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510 results for “STORM”
GPS dataset for 'Global View of Ionospheric Disturbance Impacts on Kinematic GPS Positioning Solutions during the 2015 St Patrick's Day Storm' by Zhe Yang, Y. Jade Morton, Irina Zakharenkova, Iurii Cherniak, Shuli Song, Wei Li
<p>This dataset contains observations of ionospheric plasma irregularities and GPS positioning errors for ~5500 stations reported in the paper 'Global View of Ionospheric Disturbance Impacts on Kinematic GPS Positioning Solutions during the 2015 St Patrick’s Day Storm' by Zhe Yang, Y. Jade Morton, Irina Zakharenkova, Iurii Cherniak, Shuli Song, Wei Li</p>
CoDEC Dataset - Data underlying the paper "A high-resolution global dataset of extreme sea levels, tides and storm surges including future projections "
<p>The world’s coastal areas are increasingly at risk of coastal flooding due to sea-level rise (SLR). We present a novel global dataset of extreme sea levels, the Coastal Dataset for the Evaluation of Climate Impact (CoDEC), which can be used to accurately map the impact of climate change on coastal regions around the world. The third generation Global Tide and Surge Model (GTSM), with a coastal resolution of 2.5 km (1.25 km in Europe), was used to simulate extreme sea levels for the ERA5 climate reanalysis from 1979 to 2017, as well as for future climate scenarios from 2040 to 2100. The validation against observed sea levels demonstrated a good performance, and the annual maxima had a mean bias (MB) of -0.04 m, which is 50% lower than the MB of the previous GTSR dataset. The CoDEC-ERA5 dataset is the successor of GTSR <a href="https://www.nature.com/articles/ncomms11969">(Muis et al., 2016)</a> and is based on the next generation climate and hydrodynamic models. The main improvements are summarized in Table 2 of the accompanying paper <a href="https://www.frontiersin.org/articles/10.3389/fmars.2020.00263/abstract">(Muis et al., 2020)</a>.</p> <p><br> </p>
TEC obtained from Madrigal for 'typical' Geomagnetic storms over the US (2000-2018)
<p>Contains Quiet day and storm day TEC gridded on the basis of dip and declination over the United States.</p> <p>TEC data are obtained from the Madrigal database (<a href="http://millstonehill.haystack.mit.edu/">http://millstonehill.haystack.mit.edu/</a>)</p> <p>Quiet days are in the same month as the storm days. These days are obtained from the kyoto database</p> <p>Files named as Storm/Quiet_ID_Sector.h5</p> <p>The storm ID and sector information are in a paper submitted to JGR-Space Physics.. </p>
Study of fluid and dust field features during the sand and dust storms in the Qingtu Lake Observatory
<p>The dataset concludes the fluid and dust filed information used in the work.</p>
The role of storms in sand wave formation: A numerical modeling study
<p>The data is mainly the results from the simulation for manuscript "The role of storms in sand wave formation: A numerical modeling study".</p>
Storm-Time Plasma Pressure Inferred from Multi-Mission Measurements and Its Validation using Van Allen Probes Particle Data
<p>Data associated with Space Weather Journal manuscript submission titled: "Storm-Time Plasma Pressure Inferred from Multi-Mission Measurements and Its Validation using Van Allen Probes Particle Data". This includes all the digital data that was used in constructing the Figures from the main text, along with files containing the fit set of coefficients and parameters for the model, and files describing the subset of magnetometer used for fitting the model. </p>
Dynamic Load Balancing for Predictions of Storm Surge and Coastal Flooding-Model setup and source code
<p>Source code and model setup/inputs for the paper titled "Dynamic Load Balancing for Predictions of Storm Surge and Coastal Flooding" article. Simulations were conducted using a modified version of ADCIRC+DLB (ADCIRC + Dynamic Load Balancing) on unstructured triangular meshes.</p> <p>Contains:</p> <ol> <li>Model input files. <ol> <li>ADCIRC model input files for the ideal channel setup and Hurricane Irene simulation (*.13, *.14, *.15)</li> </ol> </li> <li>Zipped archive of the ADCIRC code (adcirc-cg-DLB.zip) used to produce the simulations for the paper.</li> <li>Step-by-step compilation and usage instructions for ADCIRC+DLB. <ol> <li>Installation.html </li> <li>Usage.html</li> </ol> </li> </ol>
The Probabilistic Model Checker Storm: Evaluation Results and Replication Package
<p>This package contains logdata and replication scripts for the evaluation of the model checker Storm (www.stormchecker.org) as part of the paper:<br> "The Probabilistic Model Checker Storm" by Christian Hensel, Sebastian Junges, Joost-Pieter Katoen, Tim Quatmann, and Matthias Volk</p>
Data set for the manuscript "The Atmospheric Drivers of the Major Saharan Dust Storm in June 2020"
<p>This publication is under consideration at geophysical research letters.</p>
The perfect storm: Gene tree estimation error, incomplete lineage sorting, and ancient gene flow explain the most recalcitrant ancient angiosperm clade, Malpighiales
<p>The genomic revolution offers renewed hope of resolving rapid radiations in the Tree of Life. The development of the multispecies coalescent (MSC) model and improved gene tree estimation methods can better accommodate gene tree heterogeneity caused by incomplete lineage sorting (ILS) and gene tree estimation error stemming from the short internal branches. However, the relative influence of these factors in species tree inference is not well understood. Using anchored hybrid enrichment, we generated a data set including 423 single-copy loci from 64 taxa representing 39 families to infer the species tree of the flowering plant order Malpighiales. This order includes nine of the top ten most unstable nodes in angiosperms, which have been hypothesized to arise from the rapid radiation during the Cretaceous. Here, we show that coalescent-based methods do not resolve the backbone of Malpighiales and concatenation methods yield inconsistent estimations, providing evidence that gene tree heterogeneity is high in this clade. Despite high levels of ILS and gene tree estimation error, our simulations demonstrate that these two factors alone are insufficient to explain the lack of resolution in this order. To explore this further, we examined triplet frequencies among empirical gene trees and discovered some of them deviated significantly from those attributed to ILS and estimation error, suggesting gene flow as an additional and previously unappreciated phenomenon promoting gene tree variation in Malpighiales. Finally, we applied a novel method to quantify the relative contribution of these three primary sources of gene tree heterogeneity and demonstrated that ILS, gene tree estimation error, and gene flow contributed to 15%, 52%, and 32% of the variation, respectively. Together, our results suggest that a perfect storm of factors likely influence this lack of resolution, and further indicate that recalcitrant phylogenetic relationships like the backbone of Malpighiales may be better represented as phylogenetic networks. Thus, reducing such groups solely to existing models that adhere strictly to bifurcating trees greatly oversimplifies reality, and obscures our ability to more clearly discern the process of evolution.</p>
Data for "Martian oxygen and hydrogen upper atmospheres responding to solar and dust storm drivers: Hisaki space telescope observations"
<p>Data files (.npy) and python codes (.ipynb) to produce the figures in the paper.</p> <p>Download the zip file (dataforfigures_v2.zip), open plot_figX.ipynb with Jupyter notebook, and run it.</p> <p> </p>
Data from: Understanding the mechanisms of anti-tropical divergence in the seabird White-faced Storm-petrel (Procellariiformes: Pelagodroma marina) using a multi-locus approach
Analytical methods that apply coalescent theory to multilocus data have improved inferences of demographic parameters that are critical to understanding population divergence and speciation. In particular, at the early stages of speciation, it is important to implement models that accommodate conflicting gene trees, and benefit from the presence of shared polymorphisms. Here, we employ eleven nuclear loci and the mitochondrial control region to investigate the phylogeography and historical demography of the pelagic seabird White-faced Storm-petrel (Pelagodroma marina) by sampling subspecies across its antitropical distribution. Groups are all highly differentiated: global mitochondrial ΦST = 0.89 (P < 0.01) and global nuclear ΦST varies between 0.22 and 0.83 (all P < 0.01). The complete lineage sorting of the mitochondrial locus between hemispheres is corroborated by approximately half of the nuclear genealogies, suggesting a long-term antitropical divergence in isolation. Coalescent-based estimates of demographic parameters suggest that hemispheric divergence of P. marina occurred approximately 840 000 ya (95% HPD 582 000–1 170 000), in the absence of gene flow, and divergence within the Southern Hemisphere occurred 190 000 ya (95% HPD 96 000–600 000), both probably associated with the profound palaeo-oceanographic changes of the Pleistocene. A fledgling sampled in St Helena (tropical South Atlantic) suggests recent colonization from the Northern Hemisphere. Despite the great potential for long-distance dispersal, P. marina antitropical groups have been evolving as independent, allopatric lineages, and divergence is probably maintained by philopatry coupled with asynchronous reproductive phenology and local adaptation.
Data supporting Satellite in-situ electron density observations of the mid-latitude storm enhanced density on the noon meridional plane in the F region during the 20 November 2003 magnetic storm
<p>This is the data for the submitted paper: Satellite in-situ electron density observations of the mid-latitude storm enhanced density on the noon meridional plane in the F region during the 20 November 2003 magnetic storm. The data contains five files. The file NE_TGWeimer_2003324 is the electron density (NE) data along the CHAMP orbit on Nov 20, 2003. The file TGSED4_Mlat30_2003324 is the NE, HMF2, WI_ExB, VI_ExB and VN at Mlat = 30 on the noon meridional plane (MLT = 12 hr) in the Northern hemisphere on Nov 20, 2003. The temporal resolution is 1-min. The file TGSED4_Mlat60_2003324 is the NE, HMF2, WI_ExB, VI_ExB and VN at Mlat = 60 on the noon meridional plane (MLT = 12 hr) in the Northern hemisphere on Nov 20, 2003. The temporal resolution is 1-min. The file TGSED3_Mlat30_2003324 is the NE at Mlat = 30 as a function of MLT and UT. The temporal resolution is 5-min. The file TGSED3_Mlat60_2003324 is the NE at Mlat = 60 as a function of MLT and UT. The temporal resolution is 5-min.</p>
Tropical Cyclones in Global Storm-Resolving Models
This dataset contains information about the tropical cyclones simulated by nine global storm-resolving models (global storm-resolving models are global models with a horizontal resolution of < 5 km). The dataset contains two distinct data sources: (1) track files, which contain information about TC position, intensity, and size. (2) gridded data files with radius-height composites of the TC dynamic and thermodynamic structure. There is one track file and one gridded data file for each model. The overall dataset is part of the global storm-resolving model intercomparison project "DYAMOND" (Stevens et al. 2019, https://link.springer.com/article/10.1186/s40645-019-0304-z), and has been used in a study that is currently under review.
Investigation of a neutral 'tongue' observed by GOLD during the geomagnetic storm on May 11, 2019
<p>This dataset include all the data needed for the figures in the main text of JGR paper "Investigation of a neutral 'tongue' observed by GOLD during the geomagnetic storm on May 11, 2019". It include the percentage difference of TIE-GCM simulated column density ratio of O to N2 (O/N2) between DOY 128 and 130, between DOY 128 and 131, and the absolute difference of horizontal advection of O and N2 at pressure level -1.375 between DOY 128 and 131 from 0:10 to 6:10 UT, and the absolute difference of zonal and meridional wind at pressure level -1.375 between DOY 128 and 131 from 0:10 to 6:10</p>
Data repository for Lin et al. (2022) "Thermospheric neutral density variation during the "SpaceX" storm: Implications from physics-based whole geospace modeling"
This dataset contains the necessary data and plotting tools supporting the paper titled "Thermospheric neutral density variation during the "SpaceX" storm: Implications from physics-based whole geospace modeling", by Lin et al., 2022. The data set contains thermospheric mass density simulated by MAGE, TIEGCM, DTM, and MSIS for the 1-6 February 2022 geomagnetic storm event.
Storm-Time GNSS Propagation at Mid-Latitude Magnetic Conjugate Points
<p>This data set was used to investigate the responses of Total Electron Content (TEC) values at magnetic conjugate points during geomagnetically active conditions. It was performed for three magnetic conjugate pairs of Beijing-Learmonth, Petropavlovsk-Canberra and Bar Harbor-Palmer Station located in the mid-latitude region.</p>
Storm Surge Dataset
<p>This is the dataset used in a paper of "Model of Storm Surge Maximum Water Level Increase in a Coastal Area Using Ensemble Machine Learning and Explicable Algorithm" </p>
Code to run the analyses of "Forest storm resilience depends on the interplay between functional composition and climate - insights from European-scale simulations" by Barrere et al. (2024).
<p>Repository containing the code to run the model and statistical analyses of the paper "Forest storm resilience depends on the interplay between functional composition and climate - insights from European-scale simulations" by Julien Barrere, Björn Reineking, Maxime Jeaunatre and Georges Kunstler, accepted by Functional Ecology in 2024.</p><p> </p><p>The code requires prior installation of the <a href="https://github.com/gowachin/matreex">matreex</a> R package, developped by Maxime Jeaunatre (INRAE), and of the ```targets``` package. The data folder, required to run the code, can be made available upon request to julienbarrere3@gmail.com</p><p> </p><p>Once the packages are installed and the data folder is placer in the main folder, just run ```targets::tar_make()``` from R and the script will download the other packages required and run the analyses.</p><p> </p><p>A version of this code is also available in the github <a href="https://github.com/jbarrere3/FunDiv_ipm">repository</a></p><p> </p><p> </p>
Data for: The Precipitation Response to Warming and CO2 Increase: A Comparison of a Global Storm Resolving Model and CMIP6 Models
<p>Data to reproduce figures in manuscript "The Precipitation Response to Warming and CO$_2$ Increase: A Comparison of a Global Storm Resolving Model and CMIP6 Models" submitted to GRL</p>
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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.