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Process‐based land surface models are important tools for estimating global wetland methane (CH₄) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site‐level patterns of freshwater wetland CH₄fluxes (FCH₄) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model‐observation disagreements are mainly at multi‐day time scales (<15 days); (b) most of the models can capture the CH₄variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH₄production). Our evaluation suggests the need to accurately replicate FCH₄variability, especially at short time scales, in future wetland CH₄model developments.

 

Abstract The BlueFlux field campaign, supported by NASA’s Carbon Monitoring System, will develop prototype blue carbon products to inform coastal carbon management. While blue carbon has been suggested as a nature-based climate solution (NBS) to remove carbon dioxide (CO 2 ) from the atmosphere, these ecosystems also release additional greenhouse gases (GHGs) such as methane (CH 4 ) and are sensitive to disturbances including hurricanes and sea-level rise. To understand blue carbon as an NBS, BlueFlux is conducting multi-scale measurements of CO 2 and CH 4 fluxes across coastal landscapes, combined with long-term carbon burial, in Southern Florida using chambers, flux towers, and aircraft combined with remote-sensing observations for regional upscaling. During the first deployment in April 2022, CO 2 uptake and CH 4 emissions across the Everglades National Park averaged −4.9 ± 4.7 μ mol CO 2 m −2 s −1 and 19.8 ± 41.1 nmol CH 4 m −2 s −1 , respectively. When scaled to the region, mangrove CH 4 emissions offset the mangrove CO 2 uptake by about 5% (assuming a 100 year CH 4 global warming potential of 28), leading to total net uptake of 31.8 Tg CO 2 -eq y −1 . Subsequent field campaigns will measure diurnal and seasonal changes in emissions and integrate measurements of long-term carbon burial to develop comprehensive annual and long-term GHG budgets to inform blue carbon as a climate solution. 

Femtosecond pump-probe spectroscopy using ultrafast optical and infrared pulses has become an essential tool to discover and understand complex electronic and structural dynamics in solvated molecular, biological, and material systems. Here we report the experimental realization of an ultrafast two-color X-ray pump X-ray probe transient absorption experiment performed in solution. A 10 fs X-ray pump pulse creates a localized excitation by removing a 1selectron from an Fe atom in solvated ferro- and ferricyanide complexes. Following the ensuing Auger–Meitner cascade, the second X-ray pulse probes the Fe 1s → 3ptransitions in resultant novel core-excited electronic states. Careful comparison of the experimental spectra with theory, extracts +2 eV shifts in transition energies per valence hole, providing insight into correlated interactions of valence 3dwith 3pand deeper-lying electrons. Such information is essential for accurate modeling and predictive synthesis of transition metal complexes relevant for applications ranging from catalysis to information storage technology. This study demonstrates the experimental realization of the scientific opportunities possible with the continued development of multicolor multi-pulse X-ray spectroscopy to study electronic correlations in complex condensed phase systems.

 

A frequently expressed viewpoint across the Earth science community is that global soil moisture estimates from satellite L‐band (1.4 GHz) measurements represent moisture only in a shallow surface layer (0–5 cm) and consequently are of limited value for studying global terrestrial ecosystems because plants use water from deeper rootzones. Using this argumentation, many observation‐based land surface studies avoid satellite‐observed soil moisture. Here, based on peer‐reviewed literature across several fields, we argue that such a viewpoint is overly limiting for two reasons. First, microwave soil emission depth considerations and statistical considerations of vertically correlated soil moisture information together indicate that L‐band measurements carry information about soil moisture extending below the commonly referenced 5 cm in many conditions. However, spatial variations of effective depths of representation remain uncertain. Second, in reviewing isotopic tracer field studies of plant water uptake, we find a prevalence of vegetation that primarily draws moisture from these upper soil layers. This is especially true for grasslands and croplands covering more than a third of global vegetated surfaces. Even some deeper‐rooted species (i.e., shrubs and trees) preferentially or seasonally draw water from the upper soil layers. Therefore, L‐band satellite soil moisture estimates are more relevant to global vegetation water uptake than commonly appreciated (i.e., relevant beyond only shallow soil processes like soil evaporation). Our commentary encourages the application of satellite soil moisture across a broader range of terrestrial hydrosphere and biosphere studies while urging more rigorous estimates of its effective depth of representation.

 

Wetlands are responsible for 20%–31% of global methane (CH₄) emissions and account for a large source of uncertainty in the global CH₄budget. Data‐driven upscaling of CH₄fluxes from eddy covariance measurements can provide new and independent bottom‐up estimates of wetland CH₄emissions. Here, we develop a six‐predictor random forest upscaling model (UpCH4), trained on 119 site‐years of eddy covariance CH₄flux data from 43 freshwater wetland sites in the FLUXNET‐CH4 Community Product. Network patterns in site‐level annual means and mean seasonal cycles of CH₄fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash‐Sutcliffe Efficiency ∼0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH₄emissions of 146 ± 43 TgCH₄ y⁻¹for 2001–2018 which agrees closely with current bottom‐up land surface models (102–181 TgCH₄ y⁻¹) and overlaps with top‐down atmospheric inversion models (155–200 TgCH₄ y⁻¹). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH₄fluxes has the potential to produce realistic extra‐tropical wetland CH₄emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid‐to‐arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25° from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ORNLDAAC/2253).

 

The northern permafrost region has been projected to shift from a net sink to a net source of carbon under global warming. However, estimates of the contemporary net greenhouse gas (GHG) balance and budgets of the permafrost region remain highly uncertain. Here, we construct the first comprehensive bottom‐up budgets of CO₂, CH₄, and N₂O across the terrestrial permafrost region using databases of more than 1000 in situ flux measurements and a land cover‐based ecosystem flux upscaling approach for the period 2000–2020. Estimates indicate that the permafrost region emitted a mean annual flux of 12 (−606, 661) Tg CO₂–C yr⁻¹, 38 (22, 53) Tg CH₄–C yr⁻¹, and 0.67 (0.07, 1.3) Tg N₂O–N yr⁻¹to the atmosphere throughout the period. Thus, the region was a net source of CH₄and N₂O, while the CO₂balance was near neutral within its large uncertainties. Undisturbed terrestrial ecosystems had a CO₂sink of −340 (−836, 156) Tg CO₂–C yr⁻¹. Vertical emissions from fire disturbances and inland waters largely offset the sink in vegetated ecosystems. When including lateral fluxes for a complete GHG budget, the permafrost region was a net source of C and N, releasing 144 (−506, 826) Tg C yr⁻¹and 3 (2, 5) Tg N yr⁻¹. Large uncertainty ranges in these estimates point to a need for further expansion of monitoring networks, continued data synthesis efforts, and better integration of field observations, remote sensing data, and ecosystem models to constrain the contemporary net GHG budgets of the permafrost region and track their future trajectory.

 

Abstract Achieving food security is a critical challenge of the Anthropocene that may conflict with environmental and societal goals such as increased energy access. The “fuel versus food” debate coupled with climate mitigation efforts has given rise to next-generation biofuels. Findings of this systematic review indicate just over half of the studies (56% of 224 publications) reported a negative impact of bioenergy production on food security. However, no relationship was found between bioenergy feedstocks that are edible versus inedible and food security ( P value = 0.15). A strong relationship was found between bioenergy and type of food security parameter ( P value < 0.001), sociodemographic index of study location ( P value = 0.001), spatial scale ( P value < 0.001), and temporal scale ( P value = 0.017). Programs and policies focused on bioenergy and climate mitigation should monitor multiple food security parameters at various scales over the long term toward achieving diverse sustainability goals. 

Drylands cover ca. 40% of the land surface and are hypothesised to play a major role in the global carbon cycle, controlling both long-term trends and interannual variation. These insights originate from land surface models (LSMs) that have not been extensively calibrated and evaluated for water-limited ecosystems. We need to learn more about dryland carbon dynamics, particularly as the transitory response and rapid turnover rates of semi-arid systems may limit their function as a carbon sink over multi-decadal scales. We quantified aboveground biomass carbon (AGC; inferred from SMOS L-band vegetation optical depth) and gross primary productivity (GPP; from PML-v2 inferred from MODIS observations) and tested their spatial and temporal correspondence with estimates from the TRENDY ensemble of LSMs. We found strong correspondence in GPP between LSMs and PML-v2 both in spatial patterns (Pearson’s r = 0.9 for TRENDY-mean) and in inter-annual variability, but not in trends. Conversely, for AGC we found lesser correspondence in space (Pearson’s r = 0.75 for TRENDY-mean, strong biases for individual models) and in the magnitude of inter-annual variability compared to satellite retrievals. These disagreements likely arise from limited representation of ecosystem responses to plant water availability, fire, and photodegradation that drive dryland carbon dynamics. We assessed inter-model agreement and drivers of long-term change in carbon stocks over centennial timescales. This analysis suggested that the simulated trend of increasing carbon stocks in drylands is in soils and primarily driven by increased productivity due to CO 2 enrichment. However, there is limited empirical evidence of this 50-year sink in dryland soils. Our findings highlight important uncertainties in simulations of dryland ecosystems by current LSMs, suggesting a need for continued model refinements and for greater caution when interpreting LSM estimates with regards to current and future carbon dynamics in drylands and by extension the global carbon cycle.