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At least 127 records · Page 7

Tracking transient temperatures with liquid crystals

The theoretical basis of the use of the liquid crystal technique to obtain transient thermal data is discussed. Results of calibrations of liquid crystal temperature sensors are given. The effects of crystal aging, lighting effects, observer bias, etc., on accuracy are discussed. The sensitivity of liquid crystal tapes as sensors of dynamic temperature changes is quite high. The accuracy of the technique is determined primarily by the type of calibration apparatus used.

Grodzka, P. G.↗

High Temperature Propulsion System Structural Seals for Future Space Launch Vehicles

High temperature, dynamic structural seals are required in advanced hypersonic engines to seal the perimeters of movable engine ramps for efficient, safe operation in high heat flux environments at temperatures from 2000 to 2500 F. NASA GRC became involved in the development of high temperature structural seals in the late 1980 s and early 1990 s during the National Aerospace Plane (NASP) program. Researchers at GRC carried out an in-house program to develop seals for the NASP hypersonic engine and oversaw industry efforts for airframe and propulsion system seal development for this vehicle. The figure shows one of the seal locations in the NASP engine. Seals were needed along the edges of movable panels in the engine to seal gaps between the panels and adjacent engine sidewalls. Seals developed during the NASP program met many requirements but fell short of leakage, durability, and resiliency goals. Due to program termination the seals could not be adequately matured. To overcome these shortfalls, GRC is currently developing advanced seals and seal preloading devices for the hypersonic engines of future space vehicles as part of NASA s Next Generation Launch Technology (NGLT) program.

Dunlap, Patrick H., Jr.↗

Evaluating the effects of heatwave events on hydrological processes in the contiguous United States (2003–2022)

Extreme heat and drought conditions are affecting water availability in many regions worldwide, leading to negative impacts on human societies, agriculture, and ecosystems. However, current research lacks comprehensive spatiotemporal analysis examining the interplay between multiple hydrological factors and heatwave events, especially in the context of climate change. This research broadly pertains to understanding the dynamics of hydrological factors and their potential responses to heatwave during warm seasons across the contiguous United States for the period from 2003 to 2022. Utilizing data from the Global Land Data Assimilation System (GLDAS), we analyzed surface runoff, evapotranspiration (ET), precipitation, Groundwater Storage (GWS), Root Zone Soil Moisture (RZSM), and Total Water Storage (TWS) to discern annual patterns and the impacts of heatwave. Further, the spatial patterns of heatwave highlighted a higher occurrence in the western, central, and northeastern U.S., with longer average durations in the western and south-central regions. These events are predominantly dry, characterized by low Relative Humidity (RH), except in the southeastern U.S., where heatwave coincide with high RH levels. Post-heatwave analysis indicated a reduction in GWS, TWS, RZSM, and ET, alongside an increase in surface runoff, RH, and precipitation. An in-depth examination of rainfall and temperature dynamics during heatwave revealed weak correlations between rainfall and temperature, as well as between rainfall and heatwave duration, highlighting the complex nature of these interactions. The study also found an enhanced probability of rainfall following heatwave, particularly in the eastern regions, drawing attention to the potential for increased flood risks post-heatwave. Our findings contribute to the growing body of knowledge on the impacts of heatwave on hydrological factors, providing valuable insights for climate change adaptation and water resource management strategies.

54 ENVIRONMENTAL SCIENCES↗

Designing Stress-Adaptive Dense Suspensions Using Dynamic Covalent Chemistry

The non-Newtonian behaviors of dense suspensions are central to their use in technological and industrial applications and arise from a network of particle–particle contacts that dynamically adapt to imposed shear. Reported herein are studies aimed at exploring how dynamic covalent chemistry between particles and the polymeric solvent can be used to tailor such stress-adaptive contact networks, leading to their unusual rheological behaviors. Specifically, a room temperature dynamic thia-Michael bond is employed to rationally tune the equilibrium constant (K eq ) of the polymeric solvent to the particle interface. It is demonstrated that low Keq leads to shear thinning, while high K eq produces antithixotropy, a rare phenomenon where the viscosity increases with shearing time. It is proposed that an increase in K eq increases the polymer graft density at the particle surface and that antithixotropy primarily arises from partial debonding of the polymeric graft/solvent from the particle surface and the formation of polymer bridges between particles. Thus, the implementation of dynamic covalent chemistry provides a new molecular handle with which to tailor the macroscopic rheology of suspensions by introducing programmable time dependence. These studies open the door to energy-absorbing materials that not only sense mechanical inputs and adjust their dissipation as a function of time or shear rate but also can switch between these two modalities on demand.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deep Learning Advances Arctic River Water Temperature Predictions

The accelerated warming in the Arctic poses serious risks to freshwater ecosystems by altering streamflow and river thermal regimes. However, limited research on Arctic River water temperatures exists due to data scarcity and the absence of robust methodologies, which often focus on large, major river basins. To address this, we leveraged the newly released, extensive AKTEMP data set and advanced machine learning techniques to develop a Long Short-Term Memory (LSTM) model. By incorporating ERA5-Land reanalysis data and integrating physical understanding into data-driven processes, our model advanced river water temperature predictions in ungauged, snow- and permafrost-affected basins in Alaska. Our model outperformed existing approaches in high-latitude regions, achieving a median Nash-Sutcliffe Efficiency of 0.95 and root mean squared error of 1.0°C. The LSTM model learned air temperature, soil temperature, solar radiation, and thermal radiation—factors associated with energy balance—were the most important drivers of river temperature dynamics. Soil moisture and snow water equivalent were highlighted as critical factors representing key processes such as thawing, melting, and groundwater contributions. Glaciers and permafrost were also identified as important covariates, particularly in seasonal river water temperature predictions. Our LSTM model successfully captured the complex relationships between hydrometeorological factors and river water temperatures across varying timescales and hydrological conditions. This scalable and transferable approach can be potentially applied across the Arctic, offering valuable insights for future conservation and management efforts.

54 ENVIRONMENTAL SCIENCES↗

Continuous snow depth, ground interface temperature and shallow soil temperature measurements from 2021-10-1 to 2022-6-14, Seward Peninsula, Alaska

The dataset contains co-located snow depth, ground interface temperature, and shallow soil temperature measured at 98 discrete locations in a watershed located along the Nome-Teller road at mile marker 27 (referred to as T27), and at 53 discrete locations on a hillslope located along the Kougarok road at mile marker 64 (referred to as K64), in Seward Peninsula, Alaska. The dataset aims to understand the local heterogeneity of snow depth, snow temperature, and soil temperature dynamics and their interactions in a discontinuous permafrost region. The dataset is also valuable to train and evaluate machine learning and physical models to predict snow depth or the impact of snow depth on ground surface temperature. At each location, temperatures above and below the ground surface were measured by a pair of vertically deployed distributed temperature profiling probes designed based on Dafflon et al (2022). The probes have high precision temperature sensors spaced at 5 or 10 cm. The mean daily snow depth was estimated by identifying the pair of consecutive sensors with maximum drop of daily temperature high-frequency fluctuations. The ground interface temperature was measured by the sensor located 1-5 cm above the ground surface at 15-minute intervals. The shallow soil temperature was measured by the sensor located 1-5 cm below the ground surface at 15-minute intervals. The dataset includes a description of the probe locations in the "Probe_locations_*.csv" file and the 3 data files (Snow_depths_*.csv, Ground_interface_temperatures_*.csv, Shallow_soil_temperatures_*.csv). * is either T27 or K64, which are the two study sites. In each data file, each column corresponds to a measurement location. Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in xxxx_flmd.csv. A more detailed description of data processing, along with an updated dataset incorporating multiple seasons and improved snow depth estimation is available at https://doi.org/10.15485/2480365 (Wang et al., 2025a, Wang et al., 2025b).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Static and Dynamic Correlations in Water: Comparison of Classical Ab Initio Molecular Dynamics at Elevated Temperature with Path Integral Simulations at Ambient Temperature

It is a common practice in ab initio molecular dynamics (AIMD) simulations of water to use an elevated temperature to overcome the overstructuring and slow diffusion predicted by most current density functional theory (DFT) models. The simulation results obtained in this distinct thermodynamic state are then compared with experimental data at ambient temperature based on the rationale that a higher temperature effectively recovers nuclear quantum effects (NQEs) that are missing in the classical AIMD simulations. In this work, we systematically examine the foundation of this assumption for several DFT models as well as for the many-body MB-pol model. Here, we find for the cases studied that a higher temperature does not correctly mimic NQEs at room temperature, which is especially manifest in significantly different three-molecule correlations as well as hydrogen bond dynamics. In many of these cases, the effects of NQEs are the opposite of the effects of carrying out the simulations at an elevated temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The CIRS Investigation on Cassini after Six Years at Saturn

The CIRS investigation designed to provide: 1) infrared spectroscopy of thermal emission from atmospheres, rings, and surfaces in 10 +/- 1450 cm(exp -1) (1000 +/- 7 micron) region; 2) global mapping in atmospheres of three dimensional and temporal variation of gas composition, temperatures, dynamics, and aerosols and clouds; and 3) mapping of rings and icy satellite surfaces for composition and thermal properties. Topics include: optical and mechanical layouts, instrument description, preparation for launch, Saturn's rings in the light spectrum, Saturn brightness temperature spectrum, and views of Saturn's surface, rings, and Saturn's moons and their atmospheres.

Jennings, Donald↗

Quantifying Variability and Controls of Riverine Dissolved Organic Carbon Exported to Arctic Coastal Margins of North America (Final Report)

This project involved implementation and application of a coupled permafrost hydrology and dissolved organic carbon process models to investigate how spatial and seasonal variations in terrestrial hydrology and soil freeze/thaw dynamics influence the mobilization, loading, and export of organic carbon to the stream network for selected arctic basins across northern Alaska and northwest Canada. The model simulations were constrained by detailed observations of in- stream chemistry, soil active layer profile moisture and temperature dynamics, streamflow, soil carbon inventories and satellite microwave remote sensing based assessments of surface soil freeze-thaw dynamics. We developed and applied the numerical modeling and data analysis, incorporating observed data for calibration and validation, in order to investigate the terrestrial hydrology, permafrost dynamics, and associated DOC production and loading to rivers across a region encompassing watersheds draining to the coast. The project produced six publications and three datasets archived in public repositories.

54 ENVIRONMENTAL SCIENCES↗

Impact of Different Thermal Gradients on the Dynamics of Cylindrical Lithium-ion Cells Subject to Accelerated Aging and on Module Performance

This study investigates the impacts of applying different thermal gradient patterns to cylindrical lithium-ion cells in a module on cell dynamics (temperatures, current flows, state of charge), module performance (evolution of resistance, capacity, and energy versus cycle number), and module lifetime. The thermal gradients were generated using cooling plates (CPs) with three different flow-field designs, namely, straight, perpendicular, and U-turn. The study uses computational fluid dynamics (CFD), the pseudo-two-dimensional (P2D) battery model, capacity loss and increased impedance due to the growth of a solid-electrolyte-interphase, and the electric current distribution from module terminals to cells that depends on the series-parallel electrical connections among the cells. The impact of the thermal gradient (resulting from the CP designs) on the variability in resistance, current, state of charge, and voltage among the cells was analyzed and linked to differences in the module's performance. Applying a thermal gradient to parallel-connected strings of series-connected cells led to variation in the current through each parallel string and an imbalance in the voltage of series-connected cells. Module performance is poorer when the thermal gradient causes a voltage imbalance than when it causes a current imbalance. Module performance becomes the worst when both current variation and voltage imbalance happen together. For instance, the module's lifetime (estimated as reaching 80% of its initial capacity) varied by 5% to 17.5%, depending on the magnitude and pattern of the imposed thermal gradient. As the relative orientation between thermal gradients and cells' electrical connectivity influences the module's performance, appropriate consideration should be given to the choice of the CP, especially if large thermal gradients are allowed.

Battery thermal management↗

Monitoring Sulfuric Acid and Temperature Using Raman Spectroscopy and Multivariate Chemometrics

Multivariate regression models were optimized for the quantification of sulfuric acid (H 2 SO 4 ) [0–8 M] and temperature (20 °C–80 °C) in the presence of ammonium sulfate ((NH 4 ) 2 SO 4 [0–0.6 M]) using Raman spectroscopy. Optical vibrational spectroscopy is a useful nondestructive technique for the in situ analysis of complex chemical systems notoriously difficult to monitor in situ and in real-time. Multivariate analysis, a chemometrics method, can be paired with these nondestructive optical methods for determining analyte concentration and speciation in complex solutions, such as dissociated species in polyprotic acids, e.g., H 2 SO 4 . The effect of temperature is often overlooked although it can have a major influence on speciation and the corresponding Raman spectra. Here, in this study, partial least squares regression models were optimized for the quantification of H 2 SO 4 and its two deprotonated forms as a function of temperature. Measuring bisulfate as a function of temperature is particularly challenging owing to changes in the second dissociation constant. A designed training set effectively minimized the sample set size and trained a robust predictive model with percent root mean square error of <3% for H 2 SO 4 . The practical strategy employed here was demonstrated to be effective for building chemometric models that directly account for dynamic temperatures with static samples and is shown to be amenable to flow cell analysis applications with a simple calibration transfer for process monitoring applications.

D-optimal design↗

Projecting Permafrost Thaw of Sub-Arctic Tundra With a Thermodynamic Model Calibrated to Site Measurements

Northern circumpolar permafrost thaw affects global carbon cycling, as large amounts of stored soil carbon becomes accessible to microbial breakdown under a warming climate. The magnitude of carbon release is linked to the extent of permafrost thaw, which is locally variable and controlled by soil thermodynamics. Soil thermodynamic properties, such as thermal diffusivity, govern the reactivity of the soil-atmosphere thermal gradient, and are controlled by soil composition and drainage. In order to project permafrost thaw for an Alaskan tundra experimental site, we used seven years of site data to calibrate a soil thermodynamic model using a data assimilation technique. The model reproduced seasonal and interannual temperature dynamics for shallow (5–40 cm) and deep soil layers (2–4 m), and simulations of seasonal thaw depth closely matched observed data. The model was then used to project permafrost thaw at the site to the year 2100 using climate forcing data for three future climate scenarios (RCP 4.5, 6.0, and 8.5). Minimal permafrost thawing occurred until mean annual air temperatures rose above the freezing point, after which we measured over a 1 m increase in thaw depth for every 1 °C rise in mean annual air temperature. Under no projected warming scenario was permafrost remaining in the upper 3 m of soil by 2100. We demonstrated an effective data assimilation method that optimizes parameterization of a soil thermodynamic model. The sensitivity of local permafrost to climate warming illustrates the vulnerability of sub-Arctic tundra ecosystems to significant and rapid soil thawing.

54 ENVIRONMENTAL SCIENCES↗

Characterization and Correction of Aquarius Long Term Calibration Drift Using On-Earth Brightness Temperature Refernces

The Aquarius/SAC-D mission was launched on June 10, 2011 from Vandenberg Air Force Base. Aquarius consists of an L-band radiometer and scatterometer intended to provide global maps of sea surface salinity. One of the main mission objectives is to provide monthly global salinity maps for climate studies of ocean circulation, surface evaporation and precipitation, air/sea interactions and other processes. Therefore, it is critical that any spatial or temporal systematic biases be characterized and corrected. One of the main mission requirements is to measure salinity with an accuracy of 0.2 psu on montly time scales which requires a brightness temperature stability of about 0.1K, which is a challenging requirement for the radiometer. A secondary use of the Aquarius data is for soil moisture applications, which requires brightness temperature stability at the warmer end of the brightness temperature dynamic range. Soon after launch, time variable drifts were observed in the Aquarius data compared to in-situ data from ARGO and models for the ocean surface salinity. These drifts could arise from a number of sources, including the various components of the retrieval algorithm, such as the correction for direct and reflected galactic emission, or from the instrument brightness temperature calibration. If arising from the brightness temperature calibration, they could have gain and offset components. It is critical that the nature of the drifts be understood before a suitable correction can be implemented. This paper describes the approach that was used to detect and characterize the components of the drift that were in the brightness temperature calibration using on-Earth reference targets that were independent of the ocean model.

Aquarius↗

Thermomechanical deformation testing and modeling in the presence of metallurgical instabilities

A number of viscoplastic constitutive models were developed to describe deformation behavior under complex combinations of thermal and mechanical loading. Questions remain, however, regarding the validity of procedures used to characterize these models for specific structural alloys. One area of concern is that the majority of experimental data available for this purpose are determined under isothermal conditions. This experimental study is aimed at determining whether viscoplastic constitutive theories characterized using an isothermal data base can adequately model material response under the complex thermomechanical loading conditions typical of power generation service. The approach adopted was to conduct a series of carefully controlled thermomechanical experiments on a nickel-based superalloy, Hastelloy Alloy X. Previous investigations had shown that this material experiences metallurgical instabilities leading to complex hardening behavior, termed dynamic strain aging. Investigating this phenomenon under full thermomechanical conditions leads to a number of challenging experimental difficulties which up to the present work were unresolved. To correct this situation, a number of advances were made in thermomechanical testing techniques. Advanced methods for dynamic temperature gradient control, phasing control and thermal strain compensation were developed and incorporated into real time test control software. These advances allowed the thermomechanical data to be analyzed with minimal experimental uncertainty. The thermomechanical results were evaluated on both a phenomenological and microstructural basis. Phenomenological results revealed that the thermomechanical hardening trends were not bounded by those displayed under isothermal conditions. For the case of Hastelloy Alloy X (and similar dynamic strain aging materials), this strongly suggests that some form of thermomechanical testing is necessary when characterizing a thermoviscoplastic deformation model. Transmission electron microscopy was used to study the microstructural physics, and analyze the unique phenomenological behavior.

Castelli, Michael G.↗

Rise and fall of Mott insulating gaps in YNiO 3 paramagnets as a reflection of symmetry breaking and remaking

The YNiO 3 nickelate is a paradigm d-electron oxide that manifests the intriguing temperature-mediated sequence of three phases transitions from (i) magnetically ordered insulator to (ii) paramagnetic (PM) insulator and then to (iii) PM metal. Such phenomena raised the question of the nature of the association of magnetism and structural symmetry breaking with the appearance in (i) and (ii) and disappearance in (iii) of insulating band gaps. It is demonstrated here that first-principles mean-field–like density-functional theory (DFT), driven by molecular dynamics temperature evolution, can describe not only the origin of the magnetically long-range ordered insulating phase (i), but also the creation of an insulating paramagnet (ii) that lacks spin- long-range order, and of a metallic paramagnet (iii) as temperature rises. This approach provides the patterns of structural and magnetic symmetry breaking at different temperatures, in parallel with band gaps obtained when the evolving geometries are used as input to DFT electronic band-structure calculations. This disentangles the complex interplay among spin, charge, and orbital degrees of freedom. Analysis shows that the success in describing the rise and fall of the insulating band gaps along the phase transition sequence is enabled by allowing sufficient flexibility in describing diverse local structural and magnetic motifs as input to DFT. This entails the use of sufficiently large supercells that allow expressing structural disproportionation of octahedra, as well as a description of PM phases as a distribution of local magnetic moments (rather than using a single averaged moment). It appears that the historic dismissal of mean-field–like DFT as being unable to describe such Mott-like transitions was premature, as it was based on consideration of averaged crystallographic unit cells, a description that washes out local symmetry-breaking motifs. The magnetically ordered insulating YNiO 3 phase (i) and the PM insulating phase (ii) result in DFT from allowing symmetry breaking, evident already by considering the athermal internal energy. In contrast, the PM metallic phase (iii) is formed thermally by smearing out thus weakening symmetry breaking. Analysis of snapshots of the different forms of structural vs magnetic symmetry breaking shows that only the loss of the polymorphous distribution of magnetic moments existing in (ii) causes the fall of the band gap, resulting in the metallic state in (iii). Finally, the interesting conclusion is that such a description of the rise [in phases (i) and (ii)] and fall [in phase (iii)] of the insulating gap does not rely on the traditional Mott-like strong correlation understanding, but on breaking and remaking of magnetic and structural symmetries reflected in energy lowering.

36 MATERIALS SCIENCE↗

Computational simulation of acoustic fatigue for hot composite structures

Predictive methods/computer codes for the computational simulation of acoustic fatigue resistance of hot composite structures subjected to acoustic excitation emanating from an adjacent vibrating component are discussed. Select codes developed over the past two decades at the NASA Lewis Research Center are used. The codes include computation of acoustic noise generated from a vibrating component, degradation in material properties of a composite laminate at use temperature, dynamic response of acoustically excited hot multilayered composite structure, degradation in the first ply strength of the excited structure due to acoustic loading, and acoustic fatigue resistance of the excited structure, including the propulsion environment. Effects of the laminate lay-up and environment on the acoustic fatigue life are evaluated. The results show that, by keeping the angled plies on the outer surface of the laminate, a substantial increase in the acoustic fatigue life is obtained. The effect of environment (temperature and moisture) is to relieve the residual stresses leading to an increase in the acoustic fatigue life of the excited panel.

Singhal, Surendra N.↗

In Situ Probe Science at Saturn

A fundamental goal of solar system exploration is to understand the origin of the solar sys-tem, the initial stages, conditions, and processes by which the solar system formed, how the formation pro-cess was initiated, and the nature of the interstellar seed material from which the solar system was born. Key to understanding solar system formation and subsequent dynamical and chemical evolution is the origin and evolution of the giant planets and their atmospheres. Several theories have been put forward to explain the process of solar system formation, and the origin and evolution of the giant planets and their atmospheres. Each theory offers quantifiable predictions of the abundances of noble gases He, Ne, Ar, Kr, and Xe, and abundances of key isotopic ratios 4He3He, DH, 15N14N, 18O16O, and 13C12C. Detection of certain dis-equilibrium species, diagnostic of deeper internal pro-cesses and dynamics of the atmosphere, would also help discriminate between competing theories. Measurements of the critical abundance profiles of these key constituents into the deeper well-mixed at-mosphere must be complemented by measurements of the profiles of atmospheric structure and dynamics at high vertical resolution and also require in situ explora-tion. The atmospheres of the giant planets can also serve as laboratories to better understand the atmospheric chem-istries, dynamics, processes, and climates on all planets including Earth, and offer a context and provide a ground truth for exoplanets and exoplanetary systems. Additionally, Giant planets have long been thought to play a critical role in the development of potentially habitable planetary systems. In the context of giant planet science provided by the Galileo, Juno, and Cassini missions to Jupiter and Sat-urn, a small, relatively shallow Saturn probe capable of measuring abundances and isotopic ratios of key at-mospheric constituents, and atmospheric structure in-cluding pressures, temperatures, dynamics, and cloud locations and properties not accessible by remote sens-ing can serve to test competing theories of solar system and giant planet origin, chemical, and dynamical evolution.

Interstellar↗

Hunga Tonga–Hunga Ha′apai Volcano Impact Model Observation Comparison (HTHH-MOC) project: experiment protocol and model descriptions

The 2022 Hunga volcanic eruption injected a significant amount of water vapor and a moderate amount of sulfur dioxide into the stratosphere, causing observable responses in the climate system. We have developed a model–observation comparison project to investigate the evolution of volcanic water and aerosols and their impacts on atmospheric dynamics, chemistry, and climate, using several state-of-the-art chemistry climate models. The project goals are (1) to evaluate the current chemistry–climate models to quantify their performance in comparison to observations and (2) to understand atmospheric responses in the Earth system after this exceptional event and investigate the potential impacts in the projected future. To achieve these goals, we designed specific experiments for direct comparisons to observations, for example from balloons and the Microwave Limb Sounder satellite instrument. Experiment 1 consists of two sets of free-running ensemble experiments from 2022 to 2031: one with fixed sea-surface temperatures and sea ice and one with coupled ocean. These experiments will help to understand the long-term evolution of water vapor and aerosols; quantify HTHH effects on stratospheric and mesospheric temperatures, dynamics, and transport; understand the impact of dynamic changes on ozone chemistry; quantify the net radiative forcings; and evaluate any surface climate impact. Experiment 2 is a nudged-run experiment from 2022 to 2023 using observed meteorology. To allow participation of more climate models with varying complexities of aerosol simulation, we include two sets of simulations in Experiment 2: Experiment 2a is designed for models with internally generated aerosol, while Experiment 2b is designed for models using prescribed aerosol surface area density. This experiment will help to analyze H 2 O and aerosol evolution, quantify the net radiative forcings, understand the impacts on mid-latitude and polar O 3 chemistry, and allow close comparisons with observations.

Zhu, Yunqian [Univ. of Colorado, Boulder, CO (Unit↗