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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Agricultural Burning and Air Quality over Northern India: A Synergistic Analysis using NASA’s A-train Satellite Data and Ground Measurements

In recent years, New Delhi, the capital city of India, has been ranked among the most polluted cities in the world in terms of air quality related to Particulate Matter (PM). In this paper, we show that the PM 2.5 , a major component of the measure of air quality, over New Delhi is strongly impacted by the agricultural fires in the north-western Indian states of Punjab and Haryana during the post-monsoon season (October and November). Using data from NASA’s A-train sensors (MODIS, OMI, and CALIOP) in conjunction with the ground-level PM 2.5 mass concentration measured at the US Embassy site in New Delhi (2013-2015), and back-trajectory analysis, it is shown that the smoke particles produced from numerous fires in Punjab and Haryana are advected over the national capital region under the influence of north-westerly winds, thereby greatly increasing the ground-level PM 2.5 from 50 µg/m -3 before the onset of burning in early October to as high as 300 µg/m -3 (24-hour averaged, 7-day running mean) during the peak burning period in early November. Relationships between the satellite measurements of fire counts and aerosols in the crop burning region and PM 2.5 over New Delhi are found to be strongly correlated. A linear regression analysis reveals that increments in the fire counts, aerosol optical depth, UV Aerosol Index, and aerosol absorption optical depth by 100, 1.0, 1.0, and 0.1 over the burning areas result in an increase in PM 2.5 by 20, 47, 134, and 142 µg/m -3 , respectively, over New Delhi. Back-trajectory analysis shows that about 74%, 62%, and 51% of total number of daily trajectories for altitudes 10 m, 500 m, and 1500 m, respectively, intercepted the biomass burning region before arriving at the receptor location in New Delhi; this further corroborates the transport mechanism observed in the satellite data. A 15-year long record of A-train satellite measurements shows an increasing number of agricultural fires (29% higher) and aerosol loading during the second half of the record (2009-2015) compared to that during the first half (2002-2008), which is one of the major concerns for the deteriorating air quality in the region.

54 ENVIRONMENTAL SCIENCES↗

Ice particle production in mid-level stratiform mixed-phase clouds observed with collocated A-Train measurements

Abstract. Collocated A-Train CloudSat radar and CALIPSO lidar measurements between 2006 and 2010 are analyzed to study primary ice particle production characteristics in mid-level stratiform mixed-phase clouds on a global scale. For similar clouds in terms of cloud top temperature and liquid water path, Northern Hemisphere latitude bands have layer-maximum radar reflectivity (ZL) that is ∼ 1 to 8 dBZ larger than their counterparts in the Southern Hemisphere. The systematically larger ZL under similar cloud conditions suggests larger ice number concentrations in mid-level stratiform mixed-phase clouds over the Northern Hemisphere, which is possibly related to higher background aerosol loadings. Furthermore, we show that springtime northern mid- and high latitudes have ZL that is larger by up to 6 dBZ (a factor of 4 higher ice number concentration) than other seasons, which might be related to more dust events that provide effective ice nucleating particles. Our study suggests that aerosol-dependent ice number concentration parameterizations are required in climate models to improve mixed-phase cloud simulations, especially over the Northern Hemisphere.

47 OTHER INSTRUMENTATION↗

The correlation between Arctic sea ice, cloud phase and radiation using A-Train satellites

Abstract. Climate warming has a stronger impact on Arctic climate and sea ice cover (SIC) decline than previously thought. Better understanding and characterization of the relationship between sea ice and clouds and the implications for surface radiation is key to improving our confidence in Arctic climate projections. Here we analyze the relationship between sea ice, cloud phase and surface radiation over the Arctic, defined as north of 60° N, using active- and passive-sensor satellite observations from three different datasets. We find that all datasets agree on the climatology of and seasonal variability in total and liquid-bearing (liquid and mixed-phase) cloud covers. Similarly, our results show a robust relationship between decreased SIC and increased liquid-bearing clouds in the lowest levels (below 3 km) for all seasons (strongest in winter) but summer, while increased SIC and ice clouds are positively correlated in two of the three datasets. A refined map correlation analysis indicates that the relationship between SIC and liquid-bearing clouds can change sign over the Bering, Barents and Laptev seas, likely because of intrusions of warm air from low latitudes during winter and spring. Finally, the increase in liquid clouds resulting from decreasing SIC is associated with enhanced radiative cooling at the surface. Our findings indicate that the newly formed liquid clouds reflect more shortwave (SW) radiation back to space compared to the surface, generating a cooling effect of the surface, while their downward longwave (LW) radiation is similar to the upward LW surface emission, which has a negligible radiative impact on the surface. This overall cooling effect should contribute to dampening future Arctic surface warming as SIC continues to decline.

54 ENVIRONMENTAL SCIENCES↗

Distinct Contributions of Ice Nucleation, Large-Scale Environment, and Shallow Cumulus Detrainment to Cloud Phase Partitioning With NCAR CAM5

Mixed-phase clouds containing both liquid droplets and ice particles occur frequently at high latitudes and in the midlatitude storm track regions. Simulations of the cloud phase partitioning between liquid and ice hydrometeors in state-of-the-art global climate models are still associated with large biases. For this study, the phase partitioning in terms of liquid mass phase ratio (MPR liq , defined as the ratio of liquid mass to total condensed water mass) simulated from the NCAR Community Atmosphere Model version 5 (CAM5) is evaluated against the observational data from A-Train satellite remote sensors. Modeled MPR liq is significantly lower than observations on the global scale, especially in the Southern Hemisphere (e.g., Southern Ocean and the Antarctic). Sensitivity tests with CAM5 are conducted to investigate the distinct contributions of heterogeneous ice nucleation, shallow cumulus detrainment, and large-scale environment (e.g., winds, temperature, and water vapor) to the low MPR liq biases. Our results show that an aerosol-aware ice nucleation parameterization increases the MPR liq especially at temperatures colder than -20°C and significantly improves the model agreements with observations in the Polar regions in summer. The decrease of threshold temperature over which all detrained cloud water is liquid from 268 to 253 K enhances the MPR liq and improves the MPR liq mostly over the Southern Ocean. By constraining water vapor in CAM5 toward reanalysis, modeled low biases in many geographical regions are largely reduced through a significant decrease of cloud ice mass mixing ratio.

47 OTHER INSTRUMENTATION↗

Neural network potentials with effective charge separation for non-equilibrium dynamics of ionic solids: a ZnO case study

Developing neural network potentials (NNPs) accurate under non-equilibrium dynamics is challenging, as such systems require extensive sampling beyond equilibrium phases. Here we construct high-fidelity NNPs for zinc oxide (ZnO), a polymorphic ionic solid, using density functional theory (DFT) reference data. To efficiently capture transitional configurations, we combine enhanced-sampling molecular dynamics with empirical potentials, data distillation, and pretraining on short-range atomic energies (A-Train), followed by transfer learning with DFT-relabeled datasets. This hierarchical approach improves transferability across polymorphs and stress states. We further introduce effective charge separation, treating long-range Coulombic terms analytically while short-range residual interactions are learned by the NNP. The optimal effective charges fall in the range 0.5–1.0 q e , consistent with dielectric-screened values derived from formal charges but distinct from Bader estimates. Motivated by this observation, we propose a simple data-driven protocol in which effective charges are optimized by comparing DFT reference energies with explicit Coulomb calculations, without additional NNP training. This strategy improves accuracy and transferability in DFT-level predictions of energies, forces, and stress. Together, these results provide a practical charge-selection framework for robust NNP development in ionic solids, enabling reliable simulation of polymorphic phase transformations and non-equilibrium dynamics.

Chemistry↗

Upper troposphere dust belt formation processes vary seasonally and spatially in the Northern Hemisphere

Dust aerosols impact global energy balance substantially by acting as efficient ice nuclei to alter cold cloud properties. However, the estimate of dust indirect effect remains uncertain due to simulating dust distributions poorly and lacking reliable dust observations, especially in the upper-troposphere. Here, we characterize and understand upper-troposphere dust sources and transport with an improved dust dataset derived from A-train satellite lidar and radar measurements and an air parcel trajectory model. The distinct upper-troposphere dust belt over the northern hemisphere has seasonally varying base and top heights of 3.65 ± 2.84 and 8.35 ± 1.50 km above mean sea level and its column loading is strongest during spring (March-April-May). The out-of-phase annual cycles of mid-level dust concentration and westerly wind over source regions control the seasonal upper-tropospheric dust loading variations. African deserts contribute the most (46.3%) to the upper-troposphere dust belt in spring and the synoptic trough is the leading (49%) dust lifting mechanism.

54 ENVIRONMENTAL SCIENCES↗

AMF3 CloudSat Overpasses Field Campaign Report

Synergy between ground-based and satellite radar observations of clouds and precipitation is important for refining the algorithms to retrieve hydrometeor microphysical parameters, improvements in the retrieval accuracy, and better understanding the advantages and limitations of different retrieval approaches. The new dual-frequency (Ka- and W-band, 35 GHz and 94 GHz) fully polarimetric scanning U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Research Facility cloud radars (SACRs-2) are advanced sensors aimed to significantly enhance remote sensing capabilities (Kollias et al. 2016). One of these radars was deployed as part of the third ARM Mobile Facility (AMF3) at Oliktok Point, Alaska (70.495o N, 149.886oW). The National Aeronautics and Space Administration (NASA) CloudSat satellite, which is part of the polar-orbiting A-train satellite constellation, passes over the vicinity of the AMF3 location (typically within 0-7 km depending on a particular overpass) on a descending orbit every 16 days at approximately 13:21 UTC. The nadir pointing W-band CloudSat cloud profiling radar (CPR) provides vertical profiles of reflectivity that are then used for retrievals of hydrometeor parameters (Tanelli et al. 2008). The main objective of the AMF3 CloudSat overpasses intensive operating period (IOP) campaign was to collect approximately collocated in space and time radar data from the SACR-2 and the CloudSat CPR measurements for subsequent joint analysis of radar variables and microphysical retrievals of cloud and precipitation parameters. Providing the reference for the SACR-2 absolute calibration from the well-calibrated CloudSat CPR was another objective of this IOP. The IOP objectives were achieved by conducting seven special SACR-2 scans during the 10.5-min period centered at the exact time of the CloudSat overpass over the AMF3 (~1321 UTC) on six dates of the CloudSat overpasses during the three-month period allocated to this IOP. These six days were March 5 and 21, April 6 and 22, and May 8 and 24.

54 ENVIRONMENTAL SCIENCES↗

Aerosol-induced closure of marine cloud cells: enhanced effects in the presence of precipitation

Abstract. The Weather Research Forecasting (WRF) version 4.3 model is configured within a Lagrangian framework to quantify the impact of aerosols on evolving cloud fields. Kilometer-scale simulations utilizing meteorological boundary conditions are based on 10 case study days offering diverse meteorology during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA). Measurements from aircraft, the ground-based Atmosphere Radiation Measurement (ARM) site at Graciosa Island in the Azores, and A-Train and geostationary satellites are utilized for validation, demonstrating good agreement with the WRF-simulated cloud and aerosol properties. Higher aerosol concentration leads to suppressed drizzle and increased cloud water content in all case study days. These changes lead to larger radiative cooling rates at cloud top, enhanced vertical velocity variance, and increased vertical and horizontal wind speed near the base of the lower-tropospheric inversion. As a result, marine cloud cell area expands, narrowing the gap between shallow clouds and increasing cloud optical thickness, liquid water content, and the top-of-atmosphere outgoing shortwave flux. While similar aerosol effects are observed in lightly to non-raining clouds, they tend to be smaller by comparison. These simulations show a relationship between cloud cell area expansion and the radiative adjustments caused by liquid water path and cloud fraction changes. The adjustments are positive and scale as 74 % and 51 %, respectively, relative to the Twomey effect. While higher-resolution large-eddy simulations may provide improved representation of cloud-top mixing processes, these results emphasize the importance of addressing mesoscale cloud-state transitions in the quantification of aerosol radiative forcing that cannot be attained from traditional climate models.

54 ENVIRONMENTAL SCIENCES↗