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Abstract The Hunga Tonga‐Hunga Ha'apai (Hunga) volcanic eruption in January 2022 injected a substantial amount of water vapor and a moderate amount of SO₂into the stratosphere. Both satellite observations in 2022 and subsequent chemistry‐climate model simulations forced by realistic Hunga perturbations reveal large‐scale cooling in the Southern Hemisphere (SH) tropical to subtropical stratosphere following the Hunga eruption. This study analyzes the drivers of this cooling, including the distinctive role of anomalies in water vapor, ozone, and sulfate aerosol concentration on the simulated climate response to the Hunga volcanic forcing, based on climate simulations with prescribed chemistry/aerosol. Simulated circulation and temperature anomalies based on specified‐chemistry simulations show good agreement with previous coupled‐chemistry simulations and indicate that each forcing of ozone, water vapor, and sulfate aerosol from the Hunga volcanic eruption contributed to the circulation and temperature anomalies in the SH stratosphere. Our results also suggest that (a) the large‐scale stratospheric cooling during the austral winter was mainly induced by changes in dynamical processes, not by radiative processes, and that (b) the radiative feedback from negative ozone anomalies contributed to the prolonged cold temperature anomalies in the lower stratosphere (∼70 hPa level) and hence to long lasting cold conditions of the polar vortex. 

Abstract The global energy budget is pivotal to understanding planetary evolution and climate behaviors. Assessing the energy budget of giant planets, particularly those with large seasonal cycles, however, remains a challenge without long-term observations. Evolution models of Saturn cannot explain its estimated Bond albedo and internal heat flux, mainly because previous estimates were based on limited observations. Here, we analyze the long-term observations recorded by the Cassini spacecraft and find notably higher Bond albedo (0.41 ± 0.02) and internal heat flux (2.84 ± 0.20 Wm⁻²) values than previous estimates. Furthermore, Saturn’s global energy budget is not in a steady state and exhibits significant dynamical imbalances. The global radiant energy deficit at the top of the atmosphere, indicative of the planetary cooling of Saturn, reveals remarkable seasonal fluctuations with a magnitude of 16.0 ± 4.2%. Further analysis of the energy budget of the upper atmosphere including the internal heat suggests seasonal energy imbalances at both global and hemispheric scales, contributing to the development of giant convective storms on Saturn. Similar seasonal variabilities of planetary cooling and energy imbalance exist in other giant planets within and beyond the Solar System, a prospect currently overlooked in existing evolutional and atmospheric models. 

Abstract MotivationGenome-wide association studies (GWAS) benefit from the increasing availability of genomic data and cross-institution collaborations. However, sharing data across institutional boundaries jeopardizes medical data confidentiality and patient privacy. While modern cryptographic techniques provide formal secure guarantees, the substantial communication and computational overheads hinder the practical application of large-scale collaborative GWAS. ResultsThis work introduces an efficient framework for conducting collaborative GWAS on distributed datasets, maintaining data privacy without compromising the accuracy of the results. We propose a novel two-step strategy aimed at reducing communication and computational overheads, and we employ iterative and sampling techniques to ensure accurate results. We instantiate our approach using logistic regression, a commonly used statistical method for identifying associations between genetic markers and the phenotype of interest. We evaluate our proposed methods using two real genomic datasets and demonstrate their robustness in the presence of between-study heterogeneity and skewed phenotype distributions using a variety of experimental settings. The empirical results show the efficiency and applicability of the proposed method and the promise for its application for large-scale collaborative GWAS. Availability and implementationThe source code and data are available at https://github.com/amioamo/TDS. 

Abstract To understand diurnal variations in PM_2.5composition and aerosol extract absorption, PM_2.5samples were collected at intervals of 2 hr from 8:00 to 20:00 and 6 hr from 20:00 to 8:00 (the next day) in northern Nanjing, China, during the winter and summer of 2019–2020 and analyzed for bulk components, organic tracers, and light absorption of water and methanol extracts—a proxy measure of brown carbon (BrC). Diurnal patterns of measured species reflected the influences of primary emissions and atmospheric processes. Light absorption coefficients of water (Abs_365,w) and methanol extracts (Abs_365,m) at 365 nm shared a similar diurnal profile peaking at 18:00–20:00, generally following changes in biomass burning tracers. However, Abs_365,w, Abs_365,m, and their normalizations to organic aerosols increased at 14:00–16:00, earlier than that of levoglucosan in the late afternoon, which was attributed to secondarily formed BrC. The methanol extracts showed a less drastic decrease in light absorption at night than the water extracts and elevated absorption efficiency during 2:00–8:00. This is due to the fact that the water‐insoluble OC has a longer lifetime and stronger light absorption than the water‐soluble OC. According to the source apportionment results solved by positive matrix factorization (PMF), biomass burning and secondary formation were the major BrC sources in northern Nanjing, with an average total relative contribution of about 90%. Compared to previous studies, diurnal source cycles were added to the PMF simulations in this work by using time‐resolved speciation data, which avoided misclassification of BrC sources. 

Abstract Multiple species within the order Hemiptera cause severe agricultural losses on a global scale. Aphids and whiteflies are of particular importance due to their role as vectors for hundreds of plant viruses, many of which enter the insect via the gut. To facilitate the identification of novel targets for disruption of plant virus transmission, we compared the relative abundance and composition of the gut plasma membrane proteomes of adultBemisia tabaci(Hemiptera: Aleyrodidae) andMyzus persicae(Hemiptera: Aphididae), representing the first study comparing the gut plasma membrane proteomes of two different insect species. Brush border membrane vesicles were prepared from dissected guts, and proteins extracted, identified and quantified from triplicate samples via timsTOF mass spectrometry. A total of 1699B. tabaciand 1175M. persicaeproteins were identified. Following bioinformatics analysis and manual curation, 151B. tabaciand 115M. persicaeproteins were predicted to localize to the plasma membrane of the gut microvilli. These proteins were further categorized based on molecular function and biological process according to Gene Ontology terms. The most abundant gut plasma membrane proteins were identified. The ten plasma membrane proteins that differed in abundance between the two insect species were associated with the terms “protein binding” and “viral processes.” In addition to providing insight into the gut physiology of hemipteran insects, these gut plasma membrane proteomes provide context for appropriate identification of plant virus receptors based on a combination of bioinformatic prediction and protein localization on the surface of the insect gut. 

Abstract Structural health monitoring (SHM) is the automation of the condition assessment process of an engineered system. When applied to geometrically large components or structures, such as those found in civil and aerospace infrastructure and systems, a critical challenge is in designing the sensing solution that could yield actionable information. This is a difficult task to conduct cost-effectively, because of the large surfaces under consideration and the localized nature of typical defects and damages. There have been significant research efforts in empowering conventional measurement technologies for applications to SHM in order to improve performance of the condition assessment process. Yet, the field implementation of these SHM solutions is still in its infancy, attributable to various economic and technical challenges. The objective of this Roadmap publication is to discuss modern measurement technologies that were developed for SHM purposes, along with their associated challenges and opportunities, and to provide a path to research and development efforts that could yield impactful field applications. The Roadmap is organized into four sections: distributed embedded sensing systems, distributed surface sensing systems, multifunctional materials, and remote sensing. Recognizing that many measurement technologies may overlap between sections, we define distributed sensing solutions as those that involve or imply the utilization of numbers of sensors geometrically organized within (embedded) or over (surface) the monitored component or system. Multi-functional materials are sensing solutions that combine multiple capabilities, for example those also serving structural functions. Remote sensing are solutions that are contactless, for example cell phones, drones, and satellites. It also includes the notion of remotely controlled robots. 

Abstract The stratospheric influence on summertime high surface ozone ( ${\mathrm{O}}_3$) events is examined using a twenty-year simulation from the Whole Atmosphere Community Climate Model. We find that ${\mathrm{O}}_3$transported from the stratosphere makes a significant contribution to the surface ${\mathrm{O}}_3$variability where background surface ${\mathrm{O}}_3$exceeds the 95thpercentile, especially over western U.S. Maximum covariance analysis is applied to ${\mathrm{O}}_3$anomalies paired with stratospheric ${\mathrm{O}}_3$tracer anomalies to identify the stratospheric intrusion and the underlying dynamical mechanism. The first leading mode corresponds to deep stratospheric intrusions in the western and northern tier of the U.S., and intensified northeasterlies in the mid-to-lower troposphere along the west coast, which also facilitate the transport to the eastern Pacific Ocean. The second leading mode corresponds to deep intrusions over the Intermountain Regions. Both modes are associated with eastward propagating baroclinic systems, which are amplified near the end of the North Pacific storm tracks, leading to strong descents over the western U.S.