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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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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Standardized Data to Improve Understanding and Modeling of Soil Nitrogen at Continental Scale

Abstract Nitrogen (N) is a key limiting nutrient in terrestrial ecosystems, but there remain critical gaps in our ability to predict and model controls on soil N cycling. This may be in part due to lack of standardized sampling across broad spatial–temporal scales. Here, we introduce a continentally distributed, publicly available data set collected by the National Ecological Observatory Network (NEON) that can help fill these gaps. First, we detail the sampling design and methods used to collect and analyze soil inorganic N pool and net flux rate data from 47 terrestrial sites. We address methodological challenges in generating a standardized data set, even for a network using uniform protocols. Then, we evaluate sources of variation within the sampling design and compare measured net N mineralization to simulated fluxes from the Community Earth System Model 2 (CESM2). We observed wide spatiotemporal variation in inorganic N pool sizes and net transformation rates. Site explained the most variation in NEON’s stratified sampling design, followed by plots within sites. Organic horizons had larger pools and net N transformation rates than mineral horizons on a sample weight basis. The majority of sites showed some degree of seasonality in N dynamics, but overall these temporal patterns were not matched by CESM2, leading to poor correspondence between observed and modeled data. Looking forward, these data can reveal new insights into controls on soil N cycling, especially in the context of other environmental data sets provided by NEON, and should be leveraged to improve predictive modeling of the soil N cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

TensorFlow Quantum: A Software Framework for Quantum Machine Learning

We introduce TensorFlow Quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data. This framework offers high-level abstractions for the design and training of both discriminative and generative quantum models under TensorFlow and supports high-performance quantum circuit simulators. We provide an overview of the software architecture and building blocks through several examples and review the theory of hybrid quantum-classical neural networks. We illustrate TFQ functionalities via several basic applications including supervised learning for quantum classification, quantum control, simulating noisy quantum circuits, and quantum approximate optimization. Moreover, we demonstrate how one can apply TFQ to tackle advanced quantum learning tasks including meta-learning, layerwise learning, Hamiltonian learning, sampling thermal states, variational quantum eigensolvers, classification of quantum phase transitions, generative adversarial networks, and reinforcement learning. We hope this framework provides the necessary tools for the quantum computing and machine learning research communities to explore models of both natural and artificial quantum systems, and ultimately discover new quantum algorithms which could potentially yield a quantum advantage.

Broughton, Michael↗
DOE OSTI2024

Machine learning materials properties with accurate predictions, uncertainty estimates, domain guidance, and persistent online accessibility

One compelling vision of the future of materials discovery and design involves the use of machine learning (ML) models to predict materials properties and then rapidly find materials tailored for specific applications. However, realizing this vision requires both providing detailed uncertainty quantification (model prediction errors and domain of applicability) and making models readily usable. At present, it is common practice in the community to assess ML model performance only in terms of prediction accuracy (e.g. mean absolute error), while neglecting detailed uncertainty quantification and robust model accessibility and usability. Here, we demonstrate a practical method for realizing both uncertainty and accessibility features with a large set of models. We develop random forest ML models for 33 materials properties spanning an array of data sources (computational and experimental) and property types (electrical, mechanical, thermodynamic, etc). All models have calibrated ensemble error bars to quantify prediction uncertainty and domain of applicability guidance enabled by kernel-density-estimate-based feature distance measures. All data and models are publicly hosted on the Garden-AI infrastructure, which provides an easy-to-use, persistent interface for model dissemination that permits models to be invoked with only a few lines of Python code. We demonstrate the power of this approach by using our models to conduct a fully ML-based materials discovery exercise to search for new stable, highly active perovskite oxide catalyst materials.

domain of applicability↗
DOE OSTI2023

A mountain-induced moist baroclinic wave test case for the dynamical cores of atmospheric general circulation models

Idealized test cases for the dynamical cores of atmospheric general circulation models are informative tools to assess the accuracy of the numerical designs and investigate the general characteristics of atmospheric motions. A new test case is introduced that is built upon a baroclinically unstable base state with an added orographic barrier. The topography is analytically prescribed and acts as a trigger of both baroclinic Rossby waves and inertia–gravity waves on a rotating, regular-sized planet. Both dry and idealized moist configurations are suggested. The latter utilizes the Kessler warm-rain precipitation scheme. The test case enhances the complexity of the existing test suite hierarchy and focuses on the impacts of two midlatitudinal mountain ridges on the circulation. Selected simulation examples from four dynamical cores are shown. These are the Spectral Element and Finite Volume dynamical cores, which are part of the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM), versions 2.1.3 and 2.2, and the Cubed-Sphere Finite Volume dynamical cores, which is new to CESM version 2.2. In addition, the Model for Prediction Across Scales (MPAS) is tested. The overall flow patterns agree well in the four dynamical cores, but the details can vary greatly. The examples highlight the broad palette of use cases for the test case and reveal physics–dynamics coupling issues.

58 GEOSCIENCES↗
DOE OSTI2023

Causes and evolution of winter polynyas north of Greenland

During the 42-year period (1979–2020) of satellite measurements, four major winter (December–March) polynyas have been observed north of Greenland: one in December 1986 and three in the last decade, i.e., February of 2011, 2017, and 2018. The 2018 polynya was unparalleled in its magnitude and duration compared to the three previous events. Given the apparent recent increase in the occurrence of these extreme events, this study aims to examine their evolution and causality, in terms of forced versus natural variability. The limited weather station and remotely sensed sea ice data are analyzed combining with output from the fully coupled Regional Arctic System Model (RASM), including one hindcast and two ensemble simulations. We found that neither the accompanying anomalous warm surface air intrusion nor the ocean below had an impact (i.e., no significant ice melting) on the evolution of the observed winter open-water episodes in the region. Instead, the extreme atmospheric wind forcing resulted in greater sea ice deformation and transport offshore, accounting for the majority of sea ice loss in all four polynyas. Our analysis suggests that strong southerly winds (i.e., northward wind with speeds greater than 10 m s –1 ) blowing persistently over the study region for at least 2 d or more were required over the study region to mechanically redistribute some of the thickest Arctic sea ice out of the region and thus to create open-water areas (i.e., a latent heat polynya). To assess the role of internal variability versus external forcing of such events, we carried out and examined results from the two RASM ensembles dynamically downscaled with output from the Community Earth System Model (CESM) Decadal Prediction Large Ensemble (DPLE) simulations. Out of 100 winters in each of the two ensembles (initialized 30 years apart: one in December 1985 and another in December 2015), 17 and 16 winter polynyas were produced north of Greenland, respectively. The frequency of polynya occurrence had no apparent sensitivity to the initial sea ice thickness in the study area pointing to internal variability of atmospheric forcing as a dominant cause of winter polynyas north of Greenland. We assert that dynamical downscaling using a high-resolution regional climate model offers a robust tool for process-level examination in space and time, synthesis with limited observations, and probabilistic forecasts of Arctic events, such as the ones being investigated here and elsewhere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Optimal Stopping Ages for Colorectal Cancer Screening

Importance Prior studies have shown that the benefits, harms, and costs of colorectal cancer (CRC) screening at older ages are associated with a patient’s sex, health, and screening history. However, these studies were hypothetical exercises and not directly informed by data on CRC risk. Objective To identify the optimal stopping ages for CRC screening by sex, comorbidity, and screening history from a cost-effectiveness perspective. Design, Setting, and Participants This economic evaluation first validated the MISCAN-Colon (Microsimulation Screening Analysis–Colon) model against community-based CRC incidence and mortality rates for 2 subcohorts of the PRECISE (Optimizing Colorectal Cancer Screening Precision and Outcomes in Community-Based Populations) cohort. Subsequently, different CRC screening scenarios were simulated in older individuals. Cohorts of US adults aged 76 to 90 years varied by sex and comorbidity status (none, low, moderate, or severe). Statistical and sensitivity analyses were performed from March 2023 to May 2024. Exposures CRC screening histories including fecal immunochemical test (FIT) or colonoscopy, such as a negative colonoscopy result from 10, 15, 20, 25, or 30 years before the index age; 1 to 5 negative FIT results within 5 years of the index age, with different patterns of recency; or a combination of negative colonoscopy and negative FIT results. Main Outcomes and Measures The main outcomes included estimated lifetime clinical outcomes, incremental costs, and quality-adjusted life-years gained (QALYG) associated with 1 additional FIT or colonoscopy. Optimal stopping age for screening, defined as the oldest age for which the incremental cost-effectiveness ratio was still below the willingness-to-pay threshold of $\$$100 000 per QALYG, was evaluated. Results The first of the 2 PRECISE subcohorts used in validating the simulation model included 25 974 adults (15 060 females [58.0%]; 54.7% aged 76 to 80 years) with a negative colonoscopy result 10 years before the index date. The second subcohort consisted of 118 269 adults (67 058 females [56.7%]; 90.5% aged 76 to 80 years) with a negative FIT result 1 year before the index date. Older age, male sex, higher comorbidity levels, and recent CRC screenings were associated with reduced incremental benefit and cost-effectiveness of additional screening. For the reference cohort of 76-year-old females without comorbidities and a negative colonoscopy result 10 years before the index age, 1 additional colonoscopy cost $\$$38 226 per QALYG. For cohorts with otherwise equivalent characteristics, associated costs increased to $\$$1 689 945 per QALYG for females at age 90 years without comorbidities and a negative colonoscopy results 10 years before the index age, $\$$51 604 per QALYG for males at age 76 years without comorbidities and a negative colonoscopy result 10 years before the index age, and $\$$108 480 per QALYG for females at age 76 years with severe comorbidities and a negative colonoscopy result 10 years before the index age and decreased to $\$$16 870 per QALYG for females without comorbidities and a negative colonoscopy result 30 years before the index age. The optimal stopping ages across different cohorts ranged from younger than 76 to 86 years for colonoscopy and younger than 76 to 88 years for FIT. Conclusions and Relevance In this economic evaluation, age, sex, screening history, comorbidity, and future screening modality were associated with the clinical outcomes, cost-effectiveness, and optimal stopping age for CRC screening. These results can inform guideline development and patient-directed informed decision-making.

Harlass, Matthias [Erasmus Erasmus University Medi↗
DOE OSTI2024

Technical Potential and Meaningful Benefits of Community Solar in the United States

The report describes the methodology and results from a study on the technical potential of community solar and associated meaningful benefits. A key finding of the study suggests that the opportunity space for community solar to meet unmet demand for solar energy is not primarily constrained by technical potential, but by technological, market, and policy factors. NREL used rooftop and ground-mount photovoltaic siting data to model annual energy production from community solar based on various constraints and system performance. Given modeled results and community solar deployment, we discuss potential benefits including household savings, low-to-moderate income household access to solar, resilience and grid benefits, community ownership, workforce development and entrepreneurship as well as insights into community solar siting opportunities.

14 SOLAR ENERGY↗
DOE OSTI2024

Achieving Scale: Community Solar Technical Potential and Meaningful Benefits in the United States

The slide deck was presented at the webinar on February 28th titled Achieving Scale: Community Technical Potential and Meaningful Benefits in the United States. It describes the National Community Solar Partnership program followed by methodology and results from a study on the technical potential of community solar and associated meaningful benefits. A key finding of the study suggests that the opportunity space for community solar to meet unmet demand for solar energy is not primarily constrained by technical potential, but by technological, market, and policy factors. NREL used rooftop and ground-mount photovoltaic siting data to model annual energy production from community solar based on various constraints and system performance. Given modeled results and community solar deployment, we discuss potential benefits including household savings, low-to-moderate income household access to solar, resilience and grid benefits, community ownership, workforce development and entrepreneurship as well as insights into community solar siting opportunities.

community solar↗
DOE OSTI2020

Leveraging Open-Source Tools for Collaborative Macro-energy System Modeling Efforts

The authors are founding team members of a new effort to develop an Open Energy Outlook for the United States. The effort aims to apply best practices of policy-focused energy system modeling, ensure transparency, build a networked community, and work toward a common purpose: examining possible US energy system futures to inform energy and climate policy efforts. Individual author biographies can be found on the project website: https://openenergyoutlook.org/.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Understanding Soil Microbial Sources of Nitrous Acid and their Effect on Carbon-Nitrogen Cycle Interactions

Descriptions of soil emissions of reactive nitrogen (NO y ) in climate models are underdeveloped or non-existent, due to the fact that details of the mechanisms leading to nitrous acid (HONO) and nitrogen di-oxide (NO 2 ) formation in soil are lacking. This represents a major gap in our understanding of a significant land-atmosphere interaction that prevents us from scaling these processes from the laboratory scale to the ecosystem and global scales. There is a critical need to include these mechanisms into climate models since NO y controls the oxidative capacity of the atmosphere and the lifetime of greenhouse gases and the rate of secondary aerosol formation that directly and indirectly affect climate. The first objective of this proposal is to conduct laboratory and field measurements of NO y fluxes from diverse soil types and determine the mechanism of biogenic NO y formation. The working hypothesis based on preliminary data is that soil HONO and NO 2 is ultimately derived from ammonia-oxidizing archaea (AOA) and bacteria (AOB) that are widespread, but whose abundance varies across ecosystems. In the case of NO 2 , reactive oxygen species derived from iron-containing minerals and heterotrophic bacteria drive NO-to-NO 2 conversion. The approach is to link soil fluxes of HONO and NO 2 to AOA, AOB, and other heterotrophs using a combination of laboratory and field experiments, isotopic analysis, and molecular techniques to address how variability in land surfaces and edaphic properties impact emissions. In addition, we will determine the effect of HONO and NO 2 on nitrogen immobilization and the photo-oxidative capacity of soil. The working hypothesis is that HONO uptake in soil will be a source of nitrosonium and hydroxyl radical that will lead to thermal- and photodegradation of soil organic matter to CO 2 and CO, and the incorporation of N in soil organic matter. We will use surface-sensitive mass spectrometry techniques and gas phase detection to study N-immobilization in soil and subsequent enhancements in reactivity that lead to decomposition of organic matter. The results will be used to reduce the uncertainty in projections from the Community Earth System Model (CESM) stemming from inaccurate representations of soil NO y emissions. The proposed research is significant because, in addition to demonstrating new mechanisms of NO y formation and loss, it will be a crucial first step towards modeling the land-atmosphere exchange of HONO and NO 2 in the CESM. Improved model treatment of land-air exchange of NO y is key for understanding feedbacks between human activity and climate, and addressing societal concerns about the fate of N and C emitted to the atmosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Graphene oxide exposure alters gut microbial community composition and metabolism in an in vitro human model

Graphene oxide (GO) nanomaterials have unique physicochemical properties that make them highly promising for biomedical, environmental, and agricultural applications. Despite the increasing interest and the use of GO, assessments of its nanotoxicity have largely not interrogated its potential impact on the gut microbiome. This study addresses an important knowledge gap by investigating the impact of GO exposure- both at low (25 ppm) and high (250ppm) doses and fed (nutrient rich) and fasted (nutrient deplete) conditions- on the gut microbial community structure and function, using an in vitro human colon bioreactor model. 16S rRNA amplicon sequencing revealed that GO exposure resulted in a restructuring of community composition. 25 ppm GO induced a marked decrease in the Bacteroidota phylum and increased the ratio of Firmicutes to Bacteroidota (F/B). Untargeted metabolomics on the supernatants indicated that 25 ppm GO impaired microbial utilization and metabolism of substrates (amino acids, carbohydrate metabolites) and reduced production of beneficial microbial metabolites such as 5-hydroxyindole-3-acetic acid and GABA. Exposure to 250 ppm GO resulted in community composition and metabolome profiles that were very similar to the controls that lacked both GO and digestive enzymes, suggesting that high concentrations of GO may interact with digestive enzymes to form protein coronas, causing their depletion in the gut environment. Differential abundance analyses revealed that 3 genera from the phylum Bacteroidota (Bacteroides, Dysgonomonas, and Parabacteroides) were more abundant after 250 ppm GO exposure, irrespective of feed state. Integrative correlation network analysis indicated that the phylum Bacteroidota showed strong positive correlations to multiple microbial metabolites including GABA and 3-indoleacetic acid, are much larger number of correlations compared to other phyla. These results show that GO exposure has a significant impact on gut microbial community composition and metabolism and different mechanisms are at play for low and high GO concentrations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry–meteorology feedbacks on air quality

The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more realistically represent the atmosphere by accounting for complex chemistry–meteorology feedbacks. In this study, we present a comparative analysis of two-way (with consideration of both aerosol direct and indirect effects) and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US. Long-term (5 years from 2008 to 2012) simulations using WRF-CMAQ with both offline and two-way coupling modes are carried out with anthropogenic emissions based on multiple years of the U.S. National Emission Inventory and chemical initial and boundary conditions derived from an advanced Earth system model (i.e., a modified version of the Community Earth System Model/Community Atmospheric Model). The comprehensive model evaluations show that both two-way WRF-CMAQ and WRF-only simulations perform well for major meteorological variables such as temperature at 2 m, relative humidity at 2 m, wind speed at 10 m, precipitation (except for against the National Climatic Data Center data), and shortwave and longwave radiation. Both two-way and offline CMAQ also show good performance for ozone (O3) and fine particulate matter (PM 2.5 ). Due to the consideration of aerosol direct and indirect effects, two-way WRF-CMAQ shows improved performance over offline coupled WRF and CMAQ in terms of spatiotemporal distributions and statistics, especially for radiation, cloud forcing, O 3 , sulfate, nitrate, ammonium, elemental carbon, tropospheric O 3 residual, and column nitrogen dioxide (NO 2 ). For example, the mean biases have been reduced by more than 10 W m –2 for shortwave radiation and cloud radiative forcing and by more than 2 ppb for max 8 h O 3 . However, relatively large biases still exist for cloud predictions, some PM 2.5 species, and PM 10 that warrant follow-up studies to better understand those issues. The impacts of chemistry–meteorological feedbacks are found to play important roles in affecting regional air quality in the US by reducing domain-average concentrations of carbon monoxide (CO), O 3 , nitrogen oxide (NO x ), volatile organic compounds (VOCs), and PM 2.5 by 3.1 % (up to 27.8 %), 4.2 % (up to 16.2 %), 6.6 % (up to 50.9 %), 5.8 % (up to 46.6 %), and 8.6 % (up to 49.1 %), respectively, mainly due to reduced radiation, temperature, and wind speed. The overall performance of the two-way coupled WRF-CMAQ model achieved in this work is generally good or satisfactory and the improved performance for two-way coupled WRF-CMAQ should be considered along with other factors in developing future model applications to inform policy making.

58 GEOSCIENCES↗
DOE OSTI2021

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

With the increasing digitalization of processes throughout the lifecycle of buildings, data exchanged between stakeholders and between building systems has grown significantly. However, a lack of semantic interoperability between data in different systems is still prevalent, hindering the development of applications that can be reused across buildings and limiting the scalability of innovative solutions. Semantics refers to the description of the meaning of the data in a way that can be consistently understood by applications. Recently, several competing initiatives have been developing metadata schemas and ontologies to express this semantic information for different applications in the building domain. This paper systematically reviews these schemas and conducts an analysis of five of them to evaluate their applicability to three high-value use cases for building operations: energy audits, automated fault detection and diagnostics and optimal control. The survey finds 40 schemas published in the last 10 years but but their actual use in industry is difficult to estimate. Among the five selected ontologies, several gaps are highlighted in relation to the three use cases. Recommendations for the future include better harmonization of these initiatives, more centralized repositories and search engines for these schemas as well as better industry engagement to facilitate their adoption.

Smart Building, Sematic, Metadata, Ontology, Data ↗
DOE OSTI2025

Lack of clear standards and usable comparisons of downscaled climate projections pose a roadblock for US climate discovery and adaptation

Abstract The release of global climate projections coupled with the demand for local-resolution climate-forced meteorology has prompted many research groups to downscale these projections using various statistical, dynamical, and current machine learning techniques. Such downscaled datasets are being used to plan infrastructure and other community needs over the coming decades. Faced with roughly a dozen available US downscaled datasets, many practitioners ask, ‘What are the relevant differences between datasets?’ This work highlights the difficulty of comparing downscaled datasets and illustrates ways in which datasets differ even when using identical climate model input data. We show that substantial variability in precipitation projections arises from downscaling alone and that the downscaled dataset agreement varies depending on global climate projection. This analysis emphasizes the need for greater coordination and movement toward rigorous benchmarking of downscaling strategies within the downscaling research community, à la the land-modeling community, to better quantify downscaling dataset differences, strengths, and weaknesses for practitioners.

Hartke, Samantha H. (ORCID:0000000202394723)↗
DOE OSTI2023

A convection-permitting dynamically downscaled dataset over the Midwestern United States

Climate change is expected to have far-reaching effects at both the global and regional scale, but local effects are difficult to determine from coarse-resolution climate studies. Dynamical downscaling can provide insight into future climate projections on local scales. Here, we present a new dynamically downscaled dataset for Indiana and the surrounding regions. Output from the Community Earth System Model (CESM) version 1 is downscaled using the Weather Research and Forecasting model (WRF). Simulations are run with a 24-hr reinitialization strategy and a 12-hr spin-up window. WRF output is bias corrected to the National Centers for Environmental Protection/National Center for Atmospheric Research 40-year Reanalysis project (NCEP) using a modified quantile mapping method. Bias-corrected 2-m air temperature and accumulated precipitation are the initial focus, with additional variables planned for future releases. Regional climate change signals agree well with larger global studies, and local fine-scaled features are visible in the resulting dataset, such as urban heat islands, frontal passages, and orographic temperature gradients. This high-resolution climate dataset could be used for down-stream applications focused on impacts across the domain, such as urban planning, energy usage, water resources, agriculture and public health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Improved Simulation of East Asian Summer Monsoon in the High-resolution CESM1 and Its Causes

Based on the high- and low-resolution Community Earth System Model, version 1 (CESM1), and corresponding simulations from phase 6 of the Coupled Model Intercomparison Project (CMIP6), we compare the interannual variability of the East Asian summer monsoon (EASM). The EASM interannual variability is characterized by the anomalous western North Pacific anticyclone (WNPAC) circulation and the dipole rainfall pattern with a negative southern lobe over the western North Pacific and a positive northern lobe along the Meiyu–Baiu region, which is better reproduced by the high-resolution models. Here, the reason for the improvement in the high-resolution models has been attributed to the better simulation of the warm temperature advection from the wind anomalies on the climatological temperature gradient. Positive sea surface temperature (SST) anomalies over the tropical Indian Ocean are the key to the improved wind anomalies featuring a WNPAC in the high-resolution models. The warm SST anomalies over the tropical Indian Ocean strengthen the WNPAC by triggering a Kelvin-wave response to the enhanced heat release induced by the increased precipitation. Based on the mixed-layer heat budget analysis, the warm SST anomalies over the western Indian Ocean in the high-resolution CESM1 are tied to the anomalous easterly wind along the equator, which reduces surface evaporation and upwelling. Therefore, the better simulations of air-sea feedback and the oceanic mesoscale eddy over the western Indian Ocean are the key for the improved simulation of the EASM interannual variations in the high-resolution CESM1.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The influence of wintertime SST variability in the Western North Pacific on ENSO diversity

Abstract Sea surface temperature anomalies (SSTa) in the Western North Pacific (WNP) have been linked to the development of El Niño Southern Oscillation (ENSO) events a full year in advance. However, the contribution of the WNP precursor to the temporal evolution and spatial complexity of ENSO remains unclear. Using the preindustrial experiment of the Community Earth System Model as the control climate, a partially coupled experiment is conducted in which WNP SSTa are restored to the model climatology. By comparing the perturbed experiment to the control, we are able to clearly characterize ENSO’s response to WNP SST variability. We find that the WNP is predominantly linked to eastern Pacific (EP) ENSO events. Without SST variability in the WNP, central Pacific (CP) ENSO events are more likely to develop. This variation in ENSO flavor is controlled by how the WNP projects onto wind stress anomalies in the western equatorial Pacific, which in turn impacts the discharge and recharge of ocean heat during the ENSO cycle. Specifically, the removal of SSTa in the WNP weakens the buildup of ocean heat in the western equatorial Pacific, which then hinders the development of EP-type events.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

Projections of winter polynyas and their biophysical impacts in the Ross Sea Antarctica

Abstract This study investigates winter polynyas in the southern Ross Sea, Antarctica where several polynyas are known to form. Coastal polynyas are areas of lower sea ice concentration and/or thickness along the coast that are otherwise surrounded by more extensive, thicker sea ice pack. Polynyas are also locations where organisms can exploit both the ice substrate and pelagic resources. Using a self organizing map algorithm, we identify polynya events in the Community Earth System Model Version 2 Large Ensemble (CESM2-LE). The neural network algorithm is able to identify polynya events without imposing an ice concentration or thickness threshold, as is often done when identifying polynyas. The CESM2-LE produces a wintertime polynya feature comparable in size and location to the Ross Sea polynya, and during polynya events there are large turbulent heat fluxes and export of sea ice from the Ross Sea. In the CESM2-LE polynya event frequency is projected to decrease sharply in the later twentyfirst century, leading to increasing sea ice concentrations and thicknesses in the region. The drivers of the polynya frequency decline are likely both large scale circulation changes and local atmosphere and ocean feedbacks. If declines in wintertime polynya frequency over the twentyfirst century do occur they may impact Antarctic Bottom Water formation and local net primary productivity. Thus, better understanding potential local and unexpected sea ice changes in the Ross Sea is important for both assessing climate system impacts and ecological impacts on the Ross Sea ecosystem, which is currently protected by an internationally recognized marine protected area.

Meteorology & Atmospheric Sciences↗