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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Behaviour of cadmium isotopes in sulfidic waters and sediments of the Black Sea: Implications for global cadmium cycling and the application of cadmium isotopes as a paleo-oceanographic proxy

The cadmium isotope system has found use as a tracer for biological productivity, redox and organic carbon burial in the oceans. There are, however, very few observational constraints on Cd isotopic behaviour in modern sulfidic marine conditions, limiting our understanding of the modern Cd cycle, and our ability to use Cd isotope measurements of ancient sedimentary deposits as a paleoceanographic proxy. Here we study the behaviour of dissolved Cd in the water column of the Black Sea and its incorporation into sediments on the basin floor. The isotopic composition of dissolved Cd in the upper ∼50 m of the Black Sea water column is controlled by a combination of biological uptake and regeneration along with mixing of river water and Mediterranean seawater. Cadmium declines to <2 % of its peak subsurface concentration within the zone of nitrate-reduction but above the sulfide chemocline. The isotopic composition of dissolved Cd below the sulfide chemocline evolves in a manner that is consistent with experimental Cd sulfide fractionation factors, providing field-based support for these earlier studies. In contrast, the stability of the dissolved Cd isotopic signature above the chemocline, despite a large reduction in dissolved Cd concentrations, is explained by diffusion towards the Cd-sulfide sink below the chemocline. Sediments accumulating in the deep Black Sea below the sulfide chemocline have isotopic compositions that are similar to dissolved Cd in its near-surface aqueous concentration maximum. Sediments accumulating at shallower depths have lighter isotopic compositions that are likely affected by non-sulfidic burial pathways mediated by macrofaunal mixing and diagenesis of shallow burial phases. Our study shows that the isotopic composition of bulk sediments accumulating under sulfidic conditions is similar to dissolved Cd in the upper water column, supporting its use as a paleo-chemical proxy for ancient seawater as long as basin-scale controls on open ocean seawater sources are considered. We show that Cd burial in the deep Black Sea, predominantly as CdS, accounts for ∼0.5–15 % of total annual Cd burial in the global ocean.

Biogeochemical cycles↗
DOE OSTI2021

The Relationship Between Topography, Bedrock Weathering, and Water Storage Across a Sequence of Ridges and Valleys

Abstract Bedrock weathering regulates nutrient mobilization, water storage, and soil production. Relative to the mobile soil layer, little is known about the relationship between topography and bedrock weathering. Here, we identify a common pattern of weathering and water storage across a sequence of three ridges and valleys in the sedimentary Great Valley Sequence in Northern California that share a tectonic and climate history. Deep drilling, downhole logging, and characterization of chemistry and porosity reveal two weathering fronts. The shallower front is ∼7 m deep at the ridge of all three hillslopes, and marks the extent of pervasive fracturing and oxidation of pyrite and organic carbon. A deeper weathering front marks the extent of open fractures and discoloration. This front is 11 m deep under two ridges of similar ridge‐valley spacing, but 17.5 m deep under a ridge with nearly twice the ridge‐valley spacing. Hence, at ridge tops, the fraction of the hillslope relief that is weathered scales with hillslope length. In all three hillslopes, below this second weathering front, closed fractures and unweathered bedrock extend about one‐half the hilltop elevation above the adjacent channels. Neutron probe surveys reveal that seasonally dynamic moisture is stored to approximately the same depth as the shallow weathering front. Under the channels that bound our study hillslopes, the two weathering fronts coincide and occur within centimeters of the ground surface. Our findings provide evidence for feedbacks between erosion and weathering in mountainous landscapes that result in systematic subsurface structuring and water routing.

58 GEOSCIENCES↗
DOE OSTI2023

Quantifying the Impact of Vertical Resolution on the Representation of Marine Boundary Layer Physics for Global-Scale Models

Abstract While GCM horizontal resolution has received the majority of scale improvements in recent years, ample evidence suggests that a model’s vertical resolution exerts a strong control on its ability to accurately simulate the physics of the marine boundary layer. Here we show that, regardless of parameter tuning, the ability of a single-column model (SCM) to simulate the subtropical marine boundary layer improves when its vertical resolution is improved. We introduce a novel objective tuning technique to optimize the parameters of an SCM against profiles of temperature and moisture and their turbulent fluxes, horizontal winds, cloud water, and rainwater from large-eddy simulations (LES). We use this method to identify optimal parameters for simulating marine stratocumulus and shallow cumulus. The novel tuning method utilizes an objective performance metric that accounts for the uncertainty in the LES output, including the covariability between model variables. Optimization is performed independently for different vertical grid spacings and value of time step, ranging from coarse scales often used in current global models (120 m, 180 s) to fine scales often used in parameterization development and large-eddy simulations (10 m, 15 s). Uncertainty-weighted disagreement between the SCM and LES decreases by a factor of ∼5 when vertical grid spacing is improved from 120 to 10 m, with time step reductions being of secondary importance. Model performance is shown to converge at a vertical grid spacing of 20 m, with further refinements to 10 m leading to little further improvement. Significance Statement In successive generations of computer models that simulate Earth’s atmosphere, improvements have been mainly accomplished by reducing the horizontal sizes of discretized grid boxes, while the vertical grid spacing has seen comparatively lesser refinements. Here we advocate for additional attention to be paid to the number of vertical layers in these models, especially in the model layers closest to Earth’s surface where climatologically important marine stratocumulus and shallow cumulus clouds reside. Our experiments show that the ability of a one-dimensional model to represent physical processes important to these clouds is strongly dependent on the model’s vertical grid spacing.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Effects of Cone Penetrometer Testing on Shallow Hydrogeology at a Contaminated Site

Penetration testing is a popular and instantaneous technique for subsurface mapping, contaminant tracking, and the determination of soil characteristics. While the small footprint and reproducibility of cone penetrometer testing makes it an ideal method for in-situ subsurface investigations at contaminated sites, the effects to local shallow groundwater wells and measurable influence on monitoring networks common at contaminated sites is unknown. Physical and geochemical parameters associated with cone penetrometer testing were measured from a transect of shallow groundwater monitoring wells adjacent to penetrometer testing. For wells screened above the depth of cone refusal, the physical advancement and retraction of the cone had a significant effect ( p < 0.01) on water level for several pushes within 10 meters of a monitoring well, and a measured increase in specific conductivity. No effect on geochemistry or water level was observed in continuous monitoring data from wells screened below the depth of cone refusal, but variability in specific conductivity from these wells during penetration testing was only a fraction of the natural variation measured during precipitation events. Continuous measurements of specific conductivity and water level demonstrated that the effects of penetration testing have limited spatial and temporal distributions with a null effect post-testing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Analysis of bipolar membranes for electrochemical CO 2 capture from air and oceanwater

Carbon dioxide (CO 2 ) must be removed from the atmosphere to mitigate the negative effects of climate change. However, the most scalable methods for removing CO 2 from the air require heat from fossil-fuel combustion to produce pure CO 2 and continuously regenerate the sorbent. Bipolar-membrane electrodialysis (BPM-ED) is a promising technology that uses renewable electricity to dissociate water into acid and base to regenerate bicarbonate-based CO 2 capture solutions, such as those used in chemical loops of direct-air-capture (DAC) processes, and in direct-ocean capture (DOC) to promote atmospheric CO 2 drawdown via decarbonization of the shallow ocean. In this study, we develop an experimentally validated 1D model for the electrochemical regeneration of CO 2 from bicarbonate-based carbon capture solutions and seawater using BPM-ED. For DAC, our experimental and computational results demonstrate that pH swings induced by BPM water dissociation drive the formation of CO 2 at the cation-exchange layer|catholyte interface with energy-intensities of less than 150 kJ mol -1 . However, high rates of bubble formation increase energy intensity at current densities >100 mA cm -2 . Correspondingly, accelerating water dissociation catalysis and enacting bubble removal could enable CO 2 recovery at energy intensities <100 kJ mol -1 and current densities >100 mA cm -2 . For DOC, mass transport limitations associated with low carbon concentrations in oceanwater suggest that DOC is best suited for clean production of acid and base usable in downstream processes. Further, these results provide design principles for industrial-scale CO 2 recovery using BPM-ED.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Experimental performance analysis of a dual source heat pump integrated with thermal energy storage

To mitigate disturbances to the electric grid resulting from the growing penetration of intermittent and decentralized renewable generation, a dual-source (air source and ground source) heat pump (DSHP) integrated with thermal energy storage (TES) was developed. The DSHP can use either ambient air or the shallow subsurface of the ground to provide space heating or space cooling to the building as the conventional heat pump and produce hot/cold water for charging TES. Using dual sources (air and ground) can reduce the required size of the expensive ground heat exchangers while retaining high energy efficiency. During the off-peak period, the DSHP cools/heats the TES with low-cost electricity or overproduced renewable power. The stored cooling/heating energy in the TES is released during peak hours of the electric grid to meet the thermal demands of the building without consuming electricity to run the DSHP. A 2-ton (7 kW) prototype DSHP was developed and integrated with a 50-gallon (189 L) TES tank filled with a phase change material. Field tests were conducted to characterize the performance of the integrated system operating in various operation modes.

Wang, Lingshi↗
DOE OSTI2020

IMPACT OF SOIL TEMPERATURE VARIATION ON PERFORMANCE MODELING OF A NOVEL SHALLOW BORE GROUND HEAT EXCHANGER

A novel shallow bore (< 6 m deep) ground heat exchanger is proposed to substitute the conventional vertical bore ground heat exchanger (> 60 m deep) for ground source heat pump systems. A series of simulations were carried out to evaluate the impacts of the vertical soil temperature profile on the performance of the shallow bore ground heat exchanger in response to thermal loads of a ground source heat pump system, with various lengths of the shallow bore ground heat exchanger and ground thermal properties. The results indicate that the vertical soil temperature profile has a noticeable influence on the thermal response of the shallow bore ground heat exchanger. Moreover, for shallow bore ground heat exchangers with the same volume and buried depth, the one with greater length and narrower diameter has lower tank water temperature fluctuations over the year due to relatively more stable soil temperature, and the larger surface to volume ratio.

Shi, Liang↗
DOE OSTI2022

Super-hydration and reduction of manganese oxide minerals at shallow terrestrial depths

Manganese oxides are ubiquitous marine minerals which are redox sensitive. As major components of manganese nodules found on the ocean floor, birnessite and buserite have been known to be two distinct water-containing minerals with manganese octahedral interlayer separations of ~7 Å and ~10 Å, respectively. We show here that buserite is a super-hydrated birnessite formed near 5 km depth conditions. As one of the most hydrous minerals containing ca. 34.5 wt. % water, super-hydrated birnessite, i.e., buserite, remains stable up to ca. 70 km depth conditions, where it transforms into manganite by releasing ca. 24.3 wt. % water. Subsequent transformations to hausmannite and pyrochroite occur near 100 km and 120 km depths, respectively, concomitant with a progressive reduction of Mn 4+ to Mn 2+ . Our work forwards an abiotic geochemical cycle of manganese minerals in subduction and/or other aqueous terrestrial environments, with implications for water storage and cycling, and the redox capacity of the region.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hydrous SiO 2 in subducted oceanic crust and H 2 O transport to the core-mantle boundary

Subduction of oceanic lithosphere transports surface H 2 O into the mantle. Recent studies show that dense SiO 2 in the form of stishovite, an abundant mineral in subducted oceanic crust at depths greater than ~270 km, has the potential to host and transport a considerable amount of H 2 O into the lower mantle, but the H 2 O storage capacity of SiO 2 phases at high pressure and temperature remains uncertain. We investigate the hydration of stishovite and its higher-pressure polymorphs, β-stishovite and seifertite, with in situ X-ray diffraction experiments at high pressures and temperatures. The H 2 O contents in SiO 2 phases are quantified based on observed increases in unit cell volume relative to the anhydrous SiO 2 system. Density functional theory (DFT) computations permit calibration of water content as a function of volume change based on interstitial substitution of H 2 O. Regression of our experimental data indicates an H 2 O storage capacity in stishovite of ~3.5 wt% in the transition zone and shallow lower mantle, decreasing to about 0.8 wt% at the base of the mantle. We find that SiO 2 -bearing subducted oceanic crust can accommodate all the H 2 O in slab lithosphere that survives sub-arc dehydration. Hydration of silica phases in subducted oceanic crust and their unparalleled capacity to host significant amounts of H 2 O even at high mantle temperatures provides a unique mechanism for transport and storage of water in the deepest mantle.

58 GEOSCIENCES↗
DOE OSTI2025

Sensitivity of the Shallow‐To‐Deep Convective Transition to Moisture and Wind Shear in the Amazon

Deep convection is the primary influence on weather and climate in tropical regions. However, understanding and simulating the shallow‐to‐deep (STD) convective transition has long been challenging. Here, we conduct high‐resolution numerical simulations to assess the environmental controls on the evolution of isolated convection in the Amazon during the wet season. The large‐scale forcing derived through a constrained variational analysis approach for the GoAmazon2014/5 Experiment is used in the simulations. Through sensitivity experiments, we examine the relative importance of moisture and wind shear in controlling the shallow‐to‐deep convective transition for isolated convective events. Convection exhibits the greatest sensitivity to humidity within the lowest 1.5 km, where a 4 mm reduction in column water vapor nearly suppresses ice water formation on deep convective days. In contrast, a reduction in column water vapor in the free troposphere by a factor of two or more is necessary to produce a comparable impact on convection. Increasing low‐level wind speed from 6 to 9 m s -1 enhances afternoon deep convection, raising the cloud ice mixing ratio by approximately 25%. Conversely, upper‐level wind shear reveals the weakest correlation with daytime convection in our simulations. Our results help characterize the role of moisture and wind shear on the STD transition and our understanding of the underlying mechanisms.

environmental controls↗
DOE OSTI2021

Shallow-to-Deep Convective Transition in the Amazon (Final Report)

The frequent and extensive deep cloud formations over the Amazon Basin provide a vast area of atmospheric heating in the Tropics, forcing large-scale global circulations on daily to secular time scales. Motivated by the importance of these systems to the global climate system and the well-documented seasonal cycle in rainfall over the Amazon Basin, this study focused on improving understanding of the processes governing these systems on seasonal time scales and their impact on the typical growth of convection from early afternoon through evening, termed the shallow-to-deep transition. This study is based on observations from the Department of Energy (DOE) ARM Mobile Facility (AMF) near Manacapuru, Brazil collected during the Observations and Modeling of the Green Ocean Amazon (GOAmazon) field campaign from 1 January 2014 to 30 November 2015, together with total column water vapor (CWV) and surface meteorological observations from a dense Global Navigation Satellite System (GNSS) network within 50 km of the AMF site provided by the CHUVA Program collected in coordination with the GOAmazon campaign. The specific objectives of this study were to address the following questions: 1) What environmental conditions support the shallow-to-deep convective transition over the Central Amazon? 2) How does the relative importance of these conditions compare during the wet and dry seasons? 3) How are these conditions modulated by basin-scale transient forcing? 4) How well are these processes captured by regional model simulations convective resolving scale? Our main hypothesis was that intra-seasonal atmospheric disturbances were a primary driver of rainfall during the wet season in the Central Amazon, while localized surface heating of the land was the primary driver of enhanced rainfall during the dry season. Overall, our findings supported our hypothesis, with the convectively active phase of atmospheric Kelvin waves strongly favoring the development of larger, more organized rain systems during the wet season, while localized isolated deep convection dominated the types of rain events seen during the dry season. These results have implications for the predictability of rainfall over the Central Amazon and for its representation in climate and weather models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Data for publication: "A fresh take: Seasonal changes in terrestrial freshwater inputs impact salt marsh hydrology and vegetation dynamics"

This data repository contains data associated with the manuscript "A fresh take: Seasonal changes in terrestrial freshwater inputs impact salt marsh hydrology and vegetation dynamics". This study was conducted at the Elkhorn Slough National Estuarine Research Reserve in Watsonville, California from October 2019 - June 2022. We sought to understand the role of shallow freshwater inputs from adjacent uplands on salt marsh hydrologic behavior and vegetation productivity. This dataset contains CSV files of the following: daily salt marsh subsurface water level and pore water conductivity, monthly vegetation survey measurements, soil core data. Estuary surface water level, conductivity, and local precipitation were downloaded from the National Estuarine Research Reserve System (Centralized Data Management Office) at https://cdmo.baruch.sc.edu/.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Science Plan for the Deployment of the Third ARM Mobile Facility to the Southeastern United States at the Bankhead National Forest, Alabama (AMF3 BNF)

In 2018, the U.S. Department of Energy (DOE) held a workshop for the Atmospheric Radiation Measurement (ARM) (Mather and Voyles 2013) user facility to discuss critical climate challenges and locations where key ARM Mobile Facility (AMF) observational assets could impact Earth system modeling (ESM). As an outcome, the southeast United States (SE U.S.) was identified as a high-priority region to target climate-process studies that promote a deeper understanding of the climate system and bolster ARM interactions with the community to drive ESM advancement. The DOE ARM user facility is a globally recognized leader in deploying and operating strategically located observation sites around the world for studying the properties of aerosols and clouds and their interaction with radiation, precipitation, and the Earth’s surface. In partnering with the DOE Atmospheric System Research (ASR) program, ARM solicited a multi-agency Site Science Team approach to provide input and close interaction with ARM management towards a successful SE U.S. deployment of the ARM third Mobile Facility (AMF3) (Miller et al. 2016). These efforts included identifying key locations, science drivers and instruments, and measurement strategies to address the wider climate-process needs and ESM improvement. Community input served a vital role in establishing, refining, and informing the relevant drivers and decisions regarding this AMF3 deployment. The team has identified Northern Alabama (N. AL) as regionally representative to unlock the key opportunities that will improve our understanding and model representation of aerosol, cloud, and land-surface processes and their couplings in the SE U.S. A defining aspect of the AMF3 deployment is its commitment to long-term (anticipated five-year) observations to mitigate potential seasonal-to-annual variability that often limits appropriate attribution of phenomena to local or larger-scale processes. The proposed location may leverage nearby surface networks and multi-agency and partner assets to enrich this multi-year deployment. One motivation is to understand the role of spatiotemporal variability (thermodynamic, land-surface) across aspects of the climate system, with our AMF3 team anticipating future demands on characterizing the relationships between local-to-regional cloud development and surface processes across a diverse patchwork of natural, managed, and urban landscapes as found throughout the N. AL regions. The main site targets an intact, representative, forested region – the Bankhead National Forest (BNF) – underscoring further team commitment to regionally important land-atmosphere two-way interactive studies “from the canopy to the clouds”, with enhanced tower instrumentation augmenting traditional ARM capabilities adjacent to this site. Multiple supplemental sites will also be distributed across this region, prioritizing added needs for biodiversity. Anticipated high-priority cloud science themes will target N. AL as a regional SE U.S. hotbed for high-impact weather, convective cloud onset, and shallow-to-deep cloud transitioning. Anticipated aerosol drivers will focus on chemical processes that control the evolution of organic aerosol, the seasonality and spatial distribution of water vapor and particle-phase water, and its role on aerosol optical properties. Anticipated land-atmosphere drivers consider the two-way feedbacks between surface influence on aerosols, clouds, and precipitation properties and the associated radiative impacts on plant physiology and canopy-scale fluxes. Emphasis will include the study of the impact of surface processes on aerosols via precursor emission, and on clouds via moisture flux and thermal development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Climate response to off-equatorial stratospheric sulfur injections in three Earth system models – Part 2: Stratospheric and free-tropospheric response

The paper constitutes Part 2 of a study performing a first systematic inter-model comparison of the atmospheric responses to stratospheric aerosol injection (SAI) at various single latitudes in the tropics, as simulated by three state-of-the-art Earth system models – CESM2-WACCM6, UKESM1.0, and GISS-E2.1-G. Building on Part 1 (Visioni et al., 2023) we demonstrate the role of biases in the climatological circulation and specific aspects of the model microphysics in driving the inter-model differences in the simulated sulfate distributions. We then characterize the simulated changes in stratospheric and free-tropospheric temperatures, ozone, water vapor, and large-scale circulation, elucidating the role of the above aspects in the surface SAI responses discussed in Part 1. We show that the differences in the aerosol spatial distribution can be explained by the significantly faster shallow branches of the Brewer–Dobson circulation in CESM2, a relatively isolated tropical pipe and older tropical age of air in UKESM, and smaller aerosol sizes and relatively stronger horizontal mixing (thus very young stratospheric age of air) in the two GISS versions used. We also find a large spread in the magnitudes of the tropical lower-stratospheric warming amongst the models, driven by microphysical, chemical, and dynamical differences. These lead to large differences in stratospheric water vapor responses, with significant increases in stratospheric water vapor under SAI in CESM2 and GISS that were largely not reproduced in UKESM. For ozone, good agreement was found in the tropical stratosphere amongst the models with more complex microphysics, with lower stratospheric ozone changes consistent with the SAI-induced modulation of the large-scale circulation and the resulting changes in transport. In contrast, we find a large inter-model spread in the Antarctic ozone responses that can largely be explained by the differences in the simulated latitudinal distributions of aerosols as well as the degree of implementation of heterogeneous halogen chemistry on sulfate in the models. The use of GISS runs with bulk microphysics demonstrates the importance of more detailed treatment of aerosol processes, with contrastingly different stratospheric SAI responses to the models using the two-moment aerosol treatment; however, some problems in halogen chemistry in GISS are also identified that require further attention. Overall, our results contribute to an increased understanding of the underlying physical mechanisms as well as identifying and narrowing the uncertainty in model projections of climate impacts from SAI.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

The Role of Bedrock Circulation Depth and Porosity in Mountain Streamflow Response to Prolonged Drought

Quantitative understanding is lacking on how the depth of active groundwater circulation in bedrock affects mountain streamflow response to a multi-year drought. We use an integrated hydrological model to explore the sensitivity of a variety of streamflow metrics to bedrock circulation depth and porosity under a plausible extreme drought scenario lasting up to 5 years. Endmember depth versus hydraulic conductivity relationships and porosity values for fractured crystalline rock are simulated. With drought, a deeper circulation system with higher drainable porosity more effectively buffers minimum flow and significantly limits perennial stream loss in comparison to a shallow circulation system. Streamflow buffering is accomplished through extensive groundwater storage loss. However, deeper circulation systems experience prolonged recovery from drought in comparison to storage-limited shallow systems. Research highlights the importance of characterizing the deeper bedrock hydrogeology in mountainous watersheds to better understand and predict drought impacts on stream ecosystem health and water resource sustainability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Science Plan for the Deployment of the Third ARM Mobile Facility to the Southeastern United States at the Bankhead National Forest, Alabama (AMF3 BNF)

In 2018, the U.S. Department of Energy (DOE) held a workshop for the Atmospheric Radiation Measurement (ARM) (Mather and Voyles 2013) user facility to discuss critical climate challenges and locations where key ARM Mobile Facility (AMF) observational assets could impact Earth system modeling (ESM). As an outcome, the southeast United States (SE U.S.) was identified as a high-priority region to target climate-process studies that promote a deeper understanding of the climate system and bolster ARM interactions with the community to drive ESM advancement. The DOE ARM user facility is a globally recognized leader in deploying and operating strategically located observation sites around the world for studying the properties of aerosols and clouds and their interaction with radiation, precipitation, and the Earth’s surface. In partnering with the DOE Atmospheric System Research (ASR) program, ARM solicited a multi-agency Site Science Team approach to provide input and close interaction with ARM management towards a successful SE U.S. deployment of the ARM third Mobile Facility (AMF3) (Miller et al. 2016). These efforts included identifying key locations, science drivers and instruments, and measurement strategies to address the wider climate-process needs and ESM improvement. Community input served a vital role in establishing, refining, and informing the relevant drivers and decisions regarding this AMF3 deployment. The team has identified Northern Alabama (N. AL) as regionally representative to unlock the key opportunities that will improve our understanding and model representation of aerosol, cloud, and land surface processes and their couplings in the SE U.S. A defining aspect of the AMF3 deployment is its commitment to long-term (anticipated five-year) observations to mitigate potential seasonal-to-annual variability that often limits appropriate attribution of phenomena to local or larger-scale processes. The proposed location may leverage nearby surface networks and multi-agency and partner assets to enrich this multi-year deployment. One motivation is to understand the role of spatiotemporal variability (thermodynamic, land-surface) across aspects of the climate system, with our AMF3 team anticipating future demands on characterizing the relationships between local-to-regional cloud development and surface processes across a diverse patchwork of natural, managed, and urban landscapes as found throughout the N. AL regions. The main site targets an intact, representative, forested region – the Bankhead National Forest (BNF) – underscoring further team commitment to regionally important land atmosphere two-way interactive studies “from the canopy to the clouds”, with enhanced tower instrumentation augmenting traditional ARM capabilities adjacent to this site. Multiple supplemental sites will also be distributed across this region, prioritizing added needs for biodiversity. Anticipated high-priority cloud science themes will target N. AL as a regional SE U.S. hotbed for high-impact weather, convective cloud onset, and shallow to-deep cloud transitioning. Anticipated aerosol drivers will focus on chemical processes that control the evolution of organic aerosol, the seasonality and spatial distribution of water vapor and particle-phase water, and its role on aerosol optical properties. Anticipated land atmosphere drivers consider the two-way feedbacks between surface influence on aerosols, clouds, and precipitation properties and the associated radiative impacts on plant physiology and canopy-scale fluxes. Emphasis will include the study of the impact of surface processes on aerosols via precursor emission, and on clouds via moisture flux and thermal development.

Doppler lidar, aerosols, convection↗
DOE OSTI2026

Soil Water Retention and Hydraulic Conductivity Data and Model at Pump House in East River Watershed, Colorado 2019-2024

This data package includes soil water retention and hydraulic conductivity data and model fitting results from measurements of ex-situ soil samples and in-situ soil sensors near Pump House at Mount Crested Butte in the East River Watershed. Soil water retention curves (SWRC) characterize soil water content as a function of soil water potential. SWRC depends on soil texture and pore structure and can be used to describe the constraints on biogeochemical processes in terms of soil water availability. In this data package, the sample identification follows the format ER-X-Y, where ER refers to East River, X is the location identifier, and Y is the depth identifier at the same X (shallow Y=1). Specifically, ER-PHS, ER-LMC, ER-LMF, and ER-SMN are associated with ecohydrology sites under the East-Taylor Watershed Community Observatory Sites directory, and ER-RBTn (upslope n=1) are sampling transects during the 2019 Rootball Campaign. The sample and location information can be found in metadata.csv. Sampling and Measurements Each sample falls into one of the three sampling methods – (1) intact cores, (2) repacked samples, or (3) soil sensors – and one of the two measurement methods – (a) laboratory or (b) in-situ. Both intact cores and repacked samples were measured using the laboratory methods, which include measurements of soil water potential (HYPROP & WP4C, METER), saturated (KSAT, METER) and unsaturated hydraulic conductivity (HYPROP). The in-situ method uses a pair of co-located soil sensors to measure volumetric water content (TEROS12, METER) and soil water potential (TEROS21, METER), and the hydraulic conductivity was not measured. In comparison, the laboratory methods progress from full saturation to dry conditions, and the in-situ method includes both dry-to-wet and wet-to-dry cycles. The sampling and measurement methods for each sample can be found in metadata.csv, and more information about the measurements is detailed in the Methods section below. Models Retention and hydraulic conductivity data were fitted with four van-Genuchten-type models (specified by “model_name” column in the files): (1) traditional constrained van Genuchten model (“vG_constrained”), (2) traditional unconstrained van Genuchten model (“vG_unconstrained”), (3) PDI-variant of the constrained van Genuchten model (“vG_constrained_PDI”), and (4) PDI-variant of the unconstrained van Genuchten model (“vG_unconstrained_PDI”). The difference between the constrained (1: n) and the unconstrained (2: n, m) van Genuchten models is the number of pore-size distribution parameters in the model equations, giving the unconstrained model more degrees of freedom when fitting the data. Between the traditional and the PDI-variant models, model fitting differs the most at the dry end of the measurements. The traditional models allow infinite suction at the residual water content (water content does not drop below residual water content), and the PDI-variant models enforce a soil water potential value of pF=6.8 (~ -630 MPa) at oven-dryness (water content reaches 0). The inclusion of the van-Genuchten-type models is due to their common application. If other retention models are required, users can access the data in data.csv for further data fitting. More information about the models can be found in the Methods section below. Fitting Tasks The model fitting can be categorized into three levels of tasks (specified by “fitting_task” column in the files). Level 1 (“fit_retention”) only includes retention data fitting (the only level available for the in-situ method). Level 2 (“fit_retention_conductivity”) includes both retention and hydraulic conductivity data fitting, and the saturated hydraulic conductivity (Ks, a parameter of the hydraulic conductivity functions) is fixed by the measurements from KSAT. Level 3 (“fit_retention_conductivity_Ks”) also includes both retention and hydraulic conductivity data fitting, but Ks is a fitted parameter without the constraints from KSAT measurements. Among the same retention models (e.g. vG_constrained models of the same sample), level 1 should produce the best retention data fitting. Level 2 should have the highest misfit of the retention and hydraulic conductivity data, because the retention and hydraulic conductivity functions share common model parameters, and the unsaturated hydraulic conductivity (HYPROP) data fitting is subject to Ks measured independently by KSAT. Level 3 should have mid-level misfits of the retention and hydraulic conductivity data. While level 3 fits the hydraulic conductivity data better than level 2, the fitted Ks value might be unreasonable due to the lack of constraints at the wet end of the measurements. General recommendation when using this data package: (1) Choice of sampling methods: Intact cores and in-situ soil sensors could be prioritized because these sampling methods are less destructive. While the repacked samples were packed to the target bulk density (estimated post-sampling, when sample volume was known), these samples had altered pore structures. Nevertheless, intact cores might suffer from sample gaps that would lead to overestimation of Ks (sample gaps can be inferred from the “soil_sample_volume” column in metadata.csv when the value is < 249). In-situ method also has higher uncertainty in characterizing the wet end of the SWRC because of sensor limitations and the difficulty in reaching full saturation under natural conditions. (2) Choice of fitting tasks: When only retention data is needed, level 1 (“fit_retention”) should be prioritized. When both retention and hydraulic conductivity data are needed, level 2 (“fit_retention_conductivity”) could be prioritized. (3) Choice of models: This could depend on what the downstream models call for. If no specific model is required, model misfit could be used as a ranking criterion. Model misfit values in terms of RMSE can be found in model_parameters.csv. The following files are included in this data package: (1) metadata.csv – This file includes the general information of each sample, including location (description, geocoordinates, elevation), sampling and measurements details (method, depth, time or period, volume, instruments), and soil physical properties (bulk density, saturated hydraulic conductivity, only applicable to physical soil samples). (2) data.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity data of each sample. Column “instrument” specifies the instrument (HYPROP, WP4C, or TEROS) used to perform the measurements. (3) model_fit.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity fitted from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the variable does not apply to that fitting task. (4) model_parameters.csv – This file includes the fitted model parameters, model misfits, and conventional water content thresholds (field capacity and wilting point) from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the parameter does not apply to that model and/or that fitting task. (5) data_Ks.csv – This file includes the saturated hydraulic conductivity measurements from KSAT. (6) /figure/*.png – This folder includes three quick visualizations of the data, retention model fitting results and misfits, and hydraulic conductivity model fitting results, misfits, and parameters. The model fitting results are separated by samples and fitting tasks and colored by models. Zoom-in required. (7) /hyprop/*.bdhx – This folder includes proprietary hyprop files that require the free Labros SoilView-Analysis (METER) to open. Users can explore data fitting using other retention models (i.e. Brooks-Corey, Fredlund-Xing, Kosugi, bimodal models). Be aware that Ks value is pre-entered under “Fitting tab, Conductivity functions parameters” for level 2 fitting. If the value is lost, please refer to metadata.csv under “Ks” column. (8) Six file-level metadata that summarize file, header, column, and variable information of all files. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

EARTH SCIENCE > LAND SURFACE > SOILS↗
DOE OSTI2026

Soil Water Retention and Hydraulic Conductivity Data and Model at Snodgrass Mountain in East River Watershed, Colorado 2020-2025

This data package includes soil water retention and hydraulic conductivity data and model fitting results from measurements of ex-situ soil samples and in-situ soil sensors at Snodgrass Mountain. Soil water retention curves (SWRC) characterize soil water content as a function of soil water potential. SWRC depends on soil texture and pore structure and can be used to describe the constraints on biogeochemical processes in terms of soil water availability. In this data package, the sample identification follows the format SG-X-Y, where SG refers to Snodgrass Mountain, X is the location identifier, and Y is the depth identifier at the same X (shallow Y=1). Specifically, SG-EHS is associated with ecohydrology sites under the East-Taylor Watershed Community Observatory Sites directory, and SG-ERTn (upslope n=1) are points along the Snodgrass electrical resistivity tomography transect not associated with the existing site names in the directory. The sample and location information can be found in metadata.csv. Sampling and Measurements Each sample falls into one of the three sampling methods – (1) intact cores, (2) repacked samples, or (3) soil sensors – and one of the two measurement methods – (a) laboratory or (b) in-situ. Both intact cores and repacked samples were measured using the laboratory methods, which include measurements of soil water potential (HYPROP & WP4C, METER), saturated (KSAT, METER) and unsaturated hydraulic conductivity (HYPROP). The in-situ method uses a pair of co-located soil sensors to measure volumetric water content (TEROS12, METER) and soil water potential (TEROS21, METER), and the hydraulic conductivity was not measured. In comparison, the laboratory methods progress from full saturation to dry conditions, and the in-situ method includes both dry-to-wet and wet-to-dry cycles. The sampling and measurement methods for each sample can be found in metadata.csv, and more information about the measurements is detailed in the Methods section below. Models Retention and hydraulic conductivity data were fitted with four van-Genuchten-type models (specified by “model_name” column in the files): (1) traditional constrained van Genuchten model (“vG_constrained”), (2) traditional unconstrained van Genuchten model (“vG_unconstrained”), (3) PDI-variant of the constrained van Genuchten model (“vG_constrained_PDI”), and (4) PDI-variant of the unconstrained van Genuchten model (“vG_unconstrained_PDI”). The difference between the constrained (1: n) and the unconstrained (2: n, m) van Genuchten models is the number of pore-size distribution parameters in the model equations, giving the unconstrained model more degrees of freedom when fitting the data. Between the traditional and the PDI-variant models, model fitting differs the most at the dry end of the measurements. The traditional models allow infinite suction at the residual water content (water content does not drop below residual water content), and the PDI-variant models enforce a soil water potential value of pF=6.8 (~ -630 MPa) at oven-dryness (water content reaches 0). The inclusion of the van-Genuchten-type models is due to their common application. If other retention models are required, users can access the data in data.csv for further data fitting. More information about the models can be found in the Methods section below. Fitting Tasks The model fitting can be categorized into three levels of tasks (specified by “fitting_task” column in the files). Level 1 (“fit_retention”) only includes retention data fitting (the only level available for the in-situ method). Level 2 (“fit_retention_conductivity”) includes both retention and hydraulic conductivity data fitting, and the saturated hydraulic conductivity (Ks, a parameter of the hydraulic conductivity functions) is fixed by the measurements from KSAT. Level 3 (“fit_retention_conductivity_Ks”) also includes both retention and hydraulic conductivity data fitting, but Ks is a fitted parameter without the constraints from KSAT measurements. Among the same retention models (e.g. vG_constrained models of the same sample), level 1 should produce the best retention data fitting. Level 2 should have the highest misfit of the retention and hydraulic conductivity data, because the retention and hydraulic conductivity functions share common model parameters, and the unsaturated hydraulic conductivity (HYPROP) data fitting is subject to Ks measured independently by KSAT. Level 3 should have mid-level misfits of the retention and hydraulic conductivity data. While level 3 fits the hydraulic conductivity data better than level 2, the fitted Ks value might be unreasonable due to the lack of constraints at the wet end of the measurements. General recommendation when using this data package: (1) Choice of sampling methods: Intact cores and in-situ soil sensors could be prioritized because these sampling methods are less destructive. While the repacked samples were packed to the target bulk density (estimated post-sampling, when sample volume was known), these samples had altered pore structures. Nevertheless, intact cores might suffer from sample gaps that would lead to overestimation of Ks (sample gaps can be inferred from the “soil_sample_volume” column in metadata.csv when the value is < 249). In-situ method also has higher uncertainty in characterizing the wet end of the SWRC because of sensor limitations and the difficulty in reaching full saturation under natural conditions. (2) Choice of fitting tasks: When only retention data is needed, level 1 (“fit_retention”) should be prioritized. When both retention and hydraulic conductivity data are needed, level 2 (“fit_retention_conductivity”) could be prioritized. (3) Choice of models: This could depend on what the downstream models call for. If no specific model is required, model misfit could be used as a ranking criterion. Model misfit values in terms of RMSE can be found in model_parameters.csv. The following files are included in this data package: (1) metadata.csv – This file includes the general information of each sample, including location (description, geocoordinates, elevation), sampling and measurements details (method, depth, time or period, volume, instruments), and soil physical properties (bulk density, saturated hydraulic conductivity, only applicable to physical soil samples). (2) data.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity data of each sample. Column “instrument” specifies the instrument (HYPROP, WP4C, or TEROS) used to perform the measurements. (3) model_fit.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity fitted from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the variable does not apply to that fitting task. (4) model_parameters.csv – This file includes the fitted model parameters, model misfits, and conventional water content thresholds (field capacity and wilting point) from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the parameter does not apply to that model and/or that fitting task. (5) data_Ks.csv – This file includes the saturated hydraulic conductivity measurements from KSAT. (6) /figure/*.png – This folder includes three quick visualizations of the data, retention model fitting results and misfits, and hydraulic conductivity model fitting results, misfits, and parameters. The model fitting results are separated by samples and fitting tasks and colored by models. Zoom-in required. (7) /hyprop/*.bdhx – This folder includes proprietary hyprop files that require the free Labros SoilView-Analysis (METER) to open. Users can explore data fitting using other retention models (i.e. Brooks-Corey, Fredlund-Xing, Kosugi, bimodal models). Be aware that Ks value is pre-entered under “Fitting tab, Conductivity functions parameters” for level 2 fitting. If the value is lost, please refer to metadata.csv under “Ks” column. (8) Six file-level metadata that summarize file, header, column, and variable information of all files. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

EARTH SCIENCE > LAND SURFACE > SOILS↗