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At least 973 records · Page 54

Validation and Determination of Ice Water Content - Radar Reflectivity Relationships during CRYSTAL-FACE: Flight Requirements for Future Comparisons

In order for clouds to be more accurately represented in global circulation models (GCM), there is need for improved understanding of the properties of ice such as the total water in ice clouds, called ice water content (IWC), ice particle sizes and their shapes. Improved representation of clouds in models will enable GCMs to better predict for example, how changes in emissions of pollutants affect cloud formation and evolution, upper tropospheric water vapor, and the radiative budget of the atmosphere that is crucial for climate change studies. An extensive cloud measurement campaign called CRYSTAL-FACE was conducted during Summer 2002 using instrumented aircraft and a variety of instruments to measure properties of ice clouds. This paper deals with the measurement of IWC using the Harvard water vapor and total water instruments on the NASA WB-57 high-altitude aircraft. The IWC is measured directly by these instruments at the altitude of the WB-57, and it is compared with remote measurements from the Goddard Cloud Radar System (CRS) on the NASA ER-2. CRS measures vertical profiles of radar reflectivity from which IWC can be estimated at the WB-57 altitude. The IWC measurements obtained from the Harvard instruments and CRS were found to be within 20-30% of each other. Part of this difference was attributed to errors associated with comparing two measurements that are not collocated in time an space since both aircraft were not in identical locations. This study provides some credibility to the Harvard and CRS-derived IWC measurements that are in general difficult to validate except through consistency checks using different measurement approaches.

Sayres, D. S.↗

Elevation Dependent Warming in the Eastern Siberian Arctic

There is evidence for elevation-dependent warming (EDW) in many mountainous regions, including the Alps, Rockies, and Tibetan Plateau, all of which are in mid-latitudes. Most studies finding evidence of EDW indicate that both recent decadal and future projected warming rates are greater at higher elevations. In this study, we examine the roles of Arctic amplification and elevation on future warming rates in winter and summer in eastern Siberia (50-70°N; 80-180°E). This region includes four major river basins that flow into the Arctic Ocean (the Yenisei, Lena, Indigirka, and Kolyma) and intersects with mountain ranges in northern Mongolia and eastern Siberia. We analyse projected 21st century temperature projections using a six-member ensemble of the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM4) with a radiative forcing of 8.5 W m-2. Projected warming rates in winter for the 21st century are dominated by Arctic amplification, which leads to significantly larger warming rates at higher latitudes, with latitudinal gradients of about 0.16°C per degree latitude. In summer, the latitudinal gradient is near zero (0.02°C per degree of latitude). Within specific latitude bands, we also find EDW. However, unlike most mid-latitude locations where warming rates are greater at higher elevations, we find that future warming rates are smaller at higher elevations for this high-latitude region, particularly during winter, with statistically significant rates varying between -0.70 and -2.46 °C/km for different 5° latitude bands. The decrease in warming rates with elevation in winter at the highest latitudes is primarily attributed to strong inversions and changes in the lapse rate as free-air temperatures warm at slower rates than surface temperatures. In summer, the elevation dependence is much weaker than in winter but still statistically significant and negative in all but the most northern latitude band with values ranging between -0.10 and -0.56 °C/km.

elevation-dependent warming (EDW)↗

Sensitivity of Boreal-Summer Circulation and Precipitation to Atmospheric Aerosols in Selected Regions: The Americas - Part 2

Aerosol perturbations over selected land regions are imposed in Version-4 of the Goddard Earth Observing System (GEOS-4) general circulation model (GCM) to assess the influence of increasing aerosol concentrations on regional circulation patterns and precipitation in four selected regions: India, Africa, and North and South America. Part 1 of this paper addresses the responses to aerosol perturbations in India and Africa. This paper presents the same for aerosol perturbations over the Americas. GEOS-4 is forced with prescribed aerosols based on climatological data, which interact with clouds using a prognostic scheme for cloud microphysics including aerosol nucleation of water and ice cloud hydrometeors. In clear-sky conditions the aerosols interact with radiation. Thus the model includes comprehensive physics describing the aerosol direct and indirect effects on climate (hereafter ADE and AIE respectively). Each simulation is started from analyzed initial conditions for 1 May and was integrated through June-July-August of each of the six years: 1982 1987 to provide a 6-ensemble set. Results are presented for the difference between simulations with double the climatological aerosol concentration and one-half the climatological aerosol concentration for three experiments: two where the ADE and AIE are applied separately and one in which both the ADE and AIE are applied. The ADE and AIE both yield reductions in net radiation at the top of the atmosphere and surface while the direct absorption of shortwave radiation contributes a net radiative heating in the atmosphere. A large net heating of the atmosphere is also apparent over the subtropical North Atlantic Ocean that is attributable to the large aerosol perturbation imposed over Africa. This atmospheric warming and the depression of the surface pressure over North America contribute to a northward shift of the inter-Tropical Convergence Zone over northern America, an increase in precipitation over Central America and the Caribbean, and an enhancement of convergence in the North American monsoon region.

Wilcox, E. M.↗

Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region

Global and regional projections of climate change by Earth system models are limited by their uncertain estimates of terrestrial ecosystem productivity. At the middle to low latitudes, the East Asian monsoon region has higher productivity than forests in Europe–Africa and North America, but its estimate by current generation of terrestrial biosphere models (TBMs) has seldom been systematically evaluated. Here, we developed a traceability framework to evaluate the simulated gross primary productivity (GPP) by 15 TBMs in the East Asian monsoon region. The framework links GPP to net primary productivity, biomass, leaf area and back to GPP via incorporating multiple vegetation functional properties of carbon–use efficiency (CUE), vegetation C turnover time ( τ veg ), leaf C fraction (F leaf ), specific leaf area (SLA), and leaf area index (LAI)–level photosynthesis (P LAI ), respectively. We then applied a relative importance algorithm to attribute intermodel variation at each node. The results showed that large intermodel variation in GPP over 1901–2010 were mainly propagated from their different representation of vegetation functional properties. For example, SLA explained 77% of the intermodel difference in leaf area, which contributed 90% to the simulated GPP differences. In addition, the models simulated higher CUE (18.1 ± 21.3%), τ veg (18.2 ± 26.9%), and SLA (27.4±36.5%) than observations, leading to the overestimation of simulated GPP across the East Asian monsoon region. Furthermore, these results suggest the large uncertainty of current TBMs in simulating GPP is largely propagated from their poor representation of the vegetation functional properties and call for a better understanding of the covariations between plant functional properties in terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Effects of CO 2 and H 2 S on Corrosion of Martensitic Steels in Brines at Low Temperature

Corrosion studies were conducted for martensitic carbon steels in 5 wt% NaCl brine solutions at 4°C and 10 MPa (1,450 psi). These studies simulated different subsurface environments relevant to Arctic drilling. Here, two high-strength martensitic carbon steels, S-135 and UD-165, were studied in three different environments: (1) a CO 2 -NaCl-H 2 O solution with a CO 2 :H 2 O molar ratio of 0.312 in the whole system, (2) an H 2 S-NaCl-H 2 O solution with an H 2 S:H 2 O molar ratio of 3.12 × 10 –4 , and (3) a CO 2 -H 2 S-NaCl-H 2 O solution with the same acid gas to water ratios as environments 1 and 2. Results from the CO 2 +H 2 S mixed environment indicated that sour corrosion mechanism was dominant when the CO 2 :H 2 S molar ratio was 1,000. This impact of a small amount of H 2 S on the corrosion mechanism could be attributed to the specific adsorption of H 2 S on the steel surface. Electrochemical and mass loss measurements showed a distinct drop in the corrosion rate (CR) by more than one order of magnitude when transitioning from sweet to sour corrosion. This inhibiting effect on CR was attributed to the formation of a protective sulfide thin film. Tafel analyses of the anodic reaction showed that the Bockris mechanism was unlikely in the conditions tested. As a result, when comparisons were made between modeled and experimental CRs, good agreement was found in the CO 2 -only and H 2 S-only environments, but not in the CO 2 +H 2 S environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A 17 year climatology of the macrophysical properties of convection in Darwin

Abstract. The validation of convective processes in global climate models (GCMs) could benefit from the use of large datasets that provide long-term climatologies of the spatial statistics of convection. To that regard, echo top heights (ETHs), convective areas, and frequencies of mesoscale convective systems (MCSs) from 17 years of data from a C-band polarization (CPOL) radar are analyzed in varying phases of the Madden–Julian Oscillation (MJO) and northern Australian monsoon in order to provide ample validation statistics for GCM validation. The ETHs calculated using velocity texture and reflectivity provide similar results, showing that the ETHs are insensitive to various techniques that can be used. Retrieved ETHs are correlated with those from cloud top heights retrieved by Multifunctional Transport Satellites (MTSATs), showing that the ETHs capture the relative variability in cloud top heights over seasonal scales. Bimodal distributions of ETH, likely attributable to the cumulus congestus clouds and mature stages of convection, are more commonly observed when the active phase of the MJO is over Australia due to greater mid-level moisture during the active phase of the MJO. The presence of a convectively stable layer at around 5 km altitude over Darwin inhibiting convection past this level can explain the position of the modes at around 2–4 km and 7–9 km. Larger cells were observed during break conditions compared to monsoon conditions, but only during the inactive phase of the MJO. The spatial distributions show that Hector, a deep convective system that occurs almost daily during the wet season over the Tiwi Islands, and sea-breeze convergence lines are likely more common in break conditions. Oceanic MCSs are more common during the night over Darwin. Convective areas were generally smaller and MCSs more frequent during active monsoon conditions. In general, the MJO is a greater control on the ETHs in the deep convective mode observed over Darwin, with higher distributions of ETH when the MJO is active over Darwin.

54 ENVIRONMENTAL SCIENCES↗

Satellite Sampling and Retrieval Errors in Regional Monthly Rain Estimates from TMI AMSR-E, SSM/I, AMSU-B and the TRMM PR

Passive and active microwave rain sensors onboard earth-orbiting satellites estimate monthly rainfall from the instantaneous rain statistics collected during satellite overpasses. It is well known that climate-scale rain estimates from meteorological satellites incur sampling errors resulting from the process of discrete temporal sampling and statistical averaging. Sampling and retrieval errors ultimately become entangled in the estimation of the mean monthly rain rate. The sampling component of the error budget effectively introduces statistical noise into climate-scale rain estimates that obscure the error component associated with the instantaneous rain retrieval. Estimating the accuracy of the retrievals on monthly scales therefore necessitates a decomposition of the total error budget into sampling and retrieval error quantities. This paper presents results from a statistical evaluation of the sampling and retrieval errors for five different space-borne rain sensors on board nine orbiting satellites. Using an error decomposition methodology developed by one of the authors, sampling and retrieval errors were estimated at 0.25 resolution within 150 km of ground-based weather radars located at Kwajalein, Marshall Islands and Melbourne, Florida. Error and bias statistics were calculated according to the land, ocean and coast classifications of the surface terrain mask developed for the Goddard Profiling (GPROF) rain algorithm. Variations in the comparative error statistics are attributed to various factors related to differences in the swath geometry of each rain sensor, the orbital and instrument characteristics of the satellite and the regional climatology. The most significant result from this study found that each of the satellites incurred negative longterm oceanic retrieval biases of 10 to 30%.

Fisher, Brad↗

Satellite Observations and Modeling to Understand the Lower Mekong River Basin Streamflow Variability

In this work, we have used the Soil & Water Assessment Tool (SWAT) to examine streamflow variability of the Lower Mekong River Basin (LMRB) associated with changes in the Upper Mekong River Basin (UMRB) inflows. Two hypothetical experiments were formulated and evaluated for the LMRB, where we conducted runoff simulations with multiple inflow changes that include upstream runoff yield increase and decrease scenarios. Streamflow variability of the LMRB was quantified by two streamflow metrics that explain flow variability and predictability, and high flow disturbance. The model experiments were performed for the Lower Mekong River Basin with identical climate, soil, and other watershed characteristics data. Remote sensing precipitation (Tropical Rainfall Measurement Mission, TRMM, and Global Precipitation Measurement mission, GPM), meteorological data as well as spatial data that include a digital elevation model, newly developed soil information (Harmonized World Soil Database, HWSD), and land use and land cover were processed as input to the LMRB model simulations. Observed daily streamflow data along the Lower Mekong River from Chiang Sean, Thailand to Kratie, Cambodia were used for calibration and validation. Our work results suggest that the Lower Mekong River streamflow is highly variable and has a low predictability (Colwell index of about 32%). We found that releasing more water from upstream Mekong during rainfall months by 30% would result in a reduction in the Lower Mekong streamflow predictability by about 21%. This reduction in predictability is mainly attributed to a decrease in the Contingency index. Our work shows that the ability to predict floods/droughts at the Lower Mekong River would be reduced if there is any anticipated change (i.e., increase/decrease) from UMRB releases. Our results also show that releasing more flows from the upstream Mekong would also affect flood duration and the frequency of flood occurrences downstream. The results of this work thus help to quantify the sensitivity of streamflow variability at the Lower Mekong River Basin to upstream anthropogenic changes.

Streamflow Predictability↗

The Role of Circulation Features on Black Carbon Transport into the Arctic in the Community Atmosphere Model Version 5 (CAM5)

Current climate models generally under-predict the surface concentration of black carbon (BC) in the Arctic due to the uncertainties associated with emissions, transport, and removal. This bias is also present in the Community Atmosphere Model Version 5.1 (CAM5). In this study, we investigate the uncertainty of Arctic BC due to transport processes simulated by CAM5 by configuring the model to run in an “offline mode” in which the large-scale circulations are prescribed. We compare the simulated BC transport when the offline model is driven by the meteorology predicted by the standard free-running CAM5 with simulations where the meteorology is constrained to agree with reanalysis products. Some circulation biases are apparent: the free-running CAM5 produces about 50% less transient eddy transport of BC than the reanalysis-driven simulations, which may be attributed to the coarse model resolution insufficient to represent eddies. Our analysis shows that the free-running CAM5 reasonably captures the essence of the Arctic Oscillation (AO), but some discernable differences in the spatial pattern of the AO between the free-running CAM5 and the reanalysis-driven simulations result in significantly different AO modulation of BC transport over Northeast Asia and Eastern Europe. Nevertheless, we find that the overall climatological circulation patterns simulated by the free-running CAM5 generally resembles those from the reanalysis products, and BC transport is very similar in both simulation sets. Therefore, the simulated circulation features regulating the long-range BC transport is unlikely the most important cause of the large under-prediction of surface BC concentration in the Arctic.

Arctic↗

Advanced Life Systems for Extreme Environments: An Arctic Application

The problems of obtaining adequate pure drinking water and disposing of liquid and solid waste in the U.S. Arctic, a region where virtually all water is frozen solid for much of the year, has led to unsanitary solutions (U.S. Arctic Research Commission). These solutions are also damaging to the environment. Sanitation and a safe water supply are particularly problems in rural villages. About one-fourth of Alaska's 86.000 Native residents live in these communities. They are without running water and use plastic buckets for toilets. The outbreak of diseases is believed to be partially attributable to exposure to human waste. Villages with the most frequent outbreaks of disease are those in which running water is difficult to obtain (Office of Technology Assessment, 1994). Waste is emptied into open lagoons, rivers, or onto the sea coast. It does not degrade rapidly and in addition to affecting human health, can be harmful to the fragile ecology of the Arctic and the indigenous wildlife and fish populations. Advanced Life Systems for Extreme Environments (ALSEE) provides a solution to sanitation and safe water problems. The system uses an advanced integrated technology developed for Antarctic and space applications. ALSEE uses the systems approach to address more than waste and water problems. By incorporating hydroponic horticulture and aquaculture into the waste treatment system, ALSEE addresses the quality and quantity of fresh foods available to Arctic residents. A temperate climate is required for year-round plant growth. ALSEE facilities can be designed to include a climate controlled area within the structure. This type of environment is a change from the long periods of darkness and cold found in the Arctic and can help alleviate stress so often associated with these extremes. While the overall concept of ALSEE projects is advanced, system facilities can be operated by village residents with appropriate training. ALSEE provides continuing training and education as a part of the project. Not only is this desirable but necessary. There is ample evidence in "gravoyard" throughout rural Alaska of technologies which failed not because they were not applic4tble, but because they were not integrated and could not be operated or repaired by village residents. Waste streams in villages will vary depending on the human diet and the non-food waste stream. ALSEE units can be adapted to different village situations once the content of the waste stream is known. Units located in population hubs can serve as research, education. and demonstration centers. Appropriate modifications can be determined at these centers to transfer technology to more remote locations where waste stream conditions may differ.

Lewis, Carol E.↗

Diffraction imaging for seal evaluation using ultra high resolution 3D seismic data

Cap rock is any impermeable or low permeability formation that may trap oil, gas or water, preventing it from migrating to the surface. Evaluation of sealing properties of the cap rock is a critical task for seismic exploration. It is important for oil and gas prospecting as well as for locating reservoirs appropriate for carbon dioxide storage. The latter has been proposed as one solution to global climate change caused by heat-trapping anthropogenic gasses in the atmosphere. A fluid escaped from the reservoir fills voids in the overlying strata thereby causing local changes of acoustic properties. We aim to explore such fluid-saturated areas and thus evaluate sealing properties of underlying cap rocks. We assume that local acoustic impedance changes caused by fluid migration generate seismic diffractions. We isolate diffracted waves from P-Cable seismic data acquired over the area of interest and perform diffraction analysis of the near-surface interval (above 200 m). In the diffraction image obtained, we interpret an extensive system of broad sinuous channels, narrow linear faults, and diffuse fracture networks. In addition, we detect high diffractivity anomalies, which extend vertically and laterally. We note no evidence of these anomalies in a conventional seismic image and associated seismic attribute (similarity and fracture density) volumes. We associate this high diffractivity to a variable pore fluid composition and saturation, which we infer to be due to hydrocarbon migration from the underlying strata. Consequently, we conclude poor seal quality for the underlying cap rocks. During data processing, we test diffraction focusing analysis for velocity model building. In conclusion, this option appears quite valuable for P-Cable data processing because of short offset and limitations of the standard velocity analysis.

58 GEOSCIENCES↗

Microstructure and Composition of Passivating Interfaces in Silicon Heterojunction Solar Modules Weathered in Different Climates

Sanyo/Panasonic patented silicon heterojunction with intrinsic thin layer (HIT) solar cells in the 1990's, which demonstrated world record photovoltaic (PV) efficiency around 2014 and inspired the newer generations of silicon heterojunction technology (SHJ) as well as the current world record back-contact PV cell designs. The high-quality passivation strategy, utilizing ultra-thin layers of hydrogenated amorphous silicon (a-Si:H), leads to high voltages and long carrier lifetimes, but these qualities may degrade over time as the modules operate outdoors. Here, we investigate local microstructure and composition at the interface layers of cells from HIT modules weathered in a hot, humid climate (Florida, USA) and temperate climate (Colorado, USA) for 10 years. We employ a comprehensive set of high-resolution electron microscopy imaging and spectroscopy to directly resolve structure and composition in these cells down to the nanoscale. We show features such as alignment of the In2O3 transparent conducting oxide and a-Si:H layers on the textured c-Si facets, interfacial oxidation at the a-Si:H/c-Si and In2O3/a-Si:H interfaces, and twinned c-Si resulting from epitaxial growth into the a-Si:H layer. Our results raise potential degradation mechanisms in these outdoor-weathered modules, but the root cause of electrical loss remains uncertain due to the very small changes in aged samples. This study shows that many atomic scale features at the In2O3/a-Si:H/c-Si interfaces are surprisingly robust, and the electrical losses with aging may either be attributed to other pathways or be very sensitive to the subtle chemical and microstructural features observed here.

14 SOLAR ENERGY↗

Rock Physics-Based Data Assimilation of Integrated Continuous Active-Source Seismic and Pressure Monitoring Data during Geological Carbon Storage

Summary There has been substantial controversy concerning the role of geological carbon storage (GCS) in sequestering anthropogenic carbon emissions to mitigate climate change and global warming. Arguments center on the inability to monitor a geological storage site precisely and continuously, especially highlighting the associated costs and spatiotemporal trade-offs when using conventional subsurface monitoring techniques (well logs, core samples, chemical tracers, and 4D seismics). Active surveillance of GCS sites is essential for managing and mitigating potential leaks but is also required by regulation. With the goal of enhancing the monitoring capability at GCS sites, we present a rock physics-based joint data assimilation model to study a popular GCS site at Cranfield, Mississippi, USA. Synthetic continuous active-source seismic monitoring (CASSM) data (in the form of Vp and Qp measurements) and wellbore pressure monitoring data are assimilated with an ensemble of reservoir realizations to monitor gas saturation and reservoir pressure changes over a period of 100 years. Synthetic seismic attributes are generated using rock physics models (RPMs) and wellbore pressure monitoring data are extracted from the ground truth. Two assimilation methods, ensemble Kalman filter (EnKF) and ensemble Kalman smoother (EnKS), are tested in an observation system simulation experiment (OSSE) environment to assess the prediction accuracy of the individual and composite observation systems. The joint monitoring system achieves more accurate estimates of gas saturation and pressure, across the time span from start of injection to end of forecast, as compared to a single type of monitoring tool and irrespective of data assimilation algorithm choice. These results indicate that jointly assimilated data from two types of sensors (in this case, crosswell seismic and downhole pressure) may lead to a more risk-reducing monitoring design. One would expect that more data, vis-à-vis inclusion of a new sensor type, will improve the accuracy of any GCS monitoring system. However, from a practical standpoint, one important question is whether such a gain in accuracy is worth the additional cost associated with the new sensor. This paper focuses on quantifying the gain in accuracy, such that a practitioner can answer this question.

Engineering↗

Precipitation regime changes in High Mountain Asia driven by cleaner air

High Mountain Asia (HMA) has experienced a spatial imbalance in water resources in recent decades, partly due to a dipolar pattern of precipitation changes known as South Drying-North Wetting. These changes can be influenced by both human activities and internal climate variability. While climate projections indicate a future widespread wetting trend over HMA, the timing and mechanism of the transition from a dipolar to a monopolar pattern remain unknown. Here, we demonstrate that the observed dipolar precipitation change in HMA during summer is primarily driven by westerly- and monsoon-associated precipitation patterns. The weakening of the Asian westerly jet, caused by uneven emission of anthropogenic aerosols, favors the dipolar precipitation trend during 1951-2020. Additionally, the phase transition of the interdecadal Pacific oscillation induces an out-of-phase precipitation change between the core region of the South Asian monsoon and southeastern HMA. Under medium or high emission scenarios, corresponding to a global warming of 0.6-1.1 °C compared to the present, the dipolar pattern is projected to shift into a monopolar wetting trend in the 2040s. This shift of precipitation patterns is mainly attributed to the intensified jet stream resulting from reduced emissions of anthropogenic aerosols. In conclusion, these findings underscore the importance of considering the impact of aerosol emission reduction in future social planning by policymakers.

54 ENVIRONMENTAL SCIENCES↗

A Fast and Scalable Genetic Algorithm-Based Approach for Planning of Microgrids in Distribution Networks: Preprint

As a result of climate change, extreme weather events are occurring more frequently and with increasing impact. This trend poses a significant challenge for distribution utilities and system operators to ensure that there is uninterrupted power supply to critical loads in their networks; thus, the level of proactive preparation of the distribution system to be able to handle severe impacts of extreme weather events represents the system's resilience. One method that distribution systems use to prepare for extreme events is to form multiple microgrids and thereby isolate themselves from the grid supply by using local generation as much as possible to supply critical loads. But partitioning an existing system into multiple feasible islands capable of supporting critical loads is still challenging for distribution systems - first, because of the size of the graph partitioning problem and, second, because of the difficulty in properly formulating the desired attributes of such islands or microgrids. Therefore, this paper presents a genetic algorithmbased approach that facilitates incorporating multiple objectives for grid partitioning by formulating two types of problems - node allocation and edge elimination - and it considers multiple topological and resilience-enhancing objectives. The performance of the proposed genetic algorithm-based approach is numerically evaluated on multiple test systems as well as on a real distribution feeder in Colorado, USA.

edge elimination↗

Synergetic Effects of Soil Organic Matter Components During Interactions with Minerals

Mineral-associated soil organic matter (SOM) is critical for stabilizing organic carbon and mitigating climate change. However, mineral-SOM interactions at the molecular scale, particularly synergetic adsorption through organic-organic interaction on the mineral surface known as organic multilayering, remain poorly understood. This study investigates the impact of organic multilayering on mineral-SOM interactions, by integrating macroscale experiments and molecular-scale simulations that assess the individual and sequential adsorption of major SOM compounds – lauric acid (lipid), pentaglycine (amino acid), trehalose (carbohydrate), and lignin onto soil minerals. Ferrihydrite, Al-hydroxide, and calcite are exposed to SOM compounds to determine adsorption affinities and binding energies. Results show that lauric acid has 20-40 times higher K d than pentaglycine, following the order K d (ferrihydrite) > K d (Al-hydroxide) >> K d (calcite). Molecular-scale simulations confirm that lauric acid has a higher binding energy (30.8 kcal/mol) on ferrihydrite than pentaglycine (6.0 kcal/mol), attributed to lipid hydrophobicity. The lower binding energy of pentaglycine results from its hydrophilic amide groups, facilitating partitioning into water. Sequential experiments examine how the first layer of lipid or amino acid affects the adsorption of carbohydrate/lignin, which show little or no individual adsorption affinities. Macroscale results reveal that lipid and amino acid adsorption induce ferrihydrite particle repulsion increasing reactive surface area and enhancing carbohydrate/lignin adsorption independently and synergistically through organic multilayering. Molecular-scale results reveal that amino acid adsorbed on ferrihydrite interacts more readily with lignin macroaggregates (preformed in solution) than with individual lignin units, indicating organic multilayering via H-bonding. Further, these findings reveal the molecular mechanisms of SOM-mineral interactions, crucial for enhancing soil carbon stabilization.

54 ENVIRONMENTAL SCIENCES↗

Dissolved Carbon Dynamics in Meltwaters From the Russell Glacier, Greenland Ice Sheet

Melting of the Greenland Ice Sheet (GrIS) has accelerated in recent decades. Given the close association between the water and carbon (C) cycles, melting of the GrIS may also drive local and global C cycle feedbacks. However, few studies have quantified such feedbacks, which may have important implications for predicting future climate or understanding linkages between ice sheet destabilization and climate change in the geologic past. Here, we investigate seasonal and interannual dissolved C cycling at the margin of the Russell Glacier, west Greenland. By synthesizing isotopic analyses of water (δ 18 O) and C (δ 13 C and Δ 14 C) with geomicrobiological observations, we present evidence for previously unknown connections between the GrIS's supra– and sub–glacial dissolved C cycles. Supraglacial streams have variable concentrations of dissolved organic carbon (DOC) and are the dominant source of DOC in subglacial discharge. Supraglacial stream dissolved inorganic carbon (DIC) concentrations are uniform and sourced from a spatially and temporally constant mixture of organic C (~25%) respired by aerobic heterotrophs inhabiting the GrIS surface and dissolved atmospheric C (~75%). Supraglacial inputs account for ~50% of subglacial discharge DIC. The remaining subglacial DIC derives from carbonate weathering and microbial CO 2 production, with the latter attributable to abundant anaerobic heterotrophic communities observed in subglacial discharge. Furthermore, we find that supraglacial streams deliver young DOC to the subglacial environment during snowmelt and rain events. In conclusion, these pulses of organic C may drive heterotrophic microbial respiration, with the cumulative effect being a seasonal shift in the source of basal DIC, from microbial– to carbonate–dominated.

58 GEOSCIENCES↗

Examining Cloud Feedback Components in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM)

Cloud feedback remains the main source of uncertainty in climate sensitivity estimated by global climate models (GCMs), largely because subgrid cloud responses are parameterized in GCMs due to their coarse resolution. Here, this study examines cloud feedback in the global 3.25-km Simple Cloud-Resolving Energy Exascale Earth System Model (E3SM) Atmosphere Model (SCREAM 3 km) through a pair of 1-yr atmosphere-only simulations with control and +4-K sea surface temperature perturbations. SCREAM 3 km produces a positive cloud feedback that falls within but at the upper end of the range of Coupled Model Intercomparison Project phase 5 (CMIP5) and CMIP phase 6 (CMIP6) models and expert judgment. The positive cloud feedback arises from positive contributions from both high- and low-level clouds, with increases in high-cloud altitude and decreases in low-cloud amount and optical depth playing key roles. The stronger-than-CMIP-average feedback is mainly attributable to the high-cloud altitude feedback, owing to cloud tops rising nearly isothermally in SCREAM 3 km. The positive low-cloud amount feedback is weaker in SCREAM than in GCMs because estimated inversion strength (EIS) increases more dramatically with warming. A coarser 12-km resolution version of SCREAM exhibits a weaker positive cloud feedback than SCREAM 3 km, mainly because its low-cloud-radiative flux is more sensitive to EIS, leading to a stronger negative low-cloud amount feedback. With this process-level assessment of cloud feedback, this study reveals where SCREAM aligns with and diverges from conventional GCMs and expert assessment, providing insights to inform further model improvement and future expert assessment.

Cloud radiative effects↗