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DOE OSTI2021

Impacts of Sea‐Level Rise on Hypoxia and Phytoplankton Production in Chesapeake Bay: Model Prediction and Assessment

In this study, the influence of sea-level rise (SLR) on seasonal hypoxia and phytoplankton production in Chesapeake Bay is investigated using a 3D unstructured grid model. Three SLR scenarios (0.17, 0.5, and 1.0 m) were conducted from 1991 to 1995. Results show that the summer hypoxic volume (HV) increases about 2%, 8%, and 16%, respectively, for these three scenarios, compared with Base Scenario. The contributions of physical and biological processes on the increase in the HV were analyzed. With the projected SLR, enhanced gravitational circulation transports more oxygen-rich water in the bottom layer from the mouth. However, the pycnocline moves upwards along with increasing water depth, which largely prolongs the time for dissolved oxygen (DO) to be transported to the bottom. The altered physical processes contribute greatly to a larger HV bay-wide. Besides, SLR increases the whole Bay phytoplankton production, with a larger increase in shallow areas (e.g., 53% in areas with depth <1 m under SLR of 0.5 m). Enhanced light availability is suggested to be the major driver of blooming phytoplankton under SLR in shallow areas. While increased DO production over the euphotic zone is mostly released to the atmosphere and transported downstream, the increase in settled organic matter greatly promotes DO consumption in the water column. The increased respiration is another major cause of the HV increase besides the physical contributions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Regional-scale fault-to-structure earthquake simulations with the EQSIM framework: Workflow maturation and computational performance on GPU-accelerated exascale platforms

Continuous advancements in scientific and engineering understanding of earthquake phenomena, combined with the associated development of representative physics-based models, is providing a foundation for high-performance, fault-to-structure earthquake simulations. However, regional-scale applications of high-performance models have been challenged by the computational requirements at the resolutions required for engineering risk assessments. The EarthQuake SIMulation (EQSIM) framework, a software application development under the US Department of Energy (DOE) Exascale Computing Project, is focused on overcoming the existing computational barriers and enabling routine regional-scale simulations at resolutions relevant to a breadth of engineered systems. This multidisciplinary software development—drawing upon expertise in geophysics, engineering, applied math and computer science—is preparing the advanced computational workflow necessary to fully exploit the DOE’s exaflop computer platforms coming online in the 2023 to 2024 timeframe. Achievement of the computational performance required for high-resolution regional models containing upward of hundreds of billions to trillions of model grid points requires numerical efficiency in every phase of a regional simulation. This includes run time start-up and regional model generation, effective distribution of the computational workload across thousands of computer nodes, efficient coupling of regional geophysics and local engineering models, and application-tailored highly efficient transfer, storage, and interrogation of very large volumes of simulation data. This article summarizes the most recent advancements and refinements incorporated in the workflow design for the EQSIM integrated fault-to-structure framework, which are based on extensive numerical testing across multiple graphics processing unit (GPU)-accelerated platforms, and demonstrates the computational performance achieved on the world’s first exaflop computer platform through representative regional-scale earthquake simulations for the San Francisco Bay Area in California, USA.

58 GEOSCIENCES↗

DOE OSTI2015

Physics and Dynamics Coupling Across Scales in the Next Generation CESM: Meeting the Challenge of High-Resolution (Final Report)

This project examines physics/dynamics coupling, that is, exchange of meteorological profiles and tendencies between an atmospheric model’s dynamical core and its various physics parameterizations. Most model physics parameterizations seek to represent processes that occur on scales smaller than the smallest scale resolved by the dynamical core. As a consequence a key conceptual aspect of parameterizations is an assumption about the subgrid variability of quantities such as temperature, humidity or vertical wind. Most existing parameterizations of processes such as turbulence, convection, cloud, and gravity wave drag make relatively ad hoc assumptions about this variability and are forced to introduce empirical parameters, i.e., “tuning knobs” to obtain realistic simulations. These knobs make systematic dependences on model grid size difficult to quantify.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Modeling Low Intensity Fires: Lessons Learned from 2012 RxCADRE

Coupled fire-atmosphere models are increasingly being used to study low-intensity fires, such as those that are used in prescribed fire applications. Thus, the need arises to evaluate these models for their ability to accurately represent fire spread in marginal burning conditions. In this study, wind and fuel data collected during the Prescribed Fire Combustion and Atmospheric Dynamics Research Experiments (RxCADRE) fire campaign were used to generate initial and boundary conditions for coupled fire-atmosphere simulations. We present a novel method to obtain fuels representation at the model grid scale using a combination of imagery, machine learning, and field sampling. Several methods to generate wind input conditions for the model from eight different anemometer measurements are explored. We find a strong sensitivity of fire outcomes to wind inputs. This result highlights the critical need to include variable wind fields as inputs in modeling marginal fire conditions. This work highlights the complexities of comparing physics-based model results against observations, which are more acute in marginal burning conditions, where stronger sensitivities to local variability in wind and fuels drive fire outcomes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Dust Abundance Variations in the Magellanic Clouds: Probing the Life-cycle of Metals with All-sky Surveys

Observations and modeling suggest that dust abundance (gas-to-dust ratio, G/D) depends on (surface) density. Variations of the G/D provide timescale constraints for the different processes involved in the life cycle of metals in galaxies. Recent G/D measurements based on Herschel data suggest a factor of 5–10 decrease in dust abundance between the dense and diffuse interstellar media (ISM) in the Magellanic Clouds. However, the relative nature of the Herschel measurements precludes definitive conclusions as to the magnitude of those variations. We investigate variations of the dust abundance in the LMC and SMC using all-sky far-infrared surveys, which do not suffer from the limitations of Herschel on their zero-point calibration. We stack the dust spectral energy distribution (SED) at 100, 350, 550, and 850 microns from IRAS and Planck in intervals of gas surface density, model the stacked SEDs to derive the dust surface density, and constrain the relation between G/D and gas surface density in the range 10–100 M {sub ⊙} pc{sup −2} on ∼80 pc scales. We find that G/D decreases by factors of 3 (from 1500 to 500) in the LMC and 7 (from 1.5×10{sup 4} to 2000) in the SMC between the diffuse and dense ISM. The surface-density-dependence of G/D is consistent with elemental depletions, and with simple modeling of the accretion of gas-phase metals onto dust grains. This result has important implications for the sub-grid modeling of galaxy evolution, and for the calibration of dust-based gas-mass estimates, both locally and at high redshift.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1981

The potential impact of scatterometry on oceanography - A wave forecasting case

A series of observing system simulation experiments have been performed in order to assess the potential impact of marine surface wind data on numerical weather prediction. In addition to conventional data, the experiments simulated the time-continuous assimilation of remotely sensed marine surface wind or temperature sounding data. The wind data were fabricated directly for model grid points intercepted by a Seasat-1 scatterometer swath and were assimilated into the lowest active level (945 mb) of the model using a localized successive correction method. It is shown that Seasat wind data can greatly improve numerical weather forecasts due to better definition of specific features. The case of the QE II storm is examined.

Cane, M. A.↗

NASA NTRS2003

Comparison of Flow-Dependent and Static Error Correlation Models in the DAO Ozone Data Assimilation System

In a data assimilation system the forecast error covariance matrix governs the way in which the data information is spread throughout the model grid. Implementation of a correct method of assigning covariances is expected to have an impact on the analysis results. The simplest models assume that correlations are constant in time and isotropic or nearly isotropic. In such models the analysis depends on the dynamics only through assumed error standard deviations. In applications to atmospheric tracer data assimilation this may lead to inaccuracies, especially in regions with strong wind shears or high gradient of potential vorticity, as well as in areas where no data are available. In order to overcome this problem we have developed a flow-dependent covariance model that is based on short term evolution of error correlations. The presentation compares performance of a static and a flow-dependent model applied to a global three- dimensional ozone data assimilation system developed at NASA s Data Assimilation Office. We will present some results of validation against WMO balloon-borne sondes and the Polar Ozone and Aerosol Measurement (POAM) III instrument. Experiments show that allowing forecast error correlations to evolve with the flow results in positive impact on assimilated ozone within the regions where data were not assimilated, particularly at high latitudes in both hemispheres and in the troposphere. We will also discuss statistical characteristics of both models; in particular we will argue that including evolution of error correlations leads to stronger internal consistency of a data assimilation ,

Wargan, K.↗

DOE OSTI2012

Mastering Uncertainty and Risk at Multiple Time Scales in the Future Electrical Grid

Today's electrical grids enjoy a relatively clean separation of spatio-temporal scales yielding a compartmentalization of grid design, optimization, control and risk assessment allowing for the use of conventional mathematical tools within each area. In contrast, the future grid will incorporate time-intermittent renewable generation, operate via faster electrical markets, and tap the latent control capability at finer grid modeling scales; creating a fundamentally new set of couplings across spatiotemporal scales and requiring revolutionary advances in mathematics techniques to bridge these scales. One example is found in decade-scale grid expansion planning in which today's algorithms assume accurate load forecasts and well-controlled generation. Incorporating intermittent renewable generation creates fluctuating network flows at the hourly time scale, inherently linking the ability of a transmission line to deliver electrical power to hourly operational decisions. New operations-based planning algorithms are required, creating new mathematical challenges. Spatio-temporal scales are also crossed when the future grid's minute-scale fluctuations in network flows (due to intermittent generation) create a disordered state upon which second-scale transient grid dynamics propagate effectively invalidating today's on-line dynamic stability analyses. Addressing this challenge requires new on-line algorithms that use large data streams from new grid sensing technologies to physically aggregate across many spatial scales to create responsive, data-driven dynamic models. Here, we sketch the mathematical foundations of these problems and potential solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2011

Numerical Simulations of Two-Phase Reacting Flow in a Single-Element Lean Direct Injection (LDI) Combustor Using NCC

A series of numerical simulations of Jet-A spray reacting flow in a single-element lean direct injection (LDI) combustor have been conducted by using the National Combustion Code (NCC). The simulations have been carried out using the time filtered Navier-Stokes (TFNS) approach ranging from the steady Reynolds-averaged Navier-Stokes (RANS), unsteady RANS (URANS), to the dynamic flow structure simulation (DFS). The sub-grid model employed for turbulent mixing and combustion includes the well-mixed model, the linear eddy mixing (LEM) model, and the filtered mass density function (FDF/PDF) model. The starting condition of the injected liquid spray is specified via empirical droplet size correlation, and a five-species single-step global reduced mechanism is employed for fuel chemistry. All the calculations use the same grid whose resolution is of the RANS type. Comparisons of results from various models are presented.

Liu, Nan-Suey↗

DOE OSTI2021

DERMS-RT (Distributed Energy Resource Management Solution using Real-Time Optimization) [SWR-20-46]

DERMS-RT provides a distributed energy resource management solution using real-time optimization to control different types of distributed energy resources (DERs) — such as rooftop PVs, battery energy storage systems, HVAC loads, electric water heater loads, and EV charging loads, and use these DERs to provide distribution voltage regulation and peak demand management services. The control approach implemented by DERM-RT is developed based on the real-time optimal power flow and distributed control previously developed by NREL researchers. The software codes are designed to provide modular DER management solution that can be easily applied to control heterogeneous DERs in distribution grids in coordination with centralized utility management systems. Also, DERMS-RT provides application programming interface (API) to extract useful grid model information from an open-source power system simulation software, use the information to solve the optimization problem, and apply the optimal set-points to the controlled DERs. In this way, DERMS-RT provides a plug-and-play function for implementing the real-time DER control on different utility system models, and it can be used as a simulation testbed to demonstrate the impact of real-time DER optimization on improving grid operations.

Ding, Fei↗

DOE OSTI2025

High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7

Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. Consequently, the role of enhanced horizontal resolution in improved process representation in all components of the climate system continues to be of great interest. Recent simulations suggest the possibility of significant changes in both large-scale aspects of the ocean and atmospheric circulations and in the regional responses to climate change, as well as improvements in representations of small-scale processes and extremes, when resolution is enhanced. The first phase of the High-Resolution Model Intercomparison Project (HighResMIP1) was successful at producing a baseline multi-model assessment of global simulations with model grid spacings of 25–50 km in the atmosphere and 10–25 km in the ocean, a significant increase when compared to models with standard resolutions on the order of 1° that are typically used as part of the Coupled Model Intercomparison Project (CMIP) experiments. In addition to over 250 peer-reviewed manuscripts using the published HighResMIP1 datasets, the results were widely cited in the Intergovernmental Panel on Climate Change report and were the basis of a variety of derived datasets, including tracked cyclones (both tropical and extratropical), river discharge, storm surge, and impact studies. There were also suggestions from the few ocean eddy-rich coupled simulations that aspects of climate variability and change might be significantly influenced by improved process representation in such models. The compromises that HighResMIP1 made should now be revisited, given the recent major advances in modelling and computing resources. Aspects that will be reconsidered include experimental design and simulation length, complexity, and resolution. In addition, larger ensemble sizes and a wider range of future scenarios would enhance the applicability of HighResMIP. Therefore, we propose the High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) to improve and extend the previous work, to address new science questions, and to further advance our understanding of the role of horizontal resolution (and hence process representation) in state-of-the-art climate simulations. With further increases in high-performance computing resources and modelling advances, along with the ability to take full advantage of these computational resources, an enhanced investigation of the drivers and consequences of variability and change in both large- and synoptic-scale weather and climate is now possible. With the arrival of global cloud-resolving models (currently run for relatively short timescales), there is also an opportunity to improve links between such models and more traditional CMIP models, with HighResMIP providing a bridge to link understanding between these domains. HighResMIP also aims to link to other CMIP projects and international efforts such as the World Climate Research Program lighthouse activities and various digital twin initiatives. It also has the potential to be used as training and validation data for the fast-evolving machine learning climate models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

POPSnet-SGP: A Pilot Aerosol Microphysics Network for Targeting Climate Model Uncertainty Interim Field Campaign Report

Aerosols mediate the radiative fluxes in clear and cloudy skies and dominate the uncertainty in the radiative forcing of climate. Relatively dense networks of aerosol optical depth measurements have been used to effectively constrain simulated aerosol optical properties, but model diversity of aerosol microphysical properties is much larger (Mann et al. 2014, Myhre et al. 2009). A better understanding of aerosol microphysics is essential as they are the fundamental pieces of information required to convert aerosol emissions information to radiative and cloud-nucleating properties that drive radiative effects and forcing of climate. Model representation of aerosol microphysical properties has lagged in part due to their inherently greater spatial variability, but also due to a lack of available observations. This project – the Printed Optical Particle Spectrometer Network (POPSnet)-Southern Great Plains (SGP) Pilot – launched the first spatially dense network of aerosol size distribution measurements over an area the size of a global model grid cell and demonstrated its use in providing valuable information regarding the spatial variability of aerosol microphysical properties and its drivers for improving model constraints.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Climatological simulations of ozone and atmospheric aerosols in the Greater Cairo region

An integrated chemistry-climate model (RegCM4-CHEM) simulates present-day climate, ozone and tropospheric aerosols over Egypt with a focus on Greater Cairo (GC) region. The densley populated GC region is known for its severe air quality issues driven by high levels of anthropogenic pollution in conjuction with natural sources such as dust and agricultural burning events. We find that current global emission inventories underestimate key pollutants such as nitrogen oxides and anthropogenic aerosol species. In the GC region, average-ground-based NO2 observations of 40-60 ppb are substantially higher than modeled estimates (5-10 ppb), likely due to model grid resolution, improper boundary layer representation, and poor emissions inventories. Observed ozone concentrations range from 35 ppb (winter) to 80 ppb (summer). The model reproduces the seasonal cycle fairly well, but modeled summer ozone is understimated by approximately 15 ppb and exhibits little interannual variability. For aerosols, springtime dust events dominate the seasonal aerosol cycle. The chemistry-climate model captures the springtime peak aerosol optical depth (AOD) of 0.7-1 but is slightly greater than satellite-derived AOD. Observed AOD decreases in the summer and increases again in the fall due to agricultural burning events in the Nile Delta, yet the model underestimates this fall observed AOD peak, as standard emissions inventories underestimate this burning and the resulting aerosol emissions. Our comparison of modeled gas and particulate phase atmospheric chemistry in the GC region indicates that improved emissions inventories of mobile sources and other anthropogenic activities are needed to improve air quality simulations in this region.

Steiner, A. L.↗

NASA NTRS1987

A study of frontal dynamics with application to the Australian summertime 'cool change'

The dynamics of frontal evolution is examined in terms of the Australian summertime cool change using a two-dimensional numerical model. The model is synthesized from observational data on surface cold fronts obtained during the Australian Cold Fronts Research Program, and the model develops a quasi-steady surface cold front during the 24 hours of integration. The characteristics of this model are compared with those of a kinematic model; it is observed that the features of the two models correspond. The two-dimensional and kinematic models are also compared with a 24-hour prediction of the cold front of February 1983 using the three-dimensional nested-grid model of the Australian Numerical Meteorology Research Center, developed by Gauntlett et al. (1984). Good correlation between these models is detected.

Reeder, Michael J.↗

NASA NTRS1988

Millimeter-wave diode-grid phase shifters

Monolithic diode grids have been fabricated on 2-cm square gallium-arsenide wafers with 1600 Schottky-barrier varactor diodes. Shorted diodes are detected with a liquid-crystal technique, and the bad diodes are removed with an ultrasonic probe. A small-aperture reflectometer that uses wavefront division interference was developed to measure the reflection coefficient of the grids. A phase shift of 70 deg with a 7-dB loss was obtained at 93 GHz when the bias on the diode grid was changed from -3 V to 1 V. A simple transmission-line grid model, together with the measured low-frequency parameters for the diodes, was shown to predict the measured performance over the entire capacitive bias range of the diodes, as well as over the complete reactive tuning range provided by a reflector behind the grid, and over a wide range of frequencies from 33 GHz to 141 GHz. This shows that the transmission-line model and the measured low-frequency diode parameters can be used to design an electronic beam-steering array and to predict its performance. An electronic beam-steering array made of a pair of grids using state-of-the-art diodes with 5-ohm series resistances would have a loss of 1.4 dB at 90 GHz.

Lam, Wayne W.↗

DOE OSTI2021

Challenges in simulating economic effects of climate change on global agricultural markets

Abstract Many approaches have been used to investigate climate change impacts on agriculture. However, several caveats remain in this field: (i) analyses focus only on a few major crops, (ii) large differences in yield impacts are observed between projections from site-based crops models and Global Gridded Crop Models (GGCMs), (iii) climate change impacts on livestock are rarely quantified, and (iv) several causal relations among biophysical, environmental, and socioeconomic aspects are usually not taken into account. We investigate how assumptions about these four aspects affect agricultural markets, food supply, consumer well-being, and land use at global level by deploying a large-scale socioeconomic model of the global economy with detailed representation of the agricultural sector. We find global welfare impacts several times larger when climate impacts all crops and all livestock compared to a scenario with impacts limited to major crops. At the regional level, food budget can decrease by 10 to 25% in developing countries, challenging food security. The role of land area expansion as a major source of adaptation is highlighted. Climate impacts on crop yields from site-based process crop models generate more challenging socioeconomic outcomes than those from GGCMs. We conclude that the agricultural research community should expand efforts to estimate climate impacts on many more crops and livestock. Also, careful comparison of the GGCMs and traditional site-based process crop models is needed to understand their major implications for agricultural and food markets.

Gurgel, Angelo C. (ORCID:0000000183319508)↗

DOE OSTI2026

Multidisciplinary Design, Analysis, and Optimization (MDO) for Co-Designed Transmission & Distribution Electric Grid Planning

This paper describes early experiences and example use cases applying multi-disciplinary design analysis and optimization (MDO) to the integrated design of power grids. Adapted from aerospace, MDO enables combining multiple existing tools into a coordinated optimization. Here we use MDO to simultaneously capture integrated transmission-distribution and investment-engineering trade-offs in an automated framework. Example use cases showcase prototype interactions among existing grid models using MDO and hint at the types of integrated analyses enabled by this approach. In addition, we share experiences and thoughts on grid-specific challenges and opportunities to help advance further work in this area.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2013

A SPECTROSCOPIC CATALOG OF THE BRIGHTEST (J < 9) M DWARFS IN THE NORTHERN SKY{sup ,}

We present a spectroscopic catalog of the 1564 brightest (J < 9) M dwarf candidates in the northern sky, as selected from the SUPERBLINK proper motion catalog. Observations confirm 1408 of the candidates to be late-K and M dwarfs with spectral subtypes K7-M6. From the low ({mu} > 40 mas yr{sup -1}) proper motion limit and high level of completeness of the SUPERBLINK catalog in that magnitude range, we estimate that our spectroscopic census most likely includes >90% of all existing, northern-sky M dwarfs with apparent magnitude J < 9. Only 682 stars in our sample are listed in the Third Catalog of Nearby Stars (CNS3); most others are relative unknowns and have spectroscopic data presented here for the first time. Spectral subtypes are assigned based on spectral index measurements of CaH and TiO molecular bands; a comparison of spectra from the same stars obtained at different observatories, however, reveals that spectral band index measurements are dependent on spectral resolution, spectrophotometric calibration, and other instrumental factors. As a result, we find that a consistent classification scheme requires that spectral indices be calibrated and corrected for each observatory/instrument used. After systematic corrections and a recalibration of the subtype-index relationships for the CaH2, CaH3, TiO5, and TiO6 spectral indices, we find that we can consistently and reliably classify all our stars to a half-subtype precision. The use of corrected spectral indices further requires us to recalibrate the {zeta} parameter, a metallicity indicator based on the ratio of TiO and CaH optical bandheads. However, we find that our {zeta} values are not sensitive enough to diagnose metallicity variations in dwarfs of subtypes M2 and earlier ({+-}0.5 dex accuracy) and are only marginally useful at later M3-M5 subtypes ({+-}0.2 dex accuracy). Fits of our spectra to the Phoenix atmospheric model grid are used to estimate effective temperatures. These suggest the existence of a plateau in the M1-M3 subtype range, in agreement with model fits of infrared spectra but at odds with photometric determinations of T{sub eff}. Existing geometric parallax measurements are extracted from the literature for 624 stars, and are used to determine spectroscopic and photometric distances for all the other stars. Active dwarfs are identified from measurements of H{alpha} equivalent widths, and we find a strong correlation between H{alpha} emission in M dwarfs and detected X-ray emission from ROSAT and/or a large UV excess in the GALEX point source catalog. We combine proper motion data and photometric distances to evaluate the (U, V, W) distribution in velocity space, which is found to correlate tightly with the velocity distribution of G dwarfs in the solar neighborhood. However, active stars show a smaller dispersion in their space velocities, which is consistent with those stars being younger on average. Our catalog will be most useful to guide the selection of the best M dwarf targets for exoplanet searches, in particular those using high-precision radial velocity measurements.

79 ASTRONOMY AND ASTROPHYSICS↗