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DOE OSTI2020

Thermodynamics, dynamics, and structure of supercritical water at extreme conditions

Molecular dynamics (MD) simulations to understand the thermodynamic, dynamic, and structural changes in supercritical water across the Frenkel line and the melting line have been performed. The two-phase thermodynamic model [J. Phys. Chem. B(2010), 114(24), 8191-8198] and the velocity autocorrelation functions are used to locate the Frenkel line and to calculate the thermodynamic and dynamic properties. The Frenkel lines obtained from the two-phase thermodynamic model and the velocity autocorrelation criterion do not agree with each other. Structural characteristics and the translational diffusion dynamics of water suggest that this inconsistency could arise from the two oscillatory modes in water, which are associated with the bending of hydrogen bonds and intermolecular collisions inside the first coordination shell. Finally, the overall results lead us to conclude that the universality of the Frenkel line as a dynamic crossover line from rigid to nonrigid fluids is preserved in water.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

Thermodynamic guiding principles of high-capacity phase transformation materials for splitting H 2 O and CO 2 by thermochemical looping

Here, thermochemical looping splitting of water and carbon dioxide (CO 2 ) with greenhouse-gas-free (GHG-free) energy has the potential to help address the Gt-scale GHG emissions challenge. Reaction thermodynamics largely contributes to the main bottlenecks of cost reduction for thermochemical looping water/CO 2 splitting cycle. Here, we analyze thermodynamic driving forces in such cycles with two-phase ternary ferrites as model systems. We find that cation configurational entropy chiefly determines the change of partial molar entropy with oxygen stoichiometry. In addition, our phase diagram analysis accurately predicts the optimal Fe ratio for maximal water/CO 2 splitting capacity in thermal reduction and in chemical reduction based cycles, underlining the significance of phase boundary positions. With chemical reduction, >10% CO 2 conversion and high oxygen exchange capacity can both be achieved. Furthermore, our reduced Gibbs free energy model illustrates critical thermodynamic factors that influence the water/CO 2 splitting capacity. Our research reveals the thermodynamic driving forces underlying the unconventional high-capacity Fe-poor ferrites, further explained via phase diagrams of Fe–Co–O, Fe–Ni–O and Fe–Mg–O. Future materials improvements can be guided by our reduced Gibbs free energy model.

08 HYDROGEN↗

DOE OSTI2024

Insights into controlling bacterial cellulose nanofiber film properties through balancing thermodynamic interactions and colloidal dynamics

In recent years, nanocellulose has emerged as a sustainable and environmentally friendly alternative to traditional petroleum-derived structural polymers. Sourced either from plants, algae, or bacteria, nanocellulose can be processed into colloid, gel, film and fiber forms. However, the required fundamental understanding of process parameters that govern the morphology and structure–property relationships of nanocellulose systems, from colloidal suspensions to bulk materials, has not been developed and generalized for all forms of cellulose. This further hinders the more widespread adoption of this biopolymer in applications. Our study investigates the dispersion of cellulose nanofibers (CNFs) produced by a bacterial–yeast co-culture, in solvents, highlighting the role of thermodynamic interactions in influencing their colloidal behavior. By adjusting Hansen solubility parameters, we controlled the thermodynamic relationship between CNFs and solvents across various concentrations, studying the dilute to semi-dilute regimes. Rheological measurements revealed that the threshold at which a concentration-based regime transition occurs is distinctly solvent-dependent. Complementing rheological analysis with small angle X-ray scattering and zeta potential measurements, our findings reveal that enhancing CNF–solvent interactions increases excluded volume in the dilute regime, emphasizing the importance of the balance between fiber–fiber and fiber–solvent interactions. Moreover, we investigated the transition from colloidal to solid state by creating films from dispersions with varying interaction parameters in semi-dilute regimes. Through mechanical testing and scanning electron microscopy imaging of the fracture surfaces, we highlight the significance of electrokinetic effects in such transitions, as dispersions with higher electrokinetic stabilization gave rise to stronger and tougher films despite having less favorable thermodynamic interaction parameters. Finally, our work provides insights into the thermodynamic and electrokinetic interplay that governs bacterial CNF dispersion, offering a foundation for future application and a deeper understanding of nanocellulose's colloidal and structure-property relationships.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Computing chemical potentials with machine-learning-accelerated simulations to accurately predict thermodynamic properties of molten salts

The successful design and deployment of next-generation nuclear technologies heavily rely on thermodynamic data for relevant molten salt systems. However, the lack of accurate force fields and efficient methods has limited the quality of thermodynamic predictions from atomistic simulations. Here we propose an efficient free energy framework for computing chemical potentials, which is the central free energy quantity behind many thermodynamic properties. We accelerate our simulations without sacrificing accuracy by using machine learning interatomic potentials trained on density functional theory (DFT) data. Using lithium chloride as our model system, we compute chemical potentials with DFT-accuracy for solid and liquid phases by transmuting ions into noninteracting particles. Notably, in the liquid phase, we demonstrate consistency whether we transmute one ion pair or the entire system into ideal gas particles. By locating the temperature where the chemical potential of solid and liquid phases cross, we predict a melting point of 880 ± 18 K for lithium chloride, which is remarkably close to the experimental value of 883 K. With this successful demonstration, we lay the foundation for high-throughput thermodynamic predictions of many properties that can be derived from the chemical potentials of the minority and majority components in molten salts.

Gibson, Luke D. [Oak Ridge National Laboratory (OR↗

DOE OSTI2024

Learning thermodynamically constrained equations of state with uncertainty

Numerical simulations of high energy-density experiments require equation of state (EOS) models that relate a material’s thermodynamic state variables—specifically pressure, volume/density, energy, and temperature. EOS models are typically constructed using a semi-empirical parametric methodology, which assumes a physics-informed functional form with many tunable parameters calibrated using experimental/simulation data. Since there are inherent uncertainties in the calibration data (parametric uncertainty) and the assumed functional EOS form (model uncertainty), it is essential to perform uncertainty quantification (UQ) to improve confidence in EOS predictions. Model uncertainty is challenging for UQ studies since it requires exploring the space of all possible physically consistent functional forms. Thus, it is often neglected in favor of parametric uncertainty, which is easier to quantify without violating thermodynamic laws. This work presents a data-driven machine learning approach to constructing EOS models that naturally captures model uncertainty while satisfying the necessary thermodynamic consistency and stability constraints. We propose a novel framework based on physics-informed Gaussian process regression (GPR) that automatically captures total uncertainty in the EOS and can be jointly trained on both simulation and experimental data sources. A GPR model for the shock Hugoniot is derived, and its uncertainties are quantified using the proposed framework. We apply the proposed model to learn the EOS for the diamond solid state of carbon using both density functional theory data and experimental shock Hugoniot data to train the model and show that the prediction uncertainty is reduced by considering thermodynamic constraints.

Sharma, Himanshu (ORCID:000900050235718X)↗

DOE OSTI2024

RASPA3

RASPA3, a molecular simulation code for computing adsorption and diffusion in nanoporous materials and thermodynamic and transport properties of fluids. It implements force field based classical Monte Carlo/molecular dynamics in various ensembles. RASPA3 is rewritten from the ground up in C++23 with speed and code readability in mind. Transition-matrix Monte Carlo is added to compute the density of states and free energies. The Monte Carlo code for rigid molecules is based on quaternions, and the atomic positions needed in the energy evaluation are recreated from the center of mass position and quaternion orientation. The expanded ensemble methodology for fractional molecules, with a scaling parameter λ between 0 and 1, now also keeps track of analytic expressions of dU/dλ, allowing independent verification of the chemical potential using thermodynamic integration. The source code is freely available under the MIT license on GitHub.

Dubbeldam, David↗

DOE OSTI2025

Thermodynamics of calcium binding to heparin: Implications of solvation and water structuring for polysaccharide biofunctions

Heparan sulfates are found in all animal tissues and have essential roles in living systems. This family of biomacromolecules modulates binding to calcium ions (Ca 2+ ) in low free energy reactions that influence biochemical processes from cell signaling and anticoagulant efficacy to biomineralization. Despite their ubiquity, the thermodynamic basis for how heparans and similarly functionalized biomolecules regulate Ca 2+ interactions is not yet established. Using heparosan (Control) and heparins with different positions of sulfate groups, we quantify how SO 3 − and COO − content and SO 3 − position modulate Ca 2+ binding by isothermal titration calorimetry. The free energy of all heparin-Ca2+ interactions (ΔG rxn ) is dominated by entropic contributions due to favorable water release from polar, hydrophilic groups. Heparin with both sulfate esters (O-SO 3 − ) and sulfamides (N-SO 3 − ) has the strongest binding to Ca 2+ compared to heparosan and to heparin with only O-SO 3 − groups (~3X). By linking Ca 2+ binding thermodynamics to measurements of the interfacial energy for calcite (CaCO 3 ) crystallization onto polysaccharides, we show molecule-specific differences in nucleation rate can be explained by differences in water structuring during Ca 2+ interactions. A large entropic term (-TΔS rxn ) upon Ca 2+ –polysaccharide binding correlates with high interfacial energy to CaCO 3 nucleation. Combining our measurements with literature values indicates many Ca 2+ –polysaccharide interactions have a shared thermodynamic signature. The resulting enthalpy–entropy compensation relationship suggests these interactions are generally dominated by water restructuring involving few conformational changes, distinct from Ca 2+ –protein binding. Our findings quantify the thermodynamic origins of heparin-specific interactions with Ca 2+ and demonstrate the contributions of solvation and functional group position during biomacromolecule-mediated ion regulation.

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

Ab initio anharmonic thermodynamic properties of cubic Ca Si O 3 perovskite

We present an ab initio study of the thermodynamic properties of cubic CaSiO 3 perovskite (CaPv) over the pressure and temperature range of the Earth's lower mantle. We compute the anharmonic phonon dispersions throughout the Brillouin zone by utilizing the phonon quasiparticle approach, which characterizes the intrinsic temperature dependence of phonon frequencies and, in principle, captures full anharmonicity. Such temperature-dependent phonon dispersions are used to calculate ab initio free energy in the thermodynamic limit (N → ∞) within the framework of the phonon gas model. Accurate free energy calculations enable us to investigate cubic CaPv's thermodynamic properties, e.g., thermal expansivity, Grüneisen parameter, bulk modulus, heat capacity and thermal equation of state, where anharmonic effects are demonstrated. Furthermore, the present methodology provides an important theoretical approach for exploring phase boundaries, thermodynamic, and thermoelastic properties of strongly anharmonic materials at high pressures and temperatures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Increasing the Thermodynamic Driving Force of the Phosphofructokinase Reaction in Clostridium thermocellum

Glycolysis is an ancient, widespread, and highly conserved metabolic pathway that converts glucose into pyruvate. In the canonical pathway, the phosphofructokinase (PFK) reaction plays an important role in controlling flux through the pathway. Clostridium thermocellum has an atypical glycolysis and uses pyrophosphate (PP i ) instead of ATP as the phosphate donor for the PFK reaction. The reduced thermodynamic driving force of the PP i -PFK reaction shifts the entire pathway closer to thermodynamic equilibrium, which has been predicted to limit product titers. Here, in this study, we replace the PP i -PFK reaction with an ATP-PFK reaction. We demonstrate that the local changes are consistent with thermodynamic predictions: the ratio of fructose 1,6-bisphosphate to fructose-6-phosphate increases, and the reverse flux through the reaction (determined by 13 C labeling) decreases. The final titer and distribution of fermentation products, however, do not change, demonstrating that the thermodynamic constraints of the PP i -PFK reaction are not the sole factor limiting product titer.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Thermosteam: BioSTEAM's Premier Thermodynamic Engine

Thermosteam is a thermodynamic engine capable of solving mass and energy balances, estimating mixture properties, solving thermodynamic phase equilibria, and modeling stoichiometric reactions. All chemical data in Thermosteam is imported from the chemicals library, an open-source compilation of data and functions for the estimation of pure component chemical and mixture properties. Thermosteam’s fast and flexible platform has enabled the evaluation of conceptual and emerging biochemical production processes. The Biorefinery Simulation and Techno-Economic Analysis Modules (BioSTEAM) — capable of modeling reactors, distillation columns, heat exchangers, and other unit operations — has adopted Thermosteam as its premier thermodynamic engine. Published biorefinery designs modeled in BioSTEAM implement thermodynamic property packages created with Thermosteam, including a cornstover biorefinery for the production of cellulosic ethanol, a lipid-cane biorefinery for the co-production of ethanol and biodiesel, and a wheatstraw biorefinery for the production of cellulosic ethanol.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

M3SF-24LL010302062-NEA-TDB Management and International Collaborations in Sorption and Thermodynamic Modeling

This progress report (Level 3 Milestone Number M3SF-24LL010302062) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Crystalline International Collaborations Work Package Number SF-24LL01030206. The activity is focused on our long-term commitment to engaging our partners in international nuclear waste repository research. This includes participation in the Nuclear Energy Agency Thermochemical Database (NEA-TDB) Project and development of methodologies for integrating US and international thermodynamic databases for use in SFWST Generic Disposal System Assessment (GDSA) efforts. A continuing focus for FY24 efforts is to support the US participation in the NEA-TDB effort. The focus of FY24 activities was the development of an agreement for a Phase 7 activity that will start in Q1 of 2025. Mavrik Zavarin is now the US representative on both the Management Board and the Executive group to the NEA-TDB. He is also the POC for the Cements State of the Art Report that is undergoing peer review in FY24. In FY24, we used our position on the NEA-TDB MB and EG to facilitate the integration of NEA-TDB thermochemical data with LLNL’s SUPCRTNE thermodynamic database that supports the SFWST GDSA activities. This effort is coordinated with the Argillite work package SUPCRTNE database development efforts (Wolery, 2024). The goal is to provide a downloadable database that will be hosted on LLNL’s thermodynamics website which incorporates NEA-TDB data into the LLNL database where appropriate. We also began engagement with the EURAD2 program that was initiated in FY24 by our European collaborators at the Karlsruhe Institute of Technology (KIT), Germany. The primary focus of the engagement is with WP20: DITUSC Thermodynamic database evaluation program. A kickoff meeting for this activity is planned for early FY25. Finally, we have been selected to co-host (with Clemson University) the International Conference on Chemistry and Migration Behaviour of Actinides and Fission Products in the Geosphere in 2025 (Migration2025). The meeting will be held September 21-26, 2025, in New Orleans, Louisiana, and will focus on international efforts to understand the risks of radionuclide releases into the environment. This central focus of this conference is on international efforts to develop safe disposal options for nuclear wastes. As such, we are developing a theme focused on US underground nuclear waste repository science.

58 GEOSCIENCES↗

DOE OSTI2020

As a Matter of State: The Role of Thermodynamics in Magnetohydrodynamic Turbulence

Turbulence simulations play a key role in advancing the general understanding of the physical properties of turbulence and in interpreting astrophysical observations of turbulent plasmas. For the sake of simplicity, however, turbulence simulations are often conducted in the isothermal limit. Given that the majority of astrophysical systems are not governed by isothermal dynamics, we aim to quantify the impact of thermodynamics on the physics of turbulence, through varying adiabatic index, γ, combined with a range of optically thin cooling functions. Here, we present a suite of ideal magnetohydrodynamics simulations of thermally balanced stationary turbulence in the subsonic, super-Alfvénic, high ${\beta }_{{\rm{p}}}$ (ratio of thermal to magnetic pressure) regime, where turbulent dissipation is balanced by two idealized cooling functions (approximating linear cooling and free–free emission) and examine the impact of the equation of state by considering cases that correspond to isothermal, monatomic, and diatomic gases. We find a strong anticorrelation between thermal and magnetic pressure independent of thermodynamics, whereas the strong anticorrelation between density and magnetic field found in the isothermal case weakens with increasing γ. Similarly, the linear relation between variations in density and thermal pressure with sonic Mach number becomes steeper with increasing γ. This suggests that there exists a degeneracy in these relations with respect to thermodynamics and Mach number in this regime, which is dominated by slow magnetosonic modes. These results have implications for attempts to infer (e.g.,) Mach numbers from (e.g.,) Faraday rotation measurements, without additional information regarding the thermodynamics of the plasma. However, our results suggest that this degeneracy can be broken by utilizing higher-order moments of observable distribution functions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

A modified thermodynamic sea ice model and its application

This paper presents a modified thermodynamic sea ice model based on the Winton’s three-layer model framework. Several improvements focused on the vertical thermodynamics have been made in the model. Results from a series of one-dimensional experiments show that equilibrium ice thickness in our modified model is increased by about 45 cm when compared with the original Winton’s model. Sensitivity tests indicate that all modifications mentioned above contribute to this change of ice thickness, among which the increase of ice layer has the most significant effect followed by the sea ice conductivity parameterization. The modified thermodynamic sea ice model is then coupled into the sea ice component SIS in GFDL MOM4 to exert long-term integration experiments forced by CORE2.0 data. Results indicate that the modified model shows significant improvement in simulating the Arctic sea ice, including an increase in both the sea ice thickness and volume over the whole Arctic region. This confirms the above founding from 1-D simulations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Thermodynamic assessment of nonstoichiometric oxides for solar thermochemical fuel production

Two-step solar thermochemical cycling (STC) based on nonstoichiometric oxides is an ideal means of solar fuel (e.g., H 2 , CO) production. Screening of nonstoichiometric oxides with excellent thermodynamic performance is key to achieving high solar-to-fuel efficiency. However, application-driven materials assessment intended for reactor-level solar fuel production performance requires mimicking realistic operating conditions of on-sun tests in a laboratory setting, which makes oxides assessment and screening an onerous task to accomplish experimentally. In this work, a rapid assessment and screening model of nonstoichiometric oxides for two-step solar thermochemical cycling assuming fixed-bed flow pattern and quasi-equilibration of the solid with the flowing gas phase is developed, with solar-to-fuel efficiency being the target function of optimization. The model accounts for the thermodynamic parameters of oxide materials and typical operating conditions of experimental thermochemical cycling. This study employed the model to explore and compare two groups of typical nonstoichiometric oxides (CeO 2 - and (LaSr)MnO 3 -based) for their maximum efficiency under their uniquely optimized cycling conditions. The results show that CeO 2 can reach a maximum efficiency of 12.9% at reduction temperature of 1500 °C, which is superior to other candidate materials, including 20 mol% Zr-doped CeO 2 (10.1%), La 0.6 Sr 0.4 MnO 3 (2.5%) and La 0.8 Sr 0.2 MnO 3 (3.3%). Even when the reduction temperature is lowered to 1350 °C, ceria yields the highest efficiency amongst the candidate STC materials considered. The optimal cycling strategy depends on the inherent thermodynamic properties of the oxides. This approach serves as a framework for assessing the maximum efficiency and optimal conditions of candidate thermochemical materials within a range of constraints rather than comparing materials under arbitrary cycling conditions, which may inherently favor one material over another. For oxidation temperatures below 800–1000 °C, the model could be further improved by considering reaction kinetics.

14 SOLAR ENERGY↗

DOE OSTI2023

Deuterated water as a substrate-agnostic isotope tracer for investigating reversibility and thermodynamics of reactions in central carbon metabolism

Stable isotope tracers are a powerful tool for the quantitative analysis of microbial metabolism, enabling pathway elucidation, metabolic flux quantification, and assessment of reaction and pathway thermodynamics. 13 C and 2 H metabolic flux analysis commonly relies on isotopically labeled carbon substrates, such as glucose. However, the use of 2 H-labeled nutrient substrates faces limitations due to their high cost and limited availability in comparison to 13 C-tracers. Furthermore, isotope tracer studies in industrially relevant bacteria that metabolize complex substrates such as cellulose, hemicellulose, or lignocellulosic biomass, are challenging given the difficulty in obtaining these as isotopically labeled substrates. In this study, we examine the potential of deuterated water ( 2 H 2 O) as an affordable, substrate-neutral isotope tracer for studying central carbon metabolism. We apply 2 H 2 O labeling to investigate the reversibility of glycolytic reactions across three industrially relevant bacterial species -C. thermocellum, Z. mobilis, and E. coli-harboring distinct glycolytic pathways with unique thermodynamics. We demonstrate that 2 H 2 O labeling recapitulates previous reversibility and thermodynamic findings obtained with established 13 C and 2 H labeled nutrient substrates. Furthermore, we exemplify the utility of this 2 H 2 O labeling approach by applying it to high-substrate C. thermocellum fermentations -a setting in which the use of conventional tracers is impractical-thereby identifying the glycolytic enzyme phosphofructokinase as a major bottleneck during high-substrate fermentations and unveiling critical insights that will steer future engineering efforts to enhance ethanol production in this cellulolytic organism. This study demonstrates the utility of deuterated water as a substrate-agnostic isotope tracer for examining flux and reversibility of central carbon metabolic reactions, which yields biological insights comparable to those obtained using costly 2 H-labeled nutrient substrates.

09 BIOMASS FUELS↗

DOE OSTI2024

Quantitative Predictive Theories through Integrating Quantum, Statistical, Equilibrium, and Nonequilibrium Thermodynamics

Today's thermodynamics is largely based on the combined law for equilibrium systems and statistical mechanics derived by Gibbs in 1873 and 1901, respectively, while irreversible thermodynamics for nonequilibrium systems resides essentially on the Onsager Theorem as a separate branch of thermodynamics developed in 1930s. Between them, quantum mechanics was invented and was quantitatively solved in terms of density functional theory (DFT) in 1960s. Furthermore, these three scientific domains operate based on different principles and are very much separated from each other. In analogy to the parable of the blind men and the elephant articulated by Perdew, they individually represent different portions of a complex system and thus are incomplete by themselves alone, resulting in the lack of quantitative agreement between their predictions and experimental observations. Over the last two decades, the author's group has developed a multiscale entropy approach (recently termed as zentropy theory) that integrates DFT-based quantum mechanics and Gibbs statistical mechanics and is capable of accurately predicting entropy and free energy of complex systems. Furthermore, in combination with the combined law for nonequilibrium systems developed by Hillert, the author developed the theory of cross phenomena beyond the phenomenological Onsager Theorem. The zentropy theory and theory of cross phenomena jointly provide quantitative predictive theories for systems from electronic to any observable scales as reviewed in the present work.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Transport phenomena in electrolyte solutions: Nonequilibrium thermodynamics and statistical mechanics

The theory of transport phenomena in multicomponent electrolyte solutions is presented here through the integration of continuum mechanics, electromagnetism, and nonequilibrium thermodynamics. The governing equations of irreversible thermodynamics, including balance laws, Maxwell's equations, internal entropy production, and linear laws relating the thermodynamic forces and fluxes, are derived. Green–Kubo relations for the transport coefficients connecting electrochemical potential gradients and diffusive fluxes are obtained in terms of the flux–flux time correlations. Furthermore, the relationship between the derived transport coefficients and those of the Stefan–Maxwell and infinitely dilute frameworks are presented, and the connection between the transport matrix and experimentally measurable quantities is described. To exemplify the application of the derived Green–Kubo relations in molecular simulations, the matrix of transport coefficients for lithium and chloride ions in dimethyl sulfoxide is computed using classical molecular dynamics and compared with experimental measurements.

42 ENGINEERING↗

DOE OSTI2021

Evaluation and Applications of Multi-Instrument Boundary-Layer Thermodynamic Retrievals

Recent reports have highlighted the need for improved observations of the atmosphere boundary layer. In this study, we explore the combination of ground-based active and passive remote sensors deployed for thermodynamic profiling to analyze various boundary-layer observation strategies. Optimal-estimation retrievals of thermodynamic profiles from Atmospheric Emitted Radiance Interferometer (AERI) observed spectral radiance are compared with and without the addition of active sensor observations from a May–June 2017 observation period at the Atmospheric Radiation Measurement Southern Great Plains site. In all, three separate thermodynamic retrievals are considered here: retrievals including AERI data only, retrievals including AERI data and Vaisala water vapour differential-absorption lidar data, and retrievals including AERI data and Raman lidar data. First, the three retrievals are compared to each other and to reference radiosonde data over the full observation period to obtain a bulk understanding of their differences and characterize the impact of clouds on these retrieved profiles. These analyses show that the most significant differences are in the water vapour field, where the active sensors are better able to represent the moisture gradient in the entrainment zone near the boundary-layer top. Furthermore, we also explore how differences in retrievals may affect results of applied analyses including land–atmosphere coupling, convection indices, and severe storm environmental characterization. Overall, adding active sensors to the optimal-estimation retrieval shows some added information, particularly in the moisture field. Given the costs of such platforms, the value of that added information must be weighed for the application at hand.

54 ENVIRONMENTAL SCIENCES↗