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DOE OSTI2022

Reconstructing High Resolution ESM Data Through a Novel Fast Super Resolution Convolutional Neural Network (FSRCNN)

In this work, we present the first application of a fast super resolution convolutional neural network (FSRCNN) based approach for downscaling earth system model (ESM) simulations. Unlike other SR approaches, FSRCNN uses the same input feature dimensions as the low resolution input. This allows it to have smaller convolution layers, avoiding over-smoothing, and reducing computational costs. We adapt the FSRCNN to improve reconstruction on ESM data, we term the FSRCNN-ESM. We use high-resolution (~0.25°) monthly averaged model output of five surface variables over North America from the US Department of Energy's Energy Exascale Earth System Model's control simulation. These high-resolution and corresponding coarsened low-resolution (~1°) pairs of images are used to train the FSRCNN-ESM and evaluate its use as a downscaling approach. We find that FSRCNN-ESM outperforms FSRCNN and other super-resolution methods in reconstructing high resolution images producing finer spatial scale features with better accuracy for surface temperature, surface radiative fluxes, and precipitation.

58 GEOSCIENCES↗

DOE OSTI2023

Dual origin of ferropericlase inclusions within super-deep diamonds

Ferropericlase [(Mg,Fe)O] is one of the major constituents of Earth's lower mantle and the most abundant mineral inclusion in sub-lithospheric diamonds. Although a lower mantle origin for ferropericlase inclusions has often been suggested, some studies have proposed that many of these inclusions may instead form at much shallower depths, in the deep upper mantle or transition zone. No straightforward method exists to discriminate ferropericlase of lower-mantle origin without characteristic mineral associations, such as co-existing former bridgmanite. To explore ferropericlase-diamond growth relationships, we have investigated the crystallographic orientation relationships (CORs), determined by single-crystal X-ray diffraction, between 57 ferropericlase inclusions and 37 diamonds from Juina (Brazil) and Kankan (Guinea). We show that ferropericlase inclusions can develop specific (16 inclusions in 12 diamonds), rotational statistical (9 inclusions in 7 diamonds) and random (32 inclusions in 25 diamond) CORs with respect to their diamond hosts. All measured inclusions showing a specific COR were found to be Fe-rich (X FeO > 0.30). Coexistence of non-randomly and randomly oriented ferropericlase inclusions within the same diamond indicates that their CORs may be variably affected by local growth conditions. However, the occurrence of specific CORs only for Fe-rich inclusions indicates that Fe-rich ferropericlases have a distinct genesis and are syngenetic with their host diamonds. In conclusion, this result provides strong support for a dual origin for ferropericlase in Earth's mantle, with Fe-rich compositions likely indicating redox growth in the upper mantle, while more Mg-rich compositions with random COR mostly representing ambient lower mantle trapped as protogenetic inclusions.

58 GEOSCIENCES↗

DOE OSTI2024

Dark matter raining on DUNE and other large volume detectors

Direct detection is a powerful means of searching for particle physics evidence of dark matter (DM) heavier than about a GeV with o(kiloton) volume, low-threshold detectors. In many scenarios, some fraction of the DM may be boosted to large velocities enhancing and generally modifying possible detection signatures. We investigate the scenario where 100% of the DM is boosted at the Earth due to new attractive long-range forces. This leads to two main improvements in detection capabilities: (1) the large boost allows for detectable signatures of DM well below a GeV at large-volume neutrino detectors, such as DUNE, Super-K, Hyper-K, and JUNO, as possible DM detectors, and (2) the flux at the Earth’s surface is enhanced by a focusing effect. In addition, the model leads to a significant anisotropy in the signal with the DM flowing dominantly vertically at the Earth’s surface instead of the typical approximately isotropic DM signal. We develop the theory behind this model and also calculate realistic constraints using a detailed GENIE simulation of the signal inside detectors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

ESM data downscaling: a comparison of super-resolution deep learning models

Abstract Climate projections at fine spatial resolutions are required to conduct accurate risk assessment for critical infrastructure and design adaptation planning. Generating these projections using advanced Earth system models (ESM) requires significant computational resources. To address this issue, various statistical downscaling techniques have been introduced to generate fine-resolution data from coarse-resolution simulations. In this study, we evaluate and compare five deep learning-based downscaling techniques, namely, super-resolution convolutional neural networks, fast super-resolution convolutional neural network ESM, efficient sub-pixel convolutional neural network, enhanced deep residual network (EDRN), and super-resolution generative adversarial network (SRGAN). These techniques are applied to a dataset generated by the Energy Exascale Earth System Model (E3SM), focusing on key surface variables such as surface temperature, shortwave heat flux, and longwave heat flux. Models are trained and validated using paired fine-resolution (0.25 $$^{\circ }$$ ∘ ) and coarse-resolution (1 $$^{\circ }$$ ∘ ) monthly data obtained from a 9-year simulation. Next, blind testing is performed using monthly data obtained from two different years outside of the training and validation set. To evaluate the efficiency of each technique, different statistical metrics are used, including mean squared error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and learned perceptual image patch similarity (LPIPS). The results show that EDRN outperforms other algorithms in terms of PSNR, SSIM, and MSE, but struggles to capture fine-scale features in the data. In contrast, SRGAN, a generative model that uses perceptual loss, excels in capturing fine details at boundaries and internal structures, resulting in lower LPIPS than other methods.

Pawar, Nikhil M. (ORCID:0000000211613289)↗

DOE OSTI2026

Mobility of heavy rare earth elements in magmatic-hydrothermal systems: Experimental determination of DyPO 4 solubility in supercritical fluids

Dysprosium (Dy) is part of the heavy rare earth elements (REE) and a critical component in the production of high-performance super magnets used in wind turbines, electric vehicles, and other green technologies. The HREE phosphate, xenotime, is commonly associated with hydrothermal systems, where the mobility, fractionation, and deposition of REE are controlled by the stability of aqueous complexes and solubility of REE minerals which depend on temperature, pressure, and fluid composition (salinity, pH, and ligand availability). Here, we conducted a series of synthetic DyPO 4 solubility experiments in NaCl-HCl-bearing aqueous solutions (pH of 2 at 25 °C) from 500 to 700 °C and 1.5 kbar using externally heated pressure vessels. DyPO 4 displays a strong prograde solubility with temperature across all studied fluid salinities (0–0.5 m NaCl). The DyPO₄ solubility isotherms at 500 °C, 600 °C, and 700 °C show a complex relationship with salinity where DyPO₄ solubility is highest (39.2–1552 ppm at 500–700 °C) in 0 m NaCl solutions, decreases strongly (21–331 ppm at 500–700 °C) in the 0.06 m NaCl solutions and remains relatively constant in the 0.25 m (42.8–248 ppm) and 0.5 m NaCl (40.2–124 ppm) solutions. Thermodynamic modeling suggests that pH increases as a function of temperature and salinity, and controls solubility due to the stability of chloride complexes (i.e., DyCl +2 and DyCl 2 + ) at 500–600 °C, transitioning to hydroxyl complexes (i.e., Dy(OH) 3 0 ) dominating at 700 °C and relatively alkaline pH. Comparison with NdPO 4 solubility data indicates that the light REE in monazite is significantly more soluble than the heavy REE in xenotime in saline fluids at high temperature (500–700 °C), implying efficient light/heavy REE fractionation in supercritical fluids. The lower solubility of DyPO 4 relative to NdPO 4 suggests that at high temperatures, acidic (pH 2–4), low-salinity (∼5 wt% NaCl) fluids will favor the precipitation of xenotime over monazite as it will cool from 700 °C to below 500 °C. These observations align with paragenetic mineral assemblages in NYF pegmatites (e.g., Baveno, Italy), where xenotime commonly immobilizes heavy REE during the high-temperature hydrothermal stages.

58 GEOSCIENCES↗

DOE OSTI2024

The Ecosystem as Super-Organ/ism, Revisited: Scaling Hydraulics to Forests under Climate Change

Synopsis Classic debates in community ecology focused on the complexities of considering an ecosystem as a super-organ or organism. New consideration of such perspectives could clarify mechanisms underlying the dynamics of forest carbon dioxide (CO2) uptake and water vapor loss, important for predicting and managing the future of Earth’s ecosystems and climate system. Here, we provide a rubric for considering ecosystem traits as aggregated, systemic, or emergent, i.e., representing the ecosystem as an aggregate of its individuals or as a metaphorical or literal super-organ or organism. We review recent approaches to scaling-up plant water relations (hydraulics) concepts developed for organs and organisms to enable and interpret measurements at ecosystem-level. We focus on three community-scale versions of water relations traits that have potential to provide mechanistic insight into climate change responses of forest CO2 and H2O gas exchange and productivity: leaf water potential (Ψcanopy), pressure volume curves (eco-PV), and hydraulic conductance (Keco). These analyses can reveal additional ecosystem-scale parameters analogous to those typically quantified for leaves or plants (e.g., wilting point and hydraulic vulnerability) that may act as thresholds in forest responses to drought, including growth cessation, mortality, and flammability. We unite these concepts in a novel framework to predict Ψcanopy and its approaching of critical thresholds during drought, using measurements of Keco and eco-PV curves. We thus delineate how the extension of water relations concepts from organ- and organism-scales can reveal the hydraulic constraints on the interaction of vegetation and climate and provide new mechanistic understanding and prediction of forest water use and productivity.

Zoology↗

DOE OSTI2023

Modeling Land-Atmosphere Coupling at Cloud-Resolving Scale Within the Multiple Atmosphere Multiple Land (MAML) Framework in SP-E3SM

Representing subgrid variabilities of land surface processes and their upscaled effects is crucial for global climate modeling. Here, we implement a Multiple Atmosphere Multiple Land (MAML) framework in the superparamaterized version of E3SM (SP32 E3SM) to explicitly simulate the subgrid variabilities of land states and fluxes at cloud-resolving scale and their interactions with atmosphere. Comparing to the standard SP-E3SM in which all the atmospheric columns of the cloud resolving model embedded within the global atmospheric model grid interact with the same land surface (i.e., Multiple Atmosphere Single Land (MASL)), the impact of MAML on the strength of land-atmosphere coupling is limited, partly because the current implementation mainly facilitates one-way coupling between the cloud-resolving model and the land surface model. Despite such limitation, MAML increases the surface latent heat flux at the expense of sensible heat flux, and increases precipitation in India, Amazon, and Central Africa, reducing the model dry bias compared to the standard SP-E3SM. By employing a normalized gross moist stability (NGMS) diagnostic framework, we find that the increase in precipitation minus evaporation (PE) is primarily driven by the change in large-scale moisture convergence, particularly by the increase of water vapor in the lower atmosphere, while the local effect of total surface energy flux plays a minor role in the P-E change. More specifically, MAML changes the surface energy partitioning (evaporative fraction), increases the atmosphere water vapor, and further increases P-E by decreasing the NGMS. Finally, future development in the MAML framework is discussed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

The Asteroid Rotation Period Survey Using the China Near-Earth Object Survey Telescope (CNEOST)

We initiated the bilateral collaboration between the Lulin Observatory and the Purple Mountain Observatory to collect asteroid lightcurves using the Chinese Near-Earth Object Survey Telescope at the Xuyi Observation Station. The primary goal of this collaboration was to discover super-fast rotators (SFRs) and study their physical properties. Two campaigns have been conducted: (a) a survey of ∼45 deg{sup 2} using 8 minute cadence during 2017 February 26–March 2, and (b) a survey of ∼60 deg{sup 2} using 10 minute cadence during 2018 March 9–12. Our samples are mainly main-belt asteroids and some Hildas and Jupiter Trojans. Out of 4522 collected lightcurves, 506 reliable rotation periods were obtained. Among the reliable rotation periods, we found 16 candidates with a possible rotation period of <2.2 hr, in which (134291) 2006 DZ6 shows a very convincing folded lightcurve and the other 15 candidates only have a likely trend. Further confirmation is needed for the rotation periods of these SFR candidates. In addition, (2280) Kunikov seems to have an eclipsing feature on its lightcurve with a relatively long rotation period suggesting that it is likely a fully synchronized binary asteroid. When the preliminary spin-rate distributions were carried out for asteroids using different sizes, no obvious difference was found.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Nucleon Decays into Light New Particles in Neutrino Detectors

Proton and neutron decays into light new particles 𝑋 can drastically change the experimental signatures and benefit from the complementarity of large water-Cherenkov neutrino detectors such as Super- and Hyper-Kamiokande and tracking detectors such as JUNO and DUNE. The proton decays 𝑝 → ℓ + ⁢𝑋 and 𝑝 → 𝜋 + ⁢𝑋 with 𝑚 𝑋 near phase-space closure lead to charged particles below the Cherenkov threshold, rendering them practically invisible in Super- and Hyper-Kamiokande but not in JUNO and DUNE, which are therefore uniquely positioned for these baryon-number-violating signatures despite their smaller size. As an additional signature, such nucleon decays in the Earth can produce a sizable flux of 𝑋 particles in underground detectors. We present a simple model in which nucleons decay into sub-GeV sterile neutrinos that subsequently decay through active-sterile neutrino mixing, with a promisingly large number of events in Super-Kamiokande even in the seesaw-motivated parameter space.

Baryon & lepton number symmetries↗

DOE OSTI2025

Downscaled Earth System Model Data for Resilient Energy System Planning

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Source-encoded waveform inversion in the Northern Hemisphere

SUMMARY We use source-encoded waveform inversion to image Earth’s Northern Hemisphere. The encoding method is based on measurements of Laplace coefficients of stationary wavefields. By assigning to each event a unique frequency, we compute Fréchet derivatives for all events simultaneously based on one ‘super’ forward and one ‘super’ adjoint simulation for a small fraction of the computational cost of classical waveform inversion with the same data set. No cross-talk noise is introduced in the process, and the method does not require all events to be recorded by all stations. Starting from global model GLAD_M25, we performed 100 conjugate gradient iterations using a data set consisting of 786 earthquakes recorded by 9846 stations. Synthetic inversion tests show that we achieve good convergence based on this data set, and we see a consistent misfit reduction during the inversion. The new model, named SE100, has much higher spatial resolution than GLAD_M25, revealing details of the Yellowstone and Iceland hotspots, subduction beneath the Western United States and the upper mantle structure beneath the Arctic Ocean.

Cui, Congyue↗

DOE OSTI2025

Second-generation downscaled earth system model data using generative machine learning

The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. As with the first Sup3rCC version, the data still include temperature, wind speed and direction at multiple heights, pressure, three components of downwelling solar radiation, and relative humidity—all at 4-kilometer (km) hourly resolution over the contiguous United States. This is a 25x spatial enhancement and 24x temporal enhancement of the source 100-km daily-average ESM data. This extension of the Sup3rCC dataset includes data from six ESMs from two shared socioeconomic pathways (SSPs) totaling 400 years of data with multiple future projections of changing meteorological conditions. The scenario selection was based on a structured evaluation of historical ESM skill and comprehensive representation of possible trajectories of future climate change in temperature, humidity, precipitation, solar irradiance, and near-surface wind speeds. The inclusion of multiple future projections is intended to enable users to assess key drivers of un 36 certainty and variability. All data are double-bias corrected, resulting in a product that can be used out-of-the-box for energy system analysis with minimal historical bias. The potential applications of Sup3rCC data extend to various topics in renewable energy resource assessment, energy systems modeling, and grid resilience studies. High-resolution future meteorological projections are critical for evaluating the effects of changing meteorological conditions on renewable energy generation, energy demand, and for optimizing energy storage and grid infrastructure. The 4-km hourly resolution of the downscaled data enables understanding of spatial and temporal variability at the scales necessary for energy system operational planning. In addition, the dataset can support risk assessments by providing detailed information on possible future extreme weather events and long-term meteorological variability at scales relevant to energy infrastructure. By offering an enhanced representation of possible future meteorological conditions, the second-generation Sup3rCC dataset enables more precise modeling of energy resilience and adaptation strategies in response to changing meteorological conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Toward Understanding the Simulated Phase Partitioning of Arctic Single-Layer Mixed-Phase Clouds in E3SM

21 Mixed-phase clouds are widespread in the Arctic and have substantial impacts on the 22 surface energy budget, sea ice extent, and regional climate. Significant changes are found in the 23 modeled phase partitioning of Arctic mixed-phase clouds in the newly developed U.S. 24 Department of Energy (DOE) Energy Exascale Earth System Model (E3SM) Atmosphere Model 25 version 1 (EAMv1) compared to its predecessor (CAM5/EAMv0). The mixed-phase clouds 26 simulated by EAMv1 is overly dominated by super-cool liquid which is often underestimated by 27 CAM5. Compared to CAM5, EAMv1 has made several important changes in its cloud physical 28 parameterizations, including using CLUBB to unify shallow convection, PBL turbulence, and 29 cloud macrophysics, as well as updating the MG two-moment cloud microphysics scheme and 30 using the CNT heterogeneous ice nucleation scheme to replace the Meyers scheme for mixed- 31 phase clouds. To understand which of the newly-implemented physical parameterizations is 32 responsible for the change of modeled mixed-phase cloud phase partitioning in EAMv1, 33 sensitivity tests are conducted by utilizing the short-term hindcast approach and results are 34 compared to the observations from the ARM Mixed-Phase Arctic Cloud Experiment (M-PACE) 35 field campaign. 36 It is found that although each scheme contributes to the decrease of cloud ice water 37 content (IWC) and increase of cloud liquid water content (LWC), only the combined effect of 38 CLUBB and CNT can explain the significant underestimation of IWC. By examining the budgets 39 of cloud microphysical processes, CLUBB is found to play a dominant role due to the fact that 40 CLUBB does not diagnoses cloud ice phase water in its assumed joint PDF method and thus may 41 not provide sufficient cloud ice to initialize ice phase microphysical processes such as the growth 42 of ice crystals through vapor deposition. Although a more effective heterogeneous ice nucleation 43 may alleviate the underestimation of IWC, the ice phase process in CLUBB requires urgent 44 attention in the future model development.

Zhang, Meng↗

DOE OSTI2021

Searching for millicharged particles produced in cosmic-ray air showers

Particles with small electric charges can be produced abundantly in extensive air-showers, generated from the collisions of cosmic rays with the earth's atmosphere. These millicharged particles can leave their imprints at underground experiments via scattering-off electrons. In this report, we present updated constraints using low energy data from Super-Kamiokande, and the XENON1T experiment. Moreover, we provide new sensitivity projections for millicharged particles in the future JUNO neutrino observatory, and discuss different search strategies including both, single-scattering events, and multiple-energy-deposition traces.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Flavor triangle of the diffuse supernova neutrino background

Although Galactic core-collapse supernovae (SNe) only happen a few times per century, every hour a vast number of explosions happen in the whole universe, emitting energy in the form of neutrinos, resulting in the diffuse supernova neutrino background (DSNB). The DSNB has not yet been detected, but Super-Kamiokande doped with gadolinium is expected to yield the first statistically significant observation within the next several years. Since the neutrinos produced at the core collapse undergo mixing during their propagation to Earth, the flavor content at detection is a test of oscillation physics. In this paper, we estimate the expected DSNB data at the DUNE, Hyper-K and JUNO experiments which when combined are sensitive to all different neutrino flavors. Here, we determine how well the flavor content of the DSNB will be reconstructed in the future, for a Mikheyev-Smirnov-Wolfenstein (MSW) scenario as well as a neutrino decay scenario. A large fraction of the flavor space will be excluded, but the heavy-lepton neutrino flux remains a challenge.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

On the Short-scale Spatial Variability of Electron Inflows in Electron-only Magnetic Reconnection in the Turbulent Magnetosheath Observed by MMS

We investigate the detailed properties of electron inflow in an electron-only reconnection event observed by the four Magnetospheric Multiscale (MMS) spacecraft in the Earth's turbulent magnetosheath downstream of the quasi-parallel bow shock. The lack of ion coupling was attributed to the small-scale sizes of the current sheets, and the observed bidirectional super-Alfvénic electron jets indicate that the MMS spacecraft crossed the reconnecting current sheet on both sides of an active X-line. Remarkably, the MMS spacecraft observed the presence of large asymmetries in the two electron inflows, with the inflows (normal to the current sheet) on the two sides of the reconnecting current layer differing by as much as a factor of four. Furthermore, even though the four MMS spacecraft were separated by less than seven electron skin depths, the degree of inflow asymmetry was significantly different at the different spacecraft. The asymmetry in the inflow speeds was larger with increasing distances downstream from the reconnection site, and the asymmetry was opposite on the two sides of the X-line. We compare the MMS observations with a 2D kinetic particle-in-cell (PIC) simulation and find that the asymmetry in the inflow speeds stems from in-plane currents generated via the combination of reconnection-mediated inflows and parallel flows along the magnetic separatrices in the presence of a large guide field.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Dark kinetic heating of exoplanets and brown dwarfs

Dark kinetic heating of neutron stars has been previously studied as a promising dark matter detection avenue. Kinetic heating occurs when dark matter is sped up to relativistic speeds in the gravitational well of high-escape velocity objects, and deposits kinetic energy after becoming captured by the object, thereby increasing its temperature. We show that dark kinetic heating can be significant even in objects with low-escape velocities, such as exoplanets and brown dwarfs, increasing the discovery potential of such searches. This can occur if there is a long-range dark force, creating a “dark escape velocity”, leading to heating rates substantially larger than those expected from neutron stars. We consequently set constraints on dark sector parameters using Wide-field Infrared Survey Explorer and JWST data on Super-Jupiter WISE 0855-0714, and map out future sensitivity to the dark matter scattering cross section below 10 −40 cm 2 . We compare dark kinetic heating rates of other lower escape velocity objects such as the Earth, Sun, and white dwarfs, finding complementary kinetic heating signals are possible depending on particle physics parameters.

Astrophysics↗

DOE OSTI2023

Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations

Abstract. Ice-nucleating particles (INPs) in the Southern Ocean (SO) atmosphere have significant impacts on cloud radiative and microphysical properties. Yet, INP prediction skill in climate models remains poorly understood, in part because of the lack of long-term measurements. Here we show, for the first time, how model-simulated INP concentrations compare with year-round INP measurements during the Macquarie Island Cloud Radiation Experiment (MICRE) campaign from 2017–2018. We simulate immersion-mode INP concentrations using the Energy Exascale Earth System Model version 1 (E3SMv1) by combining simulated aerosols with recently developed deterministic INP parameterizations and the native classical nucleation theory (CNT) for mineral dust in E3SMv1. Because MICRE did not collect aerosol measurements of super-micron particles, which are more effective ice nucleators, we evaluate the model's aerosol fields at other high-latitude sites using long-term in situ observations of dust and sea spray aerosol. We find that the model underestimates dust and overestimates sea spray aerosol concentrations by 1 to 2 orders of magnitude for most of the high-latitude sites in the Southern Hemisphere. We next compare predicted INP concentrations with concentrations of INPs collected on filter samples (typically for 2 or 3 d) and processed offline using the Colorado State University ice spectrometer (IS) in immersion freezing mode. We find that when deterministic parameterizations for both dust and sea spray INPs are used, simulated INPs are within a factor of 10 of observed INPs more than 60 % of the time during summer. Our results also indicate that the E3SM's current treatment of mineral dust immersion freezing in the SO is impacted by compensating biases – an underprediction of dust amount was compensated by an overprediction of its effectiveness as INPs. We also perform idealized droplet freezing experiments to quantify the implications of the time-dependent behavior assumed by the E3SM's CNT-parameterization and compare with the ice spectrometer observations. We find that the E3SM CNT 10 s diagnostic used in this study is a reasonable approximation of the exact formulation of CNT, when applied to ice spectrometer measurements in low-INP conditions similar to Macquarie Island. However, the linearized 10 s diagnostic underestimates the exact formula by an order of magnitude or more in places with high-INP conditions like the Sahara. Overall, our findings suggest that it is important to correct the biases in E3SM's simulated dust life cycle and update E3SM's INP parameterizations. INP prediction errors of 2 to 3 orders of magnitude can have considerable impacts on the simulated cloud and radiative properties in global climate models. On comparing INP concentrations during MICRE against ship-based campaigns, Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) and Antarctic Circumnavigation Expedition (ACE), we find that INPs from the latter are significantly higher only in regions closer to Macquarie Island. This alludes to the fact that physical, chemical and biological processes affecting INP concentrations as stimulated by the island could be partly responsible for the high INP concentrations observed at Macquarie Island during the MICRE campaign. Therefore, improvements to both aerosol simulation and INP parameterizations are required to adequately simulate INPs and their cloud impacts in E3SM. It will be helpful to include a parallel measurement of the size-resolved aerosol composition and explore opportunities for long-term measurement platforms in future field campaigns studying INP sources in remote marine regions.

54 ENVIRONMENTAL SCIENCES↗