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At least 253 records · Page 14

Valuation of Wind Energy Turbines Using Volatility of Wind and Price

The limitedness of the nonrenewable local energy resources in Israel, even in the background of the later gas fields’ findings, continues to force the state to devote various efforts towards ‘green’ energy development. These efforts include installations, both for the solar and for wind energy, thus improving the diversity of energy sources. While the standard discounted cash flow (DCF) method using the net present value (NPV) criterion is extensively adopted to evaluate investments, the standard DCF method is inappropriate for the rapidly changing investment climate and for the managerial flexibility in investment decisions. In recent years, the real options analysis (ROA) technique has been widely applied in many studies for the valuation of renewable energy investment projects. Taking into account the above background, we apply, in this study, the real options analysis approach for the valuation of wind energy turbines and apply it to the analysis of wind energy economic potential in Israel, which is the context of our work. We hypothesize that due to nature of wind energy production uncertainties, the ROA method is better than the alternative. The novelty of this paper includes the following: real world wind statistics of the Merom Golan site in Israel (velocity 3.73 m/s, with a standard deviation of 2.03 m/s), a realistic power generation estimation (power generation of 1205.84 kW with a standard deviation of about 0.5% in annual value which is worth about 1.3 M$ per annum), and an economic model to evaluate the profitability of such a project. We thus discuss the existing challenges of diversifying renewable energy sources in Israel by adding wind installations. Our motivation is to introduce a method which will allow investors and officials to take into account uncertainties when deciding in investing in such wind installations. The outcomes of the paper, which are obtained using the method of Weibull statistics and the Black–Scholes ROA technique, include the result that market price volatility adds to the uncertainties much more than any wind fluctuations, provided that the analysis is integrated over a long enough time.

17 WIND ENERGY↗

Unprecedented Drought Challenges for Texas Water Resources in a Changing Climate: What Do Researchers and Stakeholders Need to Know?

Long‐range water planning is complicated by factors that are rapidly changing in the 21st century, including climate, population, and water use. Here, we analyze climate factors and drought projections for Texas as an example of a diverse society straddling an aridity gradient to examine how the projections can best serve water stakeholder needs. We find that climate models are robust in projecting drying of summer‐season soil moisture and decreasing reservoir supplies for both the eastern and western portions of Texas during the 21st century. Further, projections indicate drier conditions during the latter half of the 21st century than even the most arid centuries of the last 1,000 years that included megadroughts. To illustrate how accounting for drought non‐stationarity may increase water resiliency, we consider generalized case studies involving four key stakeholder groups: agricultural producers, large surface water suppliers, small groundwater management districts, and regional water planning districts. We also examine an example of customized climate information being used as input to long‐range water planning. We find that while stakeholders value the quantitative capability of climate model outputs, more specific climate‐related information better supports resilience planning across multiple stakeholder groups. New suites of tools could provide necessary capacity for both short and long‐term, stakeholder‐specific adaptive planning.

drought↗

Detection and attribution of long-term and fine-scale changes in spring phenology over urban areas: A case study in New York State

Spring phenology plays an essential role in climate change, terrestrial ecosystem, and public health. Field-based monitoring and understanding of changes in spring phenology for long periods and in large regions are challenging due to the limited in-site observations. Space-based remotely sensed observations offer great potentials for monitoring decadal spring phenology changes from regional to global scales. However, the coarse-scale remotely sensed observations are insufficient to capture fine-scale spring phenology dynamics, especially in urban areas, and this makes it challenging for understanding the combined effects of climate change and urbanization on spring phenology. We derived the start of phenology season (SOS) in New York State using 30 m Landsat observations from 1990 to 2015 to understand the impact of the environment and urbanization on SOS. The results show that SOS for different years reveals heterogeneous spatial distribution. Most regions of New York State have been experiencing significant spring phenology changes in form of earlier onset of vegetation greening, ranging from 0.2 to 0.6 day/year during 1990 to 2015, and this trend varies slightly with latitudes and urbanization levels. Further, spatial correlation analysis shows that the increase in temperature and urbanization could both promote the advancement of SOS. However, the effect of urbanization (partial correlation coefficient (R) ranges from −0.289 to −0.542) on SOS is greater than the effect of temperature (R ranges from 0.006 to −0.192). The study generates a high spatio-temporal resolution spring phenology dataset for ecological, environmental and public health studies, especially in urban areas, and reveals the importance of better accounting for the urbanization effects when quantifying the SOS dynamics in phenology models.

Landsat↗

The Community Earth System Model version 2 (CESM2)

An overview of the Community Earth System Model version 2 (CESM2) is provided, including a discussion of the challenges encountered during its development and how they were addressed. In addition, an evaluation of a pair of CESM2 long pre-industrial control and historical ensemble simulations is presented. These simulations were performed using the nominal 1° horizontal resolution configuration of the coupled model with both the “low-top” (40 km, with limited chemistry) and “high-top” (140 km, with comprehensive chemistry) versions of the atmospheric component. CESM2 contains many substantial science and infrastructure improvements and new capabilities since its previous major release, CESM1, resulting in improved historical simulations in comparison to CESM1 and available observations. These include major reductions in low latitude precipitation and short-wave cloud forcing biases; better representation of the Madden-Julian Oscillation; better El Niño – Southern Oscillation-related teleconnections; and a global land carbon accumulation trend that agrees well with observationally-based estimates. Most tropospheric and surface features of the low- and high-top simulations are very similar to each other, so these improvements are present in both configurations. CESM2 has an equilibrium climate sensitivity of 5.1-5.3°C, larger than in CESM1, primarily due to a combination of relatively small changes to cloud microphysics and boundary layer parameters. In contrast, CESM2’s transient climate response of 1.9-2.0°C is comparable to that of CESM1. The model outputs from these and many other simulations are available to the research community, and theyrepresent CESM2’s contributions to the Coupled Model Intercomparison Project phase 6 (CMIP6).

Danabasoglu, Gokhan↗

Accelerated Carbon and Water Cycles in the Amazon and Congo Basins Revealed From TRENDY Models and Remote Sensing Products

Tropical forests play a vital role in the global carbon cycle and land–atmosphere interactions. Estimating tropical forest carbon–water dynamics is challenging due to observational and modeling uncertainties. This study leverages the “Trends and drivers of the regional scale terrestrial sources and sinks of carbon dioxide” (TRENDY) project models and satellite observations to assess changes (2003–2021) in vegetation carbon, gross primary production (GPP), evapotranspiration (ET), and net biosphere production (NBP) in the Amazon and Congo. Atmospheric CO 2 , climate variability, and land use and land cover changes constrain these variables between 1700 and 2021 with the overall increasing trends of carbon stock and fluxes. The models overestimate vegetation carbon and GPP, while ET and NBP are consistent with observations. Fire-activated models predict lower values for vegetation carbon and GPP, ET, and NBP, aligning more closely with observations. The higher ET from fire-activated models may result from enhanced soil evaporation due to increased canopy openings. Fire-inactivated models could well estimate the magnitudes of NBP. The high vegetation carbon in nitrogen-enabled models points to simulation uncertainties and imbalance in model numbers regarding the nitrogen cycle. Although the nitrogen cycle enhances water use efficiency in both the Amazon and Congo, the models show a higher sensitivity to the nitrogen cycle in the Congo. This study highlights the challenges in accurately representing tropical biogeochemical cycles and the values of satellite products in model evaluations, underscoring the need for standard modeling protocols that address biogeochemical components (e.g., nutrient cycles) to better resolve process-based representations.

Shi, Mingjie [Pacific Northwest National Laborator↗

Residential Building Energy Efficiency Field Studies: Low-Rise Multifamily

In recent years, the U.S. Department of Energy (DOE) has conducted a series of research studies to validate energy efficient building technologies in the field. Much of the work has focused on single-family construction, and some has also addressed commercial energy codes. The work detailed in this DOE-funded study (EE0007616) focuses on low-rise multifamily buildings (three stories or fewer above grade) in various regions of the United States, and reports on how state-level building codes are being implemented, both in terms of observed characteristics and also in terms of estimated energy impacts. Nearly 100 buildings across four states—Illinois, Minnesota, Oregon, and Washington—were sampled, which represent a range of climate types from mild temperature to very cold continental. Both common entry and outdoor entry buildings were included, and a parallel research project evaluated envelope air tightness and current still-evolving air tightness testing methods. Finally, a set of structured interviews of building designers and other relevant professionals was carried to out to gain more insight into this market. To the greatest extent possible, the methodology developed under the project for low-rise multifamily buildings mirrored the approach established by Pacific Northwest National Laboratory (PNNL) for single-family residential buildings (https://www.energy.gov/eere/buildings/downloads/residential-building-energy-code-field-study). This included the general approach to sampling, recruitment, and data collection, as well as data analysis and presentation. The range of permitting dates for the sites encompassed two energy code cycles in most regions. All states in the study had adopted a variation of the International Energy Conservation Code (IECC) for the structure of their state code. The low-rise multifamily occupancy presents a hybrid building type: most of the building’s conditioned floor area was covered by the residential chapter of the code while portions of the building (such as corridors and common spaces) fell under the commercial code chapter. The key items assessed in this work were: Building Shell—exterior wall insulation, ceiling insulation, foundation insulation, windows. Common Areas—HVAC and lighting. Living Units—lighting, ventilation. A few items were not assessed in detail, given their relative paucity in this occupancy type; these included duct leakage, pipe insulation, and hot water circulation controls. Building characteristics were collected via a combination of architectural, mechanical, electrical, and plumbing plan reviews and field inspections, and entered into a spreadsheet-based tool that was later queried to build a database. Data went through quality control both upon arrival and via a later semi-automated review and assurance process. Most of the data are presented graphically so that the reader can quickly assess compliance with the applicable energy codes (both by state and by code year). As a final step, EnergyPlus™ simulations were created for all buildings in the study to estimate both the as-found energy use intensity (EUI) and the energy and CO 2 that could be saved if features that were found to not meet code minimums were brought up to code. The savings estimates were tabulated for each of the four states in the study. The research team found that the single-family approach was largely applicable to low-rise multifamily buildings. This applies to both the data collection and the prototype EUI analysis. Most of the occupied space is living units and falls under residential energy codes, and many characteristics use similar envelope construction and relatively straightforward mechanical systems and lighting. One of the most challenging aspects of this work was to build an effective spreadsheet-based data collection instrument that could allow efficient collection of both building plan and field data. The research team is of the view that other methods could be equally effective if the work is done carefully with diligent quality control. The primary findings for the work center around the thermal envelope and mechanical systems and lighting at the sites: For thermal envelope components, the majority of buildings met or were better than the prescriptive code.This suggests that building designers and builders are aware of code requirements. In some cases, surveyed buildings were designed to qualify for energy efficiency certification programs. These buildings made up at least 20% of sampled buildings in each state. Almost all buildings met mechanical system efficiency requirements (for both living units and common areas). In some cases, sites employed systems that were considerably more efficient than required by the applicable energy code. Dwelling units had a majority of high-efficacy lighting, often in excess of the state’s residential code requirements. While high-efficacy fixtures were also typical in common areas (corridors and stairwells), lighting power densities (LPDs) in these areas were sometimes higher than levels dictated by the applicable part of the state commercial energy code. The simulation models run on a series of low-rise multifamily prototypes, informed by a composite of the field data collected, calculated annual EUIs of between 20 and 50 kBtu/ft2-yr, with the range representing the effects of both building characteristics and building location (climate zone). A detailed process (based on simulations of prototype buildings) was used to estimate the amount of avoided energy use that would occur if 100% adherence to energy codes were attained. The results indicated modest savings are attainable for items such as window thermal performance and common area lighting. The result is overall only a modest potential for additional energy savings, averaging about 10% of EUI.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Disentangling the Regional Climate Impacts of Competing Vegetation Responses to Elevated Atmospheric CO2

Biophysical vegetation responses to elevated atmospheric carbon dioxide (CO2) affect regional hydroclimate through two competing mechanisms. Higher CO2 increases leaf area (LAI), thereby increasing transpiration and water losses. Simultaneously, elevated CO2 reduces stomatal conductance and transpiration, thereby increasing rootzone soil moisture. Which mechanism dominates in the future is highly uncertain, partly because these two processes are difficult to explicitly separate within dynamic vegetation models. We address this challenge by using the GISS ModelE global climate model to conduct a novel set of idealized 2×CO2 sensitivity experiments to: evaluate the total vegetation biophysical contribution to regional climate change under high CO2; and quantify the separate contributions of enhanced LAI and reduced stomatal conductance to regional hydroclimate responses. We find that increased LAI exacerbates soil moisture deficits across the sub‐tropics and more water‐limited regions, but also attenuates warming by ∼0.5–1°C in the US Southwest, Central Asia, Southeast Asia, and northern South America. Reduced stomatal conductance effects contribute ∼1°C of summertime warming. For some regions, enhanced LAI and reduced stomatal conductance produce nonlinear and either competing or mutually amplifying hydroclimate responses. In northeastern Australia, these effects combine to exacerbate radiation‐forced warming and contribute to year‐round water limitation. Conversely, at higher latitudes these combined effects result in less warming than would otherwise be predicted due to nonlinear responses. These results highlight substantial regional variation in CO2‐driven vegetation responses and the importance of improving model representations of these processes to better quantify regional hydroclimate impacts.

Regional climate impacts↗

Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol applied to Earth system models

Abstract. Strongly coupled nonlinear phenomena such as those described by Earth system models (ESMs) are composed of multiple component models with independent mesh topologies and scalable numerical solvers. A common operation in ESMs is to remap or interpolate component solution fields defined on their computational mesh to another mesh with a different combinatorial structure and decomposition, e.g., from the atmosphere to the ocean, during the temporal integration of the coupled system. Several remapping schemes are currently in use or available for ESMs. However, a unified approach to compare the properties of these different schemes has not been attempted previously. We present a rigorous methodology for the evaluation and intercomparison of remapping methods through an independently implemented suite of metrics that measure the ability of a method to adhere to constraints such as grid independence, monotonicity, global conservation, and local extrema or feature preservation. A comprehensive set of numerical evaluations is conducted based on a progression of scalar fields from idealized and smooth to more general climate data with strong discontinuities and strict bounds. We examine four remapping algorithms with distinct design approaches, namely ESMF Regrid (Hill et al., 2004), TempestRemap (Ullrich and Taylor, 2015), generalized moving least squares (GMLS) (Trask and Kuberry, 2020) with post-processing filters, and WLS-ENOR (Li et al., 2020). By repeated iterative application of the high-order remapping methods to the test fields, we verify the accuracy of each scheme in terms of their observed convergence order for smooth data and determine the bounded error propagation using challenging, realistic field data on both uniform and regionally refined mesh cases. In addition to retaining high-order accuracy under idealized conditions, the methods also demonstrate robust remapping performance when dealing with non-smooth data. There is a failure to maintain monotonicity in the traditional L2-minimization approaches used in ESMF and TempestRemap, in contrast to stable recovery through nonlinear filters used in both meshless GMLS and hybrid mesh-based WLS-ENOR schemes. Local feature preservation analysis indicates that high-order methods perform better than low-order dissipative schemes for all test cases. The behavior of these remappers remains consistent when applied on regionally refined meshes, indicating mesh-invariant implementations. The MIRA intercomparison protocol proposed in this paper and the detailed comparison of the four algorithms demonstrate that the new schemes, namely GMLS and WLS-ENOR, are competitive compared to standard conservative minimization methods requiring computation of mesh intersections. The work presented in this paper provides a foundation that can be extended to include complex field definitions, realistic mesh topologies, and spectral element discretizations, thereby allowing for a more complete analysis of production-ready remapping packages.

58 GEOSCIENCES↗

Onshore U.S. Carbon Pipeline Deployment: Siting, Safety, and Regulation

Carbon capture, utilization, and storage technology has significant potential to reduce greenhouse gas emissions and mitigate the impact of climate change, particularly in hard-to-decarbonize industrial and commercial sectors. Unless utilization or storage occurs at the same location as carbon capture, which is rare, carbon must be transported from a point source to a utilization or storage site. Pipelines offer significant advantages for large-scale transportation of carbon dioxide over other methods. While studies show that reaching net-zero carbon emissions in the United States by 2050 will require between 29,000 and 66,000 miles of carbon pipelines, the U.S. had deployed fewer than 6,000 miles of carbon pipelines by 2022. Although closing this gap is important to achieving low-carbon goals, carbon pipelines operate in a complex and uncertain local, state and federal regulatory landscape and face public concerns about safety and siting. This report covers numerous regulatory issues surrounding carbon pipeline development, including the current narrow federal definition of carbon dioxide and the considerable variation in state and local governments’ laws and regulations. The report serves as a primer for regulators and stakeholders who seek to better understand the regulatory challenges and opportunities facing this critical infrastructure

01 COAL, LIGNITE, AND PEAT↗

Detecting flash drought events to inform adaptive water management

Abstract: Flash droughts are characterized by a rapid onset of drought conditions, a common feature among various indicators of these events. The lack of a standardized definition and indicator makes flash droughts particularly challenging to predict and manage. We test six state-of-the-art flash drought indicators using 41 years of daily data across all Hydrological Unit Code 4 (HUC4) regions in the contiguous United States. Our results show substantial disagreements among indicators, suggesting that the detection of a flash drought event strongly depends on the choice of indicator. From the perspective of informing management and operations, an open challenge remains: which flash drought indicator should be used to trigger operational adaptations? To this end, we propose a methodological framework that informs adaptive actions by regionally assessing the level of agreement between different indicators. The regional differences in hydroclimatic conditions are expected to be reflected in the level of agreement between indicators. To better inform adaptive actions, the framework will also consider the impacted sectoral water uses and their varying response times. The insights gained from this study improve the understanding of how these different flash drought indicators capture the different aspects of regional differences and impacted sectors. Furthermore, this information can support more targeted adaptive actions to mitigate adverse impacts through improved preparedness and response strategies.

climate resilience↗

The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present and Future

The Dark Target aerosol algorithm was developed to exploit the information content available from the observations of Moderate-Resolution Imaging Spectroradiometers (MODIS), to better characterize the global aerosol system. The algorithm is based on measurements of the light scattered by aerosols toward a space-borne sensor against the backdrop of relatively dark Earth scenes, thus giving rise to the name “Dark Target”. Development required nearly a decade of research that included application of MODIS airborne simulators to provide test beds for proto-algorithms and analysis of existing data to form realistic assumptions to constrain surface reflectance and aerosol optical properties. This research in itself played a significant role in expanding our understanding of aerosol properties, even before Terra MODIS launch. Contributing to that understanding were the observations and retrievals of the growing Aerosol Robotic Network (AERONET) of sun-sky radiometers, which has walked hand-in-hand with MODIS and the development of other aerosol algorithms, providing validation of the satellite-retrieved products after launch. The MODIS Dark Target products prompted advances in Earth science and applications across subdisciplines such as climate, transport of aerosols, air quality, and data assimilation systems. Then, as the Terra and Aqua MODIS sensors aged, the challenge was to monitor the effects of calibration drifts on the aerosol products and to differentiate physical trends in the aerosol system from artefacts introduced by instrument characterization. Our intention is to continue to adapt and apply the well-vetted Dark Target algorithms to new instruments, including both polar-orbiting and geosynchronous sensors. The goal is to produce an uninterrupted time series of an aerosol climate data record that begins at the dawn of the 21st century and continues indefinitely into the future.

Aerosol↗

Report on Automated Semantic Analysis of Scientific and Engineering Codes

The loss of the Mars Climate Orbiter due to a software error reveals what insiders know: software development is difficult and risky because, in part, current practices do not readily handle the complex details of software. Yet, for scientific software development the MCO mishap represents the tip of the iceberg; few errors are so public, and many errors are avoided with a combination of expertise, care, and testing during development and modification. Further, this effort consumes valuable time and resources even when hardware costs and execution time continually decrease. Software development could use better tools! This lack of tools has motivated the semantic analysis work explained in this report. However, this work has a distinguishing emphasis; the tool focuses on automated recognition of the fundamental mathematical and physical meaning of scientific code. Further, its comprehension is measured by quantitatively evaluating overall recognition with practical codes. This emphasis is necessary if software errors-like the MCO error-are to be quickly and inexpensively avoided in the future. This report evaluates the progress made with this problem. It presents recommendations, describes the approach, the tool's status, the challenges, related research, and a development strategy.

Stewart. Maark E. M.↗

Breaking the Ice: A Review of Phages in Polar Ecosystems

Bacteriophages, or phages, are viruses that infect and replicate within bacterial hosts, playing a significant role in regulating microbial populations and ecosystem dynamics. However, phages from extreme environments such as polar regions remain relatively understudied due to challenges such as restricted ecosystem access and low biomass. In this study, understanding the diversity, structure, and functions of polar phages is crucial for advancing our knowledge of the microbial ecology and biogeochemistry of these environments. In this review, we will explore the current state of knowledge on phages from the Arctic and Antarctic, focusing on insights gained from -omic studies, phage isolation, and virus-like particle abundance data. Metagenomic studies of polar environments have revealed a high diversity of phages with unique genetic characteristics, providing insights into their evolutionary and ecological roles. Phage isolation studies have identified novel phage–host interactions and contributed to the discovery of new phage species. Virus-like particle abundance and lysis rate data, on the other hand, have highlighted the importance of phages in regulating bacterial populations and nutrient cycling in polar environments. Overall, this review aims to provide a comprehensive overview of the current state of knowledge about polar phages, and by synthesizing these different sources of information, we can better understand the diversity, dynamics, and functions of polar phages in the context of ongoing climate change, which will help to predict how polar ecosystems and residing phages may respond to future environmental perturbations.

09 BIOMASS FUELS↗

Strong Correspondence in Evapotranspiration and Carbon Dioxide Fluxes Between Different Eddy Covariance Systems Enables Quantification of Landscape Heterogeneity in Dryland Fluxes

Abstract The eddy covariance method is widely used to investigate fluxes of energy, water, and carbon dioxide at landscape scales, providing important information on how ecological systems function. Flux measurements quantify ecosystem responses to environmental perturbations and management strategies, including nature‐based climate‐change mitigation measures. However, due to the high cost of conventional instrumentation, most eddy covariance studies employ a single system, limiting spatial representation to the flux footprint. Insufficient replication may be limiting our understanding of ecosystem behavior. To address this limitation, we deployed eight lower‐cost eddy covariance systems in two clusters around two conventional eddy covariance systems in the Chihuahuan Desert of North America for a period of 2 years. These dryland settings characterized by large temperature variations and relatively low carbon dioxide fluxes represented a challenging setting for eddy covariance. We found very good closure of energy and water balance across all systems (within ±9% of unity). We found very good correspondence between the lower‐cost and conventional systems' fluxes of sensible heat (with concordance correlation coefficient (CCC) of ≥0.87), latent energy (evapotranspiration; CCC ≥ 0.89), and useful correspondence in the net ecosystem exchange ((NEE); with CCC ≥ 0.4) at the daily temporal resolution. Relative to the conventional systems, the low‐frequency systems were characterized by a higher level of random error, particularly in the NEE fluxes. Lower‐cost systems can enable wider deployment affording better replication and sampling of spatiotemporal variability at the expense of greater measurement noise that might be limiting for certain applications. Replicated eddy covariance observations may be useful when addressing gaps in the existing monitoring of critical and underrepresented ecosystems and for measuring areas larger than a single flux footprint.

54 ENVIRONMENTAL SCIENCES↗

Quantum-Inspired Bayesian Sampling for Uncertainty Quantification and Machine Learning (Final Technical Report)

With increasing simulation and measurement data, machine learning and artificial intelligence have been widely used in computational decision-making of complex engineering systems. The resulting tools, such as uncertainty quantification solvers, reinforcement learning, and physics-informed machine learning, have achieved great success in critical DOE tasks such as material discovery and design, energy system modeling and control, and numerical weather and climate prediction. A core topic in scientific machine learning and artificial intelligence is Bayesian inference: given an observed data set, people want to estimate the posterior distribution of a (possibly large) number of hidden parameters. Due to the flexibility and weak assumptions, Bayesian sampling has been the mainstream Bayesian inference solvers despite the rapid progress of approximate Bayesian inference. Classical Bayesian sampling methods such as Markov-chain Monte Carlo suffer from a low-acceptance rate due to the random walk nature, therefore state-of-the-art techniques use Hamiltonian Monte Carlo and its variants to efficiently draw posterior samples in a high dimension. The key idea of Hamiltonian Monte Carlo and its variants is to simulate the Hamiltonian dynamics of a classical particle with a fixed mass, and their performance significantly degrades when the posterior distribution is highly spiky or has multiple modes. Leveraging the idea of quantum physics, this project has investigated new theory, algorithms and applications of Bayesian inference (especially Bayesian sampling). The main results include: (1) novel quantum-inspired Bayesian sampling methods that can lead to better accuracy for challenging multi-modal or spiky distributions, (2) more scalable machine learning framework leveraging tensor-compressed Bayesian inference, and (3) Bayesian and sampling approaches for verifying the robustness of continuous and binary neural networks.

97 MATHEMATICS AND COMPUTING↗

Finding Atmospheric Composition (AC) Metadata

The Atmospheric Composition Portal (ACP) is an aggregator and curator of information related to remotely sensed atmospheric composition data and analysis. It uses existing tools and technologies and, where needed, enhances those capabilities to provide interoperable access, tools, and contextual guidance for scientists and value-adding organizations using remotely sensed atmospheric composition data. The initial focus is on Essential Climate Variables identified by the Global Climate Observing System CH4, CO, CO2, NO2, O3, SO2 and aerosols. This poster addresses our efforts in building the ACP Data Table, an interface to help discover and understand remotely sensed data that are related to atmospheric composition science and applications. We harvested GCMD, CWIC, GEOSS metadata catalogs using machine to machine technologies - OpenSearch, Web Services. We also manually investigated the plethora of CEOS data providers portals and other catalogs where that data might be aggregated. This poster is our experience of the excellence, variety, and challenges we encountered.Conclusions:1.The significant benefits that the major catalogs provide are their machine to machine tools like OpenSearch and Web Services rather than any GUI usability improvements due to the large amount of data in their catalog.2.There is a trend at the large catalogs towards simulating small data provider portals through advanced services. 3.Populating metadata catalogs using ISO19115 is too complex for users to do in a consistent way, difficult to parse visually or with XML libraries, and too complex for Java XML binders like CASTOR.4.The ability to search for Ids first and then for data (GCMD and ECHO) is better for machine to machine operations rather than the timeouts experienced when returning the entire metadata entry at once. 5.Metadata harvest and export activities between the major catalogs has led to a significant amount of duplication. (This is currently being addressed) 6.Most (if not all) Earth science atmospheric composition data providers store a reference to their data at GCMD.

metadata search↗

State Insights On The Water-Energy Nexus And Policy Ideas To Achieve Greater Savings

Governors, state policymakers, utilities and other stakeholders across the country are increasingly aware of the connection between energy and water production and use, and the need to conserve both resources to meet economic and environmental goals. It requires substantial amounts of water to produce energy and considerable amounts of energy to treat and deliver water. The critical interdependence between energy and water was clearly illustrated during the recent winter storm in Texas and other parts of the South in February 2021. Initial power outages contributed to a longer-term water crisis. Power outages led to water pump failures while water demand increased from frozen water pipes that burst. This caused low water pressure that can lead to harmful bacteria growth in the water. The power outages also prevented water treatment plants from properly treating the water for several days, thereby leaving many residents without clean drinking water and worsening the storm’s impacts. The National Governors Association has been working with states on this connection between water and energy and strategies for conserving those resources for several years. NGA held a Water-Energy Nexus Learning Lab in September 2020. This event invited two leading states in the water-energy nexus space, Arizona and Wisconsin, to showcase some of their model policies and programs to other states, Maryland, Nevada, North Carolina, North Dakota, and Washington, looking for greater savings opportunities. This paper provides an overview of challenges that states are facing in developing integrated water and energy conservation policies; provides background on Arizona and Wisconsin’s innovative water-energy policies and programs; and summarizes action items the participating state teams identified for their respective states. The main categories of policy solutions identified by states at NGA’s Water-Energy Nexus Learning Lab were: Funding & Financing – providing financial incentives for water efficiency modeled after established energy efficiency programs, and an emphasis on financial support for small water and energy utilities. Education & Technical Assistance – providing more education and training opportunities about ways to achieve cost-effective energy and water savings, and the needs of resource-constrained small and medium utilities for training and other assistance. Structural Changes to Encourage Conservation – developing ways to incentivize agricultural conservation such as through water allocation strategies; adopting water reuse or water loss standards; and requiring electric utilities to consider water impacts as part of their integrated resource planning process. Communications & Data – conducting energy audits, reviewing water data provided to state agencies, and developing data benchmarking tools to measure and better manage energy and water use. Climate Strategy – establishing a multi-agency working group or other collaborative approach to determine ways to integrate energy and water savings in state policies and help meet the state climate objectives.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗