SEARCH · Engineering Papers

Results for “scale coupling”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,243 records · Page 69

All sources NASA NTRS DOE OSTI

NASA NTRS2008

[The Extrasolar Planetary Imaging Coronagraph]

The Extrasolar Planetary Imaging Coronagraph (EPIC) is a proposed NASA Exoplanet Probe mission to image and characterize extr asolar giant planets in orbits with semi-major axes between 2 and 10 AU. EPIC will provide insights into the physical nature of a variety of planets in other solar systems complimenting radial velocity (RV) and astrometric planet searches. It will detect and characterize the atmospheres of planets identified by radial velocity surveys, deter mine orbital inclinations and masses, characterize the atmospheres around A and F type stars which cannot be found with RV techniques, and observe the inner spatial structure and colors of debris disks. EPIC has a heliocentric Earth trailing drift-away orbit, with a 5 year mission lifetime (5 year goal). The robust mission design is simple and flexible ensuring mission success while minimizing cost and risk. The science payload consists of a heritage optical telescope assembly (OTA), and visible nulling coronagraph (VNC) instrument. The instrument achieves a contrast ratio of 10(exp 9) over a 4.84 arcsecond field-of-view with an unprecedented inner working angle of 0.14 arcseconds over the spectral range of 440-880 nm. The telescope is a 1.65 meter off-axis Cassegrain with an OTA wavefront error of /9, which when coupled to the VNC greatly reduces the requirements on the large scale optics, compressing them to stability requirements within the relatively compact VNC optical chain. The VNC features two integrated modular nullers, a spatial filter array (SFA) and an E2V-L3 photon counting CCD. Direct null control is accomplished from the science focal plane mitigating against complex wavefront and amplitude sensing and control strategies.

Clampin, Mark↗

NASA NTRS2011

Using EO-1 Hyperion to Simulate HyspIRI Products for a Coniferous Forest: The Fraction of PAR Absorbed by Chlorophyll (fAPAR(sub chl)) and Leaf Water Content (LWC)

This study presents development of prototype products for terrestrial ecosystems in preparation for the future imaging spectrometer planned for the Hyperspectral Infrared Imager (HyspIRI) mission. We present a successful demonstration example in a coniferous forest of two product prototypes: fraction of photosynthetic active radiation (PAR) absorbed by chlorophyll of a canopy (fAPAR(sub chl)) and leaf water content (LWC), for future HyspIRI implementation at 60 m spatial resolution. For this, we used existing 30 m resolution imaging spectrometer data available from the Earth Observing One (EO-1) Hyperion satellite to simulate and prototype the level one radiometrically corrected radiance (L1R) images expected from the HyspIRI visible through shortwave infrared spectrometer. The HyspIRI-like images were atmospherically corrected to obtain surface reflectance, and spectrally resampled to produce 60 m reflectance images for wavelength regions that were comparable to all seven of the MODerate resolution Imaging Spectroradiometer (MODIS) land bands. Thus, we developed MODIS-like surface reflectance in seven spectral bands at the HyspIRI-like spatial scale, which was utilized to derive fAPARchl and LWC with a coupled canopy-leaf radiative transfer model (PROSAIL2) for the coniferous forest[1]. With this study, we provide additional evidence that the fAPARchl product is more realistic for describing the physiologically active canopy than the traditional fAPAR parameter for the whole canopy (fAPAR(sub canopy)), and thus should replace it in ecosystem process models to reduce uncertainties in terrestrial carbon cycle studies and ecosystem studies.

Zhang, Qingyuan↗

NASA NTRS2012

Using EO-1 Hyperion to Simulate HyspIRI Products for a Coniferous Forest: The Fraction of PAR Absorbed by Chlorophyll (fAPAR(sub chl)) and Leaf Water Content(LWC)

This paper presents development of prototype products for terrestrial ecosystems in preparation for the future imaging spectrometer planned for the Hyperspectral Infrared Imager (HyspIRI) mission. We present a successful demonstration example in a coniferous forest of two product prototypes: fraction of photosynthetically active radiation (PAR) absorbed by chlorophyll of a canopy (fAPARchl) and leaf water content (LWC), for future HyspIRI implementation at 60-m spatial resolution. For this, we used existing 30-m resolution imaging spectrometer data available from the Earth Observing One (EO-1) Hyperion satellite to simulate and prototype the level one radiometrically corrected radiance (L1R) images expected from the HyspIRI visible through shortwave infrared spectrometer. The HyspIRIlike images were atmospherically corrected to obtain surface reflectance and spectrally resampled to produce 60-m reflectance images for wavelength regions that were comparable to all seven of the MODerate resolution Imaging Spectroradiometer (MODIS) land bands. Thus, we developed MODIS-like surface reflectance in seven spectral bands at the HyspIRI-like spatial scale, which was utilized to derive fAPARchl and LWC with a coupled canopy-leaf radiative transfer model (PROSAIL2) for the coniferous forest. With this paper, we provide additional evidence that the fAPARchl product is more realistic in describing the physiologically active canopy than the traditional fAPAR parameter for the whole canopy (fAPARcanopy), and thus, it should replace it in ecosystem process models to reduce uncertainties in terrestrial carbon cycle and ecosystem studies.

Earth Observing One↗

NASA NTRS2017

Observations of Deep Ionospheric F-Region Density Depletions with FPMU Instrumentation and Their Relationship with the Global Dynamics of the June 22-23, 2015 Geomagnetic Storm

The magnetic storm that commenced on June 22, 2015 was one of the largest storms in the current solar cycle. During this event, ionospheric F-region density measurements from the Floating Potential Measurement Unit (FPMU) on board the International Space Station (ISS) show dramatic depletions in the post-sunset (nighttime) local time sector at equatorial latitudes starting in the main phase of the storm and persisting on several subsequent orbits into the next day. Putting these low-latitude measurements in context with the global dynamics of the storm, we will present results from simulations and observations in our efforts to better understand the effects of this storm on the different regions of the coupled ionosphere-magnetosphere. The consequences of the magnetospheric penetration electric field and their role in the occurrence of these equatorial spread F observations will be investigated through the results of the SAMI3-RCM numerical model, a coupled ionosphere-magnetosphere model with self-consistent large-scale electrodynamics. Specifically, we will investigate the transient signatures of the interplanetary magnetic field component, Bz, and its role in driving the global convection electric field and ionospheric density redistribution. Lastly, measurements from the AMPERE Birkeland currents, DMSP drift velocities and the particle flux dropouts observed from the Magnetospheric Multiscale Mission (MMS) will be correlated with the FPMU density depletions and each other. Together these observations and simulation results will be assembled to provide each region’s context to the global dynamics and time evolution of the storm.

Coffey, Victoria↗

NASA NTRS2017

Observations of Deep Ionospheric F-Region Density Depletions with FPMU Instrumentation and Their Relationship with the Global Dynamics of the June 22-23, 2015 Geomagnetic Storm

The magnetic storm that commenced on June 22, 2015 was one of the largest storms in the current solar cycle. During this event, ionospheric F-region density measurements from the Floating Potential Measurement Unit (FPMU) on board the International Space Station (ISS) show dramatic depletions in the post-sunset (nighttime) local time sector at equatorial latitudes starting in the main phase of the storm and persisting on several subsequent orbits into the next day. Putting these low-latitude measurements in context with the global dynamics of the storm, we will present results from simulations and observations in our efforts to better understand the effects of this storm on the different regions of the coupled ionosphere-magnetosphere. The consequences of the magnetospheric penetration electric field and their role in the occurrence of these equatorial spread F observations will be investigated through the results of the SAMI3-RCM numerical model, a coupled ionosphere-magnetosphere model with self-consistent large-scale electrodynamics. Specifically, we will investigate the transient signatures of the interplanetary magnetic field component, Bz, and its role in driving the global convection electric field and ionospheric density redistribution. Lastly, measurements from the AMPERE Birkeland currents, DMSP drift velocities and the particle flux dropouts observed from the Magnetospheric Multiscale Mission (MMS) will be correlated with the FPMU density depletions and each other. Together these observations and simulation results will be assembled to provide each region's context to the global dynamics and time evolution of the storm.

Coffey, Victoria↗

NASA NTRS2021

Interactions Between Two Existential Threats: COVID-19 and Climate Change

The COVID-19 pandemic and climate change are complex existential threats, unpredictable in many ways and unprecedented in modern times. There are parallels between the scale and scope of their impacts and responses. Understanding shared drivers, coupled vulnerabilities, and criteria for effective responses will help societies worldwide prepare for the simultaneous threats of climate change and future pandemics. We summarize some shared characteristics of COVID-19 and climate change impacts and interventions and discuss key policy implications and recommendations.

Climate change adaptation↗

NASA NTRS2022

Perspective on Satellite-Based Land Data Assimilation to Estimate Water Cycle Components in an Era of Advanced Data Availability and Model Sophistication

The beginning of the 21st century is marked by a rapid growth of land surface satellite data and model sophistication. This offers new opportunities to estimate multiple components of the water cycle via satellite-based land data assimilation (DA) across multiple scales. By resolving more processes in land surface models and by coupling the land, the atmosphere, and other Earth system compartments, the observed information can be propagated to constrain additional unobserved variables. Furthermore, access to more satellite observations enables the direct constraint of more and more components of the water cycle that are of interest to end users. However, the finer level of detail in models and data is also often accompanied by an increase in dimensions, with more state variables, parameters, or boundary conditions to estimate, and more observations to assimilate. This requires advanced DA methods and efficient solutions. One solution is to target specific observations for assimilation based on a sensitivity study or coupling strength analysis, because not all observations are equally effective in improving subsequent forecasts of hydrological variables, weather, agricultural production, or hazards through DA. This paper offers a perspective on current and future land DA development, and suggestions to optimally exploit advances in observing and modeling systems.

Data Assimilation↗

NASA NTRSDate not supplied

Boundary Layer Analysis of Shock Tube Flows

Shock tubes offer a controlled environment to reproduce kinetic and radiative phenomena characteristic of atmospheric entry flows under ground-test conditions. The boundary layer developing behind the incident shock wave determines the available test time, influences particle residence times important for similarity scaling, and can affect radiative energy transport. In this study, we couple a quasi-1D space marcher with the compressible boundary-layer equations to numerically compute the post-shock flow in a shock frame of reference for various test gas mixtures representative of different planetary atmospheres. The solvers are individually verified against CFD simulations and analytical correlations available in the literature. Coupled solutions are computed for a finite-rate chemistry in the boundary layer and a non-catalytic isothermal wall. Results yield refined estimates of the maximum separation distance, as well as insights into concentration profiles of relevant species within the boundary layer.

Andrea Fagnani↗

DOE OSTI2023

Towards a Software Development Framework for Interconnected Science Ecosystems

The innovative science of the future must be multi-domain and interconnected to usher in the next generation of “self-driving” laboratories enabling consequential discoveries and transformative inventions. Such a disparate and interconnected ecosystem of scientific instruments will need to evolve using a system-of-systems (SoS) approach. The key to enabling application integration with such an SoS will be the use of Software Development Kits (SDKs). Currently, SDKs facilitate scientific research breakthroughs via algorithmic automation, databases and storage, optimization and structure, pervasive environmental monitoring, among others. However, existing SDKs lack instrument-interoperability and reusability capabilities, do not effectively work in an open federated architectural environment, and are largely isolated within silos of the respective scientific disciplines. Inspired by the scalable SoS framework, this work proposes the development of INTERSECT-SDK to provide a coherent environment for multi-domain scientific applications to benefit from the open federated architecture in an interconnected ecosystem of instruments. This approach will decompose functionality into loosely coupled software services for interoperability among several solutions that do not scale beyond a single domain and/or application. Furthermore, the proposed environment will allow operational and managerial inter-dependence while providing opportunities for the researchers to reuse software components from other domains and build universal solution libraries. We demonstrate this research for microscopy use-case, where we show how INTERSECT-SDK is developing the tools necessary to enable advanced scanning methods and accelerate scientific discovery.

Malviya, Addi Thakur↗

DOE OSTI2022

Understanding the Impact of Data Staging for Coupled Scientific Workflows

We report the rate of data generated by cutting-edge experimental science facilities and large-scale simulations enabled by current high-performance computing (HPC) systems has continued to grow at a far greater pace than the development of the network and storage capabilities on which these systems rely. To cope with this challenge, scientist are moving toward the creation of autonomous experiments and HPC simulations using machine learning. However, efficiently moving, storing, and processing large amounts of data away from the point of origin presents an incredible challenge. In-memory computing, in situ analysis, data staging, and data streaming are recognized viable alternatives to traditional file-based methods for transferring data between coupled workflows. However, the performance trade-offs and limitations for these methods are not fully understood when used in HPC applications. This article presents a comprehensive performance assessment of the current solutions for data staging when applied to applications that are not necessary I/O intensive which makes them not ideal candidates for these methods. Our study is based on experiments running at scale on Oak Ridge National Laboratory's Summit supercomputer using applications and simulations that cover typical computational motifs and patterns. We investigated the usability and cost/benefit trade-offs of staging algorithms for HPC applications under different scenarios and highlight opportunities for optimizing the dataflow between coupled simulation workflows.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2002

Controls on Variations of Surface Energy, Water, and Carbon Budgets within Large-Scale Amazon Basin

A key research focus of the LBA Research Program is understanding the space-time variations in interlinked surface energy, water, and carbon budgets, the controls on these variations, and the implications of these controls on the carbon sequestering capacity of the large scale forest-pasture system that dominates the Amaz6nia landscape. Quantification of these variations and controls are investigated by a combination of in situ measurements, remotely sensed measurements from space, and a realistically forced hydrometeorological model coupled to a carbon assimilation model, capable of simulating details within the surface energy and water budgets along with the principle processes of photosynthesis and respiration. Herein we describe the results of an investigation concerning the space-time controls of carbon sources and sinks distributed over the large scale Amazon basin. The results are derived from a carbon-water-energy budget retrieval system for the large scale Amazon basin, which uses a coupled carbon assimilation-hydrometeorological model as an integrating system, forced by both in situ meteorological measurements and remotely sensed radiation and precipitation fluxes obtained from a combination of GOES, SSM/I, TOMS, and TRh4M satellite measurements. Results include validation of (a) retrieved surface radiation and precipitation fluxes based on 30-min averaged surface measurements taken at Ji-Parani in Rondania and Manaus in Amazonas, and (b) modeled sensible, latent, and C02 fluxes based on tower measurements taken at Reserva Jaru, Manaus and Fazenda Nossa Senhora. The space-time controls on carbon sequestration are partitioned into sets of factors classified by: (1) above canopy meteorology, (2) incoming surface radiation, (3) precipitation interception, and (4) indigenous stomatal processes varied over the different land covers of pristine rainforest, partially, and fully logged rainforests, and pasture lands. These are the principle meteorological, thermodynamical, hydrological, and biophysical control paths which perturb net carbon fluxes and sequestration, produce time-space switching of carbon sources and sinks, undergo modulation through atmospheric boundary layer feedbacks, and respond to any discontinuous intervention on the landscape itself such as produced by human intervention in converting rainforest to pasture or conducting selective/clearcut logging operations. The results demonstrate how relative carbon sequestration capacity of the Amazonian ecosystem responds to these controls, and how interpretation of space-time heterogeneities in carbon sequestration depends on a fairly exact quantification of the interacting non-linear properties of photosynthesis in response to incoming solar flux, air-canopy temperatures, and leaf water interception -- and soil respiration in response to upper layer soil temperature and water content. The results also show how the interpretation of the control processes is highly sensitive to the scales at which the surface fluxes are analyzed.

Smith, Eric A.↗

DOE OSTI2026

Contrasting Carbon–Water–Energy Dynamics in Perennial and Annual Bioenergy Agroecosystems Using Eddy Covariance and Interpretable Machine Learning

Understanding how agroecosystems respond to environmental variability is fundamental to predicting productivity and sustainability under a changing climate. We analyzed 55 site-years of high-frequency eddy covariance observations from five agroecosystems—two perennial grasses (miscanthus and switchgrass), two annual rotation systems (maize–soybean and sorghum–soybean), and a restored native prairie—to examine ecosystem-scale carbon, water, and energy fluxes. Using an interpretable machine-learning framework with regression tree ensembles, Shapley Additive Explanations, and Accumulated Local Effects, we quantified how environmental and temporal factors regulate gross primary productivity (GPP), evapotranspiration (ET), water-use efficiency, and the Bowen ratio. Perennials exhibited stronger physiological buffering and maintained fluxes across a broader range of temperature and moisture conditions, reflecting deeper rooting and persistent canopy cover. Annuals, in contrast, showed greater short-term variability and stronger coupling to atmospheric demand, with GPP and ET declining rapidly under low humidity or soil moisture. Differences in temperature sensitivity of Bowen ratio further revealed that perennials sustained proportionally greater sensible heat flux under cool conditions, whereas annuals exhibited constrained energy exchange when evaporative demand was low. Together, these results demonstrate that crop life cycle and canopy structure are fundamental determinants of ecosystem-scale carbon–water–energy coupling. By integrating long-term flux observations with interpretable machine learning, this study identifies the environmental drivers that shape agroecosystem function and highlights how conversion from annual to perennial feedstocks can enhance climatic resilience and alter land–atmosphere energy feedbacks. These findings provide a data-driven basis for improving crop and Earth-system models and for guiding bioenergy landscape design under future climate scenarios.

Accumulated Local Effects↗

DOE OSTI2022

Benchmarking Simulated Precipitation Variability Amplitude across Time Scales

Here, objective performance metrics that measure precipitation variability across time scales from subdaily to interannual are presented and applied to Historical simulations of Coupled Model Intercomparison Project phase 5 and 6 (CMIP5 and CMIP6) models. Three satellite-based precipitation estimates (IMERG, TRMM, and CMORPH) are used as reference data. We apply two independent methods to estimate temporal variability of precipitation and compare the consistency in their results. The first method is derived from power spectra analysis of 3-hourly precipitation, measuring forced variability by solar insolation (diurnal and annual cycles) and internal variability at different time scales (subdaily, synoptic, subseasonal, seasonal, and interannual). The second method is based on time averaging and facilitates estimating the seasonality of subdaily variability. Supporting the robustness of our metric, we find a near equivalence between the results obtained from the two methods when examining simulated-to-observed ratios over large domains (global, tropics, extratropics, land, or ocean). Additionally, we demonstrate that our model evaluation is not very sensitive to the discrepancies between observations. Our results reveal that CMIP5 and CMIP6 models in general overestimate the forced variability while they underestimate the internal variability, especially in the tropical ocean and higher-frequency variability. The underestimation of subdaily variability is consistent across different seasons. The internal variability is overall improved in CMIP6, but remains underestimated, and there is little evidence of improvement in forced variability. Increased horizontal resolution results in some improvement of internal variability at subdaily and synoptic time scales, but not at longer time scales.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Degradation mechanism of lead-vanado-iodoapatite in NaCl solution

Degradation mechanism of lead-vanado-iodoapatite (IAPT) in NaCl solution at 90 °C was investigated through systematic characterization of surface morphology, microstructure and microchemistry evolution of the alteration layer. Nano-scale characterization indicated that IAPT crystals degraded from grain boundaries toward inner grains, forming ultrafine Cl-bearing crystallites. A coupled interface dissolution-reprecipitation replacement mechanism and the ion exchange between Cl - and I - across the degradation zone may together play roles in determining the nano-scale degradation behavior of IAPT. This work highlights the degradation through multiple reactions and elemental transport across the liquid-solid and solid-solid interfaces at length scales from sub-millimeter to nanoscale.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Building Intelligent Cyberinfrastructure to Learn Iteratively from both Observations and Models for Understanding Watershed Dynamics

Focal Area(s): Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising of a hierarchy of models (e.g., AI-driven model/component/parameterization selection). Science Challenge: Watershed processes, such as the fate and transport of sediment, carbon and nutrients across landscapes and their fluxes to water bodies (e.g., streams, rivers and lakes), have important implications for global and regional carbon and nutrient dynamics, biogeochemical functioning of terrestrial ecosystems, and soil functions. The magnitude of lateral surface/subsurface transport and fluxes of sediment, carbon and nutrients are key factors controlling the vulnerability of watersheds to climate extremes such as droughts, wildfires, and floods. Recent field observations and other scientific evidence suggest that the magnitudes of lateral transport and fluxes of sediment, carbon and nutrients are governed primarily by the spatial and vertical heterogeneity of landscape and soil properties and by pedogenic processes. However, the current generation of land surface and watershed models do not mechanistically couple the terrestrial and hydrologic systems, nor do they represent sufficiently the spatial and vertical heterogeneity of land surface and subsurface properties. On the other hand, increasing complexity of coupled watershed and land surface models requires more data to parameterize, calibrate and validate. Remote sensing (RS) provides a means to acquire spatial data and characterize their heterogeneity at the watershed scale, overcoming a major limitation associated with conventional point measurements. To improve the representation of land-surface and surface/subsurface process coupling and sub-grid heterogeneity in watershed models, it is essential to build our predictive understanding by learning from both the multi-scale multi-process modeling and diverse multi-scale data while leveraging powerful artificial intelligence (AI) techniques.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2015

Assessing Air-Sea Interaction in the Evolving NASA GEOS Model

In order to understand how the climate responds to variations in forcing, one necessary component is to understand the full distribution of variability of exchanges of heat and moisture between the atmosphere and ocean. Surface heat and moisture fluxes are critical to the generation and decay of many coupled air-sea phenomena. These mechanisms operate across a number of scales and contain contributions from interactions between the anomalous (i.e. non-mean), often extreme-valued, flux components. Satellite-derived estimates of the surface turbulent and radiative heat fluxes provide an opportunity to assess results from modeling systems. Evaluation of only time mean and variability statistics, however only provides limited traceability to processes controlling what are often regime-dependent errors. This work will present an approach to evaluate the representation of the turbulent fluxes at the air-sea interface in the current and evolving Goddard Earth Observing System (GEOS) model. A temperature and moisture vertical profile-based clustering technique is used to identify robust weather regimes, and subsequently intercompare the turbulent fluxes and near-surface parameters within these regimes in both satellite estimates and GEOS-driven data sets. Both model reanalysis (MERRA) and seasonal-to-interannual coupled GEOS model simulations will be evaluated. Particular emphasis is placed on understanding the distribution of the fluxes including extremes, and the representation of near-surface forcing variables directly related to their estimation. Results from these analyses will help identify the existence and source of regime-dependent biases in the GEOS model ocean surface turbulent fluxes. The use of the temperature and moisture profiles for weather-state clustering will be highlighted for its potential broad application to 3-D output typical of model simulations.

Clayson, Carol Anne↗

DOE OSTI2025

Composite quarks and leptons with embedded QCD

We construct a model of quark and lepton compositeness based on an 𝑆⁢𝑈⁡(15) gauge interaction that confines chiral preons, which are also charged under the weakly coupled 𝑆⁢𝑈⁢(4) PS ×𝑆⁢𝑈⁢(2) 𝐿 ×𝑆⁢𝑈⁢(2) 𝑅 gauge group. The breaking of the latter, down to the Standard Model group, is achieved by scalar 𝑆⁢𝑈⁡(15) bound states at a scale in the 30–100 TeV range. The embedding of the QCD gauge group in 𝑆⁢𝑈⁢(4) PS slows down the running of 𝛼 𝑠 in the UV. We estimate the effects of the strongly coupled 𝑆⁢𝑈⁡(15) dynamics on the running of the 𝑆⁢𝑈⁢(4) PS ×𝑆⁢𝑈⁢(2) 𝐿 ×𝑆⁢𝑈⁢(2) 𝑅 gauge couplings, which likely remain perturbative beyond the compositeness scale of about 10 3 –10 4 TeV, and even above a unification scale. A composite vectorlike lepton doublet acquires a mass in the TeV range probed at future colliders, and an extended Higgs sector arises from six-preon bound states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Simulating coupled surface–subsurface flows with ParFlow v3.5.0: capabilities, applications, and ongoing development of an open-source, massively parallel, integrated hydrologic model

Surface flow and subsurface flow constitute a naturally linked hydrologic continuum that has not traditionally been simulated in an integrated fashion. Recognizing the interactions between these systems has encouraged the development of integrated hydrologic models (IHMs) capable of treating surface and subsurface systems as a single integrated resource. IHMs are dynamically evolving with improvements in technology, and the extent of their current capabilities are often only known to the developers and not general users. This article provides an overview of the core functionality, capability, applications, and ongoing development of one open-source IHM, ParFlow. ParFlow is a parallel, integrated, hydrologic model that simulates surface and subsurface flows. ParFlow solves the Richards equation for three-dimensional variably saturated groundwater flow and the two-dimensional kinematic wave approximation of the shallow water equations for overland flow. The model employs a conservative centered finite-difference scheme and a conservative finite-volume method for subsurface flow and transport, respectively. ParFlow uses multigrid-preconditioned Krylov and Newton–Krylov methods to solve the linear and nonlinear systems within each time step of the flow simulations. The code has demonstrated very efficient parallel solution capabilities. ParFlow has been coupled to geochemical reaction, land surface (e.g., the Common Land Model), and atmospheric models to study the interactions among the subsurface, land surface, and atmosphere systems across different spatial scales. This overview focuses on the current capabilities of the code, the core simulation engine, and the primary couplings of the subsurface model to other codes, taking a high-level perspective.

58 GEOSCIENCES↗