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Harnessing land-atmosphere interactions to enhance subseasonal-to-seasonal predictability

2025 Advancing Understanding of Land-Atmosphere Interactions and Processes on S2S Predictability Workshop What: 227 registered workshop participants gathered in person (43%) and online (57%) to discuss state-of-the-art scientific understanding and modeling of land-atmosphere interactions and related processes in the context of subseasonal-to-seasonal (S2S) predictability. Topics covered sources of S2S predictability, land model initialization methods, model diagnosis and evaluation metrics, AI/ML analysis and applications, and coordination of future community multi-model S2S forecast focused experiments. To advance the science, this community workshop, organized by NSF NCAR, NOAA, NASA, and DOE, aimed to 1) identify process- and application-oriented metrics for assessing S2S prediction skill and 2) develop experimental protocols for coordinated experiments to isolate, quantify, and understand the role of land-atmosphere interactions in S2S predictability. When: June 16-18, 2025 Where: Boulder, CO, USA, and online.

Land-Atmosphere Interaction↗

Influence of Atmospheric Variability on Predicted Sonic Boom Metrics

As part of the Quesst mission, NASA will fly the X-59 aircraft over selected communities to survey community responses to low sonic booms. Previously, we developed a Kalman filter method to estimate the loudness metrics experienced by each survey participant during each flight. The Kalman filter fuses acoustic measurements with predictions from PCBoom, a sonic boom propagation model. PCBoom requires vertical profiles of the temperature, humidity, and wind to propagate sonic booms through the atmosphere and predict the loudness metrics at the ground. Prior to each X-59 flight, NASA will launch weather balloons to measure the vertical atmospheric profile. However, the atmosphere changes continually with geographic location and time. The purpose of this work is to determine where and when to launch these weather balloons to minimize the uncertainty in the predicted loudness metrics caused by atmospheric variability. We analyzed the effect of atmospheric variability on the predicted Perceived Level in three communities in different climate zones in the United States. To achieve acceptable uncertainty in the Perceived Level, weather balloons should be launched from at least two different sites within the survey area within one hour of each X-59 flight.

sonic boom↗

Goal-Driven Definition of Product Metrics Based on Properties

Defining product metrics requires a rigorous and disciplined approach, because useful metrics depend, to a very large extent, on one's goals and assumptions about the studied software process. Unlike in more mature scientific fields, it appears difficult to devise a "universal" set of metrics in software engineering, that can be used across application environments. We propose an approach for the definition of product metrics which is driven by the experimental goals of measurement, expressed via the Goal/Question/Metric (GQM) paradigm, and is based on the mathematical properties of the metrics. This approach integrates several research contributions from the literature into a consistent, practical and rigorous approach. The approach we outline should not be considered as a complete and definitive solution, but as a starting point for discussion about a product metric definition approach widely accepted in the software engineering community. At this point, we intend to provide an intellectual process that we think is necessary to define sound software product metrics. A precise and complete documentation of such an approach will provide the information needed to make the assessment and reuse of a new metric possible. Thus, product metrics are supported by a solid theory which facilitates their review and refinement. Moreover, their definition is made less exploratory and, as a consequence, one is less likely to identify spurious correlations between process and product metrics.

Briand, Lionel↗

Workshop on the Impacts of Aviation on Climate Change

Projections indicate that demand for aviation transportation will increase by more than two fold over the next few decades. Timely action is needed to understand and quantify the potential climate impacts of aviation emissions particularly given the sustained lapse over the last several years in U.S. research activities in this area. In response to the stated needs, a group of international experts participated in the Workshop on the Impacts of Aviation on Climate Change during June 7-9, 2006 in Boston, MA. The workshop focus was on the impacts of subsonic aircraft emissions in the UT/LS region and on the potential response of the climate system. The goals of the workshop were to assess and document the present state of scientific knowledge, to identify the key underlying uncertainties and gaps, to identify ongoing and further research needed, to explore the development of climate impact metrics, and to help focus the scientific community on the aviation-climate change research needs. The workshop concluded that the major ways that aviation can affect climate, in agreement with the 1999 assessment by the Intergovernmental Panel on Climate Change (IPCC), are the direct climate effects from CO2 and water vapor emissions, the indirect forcing on climate resulting from changes in the distributions and concentrations of ozone and methane as a primary consequence of aircraft nitrogen oxide (NOx) emissions, the direct effects (and indirect effects on clouds) from emitted aerosols and aerosol precursors, and the climate effects associated with contrails and cirrus cloud formation. The workshop was organized in three subgroups: (1) Effects of aircraft emissions on the UT/LS chemical composition, (2) Effects of water and particle emissions on contrails and on cirrus clouds, and (3) Impacts on climate from aircraft emissions and identification of suitable metrics to measure these impacts. The workshop participants acknowledged the need for focused research specifically to address the uncertainties and gaps in our understanding of current and projected impacts of aviation on climate and to develop metrics to better characterize these impacts. This may entail coordination and/or expansion of existing and planned climate research programs, or new activities. Such efforts should include strong and continuing interactions among the science and aviation communities as well as policymakers to develop well-informed decisions.

Wuebbles, Don↗

Unifying the Validation of Ambient Solar Wind Models

Progress in space weather research and awareness needs community-wide strategies and procedures to evaluate our modeling assets. Here we present the activities of the Ambient Solar Wind Validation Team embedded in the COSPAR ISWAT initiative. We aim to bridge the gap between model developers and end-users to provide the community with an assessment of the state-of-the-art in solar wind forecasting. To this end, we develop an open online platform for validating solar wind models by comparing their solutions with in situ spacecraft measurements. The online platform will allow the space weather community to test the quality of state-of-the-art solar wind models with unified metrics providing an unbiased assessment of progress over time. In this study, we propose a metadata architecture and recommend community-wide forecasting goals and validation metrics. We conclude with a status update of the online platform and outline future perspectives.

Space weather↗

Data-Driven Understanding of Low-to-Moderate Income Customers’ Adoption and Financial Qualification in Community Solar

Through this project, we sought to gather a body of customer data that either proved or disproved our assumption that metrics other than FICO can and should be used to qualify customers for community solar. Using customer data on income, FICO scores, and utility/rent/cell phone repayment history, we developed an alternative metric in order to test in the market at a small scale whether new qualifying metrics could open the shared solar market up to millions of additional households. We demonstrate that the EnergyScore is both more accurate in qualifying customers that will not default, and more inclusive in qualifying low to moderate income households. We are now in the process of utilizing the EnergyScore in a number of pilot projects, building a robust dataset of customer churn and default, and subsequently disseminating this data to more traditional and larger scale financiers and solar developer partners to change the way potential customers are qualified.

14 SOLAR ENERGY↗

A building performance-based approach to determining energy resilience for grocery stores in the event of a power outage

Evaluating progress toward a built environment that is best equipped to serve communities during a regional power outage will require metrics that capture the energy resilience of the unique buildings and businesses most crucial to the well-being of those nearby. We focused on grocery stores as key buildings for which access, and thus energy resilience, is critical during a disaster when power is unavailable. We evaluated the energy resilience of these buildings by offering and testing building-scale metrics that assess business continuity potential during a power outage. Metrics proposed in this study are calculated based on the unique power loads characteristic to grocery stores, primarily refrigeration and maintaining safe indoor environmental conditions. Building simulations based on varying levels of backup power were carried out against occupant safety and comfort parameters to apply these metrics, with additional criteria imposed on grocery stores to capture the inventory and sales loss from food spoilage resulting from a lack of refrigeration power. Findings from this study demonstrate the feasibility of our proposed metrics and methodology to serve as a low-data burden means for stakeholders to evaluate the energy resilience of grocery stores, with greater implications in helping to understand the impact on community-scale energy resilience.

Siegel, Lino Sanchez↗

Packages of Distributed Energy Technologies Demonstrating Demand Flexibility at Community Scale

The combination of increased electric load growth across all sectors, deferred electrical infrastructure investment, and other factors resulting in variable electric power supply, has created technical challenges to maintaining a resilient and reliable grid. Many federal, regional, and local efforts are in play to modernize the electric grid, including advancing building technologies and distributed energy resources (DERs) that are utilizing smarter controls to become responsive to both occupant and grid needs. This report reviews ten pilot projects demonstrating how groups of buildings combined with behind-the-meter (BTM) DERs such as electric vehicle (EV) charging, battery storage, flexible HVAC and domestic hot water systems, and photovoltaic systems can reliably and cost effectively provide grid services. Each of the ten pilot projects aim to deliver both energy efficiency and demand flexibility (DF) while supporting load growth. The ten demonstration teams are piloting flexible DER packages across diverse communities of residential and commercial buildings to address a variety of regional grid needs. The outcomes of these pilot projects will be used to inform future scaling through utility program development. This paper characterizes the ten teams, showcasing the decision-making process used by each group to develop their packages (Section 2), the grid services they plan to deliver (Section 3), the types of DER packages selected for deployment within building sectors (Section 4) and trends between building sector, DER types, and grid services In order to achieve community scale benefits, the pilot projects must utilize aggregated control mechanisms for coordinating buildings and DERs together. Several types of coordinated control architectures have evolved amongst the teams, influenced by use type, existing market conditions, and integration type. Three coordinated controls architectures have been characterized, highlighting their use cases, benefits, challenges, and tradeoffs in their design. These insights can aid utilities, control vendors, and developers in scaling community-level energy systems (Paul, 2024). Ultimately, the technology packages selected by the ten teams will be coordinated to provide power system services, also known as grid services. Insights from these demonstrations will be useful for grid operators, regulators, aggregators and other stakeholders as they look to deploy demand flexible resources as grid services in the future. The grid services that each team is targeting for demonstration are described in Section 3 and Section 4. Methods for evaluating the grid services have been described in the paper Metrics for Evaluating Grid Service Provision from Communities of Grid-interactive and Efficient Buildings and other DER (MacDonald, 2023). To identify technology packages for demonstration, Section 2 shows that project teams used a range of analysis approaches, including building energy modeling, AMI data analysis, cost-benefit frameworks, and utility pilot data. Some teams emphasized technical modeling to quantify grid impacts and demand reduction potential, while others prioritized economic evaluations, stakeholder input, or exploratory pilots to inform deployment decisions. This diversity reflects the need to tailor selection methods to project goals, available data, and organizational context. Section 5 discusses trends between the DER technologies deployed and the grid service provisions from each team. Residential buildings (multifamily and single family) lean towards technologies that enhance energy efficiency (e.g. weatherization upgrades, smart thermostats) and onsite power generation integration (e.g. solar PV). Commercial building demonstrations prioritize technologies that ensure operational reliability (e.g. battery storage) and centralized energy management systems and optimization solutions. Teams that are deploying controllable storage-based technologies are more likely to provide grid services that require a near real-time response. Teams incorporating load shifting technologies like smart thermostats with HEMs are likely to include energy markets participation and customer bill management offerings. Campus demonstrations are adopting diverse sets of DERs to emphasize renewable generation, paired with centralized control. This section also describes technologies that were considered during project planning but ultimately excluded from final deployment. These demonstrations reveal that effective DER package design should be tailored to building type, customer segment, and construction vintage. Multifamily buildings benefit from centralized HVAC upgrades and supervisory controls, while single-family homes are well-suited for individualized technologies like solar, storage, and smart home energy monitors. Commercial and campus settings prioritize EMIS integration and load optimization. New construction enables cost-effective integration of DER-ready infrastructure, whereas retrofits require deployments aligned with owner and tenant value streams. For utility program planners, early coordination with developers and building owners, paired with segmented and modular program offerings, can improve adoption, scalability, and grid impact.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Metrics as tools for bridging climate science and applications

In climate science and applications, the term “metric” is used to describe the distillation of complex, multifaceted evaluations to summarize the overall quality of a model simulation, or other data product, and/or as a means to quantify some response to climate change. Metrics provide insights into the fidelity of processes and outcomes from climate models and can assist with both differentiating models' representation of variables or processes and informing whether models are “fit for purpose.” Metrics can also provide a valuable reference point for co-production of knowledge between climate scientists and climate impact practitioners. Although continued metric developments enable model developers to better understand the impacts of decisions made in the model design process, metrics also have implications for the characterization of uncertainty and facilitating analyses of underlying physical processes. As a result, comprehensive evaluation with multiple metrics enhances usability of climate information by both scientific and stakeholder communities. Here, this paper presents examples of insights gained from the development and appropriate use of metrics, and provides examples of how metrics can be used to engage with stakeholders and inform decision-making.

54 ENVIRONMENTAL SCIENCES↗

Application Frontiers of "Designer Fluid Mechanics"--Visions Versus Reality or An Attempt to Answer the Perennial Question "Why Isn't It Used?"

Any new concept must successfully transit two sequential filters between research initiation and application, a technical filter (does it work?) and a technological filter (does it make sense in the real world? ). In general, the research community is not sufficiently knowledgeable regarding the myriad metrics of the technological filter and therefore non (application) useful research is conducted in some cases and in others the research is not carried far enough to allow technological evaluation. It is becoming imperative that the research community be more knowledgeable concerning, and in many cases work with, the application community.

Bushnell, Dennis M.↗

Quantifying air quality co-benefits to industrial decarbonization: the local Air Emissions Tracking Atlas

Many decarbonization technologies have the added co-benefit of reducing short-lived climate pollutants, such as particulate matter (PM), nitrogen oxides (NO x ), and sulfur dioxide (SO 2 ), creating a unique opportunity for identifying strategies that promote both climate change solutions and opportunities for air quality improvement. However, stakeholders and decision-makers may struggle to quantify how these co-benefits will impact public health for the communities most affected by industrial air pollution. To address this problem, the LOCal Air Emissions Tracking Atlas (LOCAETA) fills a data availability and analysis gap by providing estimated air quality benefits from industrial decarbonization options, such as carbon capture and storage (CCS). These co-benefits are calculated using an algorithm that connects disparate datasets that separately report greenhouse gas emissions and other pollutants at U.S. industrial facilities. Version 1.0 of LOCAETA displays the estimated primary PM 2.5 emission reduction co-benefits from additional pretreatment equipment for CCS on industrial and power facilities across the state of Louisiana, as well as the potential for VOC and NH 3 generation. The emission reductions are presented in the tool alongside facility pollutant emissions information and relevant air quality, environmental, demographic, and public health datasets, such as air toxics cancer risk, satellite and in situ pollutant measurements, and population vulnerability metrics. LOCAETA enables regulators, policymakers, environmental justice communities, and industrial and commercial users to compare and contrast quantifiable public health benefits due to air quality impacts from various climate change mitigation strategies using a free and publicly-available tool. Additional pollutant reductions can be calculated using the same methodology and will be available in future versions of the tool.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Clean Cities and Communities Partnership 2023 Activity Report

This is the 2023 report for the Clean Cities and Communities (CC&C) partnership. It tracks the metrics that have been reported by individual coalitions and aggregated to the national level. It looks at the various outreach activities, grant activities, and implementation of clean transportation technologies. Such technologies include natural gas vehicles, electric vehicles, propane vehicles, hydrogen fuel cell vehicles, biodiesel, ethanol, idle reduction technologies, fuel economy improvement technologies, vehicle-miles-traveled reduction technologies, and off-road technologies. The CC&C partnership had an energy use impact of over 1 billion gallons in 2023 and reduced emissions by nine million tons. Outreach, engagement, and training activities increased 18% from last year.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

American cities in a time of global environmental change: the case of the Baltimore Social-Environmental Collaborative

The Baltimore Social-Environmental Collaborative (BSEC) Urban Integrated Field Laboratory seeks a new paradigm for urban climate research. Motivated by deep uncertainties in urban climate and the future of urban systems, BSEC works collaboratively across institutions and stakeholder groups to co-generate the science needed to advance energy security and resilience to extreme events across the city of Baltimore, Maryland, USA, and to do so in a manner that can inform similar efforts in other cities. BSEC begins with stakeholder priorities (health, affordable energy, etc) and designs observation networks and models to deliver climate science to address them. This takes the form of an iterative collaborative cycle, in which an initial research strategy is repeatedly updated in conversation with community partners, and researchers and stakeholders learn from each other. To date, this cycle has included multiple rounds of collaborative deliberation on urban heat mitigation, in which a multicriteria decision tool has been updated with more community-relevant spatial structure and modified optimization metrics. The guiding objective of this cycle is to inform potential ‘secure and resilient pathways’ for energy and infrastructure. In doing so, BSEC addresses fundamental urban science questions in natural and social sciences. It also tests our ability to integrate this science in a manner that advances participatory decision-making for urban resilience.

climate↗

Reduction of the molecular hamiltonian matrix using quantum community detection

Abstract Quantum chemistry is interested in calculating ground and excited states of molecular systems by solving the electronic Schrödinger equation. The exact numerical solution of this equation, frequently represented as an eigenvalue problem, remains unfeasible for most molecules and requires approximate methods. In this paper we introduce the use of Quantum Community Detection performed using the D-Wave quantum annealer to reduce the molecular Hamiltonian matrix in Slater determinant basis without chemical knowledge. Given a molecule represented by a matrix of Slater determinants, the connectivity between Slater determinants (as off-diagonal elements) is viewed as a graph adjacency matrix for determining multiple communities based on modularity maximization. A gauge metric based on perturbation theory is used to determine the lowest energy cluster. This cluster or sub-matrix of Slater determinants is used to calculate approximate ground state and excited state energies within chemical accuracy. The details of this method are described along with demonstrating its performance across multiple molecules of interest and bond dissociation cases. These examples provide proof-of-principle results for approximate solution of the electronic structure problem using quantum computing. This approach is general and shows potential to reduce the computational complexity of post-Hartree–Fock methods as future advances in quantum hardware become available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A framework to evaluate machine learning crystal stability predictions

The rapid adoption of machine learning in various scientific domains calls for the development of best practices and community agreed-upon benchmarking tasks and metrics. We present Matbench Discovery as an example evaluation framework for machine learning energy models, here applied as pre-filters to first-principles computed data in a high-throughput search for stable inorganic crystals. We address the disconnect between (1) thermodynamic stability and formation energy and (2) retrospective and prospective benchmarking for materials discovery. Alongside this paper, we publish a Python package to aid with future model submissions and a growing online leaderboard with adaptive user-defined weighting of various performance metrics allowing researchers to prioritize the metrics they value most. To answer the question of which machine learning methodology performs best at materials discovery, our initial release includes random forests, graph neural networks, one-shot predictors, iterative Bayesian optimizers and universal interatomic potentials. We highlight a misalignment between commonly used regression metrics and more task-relevant classification metrics for materials discovery. Accurate regressors are susceptible to unexpectedly high false-positive rates if those accurate predictions lie close to the decision boundary at 0 eV per atom above the convex hull. The benchmark results demonstrate that universal interatomic potentials have advanced sufficiently to effectively and cheaply pre-screen thermodynamic stable hypothetical materials in future expansions of high-throughput materials databases.

Riebesell, Janosh↗

Meadowview Neighborhood Electrification Project

Awarded a Congressionally Directed Spend (CDS) in 2023, Sacramento Municipal Utility District (SMUD) has successfully executed the Meadowview Neighborhood Electrification Project designed to demonstrate the efficacy of residential energy efficiency and weatherization upgrades for under-resourced communities positively impacting energy use reductions, financial metrics, and indoor air quality. Initially, the project sought to electrify and upgrade 300 homes in Sacramento’s Meadowview neighborhood. However, as interest and momentum grew, the project team proved increasingly efficient and was able to retrofit 374 homes. The project built on SMUD’s years of effort increasing energy efficiency, weatherization, and electrification for low-income residential customers—moving beyond incremental improvements toward full home electrification where it was both feasible and cost-effective.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Uniting Theory and Experiment to Deliver Flexible MOFS for Superior Methane (NG) Storage

The objective of the project was to use previous insights developed through synthesis and quantitative modeling of rigid metal–organic frameworks (MOFs) in an established synergistic theoretical/experimental team to create, modify, and evaluate flexible MOFs (FlexMOFs) for natural gas (NG) storage and release at practically useful pressures and transform the NG storage economy. The goal was reduced pressure absorbed natural gas (ANG) FlexMOF storage at operating pressures less than 100 bar with physisorption exploiting the favorable thermodynamics and kinetics of flexible porous material opening in response to adsorption. Hydrogen behavior in this context was also considered. The specific aim of the project was to design and develop a standard computational modeling methodology for, first, detailed atomistic retrodiction of FlexMOF gating behavior and ultimately prediction of the effects of functionalization and/or substitution on structural transitioning. The project was also geared towards the establishment of the interaction of methane with the framework and binding sites using modeling and the FlexMOF will be both internally and external validated as a SMART metric. This has value to the scientific community both from the obvious standpoint of providing a better understanding of the promising test case systems (CdIF-13 and the MIL-53(Al) series of MOFs), but also in providing an avenue of obtaining insight into these FlexMOF systems in general, which is of particular interest given the tendency of structure-function correlation to lag behind synthesis methodology (making the latter a hit or miss proposition for applications). This gap remains significant for FlexMOF systems whose gate opening behaviors complicate computational examination. The computational methodologies are relatively inexpensive in terms of both money and computational resources enhancing the general viability of these methodologies. The ultimate gain to the public will be in the application of these techniques to design systems for natural gas storage and use to cut down on green-house emissions.

03 NATURAL GAS↗

Sonic boom acceptability studies

The determination of the magnitude of sonic boom exposure which would be acceptable to the general population requires, as a starting point, a method to assess and compare individual sonic booms. There is no consensus within the scientific and regulatory communities regarding an appropriate sonic boom assessment metric. Loudness, being a fundamental and well-understood attribute of human hearing was chosen as a means of comparing sonic booms of differing shapes and amplitudes. The figure illustrates the basic steps which yield a calculated value of loudness. Based upon the aircraft configuration and its operating conditions, the sonic boom pressure signature which reaches the ground is calculated. This pressure-time history is transformed to the frequency domain and converted into a one-third octave band spectrum. The essence of the loudness method is to account for the frequency response and integration characteristics of the auditory system. The result of the calculation procedure is a numerical description (perceived level, dB) which represents the loudness of the sonic boom waveform.

Shepherd, Kevin P.↗