Analytical Mechanics Associates (United States)

The planetary boundary layer confines moisture, turbulence, and locally emitted air pollutants, thus accurately discerning the height of this layer is important for constraining pollutant transport and distribution and improved regional weather and climate forecasting. Traditional methods of boundary layer height (BLH) determination rely on radiosonde measurements of potential temperature profiles. However, these sounding measurements lack the instrumentation needed to characterize the chemical composition of the boundary layer that can be provided by larger airborne platforms. In 2024, the NASA DC-8 flew over the Philippines, South Korea, Taiwan, and Thailand during the Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ) campaign. Measurements during this campaign included an extensive array of gas, particulate, and meteorological measurements. We will present results of a turbulence-based method using 3D winds to determine the boundary layer height across DC-8 vertical flight profiles, including missed approaches at urban airports. The results from this method were used to develop a boundary layer flag for the campaign, and the computed DC-8 BLHs were compared to mixed layer heights determined by an airborne-based LIDAR system.

<strong class="journal-contentHeaderColor">Abstract.</strong> Aerosols in the upper troposphere play an important role in Earth&rsquo;s radiative balance and atmospheric composition. Satellite observations have revealed a recurrent enhancement of aerosol extinction coefficient (AEC) in the upper troposphere and near the tropopause over the Asian summer monsoon (ASM) anticyclone (ASMA) region during July&ndash;August. However, substantial uncertainties remain regarding (i) the influence of ASM dynamics and climate variability on these aerosols, (ii) the extent to which the upper-tropospheric aerosol trends reflect changes in surface pollutant emissions, and (iii) the ability of global models to simulate aerosol amounts, variability, and key controlling processes in the upper-tropospheric ASMA region. Here, we present results from an AeroCom-coordinated global multi-model study addressing these issues. Using simulations from nine models for 2000&ndash;2018, we find large inter-model differences in non-volcanic AEC over the upper-tropospheric ASMA region, with coefficients of variation ranging from 64 % to 86 %. Approximately half of this spread is attributable to differences in transport and wet removal processes, as diagnosed using common tracers, with discrepancies in wet removal contributing about eight times more than those associated with transport. The multi-model ensemble indicates an overall increase in non-volcanic AEC over the past two decades, consistent with rising anthropogenic emissions in Asia, while interannual variability is linked to climate variability as represented by the Multivariate ENSO Index. Through comparison with satellite observations, we further identify persistent model deficiencies, particularly in the representation of volcanic aerosols, and highlight priorities for future coordinated model developments and evaluation.

Urban Air Mobility (UAM) is a rapidly emerging industry targeting delivery of air transportation services around metropolitan areas with the potential for aviation to become a practical part of everyday life while leveraging emerging technologies and operational concepts. This whitepaper, a collaboration between NASA’s Air Mobility Pathfinders (AMP) project and Wisk, explores the interoperability between crewed and uncrewed aircraft in UAM operations, leveraging operational concepts put forth in the Federal Aviation Administration (FAA) UAM Concept of Operations (ConOps) for the Midterm UAM phase. Specifically, UAM aircraft are envisioned to takeoff and land from vertiports and primarily operate within Cooperative Areas (CAs). CAs are designated as airspace volumes with specific requirements for performance, communication, and surveillance in which UAM Operators follow cooperative operating practices (COPs). Additionally, Third-Party Service Providers (TSPs) are envisioned to play a crucial role in conflict management, including both strategic and tactical deconfliction within the CAs.

Experimentally measured nuclear fragment-production cross-sections are needed for the development of cross-section models implemented in the radiation transport codes used for several endpoints, including radiation protection and health risk assessment in space. Elemental and isotopic fragment-production cross-section data have been collected from literature in a publicly available database through a combined GSI-ESA-NASA effort. The collected data for systems of interest for space exploration are discussed, and the literature gaps are indicated. The data are also compared with the nuclear fragmentation models implemented in the NASA radiation transport code HZETRN2020, namely NUCFRG3 and RAADFRG. The results show that NUCFRG3 does not take into account nuclear-structure effects, while RAADFRG does. Therefore, RAADFRG can estimate more precisely the production of certain projectile fragments, in particular helium. Nevertheless, for some systems and high energies, RAADFRG overestimates the oscillations due to odd-even effects.

<strong class="journal-contentHeaderColor">Abstract.</strong> Aerosol-cloud-precipitation interactions are assessed over the non-polar ocean from more than 11 years of combined Aqua-MODIS, CALIPSO-CALIOP, and CloudSat products. The analysis first shows the benefit of incorporating vertically resolved aerosol extinction coefficient (&sigma;<em>_ext</em>) in aerosol-cloud interactions (ACI) assessments, demonstrating that: &sigma;<em>_ext</em> vertically collocated with the cloud layer correlates best with cloud droplet number concentration (<em>N_d</em>), column-integrated aerosol optical depth (AOD) cannot explain the <em>N_d</em> variability in the extratropics, and the S-shape of the AOD-<em>N_d</em> relationship reported in previous studies is an unphysical feature that arises from using AOD as aerosol proxy over oceanic regions. ACI metric, estimated as the log-scale regression between &sigma;<em>_ext</em> vertically collocated with the cloud layer (&sigma;<em>_exi^CL</em>) and MODIS <em>N_d</em> reveals that the eastern Pacific is the region with the strongest ACI, followed by the Southern Ocean. The susceptibility of clouds to changes in their liquid water path (LWP) and frequency of precipitation followed a 2-step calculation by combining the <em>N_d</em>-&sigma;<em>_exi^CL</em> regression (ACI) with the regression between these macrophysical variables and <em>N_d</em>.LWP susceptibility is negative (LWP decreases with aerosol loading), and statistically significant over the eastern Pacific, eastern Atlantic, and extratropics. In contrast, vast areas of the tropical and subtropical ocean feature negligible changes in LWP with aerosol. Precipitation frequency susceptibility is negative, but the values are only significant over the coastal eastern Pacific and Atlantic. The findings suggest that previous modeling assessments relying on AOD may need to be revisited by taking advantage of the synergy between passive and active sensors.

Abstract Hailstorms exhibit distinct signatures in spaceborne remote sensing datasets, namely, overshooting cloud tops (OTs) in infrared (IR) imagery or large brightness temperature depressions in passive-microwave radiometer (MWR) imagery. Approaches that leverage these signatures are prone to several issues, e.g., nonuniform beamfilling in MWR datasets or insensitivity to processes below cloud top in IR imagery. Upwelling MWR can also be scattered to extremely low brightness temperatures by high concentrations of graupel-sized ice scatterers. To address this, we investigate Aqua IR, and MWR observations paired with ground-based radar maximum expected size of hail (MESH), and reanalysis environmental parameters over the continental United States. We observe that storms with low (&lt;250 K) 19-GHz brightness temperatures tend to exhibit larger, deeper OTs and a decreasing probability of large MESH with very low (&lt;180 K) 37-GHz brightness temperature. To capture the complex MWR, IR, and environmental parameter interactions, we train a deep neural network (DNN) to estimate severe hail likelihood for a given suite of Aqua observations and reanalysis variables. Leveraging these datasets in combination produces a critical success index of 0.593 and a Heidke skill score of 0.401. The satellite observation analysis and performance assessment using the DNN suggest the relationships between likelihood of large hail (vs smaller hail/graupel) and satellite parameters are complex and nonlinear. The analysis suggests that passive-microwave channels with shorter wavelengths (&lt;1 cm) are vulnerable to scattering from smaller particles, and that hail retrievals mistakenly flag these occurrences as hail, thereby pointing to error sources in previously documented climatologies. Significance Statement Satellites provide the most uniform way to map the distribution of severe weather like hail: They can observe across the globe and provide data in otherwise unreachable locations, like remote areas or over the ocean. For decades, satellite datasets have been used to estimate the global climatology of hail. Two of the most prominent datasets used are infrared (IR) cloud-top products and passive-microwave radiometer (MWR). These approaches are standard but suffer from biases, and this can result in hail being overestimated in the tropics. In this paper, we explore some of those issues to understand where the satellite datasets’ vulnerabilities are and how we might use them together to produce a more accurate result. The relationships we discover turn out to be very complex, so we explore a deep neural network machine learning model to quantify the performance of IR and MWR datasets in detecting likely severe hail over the United States.

The main goal of this paper is to demonstrate the application of metric-based mesh adaptation to real gas problems and highlight the benefits particularly when complex geometries are considered. We use the Hessian of the temperature solution as an indicator to dictate where the mesh needs refinement or coarsening. In the context of hypersonic flow simulations, these methods are not widely adopted since unstructured meshes often result in poor surface heating predictions. The present work aims to demonstrate the great flexibility metric-based mesh adaptation provides when it comes to predicting complex flow features while still maintaining comparable surface heating predictions. We consider two test cases: (a) a supersonic flow over a hemisphere and show that comparable surface heating is obtained by applying mesh adaptation and by employing hexahedra instead of prisms in the boundary layer mesh; (b) we consider a more realistic test case of a hypersonic flow of a 𝐶𝑂₂-𝑁₂ mixture past a 70^◦ sphere cone atmospheric entry capsule. For the second test case, similar surface heating predictions are obtained compared to more conventional block structured DPLR simulations. Furthermore, for the adapted unstructured simulations, the geometries of the eight Reaction Control System (RCS) jet on the backshell were taken into account. This highlights the ability of these methods to deal with complex geometries that are typically out of reach for block structured approaches.

Wall-modeled large-eddy simulations (WMLESs) of turbulent flow over a two-dimensional 30P30N multi-element airfoil at various angles of attack are performed using an unstructured finite-volume solver to document the sensitivity of the predictions to the computational grid. The stowed chord-based Reynolds number (Rec) is 9 million, and the angle of attack (α) is varied between 8 and 23 deg with the expected stall angle around 21 deg. We first analyze the predictions with baseline near-wall isotropic and mildly anisotropic grids. The predicted lift, wall pressure, near-wall velocity profiles, and the location of onset of resolved turbulence are sensitive to the near-wall grid anisotropy. The lift is better predicted at lower angles with the isotropic grid and at higher angles with the anisotropic grid. We then explore the sensitivities at lower angles of attack to independently vary the streamwise and wall-normal grid anisotropies to isolate their effects and to off-wall and near-wall grid refinement. The effects of streamwise grid refinement near the leading and trailing edges and off-body grid refinement away from the surface appear to have minimal effects on the predictions for this flow configuration. However, the wall-normal grid resolution in the vicinity of the surfaces has a dominant effect on the results. Our results suggest a monotonic trend for lift and other quantities based on the absolute value of the first wall-normal spacing, which coincides with the WMLES exchange location in our solver. Finally, for the same grid resolution away from the wall, varying the wall-normal spacing near the surface based on the angle of attack may lead to more optimal grid counts for WMLES.

Abstract. Cirrus clouds can form through two ice nucleation pathways (homo- and heterogeneous ice nucleation; henceforth hom and het, respectively) that result in very different cloud physical and radiative properties. While important to the climate system, they are poorly understood due to lack of knowledge on the relative roles of hom and het. This study differs from earlier relevant studies by estimating the relative radiative contribution of hom-affected cirrus clouds. Here, we employ new global retrievals (described in Part 1: Mitchell et al., 2025; henceforth M2025) of cirrus cloud ice particle number concentration, effective diameter (De), ice water content (IWC), shortwave extinction coefficient (αext), optical depth (τ) and cloud radiative temperature based on Imaging Infrared Radiometer (IIR) and Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP) co-located observations onboard Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). Transition from het dominated to hom-affected regimes are identified using αext and De. Over oceans outside the tropics in winter, the zonal fraction of hom-affected cirrus generally ranges between 20 % and 35 %, with comparable contributions from in situ and warm base cirrus. Using τ distributions to establish a proxy for net cloud radiative effect (CRE), the τ-weighted fraction for hom-affected cirrus over oceans outside the tropics during winter was &gt; 50 %, indicating that hom cirrus play an important role in climate. Using these retrievals (including those relating to the cloud geometric thickness), a conceptual model of cirrus cloud characterization is proposed.