil moisture drift had an impact on the simulated PBLH, presumably via changing the Bowen ratio. This is partially mitigated through nudging without requiring daily restarts, although not entirely alleviated. Soil moisture drift did not have a noticeable impact on GHG performance in our case, likely because it was dominated by other errors. However, since the PBLH is critical for accurately simulating GHG transport, we recommend transport model setups that tie soil moisture to observations. Our method of frequently re-initializing simulations with meteorological reanalysis fields proved suitable for this purpose. [ABSTRACT FROM AUTHOR]

Forecasting atmospheric CO2 concentrations on synoptic timescales (∼ days) can benefit the planning of field campaigns by better predicting the location of important gradients. One aspect of this, accurately predicting the day-to-day variation in biospheric fluxes, poses a major challenge. This study aims to investigate the feasibility of using a diagnostic light-use-efficiency model, the Vegetation Photosynthesis Respiration Model (VPRM), to forecast biospheric CO2 fluxes on the timescale of a few days. As input, the VPRM model requires downward shortwave radiation, 2 m temperature, and enhanced vegetation index (EVI) and land surface water index (LSWI), both of which are calculated from MODIS reflectance measurements. Flux forecasts were performed by extrapolating the model input into the future, i.e., using downward shortwave radiation and temperature from a numerical weather prediction (NWP) model, as well as extrapolating the MODIS indices to calculate future biospheric CO2 fluxes with VPRM. A hindcast for biospheric CO2 fluxes in Europe in 2014 has been done and compared to eddy covariance flux measurements to assess the uncertainty from different aspects of the forecasting system. In total the range-normalized mean absolute error (normalized) of the 5 d flux forecast at daily timescales is 7.1 %, while the error for the model itself is 15.9 %. The largest forecast error source comes from the meteorological data, in which error from shortwave radiation contributes slightly more than the error from air temperature. The error contribution from all error sources is similar at each flux observation site and is not significantly dependent on vegetation type. [ABSTRACT FROM AUTHOR]

Forecasting atmospheric CO2 concentrations on synoptic time scales (~ days) can benefit the planning of field campaigns by better predicting the location of important gradients. One aspect of this, accurately predicting the day-to-day variation in biospheric fluxes poses a major challenge. This research aims to investigate the feasibility of using a diagnostic light-use-efficiency model, the Vegetation Photosynthesis Respiration Model (VPRM), to forecast biospheric CO2 fluxes on the time scale of a few days. As input the VPRM model requires downward shortwave radiation, 2 m temperature, and Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI), both of which are calculated from MODIS reflectance measurements. Flux forecasts were performed by extrapolating the model input into the future, i.e. using downward shortwave radiation and temperature from a numerical weather prediction (NWP) model, as well as extrapolating the MODIS indices to calculate future biospheric CO2 fluxes with VPRM. A hindcast for biospheric CO2 fluxes in Europe in 2014 has been done and compared to eddy covariance flux measurements to assess the uncertainty from different aspects of the forecasting system. In total the range-normalized mean absolute error (normalized) of the 5 day flux forecast at daily timescales is 7.1 %, while the error for the model itself is 15.9 %. The largest forecast error source comes from the meteorological data, which fail to accurately predict cloud cover, leading to overestimated shortwave radiation in the model. The error contribution from all error sources is similar at each flux observation site, and is not significantly dependent on vegetation type. [ABSTRACT FROM AUTHOR]

Airborne measurements of CO2, CO, and CH4 proposed in the context of IAGOS (In-service Aircraft for a Global Observing System) will provide profiles from take-off and landing of airliners in the vicinity of major metropolitan areas useful for constraining sources and sinks. A proposed improvement of the top-down method to constrain sources and sinks is the use of a multispecies inversion. Different species such as CO2 and CO have partially overlapping emission patterns for given fuel-combustion-related sectors, and thus share part of the uncertainties related both to the a priori knowledge of emissions and to model-data mismatch error. We use a regional modelling framework consisting of the Lagrangian particle dispersion model STILT (Stochastic Time-Inverted Lagrangian Transport) combined with the high-resolution (10 km x 10 km) EDGARv4.3 (Emission Database for Global Atmospheric Research) emission inventory, differentiated by emission sector and fuel type for CO2, CO, and CH4, and combined with the VPRM (Vegetation Photosynthesis and Respiration Model) for biospheric fluxes of CO2. Applying the modelling framework to synthetic IAGOS profile observations, we evaluate the benefits of using correlations between different species' uncertainties on the performance of the atmospheric inversion. The available IAGOS CO observations are used to validate the modelling framework. Prior uncertainty values are conservatively assumed to be 20%, for CO2 and 50% for CO and CH4, while those for GEE (gross ecosystem exchange) and respiration are derived from existing literature. Uncertainty reduction for different species is evaluated in a domain encircling 50% of the profile observations' surface influence over Europe. We found that our modelling framework reproduces the CO observations with an average correlation of 0.56, but simulates lower mixing ratios by a factor of 2.8, reflecting a low bias in the emission inventory. Mean uncertainty reduction achieved for CO2 fossil fuel emissions is roughly 38%; for photosynthesis and respiration flux it is 41 and 44% respectively. For CO and CH4 the uncertainty reduction is roughly 63 and 67% respectively. Considering correlation between different species, posterior uncertainty can be reduced by up to 23%; such a reduction depends on the assumed error structure of the prior and on the considered time frame. The study suggests a significant uncertainty constraint on regional emissions using multi-species inversions of IAGOS in situ observations. [ABSTRACT FROM AUTHOR]

The formation of Fe(III) oxides in natural environments occurs in the presence of natural organic matter (OM), resulting in the formation of OM-mineral complexes that form through adsorption or coprecipitation processes. Thus, microbial Fe(III) reduction in natural environments most often occurs in the presence of OM-mineral complexes rather than pure Fe(III) minerals. This study investigated to what extent does the content of adsorbed or coprecipitated OM on ferrihydrite influence the rate of Fe(III) reduction by Shewanella oneidensis MR-1, a model Fe(III)-reducing microorganism, in comparison to a microbial consortium extracted from the acidic, Fe-rich Schlöppnerbrunnen fen. We found that increased OM content led to increased rates of microbial Fe(III) reduction by S. oneidensis MR-1 in contrast to earlier findings with the model organism Geobacter bremensis. Ferrihydrite-OM coprecipitates were reduced slightly faster than ferrihydrites with adsorbed OM. Surprisingly, the complex microbial consortia stimulated by a mixture of electrons donors (lactate, acetate, and glucose) mimics S. oneidensis under the same experimental Fe(III)-reducing conditions suggesting similar mechanisms of electron transfer whether or not the OM is adsorbed or coprecipitated to the mineral surfaces. We also followed potential shifts of the microbial community during the incubation via 16S rRNA gene sequence analyses to determine variations due to the presence of adsorbed or coprecipitated OM-ferrihydrite complexes in contrast to pure ferrihydrite. Community profile analyses showed no enrichment of typical model Fe(III)-reducing bacteria, such as Shewanella or Geobacter sp., but an enrichment of fermenters (e.g., Enterobacteria) during pure ferrihydrite incubations which are known to use Fe(III) as an electron sink. Instead, OM-mineral complexes favored the enrichment of microbes including Desulfobacteria and Pelosinus sp., both of which can utilize lactate and acetate as an electron donor under Fe(III)-reducing conditions. In summary, this study shows that increasing concentrations of OM in OM-mineral complexes determines microbial Fe(III) reduction rates and shapes the microbial community structure involved in the reductive dissolution of ferrihydrite. Similarities observed between the complex Fe(III)-reducing microbial consortia and the model Fe(III)-reducer S. oneidensis MR-1 suggest electron-shuttling mechanisms dominate in OM-rich environments, including soils, sediments, and fens, where natural OM interacts with Fe(III) oxides during mineral formation. [ABSTRACT FROM AUTHOR]

Inaccurate representation of atmospheric processes by transport models is a dominant source of uncertainty in inverse analyses and can lead to large discrepancies in the retrieved flux estimates. We investigate the impact of uncertainties in vertical transport as simulated by atmospheric transport models on fluxes retrieved using vertical profiles from aircraft as an observational constraint. Our numerical experiments are based on synthetic data with realistic spatial and temporal sampling of aircraft measurements. The impact of such uncertainties on the flux retrieved using the ground-based network and those retrieved using the aircraft profiles are compared. We find that the posterior flux retrieved using aircraft profiles is less susceptible to errors in boundary layer height, compared to the ground-based network. This finding highlights a benefit of utilizing atmospheric observations made onboard aircraft over surface measurements for flux estimation using inverse methods. We further use synthetic vertical profiles of CO2 in an inversion to estimate the potential of these measurements, which will be made available through the IAGOS (In-service Aircraft for a Global Observing System) project in the future, in constraining the regional carbon budget. Our results show that the regions of tropical Africa and temperate Eurasia, that are under-constrained by the existing surface-based network, will benefit the most from these measurements, with a reduction of posterior flux uncertainty of about 7 to 10%. [ABSTRACT FROM AUTHOR]

Earthworms are one of the main producers of large biopores (> 2 mm i.d.) in soil, hence affecting the infiltration and flow of water, transport of particles and nutrients as well as soil aeration. During rain events that lead to ponding conditions, earthworm burrows may serve as short circuits between the top- and subsoil, thereby bypassing the soil matrix. Yet, burrow wall characteristics and their continuity with increasing soil depth may have a severe impact on the amount and time scales of water flow and matter transport.In this study, we investigated the wettability and properties of earthworm burrow walls of Lumbricus terrestris in three depths (15, 30 and 50 cm) compared to the bulk soil. The wettability was inferred from water drop penetration time (WDPT) tests. Fourier transform infrared (FTIR) spectroscopy of burrow wall samples were analyzed for the presence of hydrophobic moieties of organic matter (OM). Scanning electron microscopy (SEM) was used to visually explore the burrow wall structure and accumulation with organic matter and microorganisms. Elemental distribution on the burrow walls was investigated with energy dispersive X-ray (EDX) spectroscopy. Earthworm burrow walls were more hydrophobic in all depths compared to the soil matrix. Long-chained aliphatic hydrocarbons, indicated by strong CH2 and CH3 vibrations in FTIR spectra, are suspected to cause water repellency. Such substances are accumulated along burrow walls during decomposition of organic matter and plant residues as well as deposition of cutaneous earthworm mucus. Larger plant residues, microorganisms and fungal hyphae as well as earthworm and microbial extracellular polymeric substances were identified along burrow walls by SEM. Clay minerals along the burrow walls were aligned. Thus, the burrow wall structure was found to be smoother compared to the soil matrix. The recurrent up- and downward burrowing and migration of earthworms and their feeding behavior and application of radial pressure on the walls results in the burrow wall characteristics (displacement of OM and minerals, aggregation and formation of organo-mineral associations and compaction) and consequently in a lower porosity and bulk density in the innermost burrow wall. Hence, lateral water transfer through the burrow wall might be impeded. However, differences in water repellency and chemical composition between the burrow walls and the soil matrix were decreasing with increasing depth. This in turn implies, that upon ponding conditions, the infiltrating water is translocated faster through the topsoil, yet may spread easier in the subsoil. This will also comprise the dissolved, colloidal and particulate organic matter and microorganisms. Thus, biopores may have a severe effect not only on the environmental conditions and biogeochemical cycles in the subsoil, but also on the habitat and established communities. [ABSTRACT FROM AUTHOR]

In the aeration zone, transients of water-saturation, fluid flow, (re-)distribution and cycling of matter and energy may strongly control the compartmentalization of subsurface ecosystems. Especially, seasonal or episodic dynamics of flow and flow paths within the aeration zone, cause transient groundwater flow partitioning that guides the quality evolution and ecology of groundwater resources. However, flow dynamics and matter cycling within the aeration zone are typically less explored and considered in resource modeling and management. This is particularly the case for topographic recharge areas with large aeration zones, themselves lacking productive groundwater bodies, but most important for the quality of the seepage. In the Hainich Critical Zone Exploratory (central Germany), we investigate the interplay of aeration zone dynamics for groundwater quality evolution along a hillslope monitoring transect. In the widely-distributed setting of alternating mixed carbonate-/siliciclastic bedrock, lysimeters, aeration zone collectors and multi-level monitoring wells were installed to access the subsurface compartments down to ~90 m. From up to eight years of monitoring weather, ground temperatures, multi-depth hydraulic heads and non-conservative environmental tracers, we were able to reconstruct hidden phenomena like localized recharge and fluctuating perched groundwater that also cause flow transients in the phreatic zone. Likely shaping the subsurface ecosystems, we found aeration zone-loading of waters, that bypass the argillaceous, oxygen-deficient overburden and cause, for instance, oxygenation of the main aquifer by seasonally ascending flow. Furthermore, our data highlight the role of (multiple) snowmelts that strongly contribute to the groundwater budget in our hillslope terrain with temperate climate. [ABSTRACT FROM AUTHOR]

The terrestrial deep biosphere hosts up to 20% of the earth’s biomass. Whereas life in deepsaline waters is suggested to be sustained mainly by H2 and CO2, microbes in shallowgroundwaters still receive input from recently fixed organic carbon. Within the researchcentre AquaDiva, we aim to understand the links between the surface and subsurfacebiogeosphere, especially how organisms inhabiting the subsurface reflect and influence theirenvironment, and affect water and matter transiting the subsurface. To achieve this, we haveconstructed a novel infrastructure, the Hainich Critical Zone Exploratory (CZE), whichprovides an excellent platform to access groundwater and aquifer rock material fromoligotrophic limestone aquifer assemblages along with soil and seepage from the respectivegroundwater recharge areas. We tracked the formation of the groundwater microbiome and the differentiation of thepredominant Cand. Patescibacteria under distinct hydrochemical regimes. Network,correlation analysis and time series allowed us to postulate different biological andhydrochemical drivers for community assembly of planktonic microbiota, with implicationsfor subsurface carbon cycling. Furthermore, our data showed the existence of a unique rockmatrix microbiome. Shallow weathered limestones contained bacterial groups most likelyoriginating from soil habitats. Low-permeable mudstones, containing mainly oligotrophicheterotrophs and thiosulfate-oxidizing autotrophs, showed similarities betweensurface-near samples and deep samples, without relation to rock type and bulk rockpermeability. The bacterial communities found on fracture surfaces of limestonesubsamples were distinct from their matrix counterparts and ranged from organic matterdecomposers in outcrop areas to autotrophs in downdip positions that receive limitedsurface input. By comparing the stable and radiogenic carbon isotope compositions ofmicrobial phospholipid-derived fatty acids (PLFAs) with those of the potentialmicrobial C sources, we determined that subsurface groundwater microbiomesappeared to assimilate up to 70% ancient organic matter derived from rocks, despite thepresence of younger organic matter. These signatures challenge the current paradigmand point to an intensive internal cycling of carbon independent of surface input. [ABSTRACT FROM AUTHOR]