bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of Anthropogenic Activities on Elevation‐Dependent Weakening of Annual Temperature Cycle Amplitude Over the Tibetan Plateau
Authors: Zhu Lihua , Huang Gang , Fan Guangzhou , Hua Wei 
Published: May 2022

AbstractThe annual cycle is the dominant component and the most prominent climate oscillation for the temperature variation over the Tibetan Plateau (TP). Identifying the relative contribution of anthropogenic and natural forcing to the changes in the annual cycle, namely, detection and attribution, is an important aspect for mountainous climate change research. The present study documents the elevation dependence of the trend in the annual temperature cycle (ATC) amplitude over the TP and detects the influence of anthropogenic activities on it. An elevation‐dependent weakening of the ATC amplitude occurs over the TP during the period 1961–2014. This variation with altitude can mainly be ascribed to the seasonal difference in warming. The influence of anthropogenic activities is detectable, with increased aerosols being the main contributor. Under aerosol‐only forcing, the larger decrease in snow‐related albedo at higher altitudes in winter can explain the amplified negative tendency of the ATC amplitude with elevation.
Assimilation of Aeolus Rayleigh‐Clear Winds Using a Footprint Operator in AROME‐Arctic Mesoscale Model
Authors: Mile Máté , Azad Roohollah , Marseille Gert‐Jan 
Published: May 2022

AbstractThe wind profiles measured by the Aeolus satellite mission are unique and valuable wind products for numerical weather prediction. However, just like any other remote sensing measurements, it has a footprint extending over a number of model grid cells, especially in high‐resolution mesoscale models. The spatial representation of Aeolus Rayleigh‐clear observations has been assessed in a mesoscale limited‐area model called AROME‐Arctic by using a footprint observation operator. The footprint representation provides small, but consistent reduction in the standard deviation of background departures and an observing system experiment comparing the default and the footprint operator based on Aeolus data assimilation showed a small positive impact on AROME‐Arctic forecasts.
What's in a Name? On the Use and Significance of the Term “Polar Vortex”
Authors: Manney Gloria L. , Butler Amy H. , Lawrence Zachary D. , Wargan Krzysztof , Santee Michelle L. 
Published: May 2022

AbstractMainstream and popular science media are rife with misunderstandings about what a “polar vortex” is. The term most aptly describes the stratospheric polar vortex, a single feature dominating the cool‐season circulation from ∼15–50 km. Regional jet stream variations dominate the tropospheric circulation, which is not well‐described as a polar vortex; indeed, there is no single consistent definition of a tropospheric polar vortex in the literature. Stratospheric polar vortex disturbances profoundly influence extreme weather events, including cold air outbreaks (CAOs). How the stratospheric polar vortex affects tropospheric jets, whose local excursions drive CAOs, is not fully understood. Public‐facing parts of publications describing research on this topic are not always clear about how the “polar vortex” is defined; greater clarity could improve communications both within the community and with non‐specialist audiences.
Simultaneous Detection of Signatures of Conjugate Photoelectrons in the Ionosphere and Thermosphere
Authors: Kil Hyosub , Paxton Larry J. , Schaefer Robert K. 
Published: May 2022

AbstractWe investigate the impact of conjugate photoelectrons (CPEs) on the topside (∼600 km altitude) ionosphere at low and midlatitudes using measurements of the ion temperature, density, and composition from the first Republic of China satellite during a period of the high to moderate solar activity (March 1999 to June 2004). Elevated ion temperatures and densities are observed in the dark Northern American‐Atlantic sector during the December solstice and in the Australian sector during the June solstice. The oxygen ion fraction and density are also elevated at these locations. These observations indicate that photoelectrons from the conjugate hemisphere heat the local ionospheric plasma. The morphology of the ion temperature in the winter hemisphere is well represented by the solar zenith angle in the sunlit conjugate hemisphere. The CPE hypothesis for the observed ionospheric heating is confirmed by coincident nighttime enhancements of the far ultraviolet airglow measured by the Global Ultraviolet Imager onboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite.
Monthly to Decadal Variability of Mesoscale Stirring in the California Current System: Links to Upwelling, Climate Forcing, and Chlorophyll Transport
Authors: Giddings A. , Franks P. J. S. , Baumann‐Pickering S. 
Published: May 2022

AbstractThe California Current System (CCS) is a highly productive eastern boundary upwelling system. Cross‐shore transport is driven by horizontal stirring from mesoscale (and submesoscale) eddies, fronts, and filaments, which shift surface productivity away from the narrow upwelling zone inshore. Using an unprecedented 25‐year daily record of finite size Lyapunov exponents (FSLEs), we characterize the spatial and temporal patterns of mesoscale stirring in the entire CCS and quantify correlations of FSLEs with satellite‐measured chlorophyll a and climate indices. The annual cycle of mesoscale stirring is highly correlated with seasonal upwelling in the CCS, with bands of intense FSLE propagating to the west during the upwelling season. Annual cycles and interannual variability in FSLE intensity were most prominent to the north and inshore of the CCS, and weaker to the south and offshore. Interannual fluctuations in mesoscale stirring showed 3–12 month lagged responses to climate indices, with the CCS oscillating out of phase with waters west and north. Chlorophyll a is positively correlated with FSLE intensity in a meridional band 200–600 km offshore, consistent with the hypothesis that increased horizontal stirring increases the export of chlorophyll a to offshore waters. When mesoscale stirring intensifies during negative phases of the Pacific Decadal Oscillation and Ocean Niño index, we predict greater offshore transport of organic carbon. Our analyses underscore the predictability of annual and interannual cycles of mesoscale stirring and chlorophyll a fluxes in the CCS and their links with climate indices.
Evidence for Interhemispheric Mercury Exchange in the Pacific Ocean Upper Troposphere
Authors: Koenig Alkuin M. , Sonke Jeroen E. , Magand Olivier , Andrade Marcos , Moreno Isabel , Velarde Fernando , Forno Ricardo , Gutierrez René , Blacutt Luis , Laj Paolo , Ginot Patrick , Bieser Johannes , Zahn Andreas , Slemr Franz , Dommergue Aurélien 
Published: May 2022

AbstractEven though anthropogenic mercury (Hg) emissions to the atmosphere are ∼2.5 times higher in the Northern Hemisphere (NH) than in the Southern Hemisphere (SH), atmospheric Hg concentrations in the NH are only ∼1.5 times higher than in the SH. Global Hg models attribute this apparent discrepancy to large SH oceanic Hg emissions or to interhemispheric exchange of Hg through the atmosphere. However, no observational data set exists to serve as a benchmark to validate whether these coarse‐resolution models adequately represent the complex dynamics of interhemispheric Hg exchange. During the 2015–2016 El Niño, we observed at mount Chacaltaya in the tropical Andes a ∼50% increase in ambient Hg compared to the year before, coinciding with a shift in synoptic transport pathways. Using this event as a case study, we investigate the impact of interhemispheric exchange on atmospheric Hg in tropical South America. We use HYSPLIT to link Hg observations to long‐range transport and find that the observed Hg increase relates strongly to air masses from the tropical Pacific upper troposphere (UT), a region directly impacted by interhemispheric exchange. Inclusion of the modeled seasonality of interhemispheric air mass exchange strengthens this relationship significantly. We estimate that interhemispheric exchange drives Hg seasonality in the SH tropical Pacific UT, with strongly enhanced Hg between July and October. We validate this seasonality with previously published aircraft Hg observations. Our results suggest that the transport of NH‐influenced air masses to tropical South America via the Pacific UT occurs regularly but became more detectable at Chacaltaya in 2015–2016 because of a westward shift in air mass origin.
On the Magnetosphere‐Ionosphere Coupling During the May 2021 Geomagnetic Storm
Authors: Piersanti M. , Del Moro D. , Parmentier A. , Martucci M. , Palma F. , Sotgiu A. , Plainaki C. , D’Angelo G. , Berrilli F. , Recchiuti D. , Papini E. , Giovannelli L. , Napoletano G. , Iuppa R. , Diego P. , Cicone A. , Mergé M. , De Donato C. , De Santis C. , Sparvoli R. , Ubertini P. , Battiston R. , Picozza P. 
Published: May 2022

AbstractOn 12 May 2021 the interplanetary doppelgänger of the 9 May 2021 coronal mass ejection impacted the Earth's magnetosphere, giving rise to a strong geomagnetic storm. This paper discusses the evolution of the various events linking the solar activity to the Earth's ionosphere with special focus on the effects observed in the circumterrestrial environment. We investigate the propagation of the interplanetary coronal mass ejection and its interaction with the magnetosphere—ionosphere system in terms of both magnetospheric current systems and particle redistribution, by jointly analyzing data from interplanetary, magnetospheric, and low Earth orbiting satellites. The principal magnetospheric current system activated during the different phases of the geomagnetic storm was correctly identified through the direct comparison between geosynchronous orbit observations and model predictions. From the particle point of view, we have found that the primary impact of the storm development is a net and rapid loss of relativistic electrons from the entire outer radiation belt. Our analysis shows no evidence for any short‐term recovery to pre‐storm levels during the days following the main phase. Storm effects also included a small Forbush decrease driven by the interplay between the interplanetary shock and subsequent magnetic cloud arrival.
A Repetitive Parameterization and Optimization Strategy for the Calibration of Complex and Computationally Expensive Process‐Based Models With Application to a 3D Water Quality Model of a Tropical Reservoir
Authors: Xia Wei , Shoemaker Christine Ann 
Published: May 2022

AbstractParameter calibration is critical for modeling, especially for current process‐based models that are complex with many chemical and biological processes and immeasurable model parameters. This analysis quantifies significant disadvantages of the traditional use of local or global sensitivity analysis (SA) for selecting calibration parameters of nonlinear, expensive models when there are a large number of constituents and parameters. We propose a new Repetitive parameterization and optimization (Rep‐OPT) strategy that uses multiple optimization steps; and between each optimization step, a modeler picks the parameters to be optimized in the next optimization step. The modeler picks the parameters in each iteration following a suggested set of steps that analyze which processes and parameters are related to the poorly fit constituents with the current parameter set. We successfully applied the Rep‐OPT strategy on a complex tropical water quality model with more than 91 parameters using real data. We demonstrate that expert knowledge with assistance of proposed postanalysis techniques (i.e., trade‐off analysis, component analysis, and mass‐balance analysis) can identify the right calibration parameters and obtain excellent model fit. In contrast, the traditional approach using SA with optimization (SA‐OPT) does not find the right calibration parameters for our data. The solution found by Rep‐OPT excellently improves manual solution by 32.7% in goodness‐of‐fit, and all calibrated constituents fit well to observations. The solution found by SA‐OPT using global SA improves manual solution by only 13.3%. Local sensitivity by SA‐OPT performs very poorly being 49.6% worse than manual solution.
Stronger Vertical Shear Leads to Earlier Secondary Eyewall Formation in Idealized Numerical Simulations
Authors: Liu Xinhang , Li Qingqing , Dai Yufan 
Published: May 2022

AbstractIdealized numerical experiments show that stronger shear is more favorable for tropical cyclone secondary eyewall formation (SEF) than weaker shear amid a moist‐tropical environment when the shear magnitude is smaller than 15 m s−1. In particular, the larger the shear, the earlier the SEF occurs. A stationary banding complex (SBC) prevails before SEF in the large shear experiments, suggesting that SBCs are helpful in the SEF. Furthermore, a well‐organized stratiform sector is associated with the SBC. With increasing shear, the shear‐forced outflow also increases in the upper layers, transporting more moisture and icy particles outward from the inner core and favoring the development of the stratiform sector. The diabatic cooling of the stratiform sector strengthens the underlying descending radial inflow, forcing updrafts immediately outside the inner core. The subsequent axisymmetrization of the updrafts leads to SEF.
Completion of Global Ionospheric TEC Maps Using a Deep Learning Approach
Authors: Yang Ding , Fang Hanxian , Liu Zhendi 
Published: May 2022

AbstractTotal electron content (TEC) is an important parameter that describes the features of the ionosphere. The International GNSS Service (IGS) has been providing IGS Global TEC maps using analysis algorithms. However, collecting the completed data is difficult because of the lack of ground receivers, and the processing to obtain the completed IGS TEC maps is time‐consuming. The fast development of deep learning brings an effective way to solve these problems. Among the various deep learning methods, the generative adversarial network (GAN) exhibits great potential in recovering missing data. In this paper, we fill the missing data of the global IGS TEC maps using pix2pixhd, which is a novel deep learning method based on GAN. Differing from the traditional GAN, pix2pixhd has two generators and three discriminators. The network enhances the ability of our model to complete images with large‐scale missing areas. The result demonstrates that our model generates the ionospheric peak structures at low latitudes well, while behaving badly (the average correlation coefficient: 0.6857) around the edge of the ionospheric peak region. Comparing different scales of the missing data areas, our model has the best performance with 0%–15% missing data. With the large scale of missing data areas (30%–45% and >45%), the performance is still satisfactory. In addition, the completion effect of our model is slightly affected by geomagnetic and solar activity. Our work demonstrates a new possibility for the application of deep learning to a broader field of geosciences, particularly for problems of missing observational data.
Statistical Properties of Whistler‐Mode Hiss Waves in the Inner Radiation Belt
Authors: Yang Ling , Li Liuyuan , Cao Jinbin , Yu Jiang 
Published: May 2022

AbstractUsing the Van Allen Probes A and B observations from 01 January 2013 to 28 February 2018, we surveyed statistically the occurrence rate, intensity, and propagation properties of hiss waves in the inner radiation belt (1.1 < L ≤ 2). Like the outer plasmaspheric hiss (L > 2), the occurrence rate and amplitude of lower‐band hiss (<600 Hz) are higher in the dayside high‐L region (L > 1.3 and magnetic local time [MLT] = 6–20 hr) than the nightside (MLT ∼ 20–6 hr) and increase with enhanced substorm activities (AE increases). Furthermore, their peak power spectral densities are located nearly in the same band (∼200–500 Hz). The equatorward propagation of middle‐latitude hiss suggests that the lower‐band hiss waves in the inner radiation belt mostly originate from the outer plasmaspheric hiss at high latitudes. Although the outer plasmaspheric hiss is also a likely source of weak upper‐band hiss (≥600 Hz) in the dayside high‐L region (L > 1.3 and MLT = 6–20 hr), the intense upper‐band hiss waves mostly appear in the dayside low‐L region (L < 1.3) and most nightside regions. In the low‐L region, the amplitude of the upper‐band hiss has no obvious substorm dependence, and the average of its wave normal angles is comparable to that of lightning‐generated whistlers reported in the past.
Micro‐Scale Plasma Instabilities in the Interaction Region of the Solar Wind and the Martian Upper Atmosphere
Authors: Akbari Hassanali , Newman David , Fowler Christopher , Pfaff Robert , Andersson Laila , Malaspina David , Schwartz Steven , Ergun Robert , McFadden James , Mitchell David , Halekas Jasper , Rowland Douglas 
Published: May 2022

AbstractWe present results, obtained by several instruments onboard NASA’s Mars Atmosphere and Volatile Evolution (MAVEN) spacecraft, that show that the interaction region of the solar wind and the Martian upper atmosphere coincides with intense plasma wave activity. The turbulence region features nonlinear structures, identified as ion phase‐space holes and double layers, that emerge in the saturation phase of instabilities in the ion‐acoustic frequency range. One‐dimensional particle‐in‐cell simulations suggest that the waves and the nonlinear structures are very effective in coupling the flowing solar wind and the Martian plasma. Specifically, the simulations show that the magnetic field‐aligned component of the solar wind protons decelerates by about 20% in temporal and spatial scales of the orders of ∼100 ms and several kilometers, respectively. The results thus suggest that the waves may play an important role in the interaction region.
Mapping Magnetic Signals of Individual Magnetite Grains to Their Internal Magnetic Configurations Using Micromagnetic Models
Authors: Cortés‐Ortuño David , Fabian Karl , de Groot Lennart V. 
Published: May 2022

AbstractMicromagnetic tomography (MMT) is a technique that combines X‐ray micro computed tomography and scanning magnetometry data to obtain information about the magnetic potential of individual grains embedded in a sample. Recovering magnetic signals of individual grains in natural and synthetic samples provides a new pathway to study the remanent magnetization that carries information about the ancient geomagnetic field and is the basis of all paleomagnetic studies. MMT infers the magnetic potential of individual grains by numerical inversion of surface magnetic measurements using spherical harmonic expansions. The magnetic potential of individual particles in principle is uniquely determined by MMT, not only by the dipole approximation, but also more complex, higher order, multipole moments. Here, we show that such complex magnetic information together with both particle shape and mineral properties severely constrains the internal magnetization structure of an individual grain. To this end, we apply a three dimensional micromagnetic model to predict the multipole signal from magnetization states of different local energy minima. We show that for certain grains it is even possible to uniquely infer the magnetic configuration from the inverted magnetic multipole moments. This result is crucial to discriminate single‐domain particles from grains in more complex configurations such as multi‐domain or vortex states. As a consequence, our investigation proves that by MMT it is feasible to select statistical ensembles of magnetic grains based on their magnetization states, which opens new possibilities to identify and characterize stable paleomagnetic recorders in natural samples.
Polymer-coated carbon nanotube hybrids with functional peptides for gene delivery into plant mitochondria
Authors: Law Simon Sau Yin , Liou Geoffrey , Nagai Yukiko , Giménez-Dejoz Joan , Tateishi Ayaka , Tsuchiya Kousuke , Kodama Yutaka , Fujigaya Tsuyohiko , Numata Keiji 
Published: May 2022

AbstractThe delivery of genetic material into plants has been historically challenging due to the cell wall barrier, which blocks the passage of many biomolecules. Carbon nanotube-based delivery has emerged as a promising solution to this problem and has been shown to effectively deliver DNA and RNA into intact plants. Mitochondria are important targets due to their influence on agronomic traits, but delivery into this organelle has been limited to low efficiencies, restricting their potential in genetic engineering. This work describes the use of a carbon nanotube-polymer hybrid modified with functional peptides to deliver DNA into intact plant mitochondria with almost 30 times higher efficiency than existing methods. Genetic integration of a folate pathway gene in the mitochondria displays enhanced plant growth rates, suggesting its applications in metabolic engineering and the establishment of stable transformation in mitochondrial genomes. Furthermore, the flexibility of the polymer layer will also allow for the conjugation of other peptides and cargo targeting other organelles for broad applications in plant bioengineering.
A nucleotide-sensing oligomerization mechanism that controls NrdR-dependent transcription of ribonucleotide reductases
Authors: Rozman Grinberg Inna , Martínez-Carranza Markel , Bimai Ornella , Nouaïria Ghada , Shahid Saher , Lundin Daniel , Logan Derek T. , Sjöberg Britt-Marie , Stenmark Pål 
Published: May 2022

AbstractRibonucleotide reductase (RNR) is an essential enzyme that catalyzes the synthesis of DNA building blocks in virtually all living cells. NrdR, an RNR-specific repressor, controls the transcription of RNR genes and, often, its own, in most bacteria and some archaea. NrdR senses the concentration of nucleotides through its ATP-cone, an evolutionarily mobile domain that also regulates the enzymatic activity of many RNRs, while a Zn-ribbon domain mediates binding to NrdR boxes upstream of and overlapping the transcription start site of RNR genes. Here, we combine biochemical and cryo-EM studies of NrdR from Streptomyces coelicolor to show, at atomic resolution, how NrdR binds to DNA. The suggested mechanism involves an initial dodecamer loaded with two ATP molecules that cannot bind to DNA. When dATP concentrations increase, an octamer forms that is loaded with one molecule each of dATP and ATP per monomer. A tetramer derived from this octamer then binds to DNA and represses transcription of RNR. In many bacteria — including well-known pathogens such as Mycobacterium tuberculosis — NrdR simultaneously controls multiple RNRs and hence DNA synthesis, making it an excellent target for novel antibiotics development.
PlasmidMaker is a versatile, automated, and high throughput end-to-end platform for plasmid construction
Authors: Enghiad Behnam , Xue Pu , Singh Nilmani , Boob Aashutosh Girish , Shi Chengyou , Petrov Vassily Andrew , Liu Roy , Peri Siddhartha Suryanarayana , Lane Stephan Thomas , Gaither Emily Danielle , Zhao Huimin 
Published: May 2022

AbstractPlasmids are used extensively in basic and applied biology. However, design and construction of plasmids, specifically the ones carrying complex genetic information, remains one of the most time-consuming, labor-intensive, and rate-limiting steps in performing sophisticated biological experiments. Here, we report the development of a versatile, robust, automated end-to-end platform named PlasmidMaker that allows error-free construction of plasmids with virtually any sequences in a high throughput manner. This platform consists of a most versatile DNA assembly method using Pyrococcus furiosus Argonaute (PfAgo)-based artificial restriction enzymes, a user-friendly frontend for plasmid design, and a backend that streamlines the workflow and integration with a robotic system. As a proof of concept, we used this platform to generate 101 plasmids from six different species ranging from 5 to 18 kb in size from up to 11 DNA fragments. PlasmidMaker should greatly expand the potential of synthetic biology.