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510 results for “STORM”
RInex files from HK GNSS network in observing simultaneous and consecutive occurrence of thunderstorm and geomagnetic storm
<p>These are the RInex files from HK GNSS network in observing simultaneous and consecutive occurrence of thunderstorm and geomagnetic storm</p>
Aerosol impacts on storm electrification and lightning discharges under different thermodynamic environments
<p>These are important data supporting the conclusion of the paper are available in the main text.</p>
Sediment exchange between southern Yellow Sea and Yangtze River Estuary in response to storm events
<p>Sediment exchange pattern between Yangtze River Estuary and southern Yellow Sea has been a crucial and controversial scientific question, which limits our understanding on the future prediction of morphological evolution of the radical sand ridges and Jiangsu tidal flats. This study investigates various processes including tides, winds and waves to identify a dominant factor controlling sediment exchange between the southern Yellow Sea and the Yangtze River Estuary under storm conditions using a validated numerical model. Our results show that tide is the dominant force controlling hydrodynamics and sediment transport between the two systems. Tide controlled residual currents and sediment fluxes are towards northwest from the Yangtze River Estuary to the southern Yellow Sea, while wind and wave-induced currents under normal wind condition (Beaufort 3 scale, 3.4m s<sup>-1</sup>) adjust net sediment flux by less than 10% and 40%, respectively. The influences of winds and waves on sediment transport vary with wind directions. South or southeast winds enhance the tide-induced northwestward sediment transport, while north or northeast winds reduce the northwestward sediment transport. Under strong winter storm condition, however, the associated northern winds and waves become more important than tides in sediment transport, leading to southeastern directed residual currents and net sediment fluxes. Sediment transport is more active in nearshore area than offshore areas, with little vertical variations.</p>
Anti-cytokine storm activity of fraxin and quercetin, alone and in combination, and their possible molecular mechanisms via TLR4 and PPARγ signaling pathways in LPS-induced RAW 264.7 cell line article data
<p>Anti-cytokine storm activity of fraxin and quercetin, alone and in combination, and their possible molecular mechanisms via TLR4 and PPARγ signaling pathways in LPS-induced RAW 264.7 cell line article data</p>
Anti-cytokine storm activity of fraxin and quercetin, alone and in combination, and their possible molecular mechanisms via TLR4 and PPARγ signaling pathways in LPS-induced RAW 264.7 cell line article data
<p>Anti-cytokine storm activity of fraxin and quercetin, alone and in combination, and their possible molecular mechanisms via TLR4 and PPARγ signaling pathways in LPS-induced RAW 264.7 cell line article data</p>
Tide and TWL Stations for "Understanding Nonlinear Interactions Between Barotropic and Baroclinic Processes in a Global Tide and Storm Surge Model"
<p>This is a dataset that contains the tidal and total water level stations used in my dissertation.</p>
Dataset to the article 'Redox-zoning in high-energy subterranean estuaries as a function of storm floods, temperatures, seasonal groundwater recharge and morphodynamics'
<p>This repository contains model input files, and pre- and post-processing scripts for the research article:</p> <p>Janek Greskowiak, Stephan L. Seibert, Vincent E.A. Post, Gudrun Massmann (2023), Redox-zoning in high-energy subterranean estuaries as a function of storm floods, temperatures, seasonal groundwater recharge and morphodynamics, Estuarine, Coastal and Shelf Science, https://doi.org/10.1016/j.ecss.2023.108418</p> <p><br> Data:</p> <p>The folder Laserascannerdata_top_and_hydr_heads contains five cross-shore topography profiles of a high energy beach on Spiekeroog Island, Germany, including a python-script that assembles them to a daily times-series over one year and that calculates the tide-averaged hydraulic heads in the intertidal zone as detailed in Greskowiak and Massmann (2021), The impact of morphodynamics and storm floods on pore water flow and transport in the subterranean estuary, Hydrological Processes, 35:e14050, https://doi.org/10.1002/hyp.14050</p> <p><br> Model input:</p> <p>The file Dynamod_1_redox_basecase.zip contains a folder with the model input textfiles (SEAWAT and PHT3D) for the case that considers all dynamic influence factors investigated in the paper, i.e., seasonal meteoric groundwater recharge, stormfloods, temperature-dependence of reaction rates and morphodynamics.</p> <p>The files pht3d_ph.dat and pht3d_datab.dat are PHT3D model specific files defining the reacants and reactions, and have to be copied into the model folder before PHT3D is started.</p> <p><br> Run models:</p> <p>First the SEAWAT model needs to be run with the name file 'Dynamod_1_redox_basecase.nam'. This creates the mt3d link file 'mt3d_link.ftl'. After that, PHT3D has to be started with the name file 'pht3d.nam'</p> <p>Note that running the models will generate 22 Gybte output.</p> <p><br> Pre-processing:</p> <p>All model input files were generated with the python-script Dynamod_1_redox_basebase.py using Flopy, a python-based groundwater modelling user-interface:<br> https://www.usgs.gov/software/flopy-python-package-creating-running-and-post-processing-modflow-based-models</p> <p><br> Post-processing:</p> <p>For the figures 3,4 and S1, S2 in the paper, the corresponding python scripts are provided in this database. Note that with respect to Figures 5 and S3, only the results for the case with all dynamic influence factors (Figure S3_h) are being plotted.</p> <p> </p> <p>Other model output:<br> Animation_A1_Dynamod_redox.mp4 is a video animation showing the dynamic modelled salinity and temperature distribution, and redox zoning in the subterranean estuary all dynamic influence factors investigated in the paper, i.e., seasonal meteoric groundwater recharge, stormfloods, temperature-dependence of reaction rates and morphodynamics.</p>
Dataset of Geomagnetic Storm Forcasting with CEEMDAN-CWT
<p>Dataset of geomagnetic storm forcasting with CEEMDAN-CWT, associated with manuscript 《A new method for predicting non-recurrent geomagnetic storms》.</p> <p> </p> <p><strong>Previous Work</strong></p> <p><strong>Ye, Q., Wang, C., He, F., Xue, B., & Zhang, X. (2022). The frequency-domain characterization of Cosmic Ray Intensity variations before Forbush decreases associated with geomagnetic storms. Space Weather, 20, e2021SW002863. https://doi.org/10.1029/2021SW002863</strong></p>
A tightly coupled river-ocean model for simulating combined flood due to storm surge and river flow in coastal-urban areas
<p>Coastal flooding, resulting from storm surges or extreme river flows, causes significant causalities and damage to properties in low-lying areas. The simultaneous occurrence of river flows and storm surges, termed combined/compound events, exacerbates the flood risk compared to independent occurrences. Combined flood events are simulated with the help of hydraulic and hydrodynamic models using a loosely or tightly coupled approach. In the loosely coupled approach, a hydrodynamic model simulates storm surges first, and a hydraulic model then simulates inland flood due to river overflow considering surge as the boundary condition at the river mouth/estuary. Conversely, the tightly coupled approach involves simultaneous simulation of both river flow and storm surge by coding the mathematical representation of river and ocean flow dynamics in the same numerical model. This allows the interaction between river and ocean flows to be simulated anywhere in the combined river-ocean computational domain, making it highly relevant for simulating combined floods. However, existing models based on this approach encounter numerical instability, especially in inland regions where topography variation is steep and highly uneven. Also, such combined models are highly limited for large scale applications. Therefore, this research focuses on developing a tightly coupled 2D finite volume river-ocean model called IROMS-C2D. The developed model intends to address the limitations of the previous models and provide a stable solution framework for the simulation of combined flooding resulting from the interaction of storm surges and river flows in coastal urban areas. Further, it enhances our understanding of flood risks in coastal areas, particularly in urban settings, and facilitates the formulation of effective measures for flood control and adaptation of coastal infrastructure.</p>
A tightly coupled river-ocean model for simulating combined flood due to storm surge and river flow in coastal-urban areas
<p>Coastal flooding, resulting from storm surges or extreme river flows, causes significant causalities and damage to properties in low-lying areas. The simultaneous occurrence of river flows and storm surges, termed combined/compound events, exacerbates the flood risk compared to independent occurrences. Combined flood events are simulated with the help of hydraulic and hydrodynamic models using a loosely or tightly coupled approach. In the loosely coupled approach, a hydrodynamic model simulates storm surges first, and a hydraulic model then simulates inland flood due to river overflow considering surge as the boundary condition at the river mouth/estuary. Conversely, the tightly coupled approach involves simultaneous simulation of both river flow and storm surge by coding the mathematical representation of river and ocean flow dynamics in the same numerical model. This allows the interaction between river and ocean flows to be simulated anywhere in the combined river-ocean computational domain, making it highly relevant for simulating combined floods. However, existing models based on this approach encounter numerical instability, especially in inland regions where topography variation is steep and highly uneven. Also, such combined models are highly limited for large scale applications. Therefore, this research focuses on developing a tightly coupled 2D finite volume river-ocean model called IROMS-C2D. The developed model intends to address the limitations of the previous models and provide a stable solution framework for the simulation of combined flooding resulting from the interaction of storm surges and river flows in coastal urban areas. Further, it enhances our understanding of flood risks in coastal areas, particularly in urban settings, and facilitates the formulation of effective measures for flood control and adaptation of coastal infrastructure.</p>
The relation among the ring current, subauroral polarization stream, and the geospace plume: MAGE Simulation of the March 31 2001 Super Storm
<p>Open data for Figure 3 to Figure 11 in manuscript, "The relation among the ring current, subauroral polarization stream, and the geospace plume: MAGE Simulation of the March 31 2001 Super Storm".</p> <p>The data was generated by the Multiscale Atmosphere Geospace Environment model.</p> <p>The manuscript is submitted to JGR for review.</p>
Configuration files for WRF and rain-producing storm identification model
<p>This repository hosts necessary configuration files to reproduce the manuscript "Studying Brown Ocean Re-intensification of Hurricane Florence Using CYGNSS and SMAP Soil Moisture Data and a Numerical Weather Model".</p> <p> </p> <p>Model description:</p> <p>WRF v4.4: https://github.com/wrf-model/WRF/tree/release-v4.4</p> <p>MET v10.0: https://github.com/dtcenter/MET/tree/main_v10.0</p> <p><a href="https://zenodo.org/api/files/b5d951b5-7e96-4f0b-a2c4-de3e0616514b/modify_SM.ncl">modify_SM.ncl</a>: NCL tool to multiply initial soil moisture and soil temperature by a factor</p> <p><a href="https://zenodo.org/api/files/b5d951b5-7e96-4f0b-a2c4-de3e0616514b/MTDConfig">MTDConfig</a>: configuration file for MET MTD analysis</p> <p><a href="https://zenodo.org/api/files/b5d951b5-7e96-4f0b-a2c4-de3e0616514b/namelist.input">namelist.input</a>: input configuration for WRF model</p> <p><a href="https://zenodo.org/api/files/b5d951b5-7e96-4f0b-a2c4-de3e0616514b/namelist.wps">namelist.wps</a>: configuration file for WPS preprocessing model</p>
Assessing the comparative effects of storm-relative helicity components within right-moving supercell environments
<p>Supercell thunderstorms develop low-level rotation via tilting of environmental horizontal vorticity (ω<sub>h</sub>) by the updraft. This rotation induces dynamic lifting that can stretch near-surface vertical vorticity into a tornado. Low-level updraft rotation is generally thought to scale with 0–500 m storm-relative helicity (SRH): the combination of storm-relative flow, |SRF|, |ω<sub>h</sub>|, and cosφ (where φ is the angle between SRF and ω<sub>h</sub>). It is unclear how much influence each component of SRH has in intensifying the low-level mesocyclone. This study surveys these three components using self-organizing maps (SOMs) to distill 15,906 proximity soundings for observed right-moving supercells. Statistical analyses reveal the component most highly correlated to SRH and to streamwise vorticity (ω<sub>s</sub>) in the observed profiles is |ω<sub>h</sub>|. Furthermore, |ω<sub>h</sub>| and SRF are themselves highly correlated due to their shared dependence on the hodograph length. The representative profiles produced by the SOMs were combined with a common thermodynamic profile to initialize quasi-realistic supercells in a cloud model. The simulations reveal that, across a range of real-world profiles, intense low-level mesocyclones are most closely linked to ω<sub>h</sub> and SRF, while the angle between them appears to be mostly inconsequential.</p>
The variable source of the plasma sheet during a geomagnetic storm: data
<p>This dataset contains the files supporting the paper "The variable source of the plasma sheet during a geomagnetic storm" published in Nature Communications. Included are the following:</p> <p>1) LEPI-HE2 contains cdf files of the He++ data of the LEPI instrument in the same format as the other species files available from the ERG science center (https://ergsc.isee.nagoya-u.ac.jp/)</p> <p>2) WIND_SWE contains idl save sets with the results of the fits to the WIND/SWE data using two proton peaks and an alpha peak. The data is in the structure ppa.fits, with variable descriptions in ppa.pnames and ppa.pdesc.</p> <p>3) The data that is plotted in Figures 3, 4, and 6. These are in tplot save formats that can be read with the spedas software (<a>http://themis.ssl.berkeley.edu/software.shtml</a>). IDL spedas programs (.pro) to read the data files and recreate the figures are also included.</p>
Results of the study "Uncertainties and discrepancies in the representation of recent storm surges in a non-tidal semi-enclosed basin: a hind-cast ensemble for the Baltic Sea" in Ocean Science
<p>This archive stores the main results, the main scripts, and the model code of the study:</p> <p>Lorenz, M. and Gräwe, U.: Uncertainties and discrepancies in the representation of recent storm surges in a non-tidal semi-enclosed basin: a hind-cast ensemble for the Baltic Sea, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-820, 2023.</p>
Ulysses Storm data v2.0
<p>Data from four versions of the 20CRv3 reanalysis for the period around the Ulysses Storm in February 1903, associated with the publications by Hawkins et al. in NHESS and Hawkins et al. in ESD.</p>
Therapeutic Plasma Exchange in Resistant Cytokine Storm of COVID 19
ClinicalTrials.gov study NCT04457349. IPD Sharing: Not stated. Countries: 1. Publications: 13.
Prophylactic Corticosteroid to Prevent COVID-19 Cytokine Storm
ClinicalTrials.gov study NCT04355247. IPD Sharing: Not stated. Countries: 1. Publications: 8.
Anakinra, COVID-19, Cytokine Storm
ClinicalTrials.gov study NCT04603742. IPD Sharing: NO. Countries: 1. Publications: 7.
CVA21 and Pembrolizumab in NSCLC & Bladder Cancer (VLA-009 STORM/ KEYNOTE-200)
ClinicalTrials.gov study NCT02043665. IPD Sharing: YES. Countries: 3. Publications: 1.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.