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

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗
NASA NTRS2014

Assimilation of MODIS Snow Cover Through the Data Assimilation Research Testbed and the Community Land Model Version 4

To improve snowpack estimates in Community Land Model version 4 (CLM4), the Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover fraction (SCF) was assimilated into the Community Land Model version 4 (CLM4) via the Data Assimilation Research Testbed (DART). The interface between CLM4 and DART is a flexible, extensible approach to land surface data assimilation. This data assimilation system has a large ensemble (80-member) atmospheric forcing that facilitates ensemble-based land data assimilation. We use 40 randomly chosen forcing members to drive 40 CLM members as a compromise between computational cost and the data assimilation performance. The localization distance, a parameter in DART, was tuned to optimize the data assimilation performance at the global scale. Snow water equivalent (SWE) and snow depth are adjusted via the ensemble adjustment Kalman filter, particularly in regions with large SCF variability. The root-mean-square error of the forecast SCF against MODIS SCF is largely reduced. In DJF (December-January-February), the discrepancy between MODIS and CLM4 is broadly ameliorated in the lower-middle latitudes (2345N). Only minimal modifications are made in the higher-middle (4566N) and high latitudes, part of which is due to the agreement between model and observation when snow cover is nearly 100. In some regions it also reveals that CLM4-modeled snow cover lacks heterogeneous features compared to MODIS. In MAM (March-April-May), adjustments to snowmove poleward mainly due to the northward movement of the snowline (i.e., where largest SCF uncertainty is and SCF assimilation has the greatest impact). The effectiveness of data assimilation also varies with vegetation types, with mixed performance over forest regions and consistently good performance over grass, which can partly be explained by the linearity of the relationship between SCF and SWE in the model ensembles. The updated snow depth was compared to the Canadian Meteorological Center (CMC) data. Differences between CMC and CLM4 are generally reduced in densely monitored regions.

data assimilation↗
NASA NTRS2021

GEWEX (Global Energy and Water Exchanges Project): Surface Radiation Budget (SRB) Release 4 Integrated Product (IP4) - Algorithm Theoretical Basis Document and Evaluation

The World Climate Research Programme’s (WCRP) Global Energy and Water Exchanges (GEWEX) program is an integrated program of research, observations, and science activities with the mission to “Observe, understand and model the hydrological cycle and energy fluxes in the Earth’s atmosphere and at the surface.” Since the public release in 2010 of SRB Release 3, GEWEX reorganized to formulate the Data and Assessments Panel (GDAP) aimed at performing community assessments of the long-term global data products with focus on integrating various data products to address issues in the closing of the global energy and water cycles. SRB Release 4 Intergrated Product (Rel4-IP) integrates data products from the cloud, aerosol, atmosphere, ocean surface, and land surface projects within GDAP to produce a long-term time series of Top-of-Atmosphere (TOA) and surface radiative estimates. This Algorithm Theoretical Basis Document (ATBD) describes the various inputs, algorithms and resulting top-of-atmosphere and surface flux products that span from July 1983 through June 2017. Comparisons of the TOA flux products are made to overlapping CERES data products when possible. The surface radiative flux products are assessed relative to the globally distribution Baseline Surface Radiation Network measurements sites. Variability of the various products are compared to ERBE and CERES during overlapping time periods. The variability of the product show excellent correspondent to CERES during overlap years and improved statistical agreement with surface measurements. This document also discusses known issues with the data products to help the user understand the uncertainty and known issues.

Surface radiation budget↗
DOE OSTI2013

CLIVAR Exchanges No. 62: Sea Level Rise, Ocean/Ice Shelf Interactions and Ice Sheets

This special issue of CLIVAR Exchanges is devoted to presenting a selection of the science contributed by both speakers and poster presenters at the CLIVAR Workshop on Sea Level Rise, Ocean/Ice Shelf Interactions and Ice Sheets at CSIRO Marine and Atmospheric Research in Hobart, Australia, on 18-20 February 2013. The workshop brought together leading international scientists and early-career researchers from the ocean, ice-sheet, ice-shelf, and sea-level rise modelling and observational communities to explore the state-of-science and emerging pathways for development of the next generation of coupled climate models.

58 GEOSCIENCES↗
DOE OSTI2025

Water Mass Transformation Budgets in Finite‐Volume Generalized Vertical Coordinate Ocean Models

Water Mass Transformation (WMT) theory provides conceptual tools that in principle enable innovative analyses of numerical ocean models; in practice, however, these methods can be challenging to implement and interpret, and therefore remain under-utilized. Our aim is to demonstrate the feasibility of diagnosing all terms in the water mass budget and to exemplify their usefulness for scientific inquiry and model development by quantitatively relating water mass changes, overturning circulations, boundary fluxes, and interior mixing. We begin with a pedagogical derivation of key results of classical WMT theory. We then describe best practices for diagnosing each of the water mass budget terms from the output of Finite-Volume Generalized Vertical Coordinate (FV-GVC) ocean models, including the identification of a non-negligible remainder term as the spurious numerical mixing due to advection scheme discretization errors. We illustrate key aspects of the methodology through the analysis of a polygonal region of the Greater Baltic Sea in a regional demonstration simulation using the Modular Ocean Model v6 (MOM6). We verify the convergence of our WMT diagnostics by brute-force, comparing time-averaged (“offline”) diagnostics on various vertical grids to timestep-averaged (“online”) diagnostics on the native model grid. Finally, we briefly describe a stack of xarray-enabled Python packages for evaluating WMT budgets in FV-GVC models (culminating in the new xwmb package), which is intended to be model-agnostic and available for community use and development.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Recent Progress on Sonic Boom Research at NASA

Sonic boom research conducted at NASA through the Supersonics Project of the Fundamental Aeronautics Program is oriented toward understanding the potential impact of sonic boom noise on communities from new low-boom supersonic aircraft designs. Encompassing research in atmospheric propagation, structural response, and human response, NASA research contributes to knowledge in key areas needed to support development of a new noise-based standard for supersonic aircraft certification. Partnerships with several industry, government, and academic institutions have enabled the recent execution of several acoustic field studies on sonic booms. An overview of recent activities funded by NASA includes: focus boom model development and experimental validation, field experiments of structural transmission of sonic booms into large buildings, and low boom community response testing.

Loubeau, Alexandra↗
DOE OSTI2017

Grand challenges in understanding the interplay of climate and land changes

Half of the Earth s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affects a myriad of land surface processes and our adaptation behaviors. We here review the status and major knowledge gaps of studying the interactions of land and atmospheric changes and present eleven grand challenge areas for scientific research and adaptation communities in the coming decade: (1) collective and separate impacts of major land changes and the interactions with non-land-change factors such as atmospheric CO2 increase, (2) carbon and other biogeochemical cycles, (3) climatically relevant biospheric emissions such as aerosols, (4) water cycle, (5) agriculture, (6) urbanization, (7) gradual acclimation of plants, communities, and ecosystems to climate and environmental changes, (8) plant migration, (9) land use projections, (10) reduction of uncertainties in models and data, and finally (11) adaptation strategies. We conclude that we need to create and maintain a close cross-disciplinary coordination between measurements and process representation in models to analyze complex multi-facet interrelated perturbations and feedbacks between land and climate changes. Along with major scientific research thrusts, land-use and land cover change mitigation and adaptation assessments should be strengthened to identify barriers that need to be overcome, evaluate and prioritize opportunities, and examine how decision making processes work in specific contexts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

THE McGill PLANAR HYDROGEN ATMOSPHERE CODE (McPHAC)

The McGill Planar Hydrogen Atmosphere Code (McPHAC) v1.1 calculates the hydrostatic equilibrium structure and emergent spectrum of an unmagnetized hydrogen atmosphere in the plane-parallel approximation, at surface gravities appropriate for neutron stars. McPHAC incorporates several improvements over previous codes for which tabulated model spectra are available: (1) Thomson scattering is treated anisotropically, which is shown to result in a 0.2%-3% correction in the emergent spectral flux across the 0.1-5 keV passband; (2) the McPHAC source code is made available to the community, allowing it to be scrutinized and modified by other researchers wishing to study or extend its capabilities; and (3) the numerical uncertainty resulting from the discrete and iterative solution is studied as a function of photon energy, indicating that McPHAC is capable of producing spectra with numerical uncertainties <0.01%. The accuracy of the spectra may at present be limited to {approx}1%, but McPHAC enables researchers to study the impact of uncertain inputs and additional physical effects, thereby supporting future efforts to reduce those inaccuracies. Comparison of McPHAC results with spectra from one of the previous model atmosphere codes (NSA) shows agreement to {approx}<1% near the peaks of the emergent spectra. However, in the Wien tail a significant deficit of flux in the spectra of the previous model is revealed, determined to be due to the previous work not considering large enough optical depths at the highest photon frequencies. The deficit is most significant for spectra with T{sub eff} < 10{sup 5.6} K, though even there it may not be of much practical importance for most observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Surface-to-Interior Transport Timescales and Ventilation Patterns in a Time-Dependent Circulation Driven by Sustained Climate Warming

Abstract The effect of climate warming in response to rising atmospheric CO 2 on the ventilation of the ocean remains uncertain. Here we make theoretical advances in elucidating the relationship between ideal age and transit time distribution (TTD) in a time-dependent flow. Subsequently, we develop an offline tracer-transport model to characterize the ventilation patterns and time scales in the time-evolving circulation for the 1850–2300 period as simulated with the Community Earth System Model version 1 (CESMv1) under a business-as-usual warming scenario. We found that by 2300 2.1% less water originates from the high-latitude deep water formation regions (both hemispheres) compared to 1850. In compensation, there is an increase in the water originating from the subantarctic. We also found that slowing meridional overturning circulation causes a gradual increase in mean age during the 1850–2300 period, with a globally averaged mean-age increase of ∼110 years in 2300. Where and when the water will be re-exposed to the atmosphere depends on the post-2300 circulation. For example, if we assume that the circulation persists in its year-2300 state (scenario 1), the mean interior-to-surface transit time in year 1850 is ∼1140 years. In contrast, if we assume that the circulation abruptly recovers to its year-1850 state (scenario 2), the mean interior-to-surface transit time in 1850 is only ∼740 years. By 2300, these differences become even larger; in scenario 1, the mean interior-to-surface transit time increases by ∼200 years, whereas scenario 2 decreases by ∼80 years. The dependence of interior-to-surface transit time on the future ocean circulation produces an additional unavoidable uncertainty in the long-term durability of marine carbon dioxide removal strategies. Significance Statement The ocean’s circulation, when altered by climate warming, can affect its capacity to absorb heat and CO 2 , which are crucial for the global climate. In our study, we investigated how global warming, caused by rising CO 2 levels, might impact the ocean circulation—the way water moves from deep ocean to the surface and vice versa. We discovered that by 2300, if we continue on our current warming trajectory, the origins of water within the ocean will shift, with less coming from deep, cold zones near the poles and more from subantarctic regions. As a result, deep water will take longer time before it resurfaces than shallow water. How quickly this water travels from deep regions to the surface could change, depending on the state of future ocean circulation. If the circulation remains as predicted in 2300, this journey will take longer. Conversely, if it reverts to the pattern in 1850, the process will be quicker. This variability introduces added uncertainty to strategies aimed at mitigating climate change by storing CO 2 in the ocean. Our work highlights the intricate ways in which climate change can influence our oceans, potentially affecting our plans to mitigate global warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Study of Multi-Scale Cloud Processes Over the Tropical Western Pacific Using Cloud-Resolving Models Constrained by Satellite Data

Clouds in the tropical western Pacific are an integral part of the large scale environment. An improved understanding of the multi-scale structure of clouds and their interactions with the environment is critical to the ARM (Atmospheric Radiation Measurement) program for developing and evaluating cloud parameterizations, understanding the consequences of model biases, and providing a context for interpreting the observational data collected over the ARM Tropical Western Pacific (TWP) sites. Three-dimensional cloud resolving models (CRMs) are powerful tools for developing and evaluating cloud parameterizations. However, a significant challenge in using CRMs in the TWP is that the region lacks conventional data, so large uncertainty exists in defining the large-scale environment for clouds. This project links several aspects of the ARM program, from measurements to providing improved analyses, and from cloud-resolving modeling to climate-scale modeling and parameterization development, with the overall objective to improve the representations of clouds in climate models and to simulate and quantify resolved cloud effects on the large-scale environment. Our objectives will be achieved through a series of tasks focusing on the use of the Weather Research and Forecasting (WRF) model and ARM data. Our approach includes: - Perform assimilation of COSMIC GPS radio occultation and other satellites products using the WRF Ensemble Kalman Filter assimilation system to represent the tropical large-scale environment at 36 km grid resolution. This high-resolution analysis can be used by the community to derive forcing products for single-column models or cloud-resolving models. - Perform cloud-resolving simulations using WRF and its nesting capabilities, driven by the improved regional analysis and evaluate the simulations against ARM datasets such as from TWP-ICE to optimize the microphysics parameters for this region. A cirrus study (Mace and co-authors) already exists for TWP-ICE using satellite and ground-based observations. - Perform numerical experiments using WRF to investigate how convection over tropical islands in the Maritime Continent interacts with large-scale circulation and affects convection in nearby regions. - Evaluate and apply WRF as a testbed for GCM cloud parameterizations, utilizing the ability of WRF to run on multiple scales (from cloud resolving to global) to isolate resolution and physics issues from dynamical and model framework issues. Key products will be disseminated to the ARM and larger community through distribution of data archives, including model outputs from the data assimilation products and cloud resolving simulations, and publications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Sensitivity of Mountain Hydroclimate Simulations in Variable-Resolution CESM to Microphysics and Horizontal Resolution

Mountains are natural dams that impede atmospheric moisture transport and water towers that cool, condense, and store precipitation. They are essential in the western United States where precipitation is seasonal, and snowpack is needed to meet water demand. With anthropogenic climate change increasingly threatening mountain snowpack, there is a pressing need to better understand the driving climatological processes. However, the coarse resolution typical of modern global climate models renders them largely insufficient for this task, and signals a need for an advanced strategy. This paper continues the assessment of variable-resolution in the Community Earth System Model (VR-CESM) in modeling mountain hydroclimatology to understand the role of grid-spacing at 55, 28, 14, and 7 km and microphysics, specifically the Morrison and Gettelman (2008, MG1, https://doi.org/10.1175/2008JCLI2105.1) scheme versus the Gettelman and Morrison (2015, MG2, https://doi.org/10.1175/JCLI-D-14-00102.1) scheme. Eight VR-CESM simulations were performed from 1999 to 2015 with the F_AMIP_CAM5 component set, which couples the atmosphere-land models and prescribes ocean data. Refining horizontal grid-spacing from 28 to 7 km with the MG1 scheme did not improve the simulated mountain hydroclimatology. Substantial improvements occurred with the use of MG2 at grid-spacings ≤28 km compared to MG1 as shown with subsequent statistics. Average SWE bias diminished by 9.4X, 4.9X, and 3.5X from 55 to 7 km. The range in minimum (maximum) DJF spatial correlations increased by 0.1–0.2 in both precipitation and SWE. Mountain windward/leeward distributions and elevation profiles improved across hydroclimate variables, however not always with model resolution alone. Disconcertingly, all VR-CESM simulations exhibited a systemic mountain cold bias that worsened with elevation and will require further examination.

58 GEOSCIENCES↗
DOE OSTI2015

Interactions among roots, mycorrhizas and free-living microbial communities differentially impact soil carbon processes

Plant roots, their associated microbial community and free-living soil microbes interact to regulate the movement of carbon from the soil to the atmosphere, one of the most important and least understood fluxes of terrestrial carbon. Our inadequate understanding of how plant-microbial interactions alter soil carbon decomposition may lead to poor model predictions of terrestrial carbon feedbacks to the atmosphere. Roots, mycorrhizal fungi and free-living soil microbes can alter soil carbon decomposition through exudation of carbon into soil. Exudates of simple carbon compounds can increase microbial activity because microbes are typically carbon limited. When both roots and mycorrhizal fungi are present in the soil, they may additively increase carbon decomposition. However, when mycorrhizas are isolated from roots, they may limit soil carbon decomposition by competing with free-living decomposers for resources. We manipulated the access of roots and mycorrhizal fungi to soil insitu in a temperate mixed deciduous forest. We added 13 C-labelled substrate to trace metabolized carbon in respiration and measured carbon-degrading microbial extracellular enzyme activity and soil carbon pools. We used our data in a mechanistic soil carbon decomposition model to simulate and compare the effects of root and mycorrhizal fungal presence on soil carbon dynamics over longer time periods. Contrary to what we predicted, root and mycorrhizal biomass did not interact to additively increase microbial activity and soil carbon degradation. The metabolism of 13 C-labelled starch was highest when root biomass was high and mycorrhizal biomass was low. These results suggest that mycorrhizas may negatively interact with the free-living microbial community to influence soil carbon dynamics, a hypothesis supported by our enzyme results. Our steady-state model simulations suggested that root presence increased mineral-associated and particulate organic carbon pools, while mycorrhizal fungal presence had a greater influence on particulate than mineral-associated organic carbon pools.Synthesis. Our results suggest that the activity of enzymes involved in organic matter decomposition was contingent upon root-mycorrhizal-microbial interactions. Using our experimental data in a decomposition simulation model, we show that root-mycorrhizal-microbial interactions may have longer-term legacy effects on soil carbon sequestration. Lastly, our study suggests that roots stimulate microbial activity in the short term, but contribute to soil carbon storage over longer periods of time.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

NASA Giovanni: Analyze, Compare, and Visualize 2000+ Earth Satellite and Model Variables Without Downloading Data and Software

Over vast oceans and remote continents, observations are often scarce and discontinuous. Satellite and model data play a critical role in research and applications. However, finding and accessing satellite and model data can be a daunting task for many, especially those outside the community. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC), one of 12 NASA Science Mission Directorate Data Centers, provides Earth science data, information, and services to everyone such as researchers, application users, educators, and students. GES DISC archives and supports datasets applicable to several NASA Earth Science Focus Areas including Atmospheric Composition, Water & Energy Cycles, Carbon Cycle & Ecosystem, and Climate Variability. To facilitate data discovery, evaluation, and exploration, GES DISC has developed the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni), an online tool to analyze and visualize NASA remote sensing and model data without downloading data and software. As of this writing, over 2000 Earth satellite and model variables are available in Giovanni, including several wellknown NASA satellite missions (e.g., TRMM, GPM) and projects (e.g., MERRA-2, GPCP). Giovanni provides twenty-two plots that can be used to analyze, compare, and explore Earth data across different disciplines. Results can be shared with colleagues and downloaded for further analysis. Over the years, Giovanni has helped publish over 3000 referral papers. In this presentation, we will showcase key variables and plot types in Giovanni with examples. In particular, we will present several popular precipitation products from GPM and CPCP for evaluation and comparison.

data analysis↗
NASA NTRSDate not supplied

Experiment Design and Visualization Techniques for an X-59 Low-boom Variability Study

This presentation outlines the design of experiments approach and data visualization techniques for a simulation study of sonic booms from NASA’s X-59 supersonic aircraft. The X-59 will soon be flown over communities across the contiguous USA as it produces a low-loudness sonic boom, or low-boom. Survey data on human perception of low-booms will be collected to support development of potential future commercial supersonic aircraft noise regulatory standards. The macroscopic atmosphere plays a critical role in the loudness of sonic booms. The extensive sonic boom simulation study presented herein was completed to assess climatological, geographical, and seasonal effects on the variability of the X-59’s low-boom loudness and noise exposure region size in order to inform X-59 community test planning. The loudness and extent of the noise exposure region make up the “sonic boom carpet.” Two spatial and temporal resolutions of atmospheric input data to the simulation were investigated. A Fast Flexible Space-Filling Design was used to select the locations across the USA for the two spatial resolutions. Analysis of simulated X-59 low-boom loudness data within a regional subset of the northeast USA was completed using a bootstrap forest to determine the final spatial and temporal resolution of the countrywide simulation study. Atmospheric profiles from NOAA’s Climate Forecast System Version 2 database were used to generate over one million simulated X-59 carpets at the final selected 138 locations across the USA. Effects of aircraft heading, season, geography, and climate zone on low-boom levels and noise exposure region size were analyzed. Models were developed to estimate loudness metrics throughout the USA for X-59 supersonic cruise overflight, and results were visualized on maps to show geographical and seasonal trends. These results inform regulators and mission planners on expected variations in boom levels and carpet extent from atmospheric variations. Understanding potential carpet variability is important when planning community noise surveys using the X-59.

X-59↗
DOE OSTI2025

Designing Future Energy Systems with Generative AI

Energy systems are experiencing various changes that impact the distribution, use, and reliability of energy. Local utilities and municipalities must respond and adapt to these changes, moving towards a future energy system with modernized infrastructure and other targeted investments and policy decisions. However, planning for and enacting these advancements requires significant effort from experts and engineers to develop strategies that ensure a reliable and secure energy future. This includes characterizing the current energy infrastructure, identifying areas for development, and engaging with local community members. Emerging generative artificial intelligence techniques can alleviate pain points and help support the development of the next generation of energy systems. Here, in this article, we highlight on-going generative AI work in the areas of atmospheric modeling, building energy management, and distribution network design, and we propose a vision for the role of generative AI that considers opportunities and identifies challenges inherent to this technology.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

CICE Consortium Progress Report, June 2018 - December 2019

The CICE Consortium accomplished a number of major upgrades to our sea ice model code, scripts and testing infrastructure, while strengthening our visibility in the international modeling community. We released CICE versions 6.0.0, 6.0.1, 6.0.2 and 6.1.0, all of which include updated releases of Icepack. Major new capabilities include a floe size distribution, new coupling infrastructure, improvements to all of CICE’s dynamics options, a new atmospheric data set for historical simulations, overhauled documentation, and more robust and flexible scripts for running and testing the code. Several key testing processes were automated this year. In addition, the team is actively engaged in planning our first user workshop and tutorial in February 2020. In addition to overseeing modifications to the Consortium’s resources and code releases, management tasks included meeting with and updating the Consortium’s Sponsors group in October 2018, prioritizing tasks by mapping them onto potential release targets, and rescuing early CICE releases (version 1 through 3.14) from a disappearing LANL archive.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Simulation of the 2003 Foss Barge - Point Wells Oil Spill: A Comparison between BLOSOM and GNOME Oil Spill Models

The Department of Energy’s (DOE’s) National Energy Technology Laboratory’s (NETL’s) Blowout and Spill Occurrence Model (BLOSOM), and the National Oceanic and Atmospheric Administration’s (NOAA’s) General NOAA Operational Modeling Environment (GNOME) are compared. Increasingly complex simulations are used to assess similarities and differences between the two models’ components. The simulations presented here are forced by ocean currents from a Finite Volume Community Ocean Model (FVCOM) implementation that has excellent skill in representing tidal motion, and with observed wind data that compensates for a coarse vertical ocean model resolution. The comprehensive comparison between GNOME and BLOSOM presented here, should aid modelers in interpreting their results. Beyond many similarities, aspects where both models are distinct are highlighted. Some suggestions for improvement are included, e.g., the inclusion of temporal interpolation of the forcing fields (BLOSOM) or the inclusion of a deflection angle option when parameterizing wind-driven processes (GNOME). Overall, GNOME and BLOSOM perform similarly, and are found to be complementary oil spill models. This paper also sheds light on what drove the historical Point Wells spill, and serves the additional purpose of being a learning resource for those interested in oil spill modeling. The increasingly complex approach used for the comparison is also used, in parallel, to illustrate the approach an oil spill modeler would typically follow when trying to hindcast or forecast an oil spill, including detailed technical information on basic aspects, like choosing a computational time step. We discuss our successful hindcast of the 2003 Point Wells oil spill that, to our knowledge, had remained unexplained. The oil spill models’ solutions are compared to the historical Point Wells’ oil trajectory, in time and space, as determined from overflight information. Our hindcast broadly replicates the correct locations at the correct times, using accurate tide and wind forcing. While the choice of wind coefficient we use is unconventional, a simplified analytic model supported by observations, suggests that it is justified under this study’s circumstances. We highlight some of the key oceanographic findings as they may relate to other oil spills, and to the regional oceanography of the Salish Sea, including recommendations for future studies.

42 ENGINEERING↗
DOE OSTI2016

An observational constraint on stomatal function in forests: evaluating coupled carbon and water vapor exchange with carbon isotopes in the Community Land Model (CLM4.5)

Abstract. Land surface models are useful tools to quantify contemporary and future climate impact on terrestrial carbon cycle processes, provided they can be appropriately constrained and tested with observations. Stable carbon isotopes of CO2 offer the potential to improve model representation of the coupled carbon and water cycles because they are strongly influenced by stomatal function. Recently, a representation of stable carbon isotope discrimination was incorporated into the Community Land Model component of the Community Earth System Model. Here, we tested the model's capability to simulate whole-forest isotope discrimination in a subalpine conifer forest at Niwot Ridge, Colorado, USA. We distinguished between isotopic behavior in response to a decrease of δ13C within atmospheric CO2 (Suess effect) vs. photosynthetic discrimination (Δcanopy), by creating a site-customized atmospheric CO2 and δ13C of CO2 time series. We implemented a seasonally varying Vcmax model calibration that best matched site observations of net CO2 carbon exchange, latent heat exchange, and biomass. The model accurately simulated observed δ13C of needle and stem tissue, but underestimated the δ13C of bulk soil carbon by 1–2 ‰. The model overestimated the multiyear (2006–2012) average Δcanopy relative to prior data-based estimates by 2–4 ‰. The amplitude of the average seasonal cycle of Δcanopy (i.e., higher in spring/fall as compared to summer) was correctly modeled but only when using a revised, fully coupled An − gs (net assimilation rate, stomatal conductance) version of the model in contrast to the partially coupled An − gs version used in the default model. The model attributed most of the seasonal variation in discrimination to An, whereas interannual variation in simulated Δcanopy during the summer months was driven by stomatal response to vapor pressure deficit (VPD). The model simulated a 10 % increase in both photosynthetic discrimination and water-use efficiency (WUE) since 1850 which is counter to established relationships between discrimination and WUE. The isotope observations used here to constrain CLM suggest (1) the model overestimated stomatal conductance and (2) the default CLM approach to representing nitrogen limitation (partially coupled model) was not capable of reproducing observed trends in discrimination. These findings demonstrate that isotope observations can provide important information related to stomatal function driven by environmental stress from VPD and nitrogen limitation. Future versions of CLM that incorporate carbon isotope discrimination are likely to benefit from explicit inclusion of mesophyll conductance.

58 GEOSCIENCES↗