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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Benchmarking Simulated Precipitation Variability Amplitude across Time Scales

Here, objective performance metrics that measure precipitation variability across time scales from subdaily to interannual are presented and applied to Historical simulations of Coupled Model Intercomparison Project phase 5 and 6 (CMIP5 and CMIP6) models. Three satellite-based precipitation estimates (IMERG, TRMM, and CMORPH) are used as reference data. We apply two independent methods to estimate temporal variability of precipitation and compare the consistency in their results. The first method is derived from power spectra analysis of 3-hourly precipitation, measuring forced variability by solar insolation (diurnal and annual cycles) and internal variability at different time scales (subdaily, synoptic, subseasonal, seasonal, and interannual). The second method is based on time averaging and facilitates estimating the seasonality of subdaily variability. Supporting the robustness of our metric, we find a near equivalence between the results obtained from the two methods when examining simulated-to-observed ratios over large domains (global, tropics, extratropics, land, or ocean). Additionally, we demonstrate that our model evaluation is not very sensitive to the discrepancies between observations. Our results reveal that CMIP5 and CMIP6 models in general overestimate the forced variability while they underestimate the internal variability, especially in the tropical ocean and higher-frequency variability. The underestimation of subdaily variability is consistent across different seasons. The internal variability is overall improved in CMIP6, but remains underestimated, and there is little evidence of improvement in forced variability. Increased horizontal resolution results in some improvement of internal variability at subdaily and synoptic time scales, but not at longer time scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Transition of Large-Scale Environmental Conditions and Characteristics of Four Rainfall Types Observed by S-PolKa During the MJO-1 Active Phase of DYNAMO/CINDY/AMIE

Analyses of National Center for Atmospheric Research (NCAR) S-PolKa dual-polarization radar data and ERA5 reanalysis fields indicate gradual changes in convection characteristics and large-scale environmental conditions during a central Indian Ocean Madden-Julian Oscillation (MJO) event observed by the DYNAMO/CINDY/AMIE field campaigns in late October 2011 (MJO-1). Examination of four rainfall types (isolated convective cores, convective, mixed, and stratiform) reveals a transition of convection characteristics (i.e., areal coverage and depth) between distinct 5-day environmental periods at the beginning and end of this ~2-week MJO active phase. A shift toward less frequent rainfall covering less of the radar domain for all four rainfall types occurs when large-scale lower-tropospheric dry air advects into the region with the westerly wind burst (WWB). Drier and warmer lower-free-tropospheric conditions associated with the WWB contribute to increased large-scale surface-based convective inhibition (CIN), surface-based convective available potential energy (CAPE), and cloud base heights. A thermodynamic budget analysis indicates reduced surface heat fluxes contribute to the increased surface-based CAPE. Greater CAPE at the end of MJO-1 coincides with deeper 50-dBZ convective echoes, while decreased 10-dBZ depth for all rainfall types corresponds in time with WWB-related dry-air advection. Increased (decreased) reflectivity values in the lower-level vertical reflectivity distribution of convective (stratiform) precipitation indicate increased (decreased) convective (stratiform) intensities when the WWB is present. The opposite depth changes for convective echoes and opposite shifts in convective and stratiform precipitation intensities underscore how the WWB can have differing impacts at different reflectivity thresholds and stages of the deep convection lifecycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Carbon Outgassing in the Antarctic Circumpolar Current Is Supported by Ekman Transport From the Sea Ice Zone in an Observation‐Based Seasonal Mixed‐Layer Budget

Despite its importance for the global cycling of carbon, there are still large gaps in our understanding of the processes driving annual and seasonal carbon fluxes in the high-latitude Southern Ocean. This is due in part to a historical paucity of observations in this remote, turbulent, and seasonally ice-covered region. Here, we use autonomous biogeochemical float data spanning 6 full seasonal cycles and with circumpolar coverage of the Southern Ocean, complemented by atmospheric reanalysis, to construct a monthly climatology of the mixed layer budget of dissolved inorganic carbon (DIC). We investigate the processes that determine the annual mean and seasonal cycle of DIC fluxes in two different zones of the Southern Ocean—the Sea Ice Zone (SIZ) and Antarctic Southern Zone (ASZ). We find that, annually, mixing with carbon-rich waters at the base of the mixed layer supplies DIC which is, in the ASZ, either used for net biological production or outgassed to the atmosphere. In contrast, in the SIZ, where carbon outgassing and the biological pump are weaker, the surplus of DIC is instead advected northward to the ASZ. In other words, carbon outgassing in the southern Antarctic Circumpolar Current (ACC), which has been attributed to remineralized carbon from deep water upwelled in the ACC, is also due to the wind-driven transport of DIC from the SIZ. These results stem from the first observation-based carbon budget of the circumpolar Southern Ocean and thus provide a useful benchmark to evaluate climate models, which have significant biases in this region.

Sauvé, Jade↗
DOE OSTI2025

Behaviour of cadmium isotopes in sulfidic waters and sediments of the Black Sea: Implications for global cadmium cycling and the application of cadmium isotopes as a paleo-oceanographic proxy

The cadmium isotope system has found use as a tracer for biological productivity, redox and organic carbon burial in the oceans. There are, however, very few observational constraints on Cd isotopic behaviour in modern sulfidic marine conditions, limiting our understanding of the modern Cd cycle, and our ability to use Cd isotope measurements of ancient sedimentary deposits as a paleoceanographic proxy. Here we study the behaviour of dissolved Cd in the water column of the Black Sea and its incorporation into sediments on the basin floor. The isotopic composition of dissolved Cd in the upper ∼50 m of the Black Sea water column is controlled by a combination of biological uptake and regeneration along with mixing of river water and Mediterranean seawater. Cadmium declines to <2 % of its peak subsurface concentration within the zone of nitrate-reduction but above the sulfide chemocline. The isotopic composition of dissolved Cd below the sulfide chemocline evolves in a manner that is consistent with experimental Cd sulfide fractionation factors, providing field-based support for these earlier studies. In contrast, the stability of the dissolved Cd isotopic signature above the chemocline, despite a large reduction in dissolved Cd concentrations, is explained by diffusion towards the Cd-sulfide sink below the chemocline. Sediments accumulating in the deep Black Sea below the sulfide chemocline have isotopic compositions that are similar to dissolved Cd in its near-surface aqueous concentration maximum. Sediments accumulating at shallower depths have lighter isotopic compositions that are likely affected by non-sulfidic burial pathways mediated by macrofaunal mixing and diagenesis of shallow burial phases. Our study shows that the isotopic composition of bulk sediments accumulating under sulfidic conditions is similar to dissolved Cd in the upper water column, supporting its use as a paleo-chemical proxy for ancient seawater as long as basin-scale controls on open ocean seawater sources are considered. We show that Cd burial in the deep Black Sea, predominantly as CdS, accounts for ∼0.5–15 % of total annual Cd burial in the global ocean.

Biogeochemical cycles↗
DOE OSTI2025

Faster recovery of North Atlantic tropical cyclone-induced cold wakes in recent decades

Intense winds associated with tropical cyclones (TCs) generate surface ocean cooling in their wakes, which can persist for several weeks in their aftermath. While multi-decadal observations of the sea surface have shown a substantial warming of the ocean, long-term changes in cold wake recovery time remain largely unknown. Here we find a trend toward faster recovery of TC cold wakes in the Atlantic main development region (MDR) since 2001. This is due primarily to a decrease in the strength of the North Atlantic trade winds, which reduces evaporative cooling of the ocean. The faster damping of TC cold wakes has led to a significant increase in the intensification of subsequent TCs that encounter lingering wakes from prior TCs, with a magnitude that is about 9% of that from long-term warming of the ocean. Finally, earth system model simulations indicate that the observed decrease in the cold wake recovery time will likely continue into the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Projecting Antarctica's contribution to future sea level rise from basal ice shelf melt using linear response functions of 16 ice sheet models (LARMIP-2)

Abstract. The sea level contribution of the Antarctic ice sheet constitutes a large uncertainty in future sea level projections. Here we apply a linear response theory approach to 16 state-of-the-art ice sheet models to estimate the Antarctic ice sheet contribution from basal ice shelf melting within the 21st century. The purpose of this computation is to estimate the uncertainty of Antarctica's future contribution to global sea level rise that arises from large uncertainty in the oceanic forcing and the associated ice shelf melting. Ice shelf melting is considered to be a major if not the largest perturbation of the ice sheet's flow into the ocean. However, by computing only the sea level contribution in response to ice shelf melting, our study is neglecting a number of processes such as surface-mass-balance-related contributions. In assuming linear response theory, we are able to capture complex temporal responses of the ice sheets, but we neglect any self-dampening or self-amplifying processes. This is particularly relevant in situations in which an instability is dominating the ice loss. The results obtained here are thus relevant, in particular wherever the ice loss is dominated by the forcing as opposed to an internal instability, for example in strong ocean warming scenarios. In order to allow for comparison the methodology was chosen to be exactly the same as in an earlier study (Levermann et al., 2014) but with 16 instead of 5 ice sheet models. We include uncertainty in the atmospheric warming response to carbon emissions (full range of CMIP5 climate model sensitivities), uncertainty in the oceanic transport to the Southern Ocean (obtained from the time-delayed and scaled oceanic subsurface warming in CMIP5 models in relation to the global mean surface warming), and the observed range of responses of basal ice shelf melting to oceanic warming outside the ice shelf cavity. This uncertainty in basal ice shelf melting is then convoluted with the linear response functions of each of the 16 ice sheet models to obtain the ice flow response to the individual global warming path. The model median for the observational period from 1992 to 2017 of the ice loss due to basal ice shelf melting is 10.2 mm, with a likely range between 5.2 and 21.3 mm. For the same period the Antarctic ice sheet lost mass equivalent to 7.4 mm of global sea level rise, with a standard deviation of 3.7 mm (Shepherd et al., 2018) including all processes, especially surface-mass-balance changes. For the unabated warming path, Representative Concentration Pathway 8.5 (RCP8.5), we obtain a median contribution of the Antarctic ice sheet to global mean sea level rise from basal ice shelf melting within the 21st century of 17 cm, with a likely range (66th percentile around the mean) between 9 and 36 cm and a very likely range (90th percentile around the mean) between 6 and 58 cm. For the RCP2.6 warming path, which will keep the global mean temperature below 2 ∘C of global warming and is thus consistent with the Paris Climate Agreement, the procedure yields a median of 13 cm of global mean sea level contribution. The likely range for the RCP2.6 scenario is between 7 and 24 cm, and the very likely range is between 4 and 37 cm. The structural uncertainties in the method do not allow for an interpretation of any higher uncertainty percentiles. We provide projections for the five Antarctic regions and for each model and each scenario separately. The rate of sea level contribution is highest under the RCP8.5 scenario. The maximum within the 21st century of the median value is 4 cm per decade, with a likely range between 2 and 9 cm per decade and a very likely range between 1 and 14 cm per decade.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Exploring Causal Relationships and Adjustment Timescales of Aerosol-Cloud Interactions in Geostationary Satellite Observations and CAM6 Using Wavelet Phase Coherence Analysis

We present for the first time within the cloud physics context, the application of wavelet phase coherence analysis to disentangle counteracting physical processes associated with the lead-lag phase difference between cloud-proxy liquid water path (LWP) and aerosol-proxy cloud droplet number concentration ( N d ) in an Eulerian framework using satellite-based observations and climate model outputs. This approach allows us to identify the causality and dominant adjustment timescales governing the correlation between LWP and N d . Satellite observations indicate a more prevalent positive correlation between daytime LWP and N d regardless of whether LWP leads or lags N d . The positive cloud water response, associated with precipitation processes, typically occurs within 1 hr, while the negative response resulting from entrainment drying, usually takes 2–4 hr. CAM6 displays excessively rapid negative responses along with overly strong negative cloud water response and insufficient positive response, leading to a more negative correlation between LWP and N d compared to observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Two-Day Westward-Propagating Inertio-Gravity Waves during GoAmazon

The dynamical and thermodynamical features of Amazonian 2-day westward-propagating inertia–gravity (WIG) waves are examined. On the basis of a linear regression analysis of satellite brightness temperature and data from the 2014–15 Observations and Modeling of the Green Ocean Amazon (GoAmazon) field campaign, it is shown that Amazonian WIG waves exhibit structure and propagation characteristics consistent with the n = 1 WIG waves from shallow water theory. These WIG waves exhibit a pronounced seasonality, with peak activity occurring from March to May and a minimum occurring from June to September. Evidence is shown that mesoscale convective systems over the Amazon are frequently organized in 2-day WIG waves. Results suggest that many of the Amazonian WIG waves come from preexisting 2-day waves over the Atlantic, which slow down when coupled with the deeper, more intense convection over tropical South America. In contrast to WIG waves that occur over the ocean, Amazonian 2-day WIG waves exhibit a pronounced signature in surface temperature, moisture, and heat fluxes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Hydrometeor Transport and the Stratiform Water Budget in Amazonian Mesoscale Convective Systems

A significant portion of precipitation falls within the stratiform regions of mesoscale convective systems (MCSs). These regions are formed from convective clouds that have either weakened and formed a horizontally stratified structure or have advected hydrometeors to form a trailing-stratiform region, with further precipitation growth promoted by in situ dynamical and microphysical processes. Green Ocean Amazon 2014/5 (GoAmazon2014/5) field campaign observations are used to quantify the stratiform water budget of six MCSs (three each from the wet and dry seasons) utilizing the framework from Leary and Houze, with an emphasis on the transfer of hydrometeors (C A ) from the convective to the stratiform regions. The storms were predominantly leading-line/trailing-stratiform MCSs, but two had embedded convection in the stratiform region, which can complicate water budget calculations. A pulse-like pattern with a mean interval of 21 min occurs in C A during each storm resulting from a lag between the initial convective updrafts and the subsequent hydrometeor transport and sedimentation in the stratiform region. Here, the peaks in C A were followed by peaks in hydrometeor growth associated with the mesoscale updraft (C mu ) in the stratiform region. Averaged over the six storms, the positive contributions of C A and C mu to the stratiform water budget were roughly equal, although storm-to-storm variations existed. Negative contributions from evaporation below cloud base in the mesoscale downdraft and detrainment from the stratiform region into the nonprecipitating anvil cloud and environment accounted for 53% and 21% of the sum of C A and C mu , respectively, resulting in a mean stratiform region precipitation efficiency of 26%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

ARM data-oriented metrics and diagnostics package for climate model evaluation (ARM-DIAGS-V3) version 3

A Python-based metrics and diagnostics package is currently being developed by the ARM Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term high frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, precipitation, and aerosols. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison as demonstrated in Zhang et al. (2018) and Zhang et al. (2020). The mean of the CMIP model can be served as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, aerosol optical depth, and radiative fluxes, with plan to extend to more fields, such as the evaluation of model simulated aerosol physicochemical properties and cloud microphysics properties. Process-oriented diagnostics focusing on aerosol, cloud, and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. In addition to the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Tropical Western Pacific (TWP) atmospheric observatories in the ARMDIAGS version 2.0, the version 3.0 package have extended to the data collected at the ARM Eastern North Atlantic (ENA) atmospheric observatory and the Observation and Modeling of the Green Ocean Amazon (GOAMAZON) field campaign. The metrics and diagnostics package are currently built upon standard Python libraries and additional Python packages developed by DOE (CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first provide an overview of major metrics in section 2. The input data, which constitutes the core content of the metrics and diagnostics package, is summarized in section 3. A user's guide documenting the workflow/structure of the version 3.0 codes and including step-by-step instruction for running the package is described in section 4.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Morning boundary layer conditions for shallow to deep convective cloud evolution during the dry season in the central Amazon

Observations of the boundary layer (BL) processes are analyzed statistically for dry seasons of 2 years and in detail, as case studies, for 4 shallow convective days (ShCu) and 4 shallow-to-deep convective days (ShDeep) using a suite of ground-based measurements from the Observation and Modeling of the Green Ocean Amazon (GoAmazon 2014/5) Experiment. The BL stages in ShDeep days, from the nighttime to the cloudy mixing layer stage, are then described in comparison with ShCu days. Atmospheric thermodynamics and dynamics, environmental profiles, and surface turbulent fluxes were employed to compare these two distinct situations for each stage of the BL evolution. Particular attention is given to the morning transition stage, in which the BL changes from stable to unstable conditions in the early morning hours. Results show that the decrease in time duration of the morning transition on ShDeep days is associated with high humidity and well-established vertical wind shear patterns. Higher humidity since nighttime not only contributes to lowering the cloud base during the rapid growth of the BL but also contributes to the balance between radiative cooling and turbulent mixing during nighttime, resulting in higher sensible heat flux in the early morning. The sensible heat flux promotes rapid growth of the well-mixed layer, thus favoring the deeper BL starting from around 08:00 LST (UTC-4 h). Under these conditions, the time duration of morning transition is used to promote convection, having an important effect on the convective BL strength and leading to the formation of shallow cumulus clouds and their subsequent evolution into deep convective clouds. Statistical analysis was used to validate the conceptual model obtained from the case studies. Despite the case-to-case variability, the statistical analyses of the processes in the BL show that the described processes are very representative of cloud evolution during the dry season.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Lifecycle of updrafts and mass flux in isolated deep convection over the Amazon rainforest: insights from cell tracking

Long-term observations of deep convective cloud (DCC) vertical velocity and mass flux were collected during the Observations and Modelling of the Green Ocean Amazon (GoAmazon2014/5) experiment. Precipitation echoes from a surveillance weather radar near Manaus, Brazil, are tracked to identify and evaluate the isolated DCC lifecycle evolution during the dry and wet seasons. A radar wind profiler (RWP) provides precipitation and air motion profiles to estimate the vertical velocity, mass flux, and mass transport rates within overpassing DCC cores as a function of the tracked cell lifecycle stage. The average radar reflectivity factor (Z), DCC area (A), and surface rainfall rate (R) increased with DCC lifetime as convective cells were developing, reached a peak as the cells matured, and decreased thereafter as cells dissipated. As the convective cells mature, cumulative DCC properties exhibit stronger updraft behaviors with higher upward mass flux and transport rates above the melting layer (compared with initial and later lifecycle stages). In comparison, developing DCCs have the lowest Z associated with weak updrafts, as well as negative mass flux and transport rates above the melting layer. Over the DCC lifetime, the height of the maximum downward mass flux decreased, whereas the height of the maximum net mass flux increased. During the dry season, the tracked DCCs had higher Z, propagation speed, and DCC area, and were more isolated spatially compared with the wet season. Dry season DCCs exhibit higher Z, mass flux, and mass transport rate while developing, whereas wet season DCCs exhibit higher Z, mass flux, and mass transport rates at later stages.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Southern Ocean Aerosols Field Campaign Report

Atmospheric processes over the Southern Ocean have a profound influence on regional and global climate. This is a part of the world where global climate models perform particularly poorly, with models persistently overpredicting the amount of sunlight reaching the Earth's surface (Regayre et al. 2020). A major challenge when trying to improve the representation of atmospheric processes in this part of the globe is the scarcity of observations capable of constraining our understanding. During 2024/25 a U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility field campaign (CAPE-k) deployed a suite of instrumentation at the kennaook/Cape Grim atmospheric monitoring station in Tasmania, Australia to provide detailed cloud-aerosol observations in this region in order to address the greatest source of uncertainty in climate models – atmospheric aerosols and how they influence cloud formation (Carslaw et al. 2013). In support of the ARM observations, an Australian Research Council (ARC)-funded project “Southern Ocean aerosols: sources, sinks and impact on cloud properties,” led by the Queensland University of Technology, complemented the ARM measurements with a suite of chemical measurements at the kennaook/Cape Grim site in northwestern Tasmania to provide more information on the processes controlling aerosol formation and growth. The deployment of the University of York LIF-SO2 instrument (Temple et al. 2025) in the ARM mobile facility container was part of this chemistry-focused deployment. Increased observational efforts are critical for understanding sources and sinks of Southern Ocean aerosols, in particular the role of marine micro-organisms (phytoplankton, algae) on aerosols formation, their properties and growth, cloud droplet formation, and the conversion of cloud droplets to ice crystals and precipitation. The observational focus of the ARC-funded project is aerosol chemical composition and their gaseous precursors. The remote nature of the Southern Ocean poses a significant analytical challenge when studying gaseous precursors, as low concentrations are often below the limits of detection of commercial instrumentation. Historically this has meant that observations have had to be time-averaged over days to weeks to achieve the limits of detection required. Although useful when considering overall average levels of aerosol precursors, this time-averaging obscures temporal variability that can provide insight into the controlling processes. Over recent years advances in analytical techniques have made high-time-resolution measurements of key gas-phase aerosol precursors achievable with sufficiently low limits of detection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Novel Freshwater to Marine Evolutionary Transition Revealed within Methylophilaceae Bacteria from the Arctic Ocean

Bacteria inhabiting polar oceans, particularly the Arctic Ocean, are less studied than those at lower latitudes. Discovering bacterial adaptations to Arctic Ocean conditions is essential for understanding responses to the accelerated environmental changes occurring in the North. The Methylophilaceae are emerging as a model for investigating the genomic basis of habitat adaptation, because related lineages are widely distributed across both freshwater and marine ecosystems. Here, we investigated Methylophilaceae diversity in the salinity-stratified surface waters of the Canada Basin, Arctic Ocean. In addition to a diversity of marine OM43 lineages, we report on the genomic characteristics and evolution of a previously undescribed Methylophilaceae clade (BS01) common to polar surface waters yet related to freshwater sediment Methylotenera species. BS01 is restricted to the lower-salinity surface waters, while OM43 is found throughout the halocline. An acidic proteome supports a marine lifestyle for BS01, but gene content shows increased metabolic versatility compared to OM43 and evidence for ongoing genome-streamlining. Phylogenetic reconstruction shows that BS01 colonized the pelagic ocean independently of OM43 via convergent evolution. Salinity adaptation and differences in one-carbon and nitrogen metabolism may play a role in niche differentiation between BS01 and OM43. In particular, urea utilization by BS01 is predicted to provide an ecological advantage over OM43 given the limited amount of inorganic nitrogen in the Canada Basin. These observations provide further evidence that the Arctic Ocean is inhabited by distinct bacterial groups and that at least one group (BS01) evolved via a freshwater to marine environmental transition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A New Decade in Seismoacoustics (2010–2022)

Several sources of interest often generate both low‐frequency acoustic and seismic signals due to energy propagation through the atmosphere and the solid Earth. Seismic and acoustic observations are associated with a wide range of sources, including earthquakes, volcanoes, bolides, chemical and nuclear explosions, ocean noise, and others. The fusion of seismic and acoustic observations contributes to a better understanding of the source, both in terms of constraining source location and physics, as well as the seismic to acoustic coupling of energy. Here in this review, we summarize progress in seismoacoustic data processing, including recent developments in open‐source data availability, low‐cost seismic and acoustic sensors, and large‐scale deployments of collocated sensors from 2010 to 2022. Similarly, we outline the recent advancements in modeling efforts for both source characteristics and propagation dynamics. Finally, we highlight the advantages of fusing multiphenomenological signals, focusing on current and future techniques to improve source detection, localization, and characterization efforts. This review aims to serve as a reference for seismologists, acousticians, and others within the growing field of seismoacoustics and multiphenomenology research.

58 GEOSCIENCES↗
DOE OSTI2025

Comparisons of the v11.1 Orbiting Carbon Observatory‐2 (OCO‐2) X CO2 Measurements With GGG2020 TCCON

The Orbiting Carbon Observatory 2 (OCO-2) is NASA's first Earth observation satellite mission dedicated to studying the sources and sinks of carbon dioxide (CO 2 ) on a global scale. The observations of reflected sunlight are inverted in a retrieval algorithm to produce estimates of the dry air mole-fractions of CO 2 (X CO2 ). The OCO-2 Level 2 data release, version 11.1 (v11.1) retrievals from the Atmospheric Carbon Observations from Space (ACOS) algorithm, includes significant improvements in the X CO2 data product compared to older OCO-2 data versions. This work compares the v11.1 X CO2 from OCO-2 against X CO2 estimates collected from a global ground-based network known as the Total Carbon Column Observing Network (TCCON), OCO-2's primary validation source. The OCO-2 project provides a version of the Level 2 data product, called “lite” files that include calibrated and bias-corrected XCO2 values, accessible together with all OCO-2 data products through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). This work shows that OCO-2 X CO2 observations made between September 2014 and December 2023, after quality filtering and the application of an averaging kernel correction, agree well with coincident TCCON data for all OCO-2 observational modes of land (nadir, glint, target) and ocean (glint). The aggregated, bias-corrected, and quality-filtered absolute average bias values are less than or equal to 0.20 parts per million (ppm) globally for all OCO-2 observation modes, where the biases do not indicate a statistically significant time dependence. The land nadir/glint mode has the lowest bias value of −0.03 ± 0.85 ppm.

54 ENVIRONMENTAL SCIENCES↗
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↗
DOE OSTI2026

Large Eddy Simulations of the Atmospheric Boundary Layer Over Satellite‐Sensed Sea Ice Maps

Surface heterogeneity in the marginal ice zone (MIZ) causes multiscale secondary atmospheric circulations that are challenging to model or observe. The absence or inadequate representation of these circulations in ocean‐atmosphere exchange schemes in climate models is partially responsible for the underestimation of Arctic sea ice loss. Observationally, such circulations obfuscate the interpretation of polar atmospheric chemistry measurements, among others. To address this open challenge, large‐eddy simulations are conducted over real‐world satellite‐sensed sea ice maps with an ice‐sea temperature contrast, as well as over idealizations of these maps that alter the ice pattern but conserve its fraction, showing that the ice fraction of a surface is not sufficient to predict the surface heat flux. In a second suite of simulations, three other heterogeneity metrics (representing the surface fragmentation, patch edge tortuosity, and patch size variability) are introduced to complement the ice fraction in describing the surface. Simulations varying these parameters suggest that they also significantly impact surface‐air interactions. A roughness contrast is then added to the surface temperature contrast, indicating that the contribution of roughness changes to the resulting atmospheric circulations is less pronounced than that of thermal heterogeneity. Based on these results, we illustrate, using a multi‐linear regression on these map features, that MIZ surface parameterizations in Earth Systems Models can be improved if they account for these various characteristics of the sea‐ice patterns.

54 ENVIRONMENTAL SCIENCES↗