bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatiotemporal Variability of Rainfall and Surface Salinity in the Eastern Pacific Fresh Pool: A Joint In Situ and Satellite Analysis During the SPURS‐2 Field Campaign
Authors: Chi Nan‐Hsun , Thompson Elizabeth J. , Chen Haonan , Shcherbina Andrey , Bingham Frederick , Rainville Luc 
Published: December 2023

AbstractWe perform a statistical characterization of the 2016–2017 SPURS‐2 field campaign in situ data and coincident satellite data spanning 8°–12°N, 120°–130°W to quantify the spatial and temporal scales of variability of rain and near‐surface salinity in the Eastern Pacific Fresh Pool. Observations of rain rate and near‐surface to surface salinity are obtained from ships, moorings, autonomous platforms, and satellite remote sensing: Integrated Multi‐satellitE Retrievals for GPM (IMERG); and Soil Moisture Active Passive (NASA SMAP L3 V5). The integral length and time scales of rain and near‐surface salinity vary seasonally. In the rainy season (August–October) when the Intertropical Convergence Zone (ITCZ) migrates over the SPURS‐2 study site, the integral time scales of rain were about 30–60 min and those of near‐surface salinity were closer to that of the rain, 1–2 days, indicating forcing by rain. Meanwhile, the zonal integral length scale of in situ near‐surface salinity was twice as large as the meridional scale (50 vs. 20 km), consistent with the ITCZ's zonally‐propagating and ‐organized rain features. The magnitude and seasonal variation of the sea surface salinity integral time scale were not captured by SMAP since the rainy ITCZ‐period scales were smaller than SMAP resolution (70 km, 8‐day running mean). In the dry season (February–May), the in situ rain integral time scale reduced to less than 30 min while that of the near‐surface salinity increased to 1–5 days, the ocean mesoscale. IMERG overestimated the rain integral time scale by a factor of two to ten in both seasons.
Six‐Component Earthquake Synchronous Observations Across Taiwan Strait: Phase Velocity and Source Location
Authors: Chen Chang , Wang Yun , Sun Lixia , Lin Chin‐Jen , Wei Yongxiang , Liao Chunqi , Lin Binhua , Qin Linpeng 
Published: December 2023

AbstractWith the development of rotational seismometers, especially the high‐sensitivity optical seismometers, rotational motions have shown increasing benefits for calculation of dispersion curves, estimation of back azimuth and many other applications. Here we present the six‐component observations of 2019 Hualien mww6.1 earthquake simultaneously on both sides of Taiwan Strait. Seismograms and time‐frequency spectrums show that the attenuations for rotations are more significant than translations. Calculations of the surface wave phase velocity are performed for both stations through single‐station records, indicating a distinct difference owning to the instrument installation conditions and site effect. Comparison of theoretical dispersion curves is consistently in trends with estimations, and reveals the influence of higher‐mode surface waves. For the first time, we locate the source of a earthquake through intersection of two stations' back azimuths estimated through rotational methods. Results of comparing to translational polarization verify that rotational observation can distinctly reduce the deviation of source location.
Simultaneous Precipitation of Sub‐Relativistic Electron Microburst and Pulsating Aurora Electrons
Authors: Namekawa T. , Mitani T. , Asamura K. , Miyoshi Y. , Hosokawa K. , Lessard M. , Moser C. , Halford A. J. , Sakanoi T. , Kawamura M. , Nose M. , Nomura R. , Teramoto M. , Shumko M. , Lynch K. A. , Jaynes A. N. , McHarg M. G. 
Published: December 2023

AbstractWe have identified for the first time an energy‐time dispersion of precipitating electron flux in a pulsating aurora patch, ranging from 6.7 to 580 keV, through simultaneous in‐situ observations of sub‐relativistic electrons of microburst precipitations and lower‐energy electrons using the Loss through Auroral Microburst Pulsation sounding rocket launched from the Poker Flat Research Range in Alaska. Our observations reveal that precipitating electrons with energies of 180–320 keV were observed first, followed by 250–580 keV electrons 0–30 ms later, and finally, after 500–1,000 ms, 6.7–14.6 keV electrons were observed. The identified energy‐time dispersion is consistent with the theoretical estimation that the relativistic electron microbursts are a high‐energy tail of pulsating aurora electrons, which are caused by chorus waves propagating along the field line.
Improving Subseasonal‐To‐Seasonal Prediction of Summer Extreme Precipitation Over Southern China Based on a Deep Learning Method
Authors: Lyu Yang , Zhu Shoupeng , Zhi Xiefei , Ji Yan , Fan Yi , Dong Fu 
Published: December 2023

AbstractThe reliable Subseasonal‐to‐Seasonal (S2S) forecast of precipitation, particularly extreme precipitation, is critical for disaster prevention and mitigation, which however remains a great challenge for mission agencies and research communities. In this study, a deep learning method based on U‐Net with additional atmospheric factor forecasts included is proposed to improve S2S quantitative forecasts of summer precipitation over Southern China. The weighted loss function integrated by mean square error and threat score is introduced to capture extreme precipitation more precisely. Generally, the U‐Net model shows promising results in both general statistics and extreme events. Predictor importance analyses show that the U‐Net forecast skills at the 1‐week lead time mainly arise from synchronous precipitation forecasts, but the contributions made by atmospheric factor forecasts rise rapidly with increasing lead times. Therefore, the channel combining numerical weather prediction model and deep learning framework is demonstrated promising in S2S precipitation forecasts.
Impacts of Biomass Burning in Southeast Asia on Tropospheric CO2 Concentration Over South China
Authors: Li Jie , Fan Wenxuan , Wu Jian , Han Zhiwei , Li Jiawei , Zhang Chuwei 
Published: December 2023

AbstractThe field observations imply that the long‐range transport of carbon dioxide (CO2) emitted by biomass burning (BB) in Southeast Asia might impact the atmospheric CO2 in South China, while the transboundary path and the contributions of long‐range transport on atmospheric CO2 concentrations in South China remain poorly understood. In this study, a regional air quality model system (RAQMS) was developed by incorporating the atmospheric process of CO2 to investigate the impacts of BB in Southeast Asia on tropospheric CO2 concentration over South China in spring during 2009–2018. CO2 emissions from BB in Southeast Asia in spring varied greatly from 2009 to 2018, and high monthly mean emissions were concentrated in the west of Myanmar, the border between Myanmar, Thailand and Laos, the north of Laos, and Cambodia, with the maximum reaching 1.0 g m−2 hr−1. Higher monthly mean concentrations of near surface CO2 and tropospheric CO2 produced by BB were mainly distributed in the source regions of Southeast Asia and South China. The monthly mean tropospheric CO2 concentrations produced by BB in Southeast Asia were higher in March 2010, 2014, and 2015, which were obviously related to the interannual variation of BB emission, and affected by the atmospheric circulation as well. The contribution of BB emission in Southeast Asia to the net change of tropospheric CO2 concentration in South China presented a belt distribution from the southwest to the northeast, with a domain average of 5.7%–38.6% over South China in March 2009–2018.
Gap‐Filled Multivariate Observations of Global Land–Climate Interactions
Authors: Bessenbacher V. , Schumacher D. L. , Hirschi M. , Seneviratne S. I. , Gudmundsson L. 
Published: December 2023

AbstractThe volume of Earth system observations has grown massively in recent decades. However, multivariate or multisource analyses at the interface of atmosphere and land are still hampered by the sparsity of ground measurements and the abundance of missing values in satellite observations. This can hinder robust multivariate analysis and introduce biases in trends. Nevertheless, gap‐filling is often done univariately, which can obscure physical dependencies. Here, we apply the new multivariate gap‐filling framework CLIMate data gapFILL (CLIMFILL). CLIMFILL combines state‐of‐the‐art spatial interpolation with an iterative approach accounting for dependencies across multiple incomplete variables. CLIMFILL is applied to a set of remotely sensed and in situ observations over land that are central to observing land–atmosphere interactions and extreme events. The resulting gridded monthly time series covers 1995–2020 globally with gap‐free maps of nine variables: surface layer soil moisture from European Space Agency (ESA)‐Climate Change Initiative (CCI), land surface temperature and diurnal temperature range from Moderate‐resolution Imaging Spectroradiometer, precipitation from GPM, terrestrial water storage from GRACE, ESA‐CCI burned area, and snow cover fraction as well as 2‐m temperature and precipitation from CRU. Time series of anomalies are reconstructed better compared to state‐of‐the‐art interpolation. The gap‐filled data set shows high correlations with ERA5‐Land, and soil moisture estimates compare favorably to in situ observations from the International Soil Moisture Network. Soil moisture drying trends in ESA‐CCI only agree with the reanalysis product ERA5‐Land trends after gap‐filling. We furthermore showcase that key features of droughts and heatwaves in major fire seasons are well represented. The data set can serve as a step toward the fusion of multivariate multisource observations.
The Predictability of the 2021 SSW Event Controlled by the Zonal‐Mean State in the Upper Troposphere and Lower Stratosphere
Authors: Cho Hyeong‐Oh , Kang Min‐Jee , Son Seok‐Woo 
Published: December 2023

AbstractSudden stratospheric warming (SSW) describes a disruption of the stratospheric polar vortex in the winter hemisphere. It affects not only the stratospheric circulation but also the surface climate for up to 2 months, serving as an important source of subseasonal‐to‐seasonal (S2S) predictability in midlatitudes. This study evaluates the predictability of the 2021 SSW and investigates the crucial factors that determine its predictability in the ECMWF and JMA S2S real‐time forecasts. In both models, only a subset of the ensemble members predicted the SSW at the lead time of about 2 weeks before the onset. By comparing the 10 ensembles with successful SSW predictions and those with failed predictions, we found that the ensembles predicting the SSW have relatively stronger wave fluxes from the upper troposphere to the stratosphere than the others. Stronger wave fluxes, particularly those of zonal wavenumber one, are not the result of the tropospheric precursors such as the Ural blocking and Aleutian cyclones but they result from the modulation of the wave propagation by the background state. In particular, the ensembles with failed SSW predictions tend to have a negative potential vorticity gradient in the upper troposphere and lower stratosphere, which limits the upward wave propagation into the stratosphere and provides an unfavorable condition for the SSW. This result suggests that not only the wave sources in the troposphere but also the background state in the upper troposphere and lower stratosphere can modulate the predictability of SSW in S2S prediction models.
Celebrating 20 Years of JGR Earth Surface
Authors: East Amy E. , Attal Mikael , Hoitink A. J. F. , Sergienko Olga V. 
Published: December 2023

AbstractDecember 2023 marks the 20th anniversary of the first issue of the Journal of Geophysical Research: Earth Surface. The past 20 years have brought rapid growth in the field of Earth‐surface processes, changes in AGU's structure and objectives, and new practices across the scientific publishing landscape. In recent years our mission has evolved to focus increasingly on science for the benefit of society and the global environment. The growth and diversification of the international Earth‐surface scientific community has enriched the science immeasurably, and we continue to reach out to scientists in parts of the globe that have remained under‐represented in the scientific literature. JGR Earth Surface strives to provide peer review that is rigorous, constructive, efficient, and with an increasing emphasis on also being civil and free of bias. As preferences and practices for publishing science change, the journal explores new opportunities, including publishing rigorous, insightful case studies and leading cross‐journal Special Collections. The Editorial Board thanks AGU for 20 years of support and the Earth‐surface scientific community for their continued dedication to moving our field forward.
2–Bit Programmable Metasurface for Low Radar Cross Section Antenna and Beam Steering Applications
Authors: Saleem Muhammad , Irfan Muhammad , Alanazi Mubarak A. , Atiq Shahid 
Published: December 2023

AbstractIn this paper, a 2‐bit water‐based programmable digital metasurface for beam steering and backscatter field reduction applications is presented, a reflective and transmissive type water based programmable metasurface (WPMS) for RCS reduction and the antenna's beam steering is suggested, respectively. It has been demonstrated that a 2‐bit water‐based programmable unit cell can reduce RCS by changing its state (0/1). If the unit cell channel is empty, the state is “0,” if the channel is filled, the state is “1.” So at different resonance frequencies, the four phase and reflection coefficient responses are achieved as "00"01"10"11". This functionality enables beam steering in both the elevation and azimuth axis and also backscattering reduction of the antenna. Furthermore, the impacts of the number of unit cells and reflection phase states on the far‐field pattern are examined. Beam steering of ±45° in the elevation is attained with 10‐dB impedance bandwidth of 4.25–4.40 GHz, radiation gain of more than 7.1 dBi is maintained. With the present antenna, it is possible to achieve volumetric beamsteering performance directly. The patterns of far‐field radiation that are predicted theoretically coincide well with full waves simulations. As such, the proposed prototype can be a good option for applications that require a low RCS platform including beam steering in radars, 5G/6G, etc.
Temporal Gap‐Filling of 12‐Hourly SMAP Soil Moisture Over the CONUS Using Water Balance Budgeting
Authors: Zhang Runze , Kim Seokhyeon , Kim Hyunglok , Fang Bin , Sharma Ashish , Lakshmi Venkataraman 
Published: December 2023

AbstractTemporal gaps in satellite‐based soil moisture (SM) products are a persistent issue. This study presents an entirely observation‐based method to derive volumetric SM content for filling gaps in Soil Moisture Active Passive (SMAP) retrievals. Using a water balance equation, 12‐hr topsoil water amount variations are determined based on observed precipitation from the Global Precipitation Measurement Mission (inflow) and a hydrologic loss function (outflow) built on SMAP dry‐downs. A temporally seamless SM product, composed of SMAP dry‐downs and precipitation‐driven moisture approximations, was generated as a secondary outcome in determining optimal water balance parameters. This data set maintains the original SMAP SM dynamics with a median Pearson correlation (R) of 0.69 and an unbiased root‐mean‐square error (ubRMSE) of 0.05 m3/m3. Using these parameters and available SMAP observations, a 12‐hourly SM product was produced over the conterminous United States. Validated against in situ measurements, this 12‐hourly SM product exhibits good performance with a median R of 0.63 and captures most SM peaks induced by heavy rainfall. A time series examination revealed the produced 12‐hourly SM product closely corresponds to in situ SM variations and outperforms two other SMAP‐based 12‐hourly SM products gap‐filled using temporal linear interpolation and a three‐dimensional smoothing approach, especially during sparse SMAP data periods. The proposed scheme's validity is further verified by the comparable performance of the exclusive filled‐on SM estimates. Utilizing the 12‐hourly SM data set and its paired hydrologic losses could enhance the quantification connections among the hydrologic components and benefit the understanding of land‐surface hydrology.
Effect of Solar Farms on Soil Erosion in Hilly Environments: A Modeling Study From the Perspective of Hydrological Connectivity
Authors: Liu Hu , Wu Chuandong , Yu Yang , Zhao Wenzhi , Liu Jintao , Yu Hailong , Zhuang Yanli , Yetemen Omer 
Published: December 2023

AbstractHydrological connectivity (HC) is a useful framework for understanding hydrological responses to landscape changes. We present herein a novel model (SOFAR) for utility‐scale solar farms (USFs), combining modules of soil moisture dynamics, roof effects of photovoltaic panels (PVs), vegetation growth and landform evolution. By augmenting the model with a DEM‐based HC index, we investigate hydrological behaviors following the construction of a USF in China's Loess Hilly Region. Nine scenarios are designed, to explore the effects of co‐evolving ecohydrology and landscape on soil erosion and HC in USFs deployed in different climates and terrains, by altering the annual precipitation, rainfall frequency, and ground slope. Our results show that the USF considerably increased runoff (99.18%–154.26%) during its operational period, and soil erosion rate (21.4%–74.84% and 25.35%–76.18%) and HC (0.08%–0.26% and 0.47%–0.91%) throughout construction and operational periods, respectively. The highest erosion rates were detected in the PV installation zones and in the areas close to the river channel. We prove the hypothesis that HC is a critical indicator for sediment yield in a USF, and thus the long‐term responses of soil erosion to USF installation and development can be explained in terms of HC. We conclude that USFs may increase soil erosion, mainly by increasing local HC and runoff, and higher background HC may in turn further aggravate the effects of USFs on soil erosion. Our results underscore the importance of including landscape ecohydrologic and geomorphic feedbacks, to improve the environmental impact assessment of USFs.
Identification of candidate DNA methylation biomarkers related to Alzheimer’s disease risk by integrating genome and blood methylome data
Authors: Sun Yanfa , Zhu Jingjing , Yang Yaohua , Zhang Zichen , Zhong Hua , Zeng Guanghua , Zhou Dan , Nowakowski Richard S. , Long Jirong , Wu Chong , Wu Lang 
Published: December 2023

AbstractAlzheimer disease (AD) is a common neurodegenerative disease with a late onset. It is critical to identify novel blood-based DNA methylation biomarkers to better understand the extent of the molecular pathways affected in AD. Two sets of blood DNA methylation genetic prediction models developed using different reference panels and modelling strategies were leveraged to evaluate associations of genetically predicted DNA methylation levels with AD risk in 111,326 (46,828 proxy) cases and 677,663 controls. A total of 1,168 cytosine-phosphate-guanine (CpG) sites showed a significant association with AD risk at a false discovery rate (FDR) < 0.05. Methylation levels of 196 CpG sites were correlated with expression levels of 130 adjacent genes in blood. Overall, 52 CpG sites of 32 genes showed consistent association directions for the methylation-gene expression-AD risk, including nine genes (CNIH4, THUMPD3, SERPINB9, MTUS1, CISD1, FRAT2, CCDC88B, FES, and SSH2) firstly reported as AD risk genes. Nine of 32 genes were enriched in dementia and AD disease categories (P values ranged from 1.85 × 10-4 to 7.46 × 10-6), and 19 genes in a neurological disease network (score = 54) were also observed. Our findings improve the understanding of genetics and etiology for AD.
Hypoxia-induced activation of NDR2 underlies brain metastases from Non-Small Cell Lung Cancer
Authors: Levallet Jérôme , Biojout Tiphaine , Bazille Céline , Douyère Manon , Dubois Fatéméh , Ferreira Dimitri Leite , Taylor Jasmine , Teulier Sylvain , Toutain Jérôme , Elie Nicolas , Bernaudin Myriam , Valable Samuel , Bergot Emmanuel , Levallet Guénaëlle 
Published: December 2023

AbstractThe molecular mechanisms induced by hypoxia are misunderstood in non-small cell lung cancer (NSCLC), and above all the hypoxia and RASSF1A/Hippo signaling relationship. We confirmed that human NSCLC (n = 45) as their brain metastases (BM) counterpart are hypoxic since positive with CAIX-antibody (target gene of Hypoxia-inducible factor (HIF)). A severe and prolonged hypoxia (0.2% O2, 48 h) activated YAP (but not TAZ) in Human Bronchial Epithelial Cells (HBEC) lines by downregulating RASSF1A/kinases Hippo (except for NDR2) regardless their promoter methylation status. Subsequently, the NDR2-overactived HBEC cells exacerbated a HIF-1A, YAP and C-Jun-dependent-amoeboid migration, and mainly, support BM formation. Indeed, NDR2 is more expressed in human tumor of metastatic NSCLC than in human localized NSCLC while NDR2 silencing in HBEC lines (by shRNA) prevented the xenograft formation and growth in a lung cancer-derived BM model in mice. Collectively, our results indicated that NDR2 kinase is over-active in NSCLC by hypoxia and supports BM formation. NDR2 expression is thus a useful biomarker to predict the metastases risk in patients with NSCLC, easily measurable routinely by immunohistochemistry on tumor specimens.
Genome-resolved metatranscriptomics reveals conserved root colonization determinants in a synthetic microbiota
Authors: Vannier Nathan , Mesny Fantin , Getzke Felix , Chesneau Guillaume , Dethier Laura , Ordon Jana , Thiergart Thorsten , Hacquard Stéphane 
Published: December 2023

AbstractThe identification of processes activated by specific microbes during microbiota colonization of plant roots has been hampered by technical constraints in metatranscriptomics. These include lack of reference genomes, high representation of host or microbial rRNA sequences in datasets, or difficulty to experimentally validate gene functions. Here, we recolonized germ-free Arabidopsis thaliana with a synthetic, yet representative root microbiota comprising 106 genome-sequenced bacterial and fungal isolates. We used multi-kingdom rRNA depletion, deep RNA-sequencing and read mapping against reference microbial genomes to analyse the in planta metatranscriptome of abundant colonizers. We identified over 3,000 microbial genes that were differentially regulated at the soil-root interface. Translation and energy production processes were consistently activated in planta, and their induction correlated with bacterial strains’ abundance in roots. Finally, we used targeted mutagenesis to show that several genes consistently induced by multiple bacteria are required for root colonization in one of the abundant bacterial strains (a genetically tractable Rhodanobacter). Our results indicate that microbiota members activate strain-specific processes but also common gene sets to colonize plant roots.