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At least 541 records · Page 30

Changes in Four Decades of Near‐CONUS Tropical Cyclones in an Ensemble of 12 km Thermodynamic Global Warming Simulations

We evaluate tropical cyclones (TCs) in a set of thermodynamic global warming (TGW) simulations over the continental United States (CONUS). A 12 km simulation forced by ERA5 provides a 40‐year historical (1980–2019) control. Four complimentary future scenarios are generated using thermodynamic deltas applied to lateral boundary, interior, and surface forcing. We curate a data set of 4,498 6‐hourly TC snapshots in the control and find a corresponding “twin” in each counterfactual, permitting a paired comparison. Warming results in an increase in mean dynamical TC intensity and moisture‐related quantities, with the latter being more pronounced. TC inner cores contract slightly but outer storm size remains unchanged. The frequency with which TCs become more intense is only moderately consistent, with snapshots having increased hazards ranging from 50% to 80% depending on warming level. The fractions of TCs undergoing rapid intensification and weakening both increase across all warming simulations, suggesting elevated short‐term intensity variability.

54 ENVIRONMENTAL SCIENCES↗

Changes in extremely hot days under stabilized 1.5 and 2.0 °C global warming scenarios as simulated by the HAPPI multi-model ensemble

Abstract. The half a degree additional warming, prognosis and projected impacts (HAPPI) experimental protocol provides a multi-model database to compare the effects of stabilizing anthropogenic global warming of 1.5 °C over preindustrial levels to 2.0 °C over these levels. The HAPPI experiment is based upon large ensembles of global atmospheric models forced by sea surface temperature and sea ice concentrations plausible for these stabilization levels. This paper examines changes in extremes of high temperatures averaged over three consecutive days. Changes in this measure of extreme temperature are also compared to changes in hot season temperatures. We find that over land this measure of extreme high temperature increases from about 0.5 to 1.5 °C over present-day values in the 1.5 °C stabilization scenario, depending on location and model. We further find an additional 0.25 to 1.0 °C increase in extreme high temperatures over land in the 2.0 °C stabilization scenario. Results from the HAPPI models are consistent with similar results from the one available fully coupled climate model. However, a complicating factor in interpreting extreme temperature changes across the HAPPI models is their diversity of aerosol forcing changes.

54 ENVIRONMENTAL SCIENCES↗

High Pressure Infiltration/Expulsion of Aqueous NaCl in Planar Hydrophobic Nanopores

Pressure-driven permeation of water in a poorly wettable material results in a conversion of mechanical work into surface free energy representing a new form of energy storage, or absorption. When water is replaced by a concentrated electrolyte solution, the storage capacity of a nanoporous medium becomes comparable to high-end supercapacitors. The addition of salt can also reduce the hysteresis of the infiltration/expulsion cycle. Our molecular simulations provide a theoretical perspective into the mechanisms involved in the process, and underlying structures and interactions in compressed nanoconfined solutions. Specifically, we consider aqueous NaCl in planar confinements of widths of 1.0 nm and 1.64 nm and pressures of up to 3 kbar. Open ensemble Monte Carlo simulations utilizing fractional exchanges of molecules for efficient additions/removal of ions have been utilized in conjunction with pressure-dependent chemical potentials to model bulk phases under pressure. Confinements open to these pressurized bulk, aqueous electrolyte phases show reversibility at narrow pore sizes and irreversibility in wider ones, consistent with experiment, as well as strong hysteresis at both pore size. The addition of salt results in significant increases in the solid/liquid interfacial tension in narrower pores and associated infiltration and expulsion pressures. Furthermore, these changes are consistent with strong desalination effects at the lower pore size observed irrespective of external pressure and initial concentration.

25 ENERGY STORAGE↗

Forces and stress in second order Møller-Plesset perturbation theory for condensed phase systems within the resolution-of-identity Gaussian and plane waves approach

The forces acting on the atoms as well as the stress tensor are crucial ingredients for calculating the structural and dynamical properties of systems in the condensed phase. Here, these derivatives of the total energy are evaluated for the second-order Møller-Plesset perturbation energy (MP2) in the framework of the resolution of identity Gaussian and plane waves method, in a way that is fully consistent with how the total energy is computed. This consistency is non-trivial, given the different ways employed to compute Coulomb, exchange, and canonical four center integrals, and allows, for example, for energy conserving dynamics in various ensembles. Based on this formalism, a massively parallel algorithm has been developed for finite and extended system. The designed parallel algorithm displays, with respect to the system size, cubic, quartic, and quintic requirements, respectively, for the memory, communication, and computation. All these requirements are reduced with an increasing number of processes, and the measured performance shows excellent parallel scalability and efficiency up to thousands of nodes. Additionally, the computationally more demanding quintic scaling steps can be accelerated by employing graphics processing units (GPU’s) showing, for large systems, a gain of almost a factor two compared to the standard central processing unit-only case. In this way, the evaluation of the derivatives of the RI-MP2 energy can be performed within a few minutes for systems containing hundreds of atoms and thousands of basis functions. With good time to solution, the implementation thus opens the possibility to perform molecular dynamics (MD) simulations in various ensembles (microcanonical ensemble and isobaric-isothermal ensemble) at the MP2 level of theory. Geometry optimization, full cell relaxation, and energy conserving MD simulations have been performed for a variety of molecular crystals including NH{sub 3}, CO{sub 2}, formic acid, and benzene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural, electronic, and dynamical properties of liquid water by ab initio molecular dynamics based on SCAN functional within the canonical ensemble

We perform ab initio molecular dynamics (AIMD) simulation of liquid water in the canonical ensemble at ambient conditions using the strongly constrained and appropriately normed (SCAN) meta-generalized-gradient approximation (GGA) functional approximation and carry out systematic comparisons with the results obtained from the GGA-level Perdew-Burke-Ernzerhof (PBE) functional and Tkatchenko-Scheffler van der Waals (vdW) dispersion correction inclusive PBE functional. We analyze various properties of liquid water including radial distribution functions, oxygen-oxygen-oxygen triplet angular distribution, tetrahedrality, hydrogen bonds, diffusion coefficients, ring statistics, density of states, band gaps, and dipole moments. We find that the SCAN functional is generally more accurate than the other two functionals for liquid water by not only capturing the intermediate-range vdW interactions but also mitigating the overly strong hydrogen bonds prescribed in PBE simulations. We also compare the results of SCAN-based AIMD simulations in the canonical and isothermal-isobaric ensembles. Our results suggest that SCAN provides a reliable description for most structural, electronic, and dynamical properties in liquid water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Impact of ENSO and NAO Initial Conditions and Anomalies on the Modeled Response to Pinatubo-Sized Volcanic Forcing

Strong, strato-volcanic eruptions are a substantial, intermittent source of natural climate variability. Initial atmospheric and oceanic conditions, such as El Niño Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO), also naturally impact climate on interannual timescales. We examine how initial conditions of ENSO and NAO contribute to the evolution of climate in the period following a Pinatubo-type eruption using a large (81-member) ensemble of model simulations in GISS model E2.1-G. Simulations are initialized from sampled conditions of ENSO and NAO using the protocol of the coordinated CMIP6 Volcanic Model Intercomparison Project (VolMIP) – where aerosols are forced with respect to time, latitude, and height. We analyze paired anomalous variations (perturbed – control) to understand changes in global and regional climate responses under positive, negative, and neutral ENSO and NAO conditions. In particular, we find that for paired anomalies there is a high probability of strong (∼1.5 °C) warming of northern Eurasia surface air temperature in the first winter after the volcanic eruption for negative NAO ensembles coincident with decreased lower stratospheric temperature at the poles, decreased geopotential height, and strengthening of the stratospheric polar vortex. Climate anomalies (relative to average conditions across the control period), however, show no mean warming and suggest that the strength of this response is impacted by conditions present in the selected period of the control run. Again using paired anomalies, we also observe that under both +ENSO and −ENSO ensembles sea surface temperature decreases in the first post-eruptive boreal winter coinciding with surface cooling from volcanic aerosols. Neutral ENSO ensembles, on the other hand, show variability in their response with no clear trend in post-eruptive warming or cooling. In general, paired anomalies from unperturbed simulations give insight into the evolution of the climate response to volcanic forcing; however, when compared with anomalies from climatological conditions, it is clear that paired anomalies are significantly affected by sampled initial conditions occurring at the time of the volcanic eruption.

volcanic eruptions↗

Phase Equilibria and Condensed Phase Properties of Fluorinated Alkanes via First Principles Simulations

Vapor liquid equilibria (VLE) of organic compounds is governed by weak non-covalent interactions. This presents a significant challenge in predicting VLE using a first principles approach where density functional theory is used to model system potential. However, a dispersion corrected approach has significantly improved the performance of traditional density functionals. Here, we predict the VLE for a nonpolar carbon tetrafluoride (R14) and polar 1,1,1,2-tetrafluoroethane (R134a)via first principles Gibbs ensemble Monte Carlo simulations using PBED3 density functional. We find that the saturated liquid density for R14 is slightly under predicted for subcritical temperatures, while for R134a it is under predicted at lower reduced temperatures and over predicted at higher reduced temperatures. In the liquid phase, angle-resolved pair correlation functions indicate slight preference for R143a to align in parallel and antiparallel orientation in the first solvation shell.The vibrational spectra reveal peak broadening in the condensed phase due to solvothermal effects. Altogether, we find thePBED3 functional performance is better for the nonpolar molecule as compared to the polar one.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluating the Uncertainty of Terrestrial Water Budget Components over High Mountain Asia

This study explores the uncertainties in terrestrial water budget estimation over High Mountain Asia (HMA) using a suite of uncoupled land surface model (LSM) simulations. The uncertainty in the water balance components of precipitation (P), evapotranspiration (ET), runoff (R), and terrestrial water storage (TWS) is significantly impacted by the uncertainty in the driving meteorology, with precipitation being the most important boundary condition. Ten gridded precipitation datasets along with a mix of model-, satellite-, and gauge-based products, are evaluated first to assess their suitability for LSM simulations over HMA. The datasets are evaluated by quantifying the systematic and random errors of these products as well as the temporal consistency of their trends. Though the broader spatial patterns of precipitation are generally well captured by the datasets, they differ significantly in their means and trends. In general, precipitation datasets that incorporate information from gauges are found to have higher accuracy with low Root Mean Square Errors and high correlation coefficient values. An ensemble of LSM simulations with selected subset of precipitation products is then used to produce the mean annual fluxes and their uncertainty over HMA in P, ET, and R to be 2.11 ± 0.45, 1.26 ± 0.11, and 0.85 ± 0.36 mm per day, respectively. The mean annual estimates of the surface mass (water) balance components from this model ensemble are comparable to global estimates from prior studies. However, the uncertainty/spread of P, ET, and R is significantly larger than the corresponding estimates from global studies. A comparison of ET, snow cover fraction, and changes in TWS estimates against remote sensing-based references confirms the significant role of the input meteorology in influencing the water budget characterization over HMA and points to the need for improving meteorological inputs.

Terrestrial water budget↗

Data-guided Multi-Map variables for ensemble refinement of molecular movies

Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. In this study, the three-dimensional electron density of a protein, as it would be determined by cryo-EM or x-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density-driven molecular dynamics methodologies that determine only the best map-model fits, our work employs the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along the chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along the reaction coordinates derived from electron densities can capture conformational transitions between known intermediates. The simulated pathways appear reversible with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein Data Bank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution density information coupled to comparatively large structural transitions. Practical considerations for probing the transitions between multiple intermediate density states are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Equipartition and the Temperature of Maximum Density of TIP4P/2005 Water

Here, we simulate TIP4P/2005 water in the temperature range of 257 to 318 K with time-steps δ = 0.25, 0.50, 1.00, 2.00, and 4.00 fs. The density–temperature behavior obtained using 0.25 or 0.50 fs is in excellent agreement with each other but differs from those obtained using time steps that have been shown earlier to lead to a breakdown of equipartition. For δt = 0.25 or 0.50 fs, the temperature of maximum density (TMD) is 277.15 K and the density value is in close agreement with experiments. For δt = 1.00 fs, the TMD is 277.15 K, but the density value is shifted higher. For the other time steps considered here, the TMD is shifted to progressively lower values for longer time steps, a trend that holds for different thermostat/barostat combinations. Enhancing the water–water dispersion interaction, as has been recommended for simulating disordered proteins in TIP4P/2005, degrades the description of the liquid–vapor phase envelope. We present a simple physically transparent explanation that highlights the separation of the time scales between translational and rotational motion. We also develop a metric, χ, that we term the equipartition anomaly, to detect equipartition violations in simulations that include molecules that are treated as rigid objects. Calculating χ is shown to be straightforward and sensitive to equipartition violations. A key takeaway from this study is that using sufficiently short time steps (≤0.5 fs) to preserve equipartition is essential for obtaining meaningful liquid water properties and for producing reliable simulation data, as correct ensemble sampling is fundamental to ensure reproducibility across codes and simulation algorithms.

Asthagiri, Dilipkumar N. [Oak Ridge National Labor↗

High-Performance Semiempirical Excited-State Molecular Dynamics Powered by Graphics Processing Units

Here, this Letter introduces excited-state molecular dynamics in PYSEQM, a GPU-accelerated semiempirical quantum chemistry engine implemented in PyTorch. The new module enables Born–Oppenheimer molecular dynamics (BOMD) using configuration-interaction singles and random phase approximation for excited states, allowing long trajectories and large statistical ensembles to be simulated efficiently on a single GPU. We also implement an extended Lagrangian excited-state BOMD (XL-ESMD) scheme that propagates auxiliary electronic variables, enabling relaxed ground and excited-state convergence thresholds without compromising energy conservation. The excited-state BOMD implementation scales smoothly from small chromophores to a nearly 900-atom dendrimer (taking 6.5 s per MD step). PYSEQM also supports batched execution, allowing many geometries or trajectories to be evaluated in a single GPU launch, substantially increasing throughput and making ensemble-based protocols routine. As a demonstration, we compute absorption, emission, and infrared spectra from trajectories propagated on the ground and first excited states. The XL-ESMD scheme yields identical spectra at significantly lower computational cost, establishing the role of extended Lagrangian based dynamics for efficient excited-state BOMD simulations. Beyond raw performance, PYSEQM’s PyTorch foundation provides automatic differentiation for forces, efficient GPU batching, and seamless interfacing with machine learning models. These capabilities position PYSEQM as a practical platform for machine learning-augmented excited-state dynamics and lay the foundation for future data-driven nonadiabatic excited-state dynamics modeling of ultrafast spectroscopic probes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-Resolution Modeling to Assess Tropical Cyclone Activity in Future Climate Regimes

Applied research is proposed with the following objectives: (i) to determine the most likely level of tropical cyclone intensity and frequency in future climate regimes, (ii) to provide a quantitative measure of uncertainty in these predictions, and (iii) to improve understanding of the linkage between tropical cyclones and the planetary-scale circulation. Current mesoscale weather forecasting models, such as the Weather Research and Forecasting (WRF) model, are capable of simulating the full intensity of tropical cyclones (TC) with realistic structures. However, in order to accurately represent both the primary and secondary circulations in these systems, model simulations must be configured with sufficient resolution to explicitly represent convection (omitting the convective parameterization scheme). Most previous numerical studies of TC activity at seasonal and longer time scales have not utilized such explicit convection (EC) model runs. Here, we propose to employ the moving nest capability of WRF to optimally represent TC activity on a seasonal scale using a downscaling approach. The statistical results of a suite of these high-resolution TC simulations will yield a realistic representation of TC intensity on a seasonal basis, while at the same time allowing analysis of the feedback that TCs exert on the larger-scale climate system. Experiments will be driven with analyzed lateral boundary conditions for several recent Atlantic seasons, spanning a range of activity levels and TC track patterns. Results of the ensemble of WRF simulations will then be compared to analyzed TC data in order to determine the extent to which this modeling setup can reproduce recent levels of TC activity. Next, the boundary conditions (sea-surface temperature, tropopause height, and thermal/moisture profiles) from the recent seasons will be altered in a manner consistent with various future GCM/RCM scenarios, but that preserves the large-scale shear and incipient disturbance activity. This will allow (i) a direct comparison of future TC activity that could be expected for an active or inactive season in an altered climate regime, and (ii) a measure of the level of uncertainty and variability in TC activity resulting from different carbon emission scenarios.

58 GEOSCIENCES↗

ENSO's Changing Influence on Temperature, Precipitation, and Wildfire in a Warming Climate

On interannual to decadal time scales, the climate mode with many of the strongest societal impacts is the El Niño–Southern Oscillation (ENSO). However, quantifying ENSO's changes in a warming climate remains a formidable challenge, due to both the noise arising from internal variability and the complexity of air-sea feedbacks in the tropical Pacific Ocean. In this paper, we use large (≥30-member) ensembles of climate simulations to show that anthropogenic climate change can produce systematic increases in ENSO teleconnection strength over many land regions, driving increased interannual variability in regional temperature extremes and wildfire frequency. As the spatial character of this intensification exhibits strong land-ocean contrasts, a causal role for land-atmosphere feedbacks is suggested. The identified increase in variance occurs in multiple model ensembles, independent of changes in sea surface temperature variance. In conclusion, this suggests that in addition to changes in the overall likelihoods of heat and wildfire extremes, the variability in these events may also be a robust feature of future climate.

54 ENVIRONMENTAL SCIENCES↗

Scaling Analysis of Two–Phase Flow in Fractal Permeability Fields

Fluid mixing in permeable media is essential in many practical applications. The mixing process is a consequence of velocity fluctuations owing to geological heterogeneities and mobility contrast of fluids. Heterogeneities in natural rocks are often spatially correlated, and their properties, such as permeability, may be described using fractal distributions. This work models the fractal characteristics of such permeability fields in which the covariance function is expressed as a power-law function. A generalized scaling relation is derived relating various fractal permeability fields using the magnitude of their fluctuations. Here, this relation reveals the self-similar behavior of two-phase flow in such permeable media. To that end, a recently developed, high-resolution numerical simulator is employed to validate the analytically derived scaling relations. Two flow problems are considered in which flow is governed by 1) a linear, and 2) a nonlinear transport equation. Due to the probabilistic representation of the fractal permeability fields, a sensitivity study is conducted for each flow scenario to determine the number of realizations required for statistical convergence. Scaling analysis is performed using ensemble averages of simulated saturation profiles and their mixing lengths. Results support the validity of the developed scaling relation across the range of investigated flow conditions at intermediate times. The dynamics of linear flow in the asymptotic regime is affected by the correlation structure of heterogeneity. In nonlinear flow, scaling behavior appears to be dominated by the degree of nonlinearity.

58 GEOSCIENCES↗

Calculation of the Gibbs Free Energy of Solvation and Dissociation of HCl in Water via Monte Carlo Simulations and Continuum Solvation Models

The free energy of solvation and dissociation of hydrogen chloride in water is calculated through a combined molecular simulation quantum chemical approach at four temperatures between T = 300 and 450 K. The free energy is first decomposed into the sum of two components: the Gibbs free energy of transfer of molecular HCl from the vapor to the aqueous liquid phase and the standard-state free energy of acid dissociation of HCl in aqueous solution. The former quantity is calculated using Gibbs ensemble Monte Carlo simulations using either Kohn-Sham density functional theory or a molecular mechanics force field to determine the system’s potential energy. The latter free energy contribution is computed using a continuum solvation model utilizing either experimental reference data or micro-solvated clusters. The predicted combined solvation and dissociation free energies agree very well with available experimental data. CJM was supported by the US Department of Energy,Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences. Pacific Northwest National Laboratory is operated by Battelle for the US Department of Energy.

McGrath, Matthew↗

Avoiding pitfalls in molecular simulation of vapor sorption: Example of propane and isobutane in metal–organic frameworks for adsorption cooling applications

This study introduces recommendations for conducting molecular simulations of vapor adsorption, with an emphasis on enhancing the accuracy, reproducibility, and comparability of results. The first aspect we address is consistency in the implementation of some details of typical molecular models, including tail corrections and cutoff distances, due to their significant influence on generated data. We highlight the importance of explicitly calculating the saturation pressures at relevant temperatures using methods such as Gibbs ensemble Monte Carlo simulations and illustrate some pitfalls in extrapolating saturation pressures using this method. For grand canonical Monte Carlo (GCMC) simulations, the input fugacity is usually calculated using an equation of state, which often requires the critical parameters of the fluid. We show the importance of using critical parameters derived from the simulation with the same model to ensure internal consistency between the simulated explicit adsorbate phase and the implicit bulk phase in GCMC. We show the advantages of presenting isotherms on a relative pressure scale to facilitate easier comparison among models and with experiment. Extending these guidelines to a practical case study, we evaluate the performance of various isoreticular metal–organic frameworks (MOFs) in adsorption cooling applications. This includes examining the advantages of using propane and isobutane as working fluids and identifying MOFs with a superior performance.

36 MATERIALS SCIENCE↗

Spectral Gap Filling Method Using the Spectral Information from CLARREO-Pathfinder Measured Earth-Reflected Solar Spectra to Support CPF-CERES Intercalibration

The high-accuracy Earth-reflected solar spectral radiances from CLARREO Pathfinder (CPF) will serve as in-orbit benchmark measurements for intercalibrating other satellite imagers. The CPF team is developing a state-of-the-art intercalibration method to calibrate the shortwave channel (300-5000 nm) of the CERES instrument against the CPF reference with an uncertainty of 0.3%. Because the CPF instrument only covers spectral range from 350 nm to 2300 nm, the team has developed a spectral extension method to fill in the gaps between the spectral domains of CPF and the CERES shortwave channel. The method solely relies on using the hyperspectral information from the CPF wavelengths to predict the radiances below 350 nm and above 2300 nm. To quantify the relationship between the CPF spectrum and the non-overlapping portions of the spectrum between CPF and CERES, the team has simulated a large ensemble of spectra that cover the spectral range for both CPF and CERES. A hyperspectral bidirectional reflectance model for land surface based on thousands of measured land surface reflectance has been developed. This land surface model as well as the Cox-Munk model for ocean surface are used in the spectral gap filling. Various water/ice clouds, aerosols, atmosphere profiles and surfaces were used to simulate Earth-reflected radiances from 200 nm to 15 um under different solar and sensor geometries. The targeted uncertainty for the CPF-extended broadband CERES radiances is less than 0.1%. The previously derived training spectra were updated to replace the Kurucz solar irradiance model with the TSIS-1 Hybrid Solar Reference Spectrum. The influence of the scalar assumption in radiative transfer model equations on the uncertainty in estimating the broadband radiances was also investigated.

Hyperspectral↗

DART-PFLOTRAN: An ensemble-based data assimilation system for estimating subsurface flow and transport model parameters

Ensemble-based Data Assimilation (EDA), based on the Monte Carlo approach, has been effectively applied to estimate model parameters through inverse modeling in subsurface flow and transport problems. However, implementation of EDA approach involves a complicated workflow that include setting up and executing ensemble forward model simulations, processing observations and model simulation results for parameter updates, and repeat for sequential or iterative EDA. To facilitate the management of such workflow and lower the barriers for adopting EDA-based parameter estimation in subsurface science, we develop a generic software frame-work linking the Data Assimilation Research Testbed (DART) with a massively parallel subsurface FLOw and TRANsport code PFLOTRAN. The new DART-PFLOTRAN leverages both the core data assimilation engines in DART and the computational power afforded by PFLOTRAN. In addition to the standard smoother and filtering options, DART-PFLOTRAN enables an iterative EDA workflow based on the Ensemble Smoother for Multiple Data Assimilation method (ES-MDA) to improve estimation accuracy for nonlinear forward problems. Here, we verify the implementation of ES-MDA in DART-PFLOTRAN using two synthetic cases designed to estimate static permeability and dynamic exchange fluxes across the riverbed, respectively, from continuous temperature measurements made across a depth profile. One-dimensional hydro-thermal simulations are performed in both cases to relate temperature responses with the parameters of interest. In the case of estimating dynamic parameters, we demonstrate the flexibility of DART-PFLOTRAN in automating sequential ES-MDA workflow, which will significantly reduce the time researchers spend on managing complex workflows in similar applications. Both studies yield accurate estimations of the parameters compared to their synthetic truth, while ES-MDA leads to more accurate estimation when a high level of nonlinearity exist between observed responses and unknown parameters. With a code base in Python and Fortran, DART-PFLOTRAN paves the way for applications in large-scale subsurface inverse modeling by automating the complex workflow of sequential ES-MDA that can be executed on various computing platforms.

97 MATHEMATICS AND COMPUTING↗