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DOE OSTI2023

Explainable deep learning for insights in El Niño and river flows

The El Niño Southern Oscillation (ENSO) is a semi-periodic fluctuation in sea surface temperature (SST) over the tropical central and eastern Pacific Ocean that influences interannual variability in regional hydrology across the world through long-range dependence or teleconnections. Recent research has demonstrated the value of Deep Learning (DL) methods for improving ENSO prediction as well as Complex Networks (CN) for understanding teleconnections. However, gaps in predictive understanding of ENSO-driven river flows include the black box nature of DL, the use of simple ENSO indices to describe a complex phenomenon and translating DL-based ENSO predictions to river flow predictions. Here we show that eXplainable DL (XDL) methods, based on saliency maps, can extract interpretable predictive information contained in global SST and discover SST information regions and dependence structures relevant for river flows which, in tandem with climate network constructions, enable improved predictive understanding. Our results reveal additional information content in global SST beyond ENSO indices, develop understanding of how SSTs influence river flows, and generate improved river flow prediction, including uncertainty estimation. Observations, reanalysis data, and earth system model simulations are used to demonstrate the value of the XDL-CN based methods for future interannual and decadal scale climate projections.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Testing effects of Lorentz invariance violation in the propagation of astroparticles with the Pierre Auger Observatory

Lorentz invariance violation (LIV) is often described by dispersion relations of the form E i 2 = m i 2 +p i 2 +δ i,n E 2+n with delta different based on particle type i , with energy E, momentum p and rest mass m. Kinematics and energy thresholds of interactions are modified once the LIV terms become comparable to the squared masses of the particles involved. Thus, the strongest constraints on the LIV coefficients δ i,n tend to come from the highest energies. At sufficiently high energies, photons produced by cosmic ray interactions as they propagate through the Universe could be subluminal and unattenuated over cosmological distances. Cosmic ray interactions can also be modified and lead to detectable fingerprints in the energy spectrum and mass composition observed on Earth. The data collected at the Pierre Auger Observatory are therefore possibly sensitive to both the electromagnetic and hadronic sectors of LIV. In this article, we explore these two sectors by comparing the energy spectrum and the composition of cosmic rays and the upper limits on the photon flux from the Pierre Auger Observatory with simulations including LIV. Constraints on LIV parameters depend strongly on the mass composition of cosmic rays at the highest energies. For the electromagnetic sector, while no constraints can be obtained in the absence of protons beyond 10 19 eV, we obtain δ γ,0 > -10 -21 , δ γ,1 > -10 -40 eV -1 and δ γ,2 > -10 -58 eV -2 in the case of a subdominant proton component up to 10 20 eV. For the hadronic sector, we study the best description of the data as a function of LIV coefficients and we derive constraints in the hadronic sector such as δ had,0 < 10 -19 , δ had,1 < 10 -38 eV -1 and δ had,2 < 10 -57 eV -2 at 5σ CL.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Evaluation of a preliminary regional Earth model through comparison of synthetic and observed waveform data

In this report, we document the process related to developing a regional geologic model of a 605 x 1334 km area centered around Utah and encompassing surrounding states. This model is developed to test the effect that composition of a model has on the generation of synthetic data with the intent of using this information to improve upon full waveform moment tensor inversions. We compare observed data from three seismic events and five stations to the synthetic data generated by a preliminary model derived from a geologic framework model (GFM) developed by the USGS. The synthetic data and observed data comparisons indicate that our preliminary model performs well at smaller offset distances in the northern and central sections of the model. However, the southern stations consistently display synthetic data P- and S-wave arrival times that do not match the observed data arrival times, indicating that the velocity structure of the southern part of the model especially is inaccurate.

58 GEOSCIENCES↗

DOE OSTI2026

Taming the Wild West: Assessing Impacts-Relevant Climate Data Products (Abbreviated Report)

Impacts-relevant Earth system data refers to observational and ESM data that are downscaled, debiased, validated, and provisioned for use by decision-makers. Impacts-relevant Earth system data is essential for mitigation and adaptation planning across a variety of regions and sectors. A vast number of these data products have emerged in recent years, which has led to confusion among stakeholders and scientists as to the best product to use. With no standard evaluation protocol available for these products, the decision on which product to use was sometimes made because it was pragmatic rather than the best product to use. This project sought to develop foundational capabilities around impacts-relevant data products that would support more informed selection and application of these products. This work has been immensely successful, driving several academic publications and supported the development of a community of practice around impacts-relevant data products. Over the project’s three years we have addressed six tasks: First, the development of standard evaluation metrics for impacts-relevant climate data; second, the development of a novel suite of atmospheric river metrics; third, the development of novel metrics for precipitation feature analysis; fourth, the development of novel metrics for assessing co-variances between temperature and precipitation; fifth, the development of a dashboard for interactive examination of impacts-relevant climate data; and sixth, the establishment of a community of practice around impacts-relevant climate data that will continue beyond the conclusion of this project.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Taming the Wild West: Assessing Impacts-Relevant Climate Data Products (Final Report)

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data

The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite developed by the European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) launched in May 2024 carries a novel 94 GHz cloud profiling radar (CPR) with Doppler capability. This work describes the open-source instrument simulator Orbital-Radar, which transforms high-resolution radar data from field observations or forward simulations of numerical models to CPR primary measurements and uncertainties. The transformation accounts for sampling geometry and surface effects. We demonstrate Orbital-Radar's ability to provide realistic CPR views of typical cloud and precipitation scenes. The presented case studies show small-scale convection, marine stratus clouds, and Arctic mixed-phase cloud cases. These results provide valuable insights into the capabilities and challenges of the EarthCARE CPR mission and its advantages over the CloudSat CPR. Finally, Orbital-Radar allows for evaluating kilometre-scale numerical weather prediction models with EarthCARE CPR observations. So, Orbital-Radar can generate calibration and validation (Cal/Val) data sets already pre-launch. Nevertheless, an evaluation of synthetic CPR output data to accurate EarthCARE CPR data is missing.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Rethink hydrologic modeling framework with AI integrating multi-processes across scales

The proposed work is to develop a new hydrologic modeling framework that leverages vast amount earth and human system observational data, AI technologies, and data-driven information flows to improve predictability of hydrologic system that involves hydrologic, terrestrial, and biogeochemical processes and their interactions with the human and atmosphere systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Leveraging Machine Learning and Geo-Tagged Citizen Science Data to Disentangle the Factors of Avian Mortality Events at the Species Level

Abrupt environmental changes can affect the population structures of living species and cause habitat loss and fragmentations in the ecosystem. During August–October 2020, remarkably high mortality events of avian species were reported across the western and central United States, likely resulting from winter storms and wildfires. However, the differences of mortality events among various species responding to the abrupt environmental changes remain poorly understood. In this study, we focused on three species, Wilson’s Warbler, Barn Owl, and Common Murre, with the highest mortality events that had been recorded by citizen scientists. We leveraged the citizen science data and multiple remotely sensed earth observations and employed the ensemble random forest models to disentangle the species responses to winter storm and wildfire. We found that the mortality events of Wilson’s Warbler were primarily impacted by early winter storms, with more deaths identified in areas with a higher average daily snow cover. The Barn Owl’s mortalities were more identified in places with severe wildfire-induced air pollution. Both winter storms and wildfire had relatively mild effects on the mortality of Common Murre, which might be more related to anomalously warm water. Our findings highlight the species-specific responses to environmental changes, which can provide significant insights into the resilience of ecosystems to environmental change and avian conservations. Additionally, the study emphasized the efficiency and effectiveness of monitoring large-scale abrupt environmental changes and conservation using remotely sensed and citizen science data.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

The future of Earth system prediction: Advances in model-data fusion

Predictions of the Earth system, such as weather forecasts and climate projections, require models informed by observations at many levels. Some methods for integrating models and observations are very systematic and comprehensive (e.g., data assimilation), and some are single purpose and customized (e.g., for model validation). We review current methods and best practices for integrating models and observations. We highlight how future developments can enable advanced heterogeneous observation networks and models to improve predictions of the Earth system (including atmosphere, land surface, oceans, cryosphere, and chemistry) across scales from weather to climate. As the community pushes to develop the next generation of models and data systems, there is a need to take a more holistic, integrated, and coordinated approach to models, observations, and their uncertainties to maximize the benefit for Earth system prediction and impacts on society.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Widespread Wildfires Over the Western United States in 2020 Linked to Emissions Reductions During COVID-19

Widespread wildfires struck western United States in 2020, directly damaging properties and threatening human lives. Meanwhile, the COVID-19 pandemic rapidly spread across the globe in 2020, which disrupted human activities and resulted in substantial reductions in anthropogenic emissions. Here, we investigate the effects of the emissions reductions of aerosols, precursors, and greenhouse gases during the pandemic on wildfire weather conditions in 2020 over western United States by using an earth system model together with observational data. We show that the COVID-19 emissions reductions in model experiments increased surface air temperature and decreased precipitation and relative humidity due to a weakened moisture transport, which explains 10-40% of the observed increase in the risk of wildfires over western United States in 2020. In conclusion, this study suggests that COVID-19-related abrupt emissions reductions have an unexpected influence on wildfires, highlighting a different but important role of human activities in affecting wildfire risks.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Discussion: Presentation of Atmospheric 14 C O2 data

ABSTRACT Observations of radiocarbon ( 14 C) in Earth’s atmosphere and other carbon reservoirs are important to quantify exchanges of CO 2 between reservoirs. The amount of 14 C is commonly reported in the so-called Delta notation, i.e., Δ 14 C, the decay- and fractionation-corrected departure of the ratio of 14 C to total C from that ratio in an absolute international standard; this Delta notation permits direct comparison of 14 C/C ratios in the several reservoirs. However, as Δ 14 C of atmospheric CO 2 , Δ 14 CO 2 is based on the ratio of 14 CO 2 to total atmospheric CO 2 , its value can and does change not just because of change in the amount of atmospheric 14 CO 2 but also because of change in the amount of total atmospheric CO 2 , complicating ascription of change in Δ 14 CO 2 to change in one or the other quantity. Here we suggest that presentation of atmospheric 14 CO 2 amount as mole fraction relative to dry air (moles of 14 CO 2 per moles of dry air in Earth’s atmosphere), or as moles or molecules of 14 CO 2 in Earth’s atmosphere, all readily calculated from Δ 14 CO 2 and the amount of atmospheric CO 2 (with slight dependence on δ 13 CO 2 ), complements presentation only as Δ 14 CO 2 , and can provide valuable insight into the evolving budget and distribution of atmospheric 14 CO 2 .

Geochemistry & Geophysics↗

DOE OSTI2020

Wildfire Smoke Particle Properties and Evolution, from Space-Based Multi-Angle Imaging

Emitted smoke composition is determined by properties of the biomass burning source and ambient ecosystem. However, conditions that mediate the partitioning of black carbon (BC) and brown carbon (BrC) formation, as well as the spatial and temporal factors that drive particle evolution, are not understood adequately for many climate and air-quality related modeling applications. In situ observations provide considerable detail about aerosol microphysical and chemical properties, although sampling is extremely limited. Satellites offer the frequent global coverage that would allow for statistical characterization of emitted and evolved smoke, but generally lack microphysical detail. However, once properly validated, data from the National Aeronautics and Space Administration (NASA) Earth Observing System’s Multi-Angle Imaging Spectroradiometer (MISR) instrument can create at least a partial picture of smoke particle properties and plume evolution. We use in situ data from the Department of Energy’s Biomass Burning Observation Project (BBOP) field campaign to assess the strengths and limitations of smoke particle retrieval results from the MISR Research Aerosol (RA) retrieval algorithm. We then use MISR to characterize wildfire smoke particle properties and to identify the relevant aging factors in several cases, to the extent possible. The RA successfully maps qualitative changes in effective particle size, light absorption, and its spectral dependence, when compared to in situ observations. By observing the entire plume uniformly, the satellite data can be interpreted in terms of smoke plume evolution, including size-selective deposition, new-particle formation, and locations within the plume where BC or BrC dominates.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A Greening Future Elevates Flash Drought Risk in Northern Mid‐to‐High Latitudes

Flash droughts have become a growing concern, as they can emerge rapidly and increase the risk of crop failure. Although past studies have investigated the meteorological drivers and future changes of flash drought, why flash drought is more frequent over humid and vegetated regions remains underexplored. This study delves further into the mechanism by which vegetation regulates flash drought and its future change using observations from multiple data sets and large ensemble simulations from three Earth system models. On an interannual timescale, both observations and simulations show robust increases in flash drought frequency and a higher flash-to-sub-seasonal drought ratio during spring or antecedent conditions with dense vegetation, supporting the important role of vegetation in flash drought occurrence, especially in the northern mid-to-high latitudes. In the latter regions, the large ensemble simulations show robust increases in flash drought (e.g., 67% and 46% increases in Eastern U.S. and North Asia in 2050–2100 relative to 1950–2000 under the high emission scenario), where the growing season is lengthening. Although greening might suggest reduced drought stress, it drives precipitation-soil moisture-evapotranspiration decoupling by increasing evapotranspiration partitioning to transpiration. As transpiration can access deep soil water through the plant root system, its increased portion can weaken the constraints of concurrent precipitation on evapotranspiration, thus accelerating soil moisture depletion under high evaporative demand, driving a slow-to-rapid drought transition. How vegetation regulates flash drought by regulating surface moisture budget is supported by observations and simulations. Although warming supports early planting, agriculture may increasingly be threatened by surging flash drought risk.

Drought↗

DOE OSTI2021

Seismic constraints from a Mars impact experiment using InSight and Perseverance

NASA’s InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) mission has operated a sophisticated suite of seismology and geophysics instruments on the surface of Mars since its arrival in 2018. On 18 February 2021, we attempted to detect the seismic and acoustic waves produced by the entry, descent and landing of the Perseverance rover using the sensors onboard the InSight lander. Similar observations have been made on Earth using data from both crewed and uncrewed spacecraft, and on the Moon during the Apollo era, but never before on Mars or another planet. This was the only seismic event to occur on Mars since InSight began operations that had an a priori known and independently constrained timing and location. It therefore had the potential to be used as a calibration for other marsquakes recorded by InSight. Here we report that no signal from Perseverance’s entry, descent and landing is identifiable in the InSight data. Nonetheless, measurements made during the landing window enable us to place constraints on the distance–amplitude relationships used to predict the amplitude of seismic waves produced by planetary impacts and place in situ constraints on Martian impact seismic efficiency (the fraction of the impactor kinetic energy converted into seismic energy).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

A review of carbon monitoring in wet carbon systems using remote sensing

Carbon monitoring is critical for the reporting and verification of carbon stocks and change. Remote sensing is a tool increasingly used to estimate the spatial heterogeneity, extent and change of carbon stocks within and across various systems. We designate the use of the term wet carbon system to the interconnected wetlands, ocean, river and streams, lakes and ponds, and permafrost, which are carbon-dense and vital conduits for carbon throughout the terrestrial and aquatic sections of the carbon cycle. We reviewed wet carbon monitoring studies that utilize earth observation to improve our knowledge of data gaps, methods, and future research recommendations. To achieve this, we conducted a systematic review collecting 1622 references and screening them with a combination of text matching and a panel of three experts. The search found 496 references, with an additional 78 references added by experts. Our study found considerable variability of the utilization of remote sensing and global wet carbon monitoring progress across the nine systems analyzed. The review highlighted that remote sensing is routinely used to globally map carbon in mangroves and oceans, whereas seagrass, terrestrial wetlands, tidal marshes, rivers, and permafrost would benefit from more accurate and comprehensive global maps of extent. We identified three critical gaps and twelve recommendations to continue progressing wet carbon systems and increase cross system scientific inquiry.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

In-orbit performance of the soft X-ray imaging telescope Xtend aboard XRISM

Here, we present a summary of the in-orbit performance of the soft X-ray imaging telescope Xtend onboard the X-Ray Imaging and Spectroscopy Mission (XRISM), based on in-flight observation data, including first-light celestial objects, calibration sources, and results from the cross-calibration campaign with other currently operating X-ray observatories. XRISM/Xtend has a large field of view of ${38{^{\prime }_{.}}5}$ $\times$ ${38{^{\prime }_{.}}5}$, covering an energy range of 0.4–13 keV, as demonstrated by the first-light observation of the galaxy cluster Abell 2319. It also features an energy resolution of 170–180 eV at 6 keV, which meets the mission requirement and enables us to resolve He-like and H-like Fe K$\alpha$ lines. Throughout the observation during the performance verification phase, we confirm that two issues identified in the Soft X-ray Imager (SXI) onboard the previous Hitomi mission—light leakage and crosstalk events—are addressed and suppressed in the case of Xtend. A joint cross-calibration observation of the bright quasar 3C 273 results in an effective area measured to be $\sim$420 cm$^{2}$ at1.5 keV and $\sim$310 cm$^{2}$ at 6.0 keV, which matches values obtained in ground tests. We also continuously monitor the health of Xtend by analyzing overclocking data, calibration source spectra, and day-Earth observations; the readout noise is stable and low, and contamination is negligible even one year after launch. A low background level compared with other major X-ray instruments onboard satellites, combined with the largest grasp ($\Omega _{\rm eff}\sim 60$ cm$^2$ deg$^2$) of Xtend, will not only support Resolve analysis, but also enable significant scientific results on its own. This includes near-future follow-up observations and transient searches in the context of time-domain and multi-messenger astrophysics.

instrumentation: detectors: Xtend↗

DOE OSTI2024

A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics

AI-based foundation models like FourCastNet, GraphCast are revolutionizing weather and climate predictions but are not yet ready for operational use. Their limitation lies in the absence of a data assimilation system to incorporate real-time Earth system observations, crucial for accurately forecasting events like tropical cyclones. To overcome these obstacles, we introduce a generic real-time data assimilation framework and demonstrate its end-to-end performance on the Frontier supercomputer. This framework comprises two primary modules: an ensemble score filter (EnSF), which significantly outperforms the state-of-the-art data assimilation method, and a vision transformer-based surrogate capable of real-time adaptation through the integration of observational data. We demonstrate both the strong and weak scaling of our framework up to 1024 GPUs on the Exascale supercomputer, Frontier. Our results not only illustrate the framework's exceptional scalability on high-performance computing systems, but also demonstrate the importance of supercomputers in real-time data assimilation for weather and climate predictions.

Lu, Dan↗

DOE OSTI2022

L0 Data from the 2018 NGEE Arctic LiDAR and Imagery Unoccupied Aerial System Campaign at the Teller 47 Field Site, Seward Peninsula, Alaska

Airborne remote sensing data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) hexacopter platform operated by NGEE Arctic scientists from EES-14 (Earth System Observations group) at Los Alamos National Laboratory. These data were collected in July 2018 at a field site near mile marker 47 along the Teller road between Nome, Alaska and Teller, Alaska. A DJI Matrice 600 Pro Airframe and Routescene UAV LiDARSystem was used to collect LiDAR data, and DJI Phantom 4 Advanced was used to collect optical red/green/blue (RGB) imagery at regular intervals along 11 flight paths. This data package contains unprocessed data products (processing level 0) including flight paths, raw photos, and raw lidar data files (*.kml, *.jpg, and *.lpd formats). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included (see Supplemental Files, *.rinex, and *.rtcm3 files). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), 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↗