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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Can general circulation models (GCMs) represent cloud liquid water path adjustments to aerosol–cloud interactions?

Abstract. General circulation models (GCMs), unlike other lines of evidence, indicate that anthropogenic aerosols cause a global-mean increase in cloud liquid water path (ℒ) and thus a negative adjustment to radiative forcing of the climate by aerosol–cloud interactions. In part 1 of this series of papers, we showed that this is true even in models that reproduce the negative correlation observed in present-day internal variability in ℒ and cloud droplet number concentration (Nd). We studied several possible confounding mechanisms that could explain the noncausal cloud–aerosol correlations in GCMs and that possibly contaminate observational estimates of radiative adjustments. Here, we perform single-column and full-atmosphere GCM experiments to investigate the causal model-physics mechanisms underlying the model radiative adjustment estimate. We find that both aerosol–cloud interaction mechanisms thought to be operating in real clouds – precipitation suppression and entrainment evaporation enhancement – are active in GCMs and behave qualitatively in agreement with physical process understanding. However, the modeled entrainment enhancement has a negligible global-mean effect. This raises the question of whether the GCM estimate is incorrect due to parametric or base-state representation errors or whether the process understanding gleaned from a limited set of canonical cloud cases is insufficiently representative of the diversity of clouds in the real climate. Regardless, even at limited resolution, the GCM physics appears able to parameterize the small-scale microphysics–turbulence interplay responsible for the entrainment enhancement mechanism. We suggest ways to resolve tension between current and future (storm-resolving) global modeling systems and other lines of evidence in synthesis climate projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Establishing robust correction schemes for improved and reliable ARM-AOS aerosol optical data products

Aerosol light absorption and scattering of solar radiation play an important role in the earth’s atmosphere in terms of direct and semi-direct radiative forcing. Optical parameters of importance to the US Department of Energy (DOE) climate models include absorption and scattering coefficients, single scattering albedo (SSA), absorption Angstrom exponents (AAE), and the asymmetry parameter (g). These parameters depend on aerosol size, shape and composition (refractive index), and are spectrally sensitive in the shortwave region. Additionally, these parameters have a complex dependency on the emission source, especially for carbonaceous aerosols. The DOE Atmospheric Radiation Measurement (ARM) user facility has deployed aerosol observing systems (AOS) containing several filter-based instruments to measure and constrain aerosol optical properties and related parameters at multiple sites worldwide. For measurement of aerosol light absorption, the AOS includes filter-based instruments (particle soot absorption photometer and tricolor absorption photometer) that infer particle-phase aerosol absorption coefficients at nominal red, green, and blue wavelength bands from the attenuation (ATN) of light passing through a particulate filter on which aerosols are deposited. Measurement of aerosol scattering is done in situ using nephelometers. By combining inferred absorption coefficients from filter-based ATN measurements and in situ scattering coefficients, value-added products (VAPs) such as SSA, AAE, and g are derived.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Experimental Report: Multi-Instrument Comparison of AAF Condensation Particle Counters

Condensation particle counters (CPCs), also known as condensation nucleus counters (CNCs) are sophisticated instruments designed to measure the concentration of aerosol particles in the atmosphere. These devices are pivotal in environmental monitoring, industrial applications, and scientific research, particularly in atmospheric studies. CPCs are vital for understanding the role of aerosols in climate systems. Aerosols influence cloud formation, radiative forcing, and atmospheric chemistry. By providing accurate measurements of particle concentrations and distributions, CPCs contribute to models that predict atmospheric impact and weather patterns (Mei et al. 2021). CPCs operate by enlarging submicron particles, including those as small as a few nanometers, to sizes detectable by optical methods. This report delves into the mechanisms, importance, and contributions of CPCs to atmospheric research at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF), highlighting their role in advancing air quality assessment, pollution control, and atmospheric studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Climate Forcing of Bioenergy Feedstocks: Insights From Carbon and Energy Flux Measurements

Bioenergy from biofuels has the potential to slow growing atmospheric carbon dioxide concentrations by reducing fossil fuel use. However, growing bioenergy feedstocks is a land-intensive process. In the United States, the recent expansion of maize bioethanol has presented some environmental costs, prompting the development of several alternative bioenergy feedstocks. These feedstocks, selected in part for traits associated with ecosystem services, may provide opportunities for environmental benefits beyond fossil fuel displacement. We hypothesized that these bioenergy ecosystems will provide direct climatic cooling through their influence on carbon and radiative energy fluxes (i.e., through albedo). To test this hypothesis, we investigated the potential cooling effect of five current or potential bioenergy feedstocks using multi-year records from eddy covariance towers. Perennial feedstocks were carbon sinks, with an annual mean net ecosystem carbon balance (NECB) of –2.7 ± 2.1 Mg C ha –1 for miscanthus, –0.8 ± 1.1 Mg C ha –1 for switchgrass, and –1.4 ± 0.7 Mg C ha –1 for prairie. In contrast, annual rotations were generally carbon sources, with an annual mean NECB of 2.6 ± 2.4 Mg C ha –1 for maize-soy and 3.2 ± 2.1 Mg C ha –1 for sorghum-soy. Using maize-soy as a baseline, conversion to alternative feedstocks increased albedo, inducing further cooling. This effect was strongest for miscanthus, with –3.5 ± 2.0 W m –2 of radiative forcing, and weakest for sorghum, with –1.4 ± 1.4 W m –2 . When feedstock effects on carbon and albedo were compared using carbon equivalents, carbon fluxes were the stronger ecosystem effect, underscoring the role of perennial species as effective carbon sinks. This work highlights the impact of feedstock choice on ecosystem processes as an element of bioenergy land conversion strategies.

09 BIOMASS FUELS↗
DOE OSTI2024

HSW-V v1.0: localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model

Abstract. A new set of standalone parameterizations is presented for simulating the injection, evolution, and radiative forcing by stratospheric volcanic aerosols against an idealized Held–Suarez–Williamson (HSW) atmospheric background in the Energy Exascale Earth System Model version 2 (E3SMv2). In this model configuration (HSW with enabled volcanism, HSW-V), sulfur dioxide (SO2) and ash are injected into the atmosphere with a specified profile in the vertical, and they proceed to follow a simple exponential decay. The SO2 decay is modeled as a perfect conversion to a long-living sulfate aerosol which persists in the stratosphere. All three species are implemented as tracers in the model framework and are transported by the dynamical core's advection algorithm. The aerosols contribute simultaneously to local heating of the stratosphere and cooling of the surface by a simple plane-parallel Beer–Lambert law applied on two zonally symmetric radiation broadbands in the longwave and shortwave ranges. It is shown that the implementation parameters can be tuned to produce realistic temperature anomaly signatures of large volcanic events. In particular, results are shown for an ensemble of runs that mimic the volcanic eruption of Mt. Pinatubo in 1991. The design requires no coupling to microphysical subgrid-scale parameterizations and thus approaches the computational affordability of prescribed aerosol forcing strategies. The idealized simulations contain a single isolated volcanic event against a statistically uniform climate, where no background aerosols or other sources of externally forced variability are present. HSW-V represents a simpler-to-understand tool for the development of climate source-to-impact attribution methods.

Hollowed, Joseph P. (ORCID:0000000286581672)↗
DOE OSTI2026

Experimental Report: Multi-Instrument Comparison of AAF Size Distribution Instruments

Aerosols are particles suspended in the atmosphere, ranging in size from nanometers to micrometers. Their size distribution affects key atmospheric processes, including nucleation, coagulation, scavenging, activation, and radiative properties (Seinfeld and Pandis 2016). Aerosol size distribution is a critical parameter in atmospheric science, influencing processes such as cloud formation and radiative forcing. Accurate representation of aerosol size distributions is essential for understanding their impact on climate, air quality, and human health. However, aerosol size and composition vary significantly across time and space due to meteorological conditions and natural or anthropogenic sources. (Wu and Boor 2021). Various instruments are used to measure aerosol size distributions, each with distinct principles, advantages, and limitations. This report begins with an in-depth overview of aerosol size-distribution comparison studies, focusing on the passive cavity aerosol spectrometer probe (PCASP), portable optical particle spectrometer (POPS), ultra-high-sensitivity aerosol spectrometer (UHSAS), aerodynamic particle sizer (APS), and scanning mobility particle sizer (SMPS). All of these instruments are used by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF), which commissioned this comparison and report. The report evaluates the strengths and weaknesses of these instruments, highlights their applications, and discusses efforts to merge data from multiple instruments for comprehensive analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Changing windstorm characteristics over the US Northeast in a single model large ensemble

Abstract Extreme windstorms pose a significant hazard to infrastructure and public safety, particularly in the highly populated US Northeast (NE). However, the influence climate change and changing land use will have on these events remains unclear. A large ensemble generated using the Max-Planck Institute (MPI) Earth system model is used to generate projections of NE windstorms under different shared socioeconomic pathways (SSPs) and to attribute changes to projected land use land cover (LULC) change, externally forced changes and internal climate variability. To reduce the influence of coarse grid cell resolution and uncertainties in surface roughness lengths, windstorms are identified using simultaneous widespread exceedance of local 99th percentile 10 m wind speeds (U 99 ). Projected declines in forest cover in the NE and the resulting reductions in surface roughness length under SSP3-7.0 lead to projections of large increases in U 99 and derived windstorm intensity and scale. However, these projected changes in regional LULC under SSP3-7.0 are unprecedented in a historical context and may not be realistic. After corrections are applied to remove the influence of LULC on wind speeds, regionally averaged U 99 exhibit declines for most of the single model initial-condition large ensemble (SMILE) members which are broadly proportional to the radiative forcing and global air temperature increase in the SSPs, with a median value of −0.15 ms −1 °C −1 . While weak cyclones are projected to decline in frequency in the NE, intense cyclones and the resulting windstorms and indices of socioeconomic loss do not. Where present, significant trends in these loss indices are positive, and some MPI SMILE members generate future windstorms that are unprecedented in the historical period.

Coburn, Jacob (ORCID:0000000309538117)↗
DOE OSTI2024

Aerosol hygroscopicity over the southeast Atlantic Ocean during the biomass burning season – Part 1: From the perspective of scattering enhancement​​​​​​​

Aerosol hygroscopicity plays a vital role in aerosol radiative forcing. One key parameter describing hygroscopicity is the scattering enhancement factor, f(RH), defined as the ratio of the scattering coefficient at humidified relative humidity (RH) to its dry value. Here, we utilize the f(80 %) from ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) 2016 and 2018 airborne measurements to investigate the hygroscopicity of aerosols, its vertical distribution, its relationship with chemical composition, and its sensitivity to organic aerosol (OA) hygroscopicity over the southeast Atlantic (SEA) Ocean during the biomass burning (BB) season. We found that aerosol hygroscopicity remains steady above 2 km, with a mean f(80 %) of 1.40 ± 0.17. Below 2 km, aerosol hygroscopicity increases with decreasing altitude, with a mean f(80 %) of 1.51 ± 0.22, consistent with higher values of BB aerosol hygroscopicity found in the literature. The hygroscopicity parameter of OA (κ OA ) is retrieved from the Mie model with a mean value of 0.11 ± 0.08, which is in the middle to upper range compared to the literature. Higher OA hygroscopicity is related to aerosols that are more aged, oxidized, and present at lower altitudes. The enhanced biomass burning aerosol (BBA) hygroscopicity at lower altitudes is mainly due to a lower OA fraction, increased sulfate fraction, and greater κ OA at lower altitudes. We propose a parameterization that quantifies f(RH) with chemical composition and κOA based on Mie simulation of internally mixed OA–(NH 4 ) 2 SO 4 –BC mixtures. The good agreement between the predictions and the ORACLES measurements implies that the aerosols in the SEA during the BB season can be largely represented by the OA–(NH 4 ) 2 SO 4 –BC internal mixture with respect to the f(RH) prediction. The sensitivity of f(RH) to κ OA indicates that applying a constant κ OA is only suitable when the OA fraction is low and κ OA shows limited variation. However, in situations deviating these two criteria, κ OA can notably impact scattering coefficients and aerosol radiative effect; therefore, accounting for κ OA variability is recommended.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

NSA Site Science: Use of ARM Observations from Northern Alaska to Evaluate and Improve Prediction Capabilities

The Arctic is warming at a rate nearly double that of the rest of the planet, leading to profound changes in atmospheric, oceanic, and ice processes. The U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility has played a significant role in Arctic research, operating observatories in Alaska's North Slope for over 25 years. These observatories provide a rich, and wide-reaching dataset that offers insight into atmospheric processes in northern Alaska. This report details the results of a nine-year research project (2015–2024) supported by the DOE Atmospheric Systems Research (ASR) program, that leverages data from ARM’s deployment of observing facilities at Utqiaġvik (known as the North Slope of Alaska, or NSA, site) and Oliktok Point, Alaska. The project was conducted in two phases: - Phase 1 (2015–2019): Focused on understanding key atmospheric processes at Oliktok Point, including cloud formation, high-latitude precipitation, aerosol-cloud interactions, and cloud properties. - Phase 2 (2019–2024): Extended the research to the broader North Slope region, using data from both Oliktok Point and Utqiaġvik. Topics explored included surface energy budgets, atmospheric stability, ice nucleation processes, and microphysics in Arctic clouds. The project resulted in numerous research products, including 50 peer-reviewed publications and dissertations, 169 presentations, and 10 data products. These products cover a variety of topics, including: - Cloud Macro- and Microphysical Properties: Arctic clouds play a crucial role in energy transfer, and accurate representation in models is critical. The study explored cloud transitions, ice crystal shapes, and dual-wavelength radar data to understand ice crystal habits and size distributions. - Aerosol Properties and Processes: The team examined aerosol sources in the Arctic, including industrial emissions and natural sources. Observations showed significant spatial gradients in aerosol concentrations due to human activities and wildfire smoke. The influence of aerosols on cloud formation and the surface energy budget was also assessed. - Aerosol-Cloud Interactions: Research revealed that aerosols might suppress cloud ice production, affecting cloud radiative forcing and precipitation. The impact of local industrial emissions on cloud properties was also investigated. - Contextualizing the North Slope of Alaska in the context of the broader Arctic: To understand broader trends, the project evaluated large-scale circulation patterns and the influence of weather systems on the Arctic. Studies indicated that large-scale processes play a significant role in temperature patterns and the timing of snowmelt. - Advancing ARM Observational and Modeling Capabilities: The project developed new radar data products and advanced measurement techniques, including clutter mitigation and drizzle detection. Uncrewed aerial systems (UAS) and tethered balloon systems (TBS) were deployed to gather detailed atmospheric data. Additionally, the project supported 10 early career scientists, providing training and mentorship to undergraduate interns, graduate students, postdoctoral researchers, and early career researchers. These efforts contributed to the advancement of ARM research capabilities and fostered a new generation of scientists skilled in Arctic atmospheric research. Ultimately, this ASR-supported project has provided valuable insights into Arctic atmospheric processes and their broader climate implications. Recommendations for future work include continuing support for long-term observing at Arctic locations to foster additional research, further exploration of aerosol-cloud interactions and the potential impacts of enhanced industrialization of the Arctic, and expanded use of uncrewed systems to gather data in this remote and harsh environment. Additionally, the data products developed by this work, and the data products developed through the ARM infrastructure, leave a treasure-trove of additional information that should be explored for many years to come to gain additional insight into physical processes in the Arctic atmosphere that drive the rapid changes occurring in at high latitudes and their global impact.

58 GEOSCIENCES↗
DOE OSTI2024

Airborne Acoustic Vortex End Effector‐Based Contactless, Multi‐Mode, Programmable Control of Object Surfing

Abstract Tweezers based on optical, electric, magnetic, and acoustic fields have shown great potential for contactless object manipulation. However, current tweezers designed for manipulating millimeter‐sized objects such as droplets, particles, and small animals exhibit limitations in translation resolution, range, and path complexity. Here, a novel acoustic vortex tweezers system is introduced, which leverages a unique airborne acoustic vortex end effector integrated with a three‐degree‐of‐freedom (DoF) linear motion stage, for enabling contactless, multi‐mode, programmable manipulation of millimeter‐sized objects. The acoustic vortex end effector utilizes a cascaded circular acoustic array, which is portable and battery‐powered, to generate an acoustic vortex with a ring‐shaped energy pattern. The vortex applies acoustic radiation forces to trap and spin an object at its center, simultaneously protecting this object by repelling other materials away with its high‐energy ring. Moreover, The vortex tweezers system facilitates contactless, multi‐mode, programmable object surfing, as demonstrated in experiments involving trapping, repelling, and spinning particles, translating particles along complex paths, guiding particles around barriers, translating and rotating droplets containing zebrafish larvae, and merging droplets. With these capabilities, It is anticipated that the tweezers system will become a valuable tool for the automated, contactless handling of droplets, particles, and bio‐samples in biomedical and biochemical research.

Li, Teng↗
DOE OSTI2024

Recalibration of missing low-frequency variability and trends in the North Atlantic Oscillation

Abstract Multi-decadal trends in the wintertime North Atlantic Oscillation (NAO) are under-represented by coupled general circulation models (CGCMs), consistent with a lack of autocorrelation in their NAO index series. This study proposes and tests two simple “reddening” approaches for correcting this problem in simulated indices based on simple one parameter short-term (AR; Auto-Regressive order 1) and long-term (FD; Fractional-Difference) time series filters. Using CGCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6), the FD filter successfully improves the autocorrelation structure of the NAO, and in turn the simulation of extreme trends, while the AR filter is less successful. The 1963–1993 NAO trend is the maximum 31-year trend in the historical period. Raw CGCMs underestimate the likelihood of this trend by a factor of ten but this discrepancy is corrected after reddening. CMIP6 future projections show that long-term (2024–2094) NAO ensemble mean trends systematically increase with the magnitude of radiative forcing: -2.4 to 3.5 hPa/century for low-to-high forcing after reddening (more than double the range using raw output). The related likelihood of future maximum 31year trends comparable to 1963–1993 ranges from 3 to 7% whereas none of these CMIP6 projections simulate this without reddening. Near-term projections of the next 31 years (2024–2054) are less sensitive than long term trends to the future scenario, showing weak-to-no forced trend. However, reddening increases the ensemble range by 74% (to +/-1 standard deviation/decade), which could increase/decrease regional climate change signals in the Northern Hemisphere by magnitudes that are underestimated when using raw CGCM output.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

Dynamic Accounting of Carbon Uptake in the Built Environment

Transforming building materials from net life-cycle CO 2 e emitters to carbon sinks is a key pathway towards decarbonizing the industrial sector. Current life-cycle assessments of materials (particularly “low-carbon” materials) often focus on cradle-to-gate emissions, which can exclude emissions and uptake (i.e., fluxes) later in the materials’ life-cycle. Further, conventional CO 2 e emission characterization disregards the dynamic effects of the timing of emissions and uptake on cumulative radiative forcing from processes like manufacturing, biomass growth, and the decadal carbon storage in long-lived building materials. This work presents a framework to analyze the cradle-to-grave CO 2 e balance of building materials using a time-dependent global warming potential calculation. We apply this framework in the dynamic accounting of carbon uptake in the built environment (D-CUBE) tool and examine two case studies: concrete and cross-laminated timber (CLT). When accounting for dynamic effects, the long storage time of biogenic carbon in CLT results in reduced warming, while the slow rate of uptake via concrete carbonation does not result in significant reductions in global warming. The D-CUBE tool allows for consistent comparisons across materials and emissions mitigation strategies at varying life-cycle stages and can be adapted to other materials or systems with different lifespans and applications. The flexibility of D-CUBE and the ability to identify CO 2 e emission hot-spot life-cycle stages will be instrumental in identifying pathways to achieving net-carbon-sequestering building materials.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Chemical Imaging of Atmospheric Biomass Burning Particles from North American Wildfires

The effects of biomass burning aerosols (BBA) on radiative forcing and cloud formation depend on chemical composition and the internal structures of individual particles within smoke plumes. To improve our understanding of the chemical and physical properties of BBA emitted at different times of the day and their evolution during atmospheric aging, we conducted a study as a part of the Fire Influence on Regional to Global Environments and Air Quality field campaign. Particle samples were collected onboard a research aircraft from smoke plumes from a wildfire in eastern Oregon during late afternoon and nighttime flights on August 28, 2019. A time-resolved aerosol collector was used to collect samples on substrates for offline spectromicroscopic imaging to investigate the single-particle characteristics of BBA particles. Approximately 20,400 individual particles from 10 selected samples were analyzed using computer-controlled scanning electron microscopy coupled with energy-dispersive X-ray microanalysis, revealing their elemental composition, morphology, and viscosity. Elemental microanalysis indicated that aged potassium is likely found in the form of K 2 SO 4 , KNO 3 , and possible K-organic salts. Further chemical speciation and carbon bonding mapping within individual particles were conducted using synchrotron-based scanning transmission X-ray microscopy (STXM) coupled with near edge X-ray absorption fine structure (NEXAFS) spectroscopy. Real-time, water-soluble light absorption measurements were acquired using a particle-into-liquid sampler instrument coupled to a liquid waveguide capillary cell and total organic analyzer. In the late afternoon samples, 65% of the total particle number population consisted entirely of organic components, compared to 46% in the nighttime particles. These differences were attributed to discrepancies in composition at the time of emission and to the daytime condensation and accumulation of photochemically formed secondary organic material on existing BBA particles, a process that halts at night. Microscopy images indicated that particle viscosity was lower in the nighttime particles (<10 1 Pa·s), likely due to increased relative humidity and a higher contribution from hygroscopic inorganic components. The chemical heterogeneity of individual particles was quantified using STXM-derived mixing state parameters. The nature of carbon bonding within individual particles was inferred from the extent of carbon sp 2 hybridization derived from NEXAFS spectra. Average percentages of sp 2 hybridization range between 40% and 60%, with no noticeable differences between late afternoon and nighttime flights. These findings were compared with the online optical properties of both late afternoon and nighttime smoke plumes, providing valuable insights into the complex relationship between chemical composition and optical properties of BBA particles at different times of the day.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Data Imbalance, Uncertainty Quantification, and Transfer Learning in Data‐Driven Parameterizations: Lessons From the Emulation of Gravity Wave Momentum Transport in WACCM

Abstract Neural networks (NNs) are increasingly used for data‐driven subgrid‐scale parameterizations in weather and climate models. While NNs are powerful tools for learning complex non‐linear relationships from data, there are several challenges in using them for parameterizations. Three of these challenges are (a) data imbalance related to learning rare, often large‐amplitude, samples; (b) uncertainty quantification (UQ) of the predictions to provide an accuracy indicator; and (c) generalization to other climates, for example, those with different radiative forcings. Here, we examine the performance of methods for addressing these challenges using NN‐based emulators of the Whole Atmosphere Community Climate Model (WACCM) physics‐based gravity wave (GW) parameterizations as a test case. WACCM has complex, state‐of‐the‐art parameterizations for orography‐, convection‐, and front‐driven GWs. Convection‐ and orography‐driven GWs have significant data imbalance due to the absence of convection or orography in most grid points. We address data imbalance using resampling and/or weighted loss functions, enabling the successful emulation of parameterizations for all three sources. We demonstrate that three UQ methods (Bayesian NNs, variational auto‐encoders, and dropouts) provide ensemble spreads that correspond to accuracy during testing, offering criteria for identifying when an NN gives inaccurate predictions. Finally, we show that the accuracy of these NNs decreases for a warmer climate (4 × CO 2 ). However, their performance is significantly improved by applying transfer learning, for example, re‐training only one layer using ∼1% new data from the warmer climate. The findings of this study offer insights for developing reliable and generalizable data‐driven parameterizations for various processes, including (but not limited to) GWs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

DiffESM: Conditional Emulation of Temperature and Precipitation in Earth System Models With 3D Diffusion Models

Earth system models (ESMs) are essential for understanding the interaction between human activities and the Earth's climate. However, the computational demands of ESMs often limit the number of simulations that can be run, hindering the robust analysis of risks associated with extreme weather events. While low-cost climate emulators have emerged as an alternative to emulate ESMs and enable rapid analysis of future climate, many of these emulators only provide output on at most a monthly frequency. This temporal resolution is insufficient for analyzing events that require daily characterization, such as heat waves or heavy precipitation. We propose using diffusion models, a class of generative deep learning models, to effectively downscale ESM output from a monthly to a daily frequency. Trained on a handful of ESM realizations, reflecting a wide range of radiative forcings, our DiffESM model takes monthly mean precipitation or temperature as input, and is capable of producing daily values with statistical characteristics close to ESM output. Combined with a low-cost emulator providing monthly means, this approach requires only a small fraction of the computational resources needed to run a large ensemble. We evaluate model behavior using a number of extreme metrics, showing that DiffESM closely matches the spatio-temporal behavior of the ESM output it emulates in terms of the frequency and spatial characteristics of phenomena such as heat waves, dry spells, or rainfall intensity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

What Controls Crystal Diversity and Microphysical Variability in Cirrus Clouds?

Abstract Variability of ice microphysical properties like crystal size and density in cirrus clouds is important for climate through its impact on radiative forcing, but challenging to represent in models. For the first time, recent laboratory experiments of particle growth (tied to crystal morphology via deposition density) are combined with a state‐of‐the‐art Lagrangian particle‐based microphysics model in large‐eddy simulations to examine sources of microphysical variability in cirrus. Simulated particle size distributions compare well against balloon‐borne observations. Overall, microphysical variability is dominated by variability in the particles' thermodynamic histories. However, diversity in crystal morphology notably increases spatial variability of mean particle size and density, especially at mid‐levels in the cloud. Little correlation between instantaneous crystal properties and supersaturation occurs even though the modeled particle morphology is directly tied to supersaturation based on laboratory measurements. Thus, the individual thermodynamic paths of each particle, not the instantaneous conditions, control the evolution of particle properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Future Anthropogenic Land Use Change Impacts on Carbonaceous Aerosol and Implications for Climate and Air Quality

Future anthropogenic land use change (LUC) may alter atmospheric carbonaceous aerosol (black carbon and organic aerosol) burden by perturbing biogenic and fire emissions. However, there has been little investigation of this effect. We examine the global evolution of future carbonaceous aerosol under the Shared Socioeconomic Pathways projected reforestation and deforestation scenarios using the CESM2 model from present‐day to 2100. Compared to present‐day, the change in future biogenic volatile organic compounds emission follows changes in forest coverage, while fire emissions decrease in both projections, driven by trends in deforestation fires. The associated carbonaceous aerosol burden change produces moderate aerosol direct radiative forcing (−0.021 to +0.034 W/m 2 ) and modest mean reduction in PM 2.5 exposure (−0.11 μg/m 3 to −0.23 μg/m 3 ) in both scenarios. We find that future anthropogenic LUC may be more important in determining atmospheric carbonaceous aerosol burden than direct anthropogenic emissions, highlighting the importance of further constraining the impact of LUC.>

anthropogenic land use change↗
DOE OSTI2025

Subsurface Cooling and Sea Surface Temperature Pattern Formation Over the Equatorial Pacific

Abstract The equatorial cold tongue region has not warmed up in response to historical radiative forcing in the real world, contrary to the strong warming often simulated by climate models. Here we demonstrate that climate models fail to represent one or both of the key processes driving observed sea surface temperature (SST) pattern formation: a realistic surface wind stress pattern shaping subsurface cooling through wind‐driven circulation changes, and effective connectivity between subsurface and surface temperatures via upwelling and mixing. Consequently, none of the models approximate the observed lack of cold tongue SST warming and strengthening of zonal SST gradient across the equatorial Pacific. Furthermore, those that come closest achieve this due to interhemispheric warming differences rather than equatorial dynamics as observed. Addressing different origins of subsurface cooling in observations and simulations, and how they connect to SST, will lead to improved understanding of tropical Pacific SST changes to date and how they will evolve in the future.

Jiang, Feng [Lamont‐Doherty Earth Observatory Colu↗