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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Securing the Modern Grid: Federal Investments, Digitization, and Supply Chain Strategy

Across the United States (U.S.) grid expansion and modernization is underway, paving the way for accelerated load growth and intelligent resource management. Digitization of the grid is supported by several state and federal programs, providing support for utilities installing advanced metering infrastructure (AMI), AI-powered analytics systems, battery energy storage systems (BESS), and distributed energy resource management systems (DERMS) to transform the grid from a one-way power delivery system into an intelligent, responsive network that will enable faster load growth and power expansion of data centers for advanced artificial intelligence (AI) applications. The digital transformation of America's grid presents opportunity for increased efficiency and resiliency but also introduces new digital risks that require careful management. Digital equipment often contains several vulnerabilities such as unencrypted communication protocols, and persistent remote access capabilities that could be exploited to manipulate device settings, coordinate service disruptions, or inject false data into grid operations. These digital risks become particularly important as the grid must rapidly scale to support AI-driven data centers, which the administration has identified as essential for maintaining U.S. technological leadership and economic competitiveness. These vulnerabilities are compounded by supply chain realities: Chinese manufacturers currently produce 70-90% of essential grid components including inverters, batteries, and control systems, with the U.S. lacking domestic manufacturing capacity for critical assets like extra-high voltage transformers. Recent federal legislation has established Foreign Entity of Concern (FEOC) restrictions to address these risks, requiring projects to achieve escalating thresholds of non-FEOC content to receive tax credits while utilities work to expand sourcing channels for their supply chains and strengthen security measures. These restrictions arrive precisely when utilities face unprecedented electricity demand growth driven by the rapid growth in data centers, creating a considerable challenge: rapidly expanding infrastructure while navigating complex compliance requirements while lacking viable alternatives for many critical components. Idaho National Laboratory (INL) and its partners have developed practical approaches to help utilities navigate these intersecting challenges as they leverage federal investment to strengthen and grow the grid. These solutions include Cyber-Informed Engineering (CIE) principles that build resilience directly into systems, the Cirrus tool for secure cloud migration, and enhanced procurement guidance that embeds security requirements throughout equipment lifecycles. Federal initiatives, such as the Technical Assistance for Digital Assurance (TADA) project, provide direct support to utilities implementing these approaches while facilitating knowledge sharing across the industry. While these tools and frameworks cannot eliminate all risks inherent in foreign supply chain dependencies, they offer pragmatic pathways for strengthening security posture without sacrificing the deployment momentum essential to meeting surging electricity demand. Ultimately, securing America's digital energy infrastructure demands dedicated coordination across multiple fronts: building domestic supply chains, implementing robust digital assurance practices, and maintaining the aggressive modernization timeline necessary for reliability, resilience, and energy independence.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Tropical High Cloud Feedback Relationships to Climate Sensitivity

Clouds constitute a large portion of uncertainty in predictions of equilibrium climate sensitivity (ECS). While low cloud feedbacks have been the focus of intermodel studies due to their high variability among global climate models, tropical high cloud feedbacks also exhibit considerable uncertainty. Here, we apply the cloud radiative kernel technique of Zelinka et al. to 22 models across the CMIP5 and CMIP6 ensembles to survey tropical high cloud feedbacks and analyze their relationship to ECS. We find that the net high cloud feedback and its altitude and optical depth feedback components are significantly positively correlated with ECS in the tropical mean. On the other hand, the tropical mean high cloud amount feedback is not correlated with ECS. These relationships are most pronounced outside of areas of strong climatological ascent, suggesting the importance of thin cirrus feedbacks. Finally, we explore connections between high cloud feedbacks, climate sensitivity, and mean state high cloud properties. In general, high ECS models are cloudier in the upper troposphere but have a thinner high cloud population. Furthermore, we find that having more thin cirrus in the mean state relates to more positive high cloud altitude and optical depth feedbacks, and it either amplifies or dampens the high cloud amount feedback depending on the large-scale dynamical regime (amplifying in descent and dampening in ascent). In summary, our analysis highlights the importance of tropical high cloud feedbacks for driving intermodel spread in ECS and suggests that mean state high cloud characteristics might provide a unique opportunity for observationally constraining high cloud feedbacks.

atmosphere↗
DOE OSTI2023

The Influence of Cloud Types on Cloud–Radiative Forcing During DYNAMO/AMIE

Cloud-radiative feedback is known to be an important process for the Madden-Julian Oscillation (MJO) and its accurate representation in general circulation models. The MJO is known to have a stronger cloud-radiative feedback compared to higher frequency convectively coupled equatorial waves (CCEW), for reasons that remain unclear. The objective of this study is to use data from the Dynamics of the MJO/Atmospheric Radiation Measurement MJO Investigation Experiment field campaign to investigate how cloud type evolution and their associated cloud-radiative forcing (CRF) differ between the MJO and CCEWs and their application to MJO dynamics under moisture mode theory. This study finds that the amplitude of CRF is the largest within the MJO compared to the higher frequency CCEWs, and CRF maximizes after the maximum precipitation (enhanced phase) of the MJO. We suggest this delay in the timing of maximum CRF occurs because most cloud types (congestus, deep, anvil, and cirrus) simultaneously maximize in frequency after the enhanced phase of the MJO, which is not seen for the higher frequency CCEWs. These specific cloud types help maintain the MJO through their radiatively-driven moistening which acts to prolong the enhanced phase of the MJO. The decomposition of radiatively-driven moistening by cloud types shows that simultaneous moistening by deep, anvil, and congestus clouds are particularly responsible for the maintenance of the MJO under moisture mode theory. Further, this analysis suggests the importance of capturing the correct evolution of different cloud types and their associated radiative effects to better understand the thermodynamics of the MJO.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part I: The retrieval algorithms

Following the release of the version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version (version 4; V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter and ice or liquid water path estimates. Dedicated retrievals for water clouds were added in V4, taking advantage of the high sensitivity of the IIR retrieval technique to small particle sizes. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results will be presented in a companion (Part II) paper. The IIR Level 2 algorithm has been modified in the V4 data release to improve the accuracy of the retrievals in clouds of very small (close to 0) and very large (close to 1) effective emissivities. To reduce biases at very small emissivities that were made evident in V3, the radiative transfer model used to compute clear-sky brightness temperatures over oceans has been updated and tuned for the simulations using Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) data to match IIR observations in clear-sky conditions. Furthermore, the clear-sky mask has been refined compared to V3 by taking advantage of additional information now available in the V4 CALIOP 5 km layer products used as an input to the IIR algorithm. After sea surface emissivity adjustments, observed and computed brightness temperatures differ by less than ±0.2 K at night for the three IIR channels centered at 08.65, 10.6, and 12.05 µm, and inter-channel biases are reduced from several tens of Kelvin in V3 to less than 0.1 K in V4. We have also improved retrievals in ice clouds having large emissivity by refining the determination of the radiative temperature needed for emissivity computation. The initial V3 estimate, namely the cloud centroid temperature derived from CALIOP, is corrected using a parameterized function of temperature difference between cloud base and top altitudes, cloud absorption optical depth, and CALIOP multiple scattering correction factor. As shown in Part II, this improvement reduces the low biases at large optical depths that were seen in V3 and increases the number of retrievals. As in V3, the IIR microphysical retrievals use the concept of microphysical indices applied to the pairs of IIR channels at 12.05 and 10.6 µm and at 12.05 and 08.65 µm. The V4 algorithm uses ice look-up tables (LUTs) built using two ice habit models from the recent “TAMUice2016” database, namely the single-hexagonal-column model and the eight-element column aggregate model, from which bulk properties are synthesized using a gamma size distribution. Four sets of effective diameters derived from a second approach are also reported in V4. Here, the LUTs are analytical functions relating microphysical index applied to IIR channels 12.05 and 10.6 µm and effective diameter as derived from in situ measurements at tropical and midlatitudes during the Tropical Composition, Cloud, and Climate Coupling (TC4) and Small Particles in Cirrus Science and Operations Plan (SPARTICUS) field experiments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A biogenic secondary organic aerosol source of cirrus ice nucleating particles

Atmospheric ice nucleating particles (INPs) influence global climate by altering cloud formation, lifetime, and precipitation efficiency. The role of secondary organic aerosol (SOA) material as a source of INPs in the ambient atmosphere has not been well defined. Here, we demonstrate the potential for biogenic SOA to activate as depositional INPs in the upper troposphere by combining field measurements with laboratory experiments. Ambient INPs were measured in a remote mountaintop location at –46°C and an ice supersaturation of 30% with concentrations ranging from 0.1 to 70 L –1 . Concentrations of depositional INPs were positively correlated with the mass fractions and loadings of isoprene-derived secondary organic aerosols. Compositional analysis of ice residuals showed that ambient particles with isoprene-derived SOA material can act as depositional ice nuclei. Laboratory experiments further demonstrated the ability of isoprene-derived SOA to nucleate ice under a range of atmospheric conditions. We further show that ambient concentrations of isoprene-derived SOA can be competitive with other INP sources. This demonstrates that isoprene and potentially other biogenically-derived SOA materials could influence cirrus formation and properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Wildfire smoke triggers cirrus formation: lidar observations over the eastern Mediterranean

The number of intense wildfires may increase further in upcoming years as a consequence of climate change. It is therefore necessary to improve our knowledge about the role of smoke in the climate system, with emphasis on the impact of smoke particles on the evolution of clouds, precipitation, and cloud radiative properties. Presently, one key aspect of research is whether or not wildfire smoke particles can initiate cirrus formation. In this study, we present lidar observations over Limassol, Cyprus, from 27 October to 3 November 2020, when extended wildfire smoke fields crossed the Mediterranean Basin from Portugal to Cyprus. We found strong evidence that aged smoke (organic aerosol particles) originating from wildfires in North America triggered significant ice nucleation at temperatures from -47 to -53 °C and caused the formation of extended cirrus layers. The observations suggest that the ice crystals were nucleated just below the tropopause in the presence of smoke particles serving as ice-nucleating particles (INPs). The main part of the 2–3 km thick smoke layer was, however, in the lower stratosphere just above the tropopause. With actual radiosonde observations of temperature and relative humidity and lidar-derived smoke particle surface area concentrations used as starting values, gravity wave simulations show that the lofting of air by 100–200 m is sufficient to initiate significant ice nucleation on the smoke particles, leading to ice crystal number concentrations of 1–100 L -1 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Impacts of Single-Scattering and Microphysical Properties of Ice Particles Smaller Than 100 µm on the Bulk Radiative Properties of Tropical Cirrus

There are large uncertainties in the single-scattering (i.e., morphologies) and microphysical (i.e., concentrations) properties of ice particles whose size are less than ~100 µm. Insufficient resolutions of the most advanced cloud probes (e.g., cloud particle imager) cannot resolve the micrometer-scale morphologies of small ice particles. Further, the shattering of large ice particles on probes’ inlets or tips causes uncertainties in the measurement of the concentrations of small ice particles. These uncertainties have large impacts on the single-scattering and microphysical properties of small ice particles that are utilized to quantify the bulk radiative properties of cirrus. In this study, the impacts of uncertainties in the morphologies and concentrations of small ice particles on the bulk radiative properties of tropical cirrus were calculated using measurements acquired during the Tropical Warm Pool-International Cloud Experiment. Five different models (i.e., budding Buckyball, Chebyshev particle, droxtal, Gaussian random sphere, and sphere) that represent the shapes of small ice particles were used to calculate the single-scattering properties. The bulk radiative properties, average phase-function ($\overline{P_{11}}$), and average asymmetry parameter ($\overline{g}$) were computed by combining the measured size/habit distributions and the calculated single-scattering properties of ice particles. The impacts of the selection of varying morphologies of small particles on the bulk radiative properties were quantified. For these calculations, the possible range of the concentrations of small ice particles which depend on the degree of shattered large particles were also used. The impacts of varying the single-scattering properties of small ice particles on the bulk radiative properties were the largest in the upper parts of cirrus (T < –60 °C), while they were the smallest in the lower parts of cirrus (–45 < T < –30 °C). The impacts of uncertainties in the concentrations of small ice particles on the bulk radiative properties were largest in the lower parts of cirrus (–45 < T < –30 °C), whereas they were smallest in the upper parts of cirrus (T < –60 °C). The effect of shattering was maximum in the lower parts of cirrus, whilst it was minimum in the upper parts of cirrus. The combined impacts of uncertainties in the single-scattering (i.e., morphologies) and microphysical (i.e., concentrations) properties of small ice particles revealed variations of up to 11.2% (127.1%; 67.3%) of the integrated intensity in the forward (sideward; backward) angles in $\overline{P_{11}}$ and a corresponding change in $\overline{g}$ by up to 12.61%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Impact of host climate model on contrail cirrus effective radiative forcing estimates

Estimates of aviation effective radiative forcing (ERF) indicate that contrail cirrus is currently its largest contributor, although with a substantial associated uncertainty of ∼ 70 %. Here, we implement the contrail parameterisation developed for the Community Atmosphere Model (CAM) in the UK Met Office Unified Model (UM), allowing us to compare, for the first time, the impact of key features of the host climate model on contrail cirrus ERF. We find that differences in background humidity between the models result in the UM-simulated contrail fractions being 2 to 3 times larger than in CAM. Additionally, the models show contrasting responses in overall global cloud fraction, with contrails increasing the total cloud fraction in the UM and decreasing it in CAM. Differences in the complexity of the cloud microphysics schemes lead to significant differences in simulated changes to cloud ice water content due to aviation. After compensating for the unrealistically low contrail optical depth in the UM, we estimate the 2018 contrail cirrus ERF to be 40.8 mW m−2 in the UM, compared to 60.1 mW m−2 in CAM. These values highlight the substantial uncertainty in contrail cirrus ERF due to differences in microphysics and radiation schemes between the two models. We also find a factor-of-8 uncertainty in contrail cirrus ERF due to existing uncertainty in contrail cirrus optical depth. Future research should focus on better representing microphysical and radiative contrail characteristics in climate models and on improved observational constraints.

Zhang, Weiyu [University of Leeds (United Kingdom)↗
DOE OSTI2021

Cloud, Aerosol, and Radiative Properties Over the Western North Atlantic Ocean

This study examines the atmospheric properties of weather states (WSs) derived from the International Satellite Cloud Climatology Project (ISCCP) over the Western North Atlantic Ocean. In particular, radiation and aerosol data corresponding to two sites in the study domain, Pennsylvania State University and Bermuda, were examined to characterize the atmospheric properties of the various satellite-derived WSs. At both sites, the fair weather WS was most prevalent, followed by the cirrus WS. Differences in the seasonality of the various WSs were observed at the two sites. Fractional sky cover and effective shortwave cloud transmissivity derived from ground-based radiation measurements were able to capture differences among the satellite-derived WSs. Speciated aerosol optical thicknesses (AOT) from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) were used to investigate potential differences in aerosol properties among the WSs. The clear sky WS exhibited below-average seasonal values of AOT at both sites year-round, as well as relatively high rates of occurrence with low AOT events. In addition, the clear sky WS showed above-average contributions from dust and black carbon to the total AOT year-round. Finally, transitions between various WSs were examined under low, high, and mid-range AOT conditions. The most common pathway was for the WSs to remain in the same state after a 3 hr interval. Some WSs, such as midlatitude storms, deep convection, middle top, and shallow cumulus, were more prevalent as ending states under high AOT conditions. This work motivates examining differences in aerosol properties between WSs in other regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Annual cycle of aerosol properties over the central Arctic during MOSAiC 2019–2020 – light-extinction, CCN, and INP levels from the boundary layer to the tropopause

Abstract. The MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition was the largest Arctic field campaign ever conducted. MOSAiC offered the unique opportunity to monitor and characterize aerosols and clouds with high vertical resolution up to 30 km height at latitudes from 80 to 90∘ N over an entire year (October 2019 to September 2020). Without a clear knowledge of the complex aerosol layering, vertical structures, and dominant aerosol types and their impact on cloud formation, a full understanding of the meteorological processes in the Arctic, and thus advanced climate change research, is impossible. Widespread ground-based in situ observations in the Arctic are insufficient to provide these required aerosol and cloud data. In this article, a summary of our MOSAiC observations of tropospheric aerosol profiles with a state-of-the-art multiwavelength polarization Raman lidar aboard the icebreaker Polarstern is presented. Particle optical properties, i.e., light-extinction profiles and aerosol optical thickness (AOT), and estimates of cloud-relevant aerosol properties such as the number concentration of cloud condensation nuclei (CCN) and ice-nucleating particles (INPs) are discussed, separately for the lowest part of the troposphere (atmospheric boundary layer, ABL), within the lower free troposphere (around 2000 m height), and at the cirrus level close to the tropopause. In situ observations of the particle number concentration and INPs aboard Polarstern are included in the study. A strong decrease in the aerosol amount with height in winter and moderate vertical variations in summer were observed in terms of the particle extinction coefficient. The 532 nm light-extinction values dropped from >50 Mm−1 close to the surface to <5 Mm−1 at 4–6 km height in the winter months. Lofted, aged wildfire smoke layers caused a re-increase in the aerosol concentration towards the tropopause. In summer (June to August 2020), much lower particle extinction coefficients, frequently as low as 1–5 Mm−1, were observed in the ABL. Aerosol removal, controlled by in-cloud and below-cloud scavenging processes (widely suppressed in winter and very efficient in summer) in the lowermost 1–2 km of the atmosphere, seems to be the main reason for the strong differences between winter and summer aerosol conditions. A complete annual cycle of the AOT in the central Arctic could be measured. This is a valuable addition to the summertime observations with the sun photometers of the Arctic Aerosol Robotic Network (AERONET). In line with the pronounced annual cycle in the aerosol optical properties, typical CCN number concentrations (0.2 % supersaturation level) ranged from 50–500 cm−3 in winter to 10–100 cm−3 in summer in the ABL. In the lower free troposphere (at 2000 m), however, the CCN level was roughly constant throughout the year, with values mostly from 30 to 100 cm−3. A strong contrast between winter and summer was also given in terms of ABL INPs which control ice production in low-level clouds. While soil dust (from surrounding continents) is probably the main INP type during the autumn, winter, and spring months, local sea spray aerosol (with a biogenic aerosol component) seems to dominate the ice nucleation in the ABL during the summer months (June–August). The strong winter vs. summer contrast in the INP number concentration by roughly 2–3 orders of magnitude in the lower troposphere is, however, mainly caused by the strong cloud temperature contrast. A unique event of the MOSAiC expedition was the occurrence of a long-lasting wildfire smoke layer in the upper troposphere and lower stratosphere. Our observations suggest that the smoke particles frequently triggered cirrus formation close to the tropopause from October 2019 to May 2020.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Prospects for future studies using deep imaging: analysis of individual Galactic cirrus filaments

The presence of Galactic cirrus is an obstacle for studying both faint objects in our Galaxy and low surface brightness extragalactic structures. With the aim of studying individual cirrus filaments in Sloan Digital Sky Survey (SDSS) Stripe 82 data, we develop techniques based on machine learning and neural networks that allow one to isolate filaments from foreground and background sources in the entirety of Stripe 82 with a precision similar to that of the human expert. Our photometric study of individual filaments indicates that only those brighter than 26 mag arcsec −2 in the SDSS r band are likely to be identified in SDSS Stripe 82 data by their distinctive colours in the optical bands. We also show a significant impact of data processing (e.g. flat-fielding, masking of bright stars, and sky subtraction) on colour estimation. Analysing the distribution of filaments’ colours with the help of mock simulations, we conclude that most filaments have colours in the following ranges: 0.55 ≤g − r ≤ 0.73 and 0.01 ≤ r − i ≤ 0.33. Our work provides a useful framework for an analysis of all types of low surface brightness features (cirri, tidal tails, stellar streams, etc.) in existing and future deep optical surveys. For practical purposes, we provide the catalogue of dust filaments.

79 ASTRONOMY AND ASTROPHYSICS↗