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256 results for “Cyclone”

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zenodo32/100

Nitrogen fixation rates in a cyclone-anticyclone eddy pair in the North Pacific Subtropical Gyre (Cruise KOK1607)

<p>Surface N<sub>2</sub> fixation rates were measured in the center of a cyclonic eddy (23.74&deg;N, 157.39&deg;W), an anticyclonic eddy (22.94&deg;N, 155.95&deg;W), and an additional station between the two eddies (23.44&deg;N, 156.78&deg;W) during May&nbsp;2016. Seawater was collected from 25 m and sampled into 4.4 L bottles, spiked with <sup>15</sup>N<sub>2</sub>-enriched seawater, and incubated in surface-seawater cooled, flow-through, deck-board incubators fitted with screening to reproduce in situ light conditions. These incubations were conducted during the day (10 h incubation, 08:00-18:00 local time) and at night (6 h incubation, 22:00-04:00 local time), using seawater from separate CTD casts prior to each incubation. Times provided are the average time of each incubation. Details on <sup>15</sup>N<sub>2</sub>-enriched seawater preparation and other methodological details for the rate measurements are provided in B&ouml;ttjer et al. (2017, <em>Limnology and Oceanography</em>, doi: 10.1002/lno.10386).</p> <p>Additional physical and biogeochemical data collected on cruise KOK1607 are available online: http://scope.soest.hawaii.edu/data/hoelegacy/data/</p>

opencc-by-4.0Oct 2021View details →
zenodo32/100

Statistics of the Subgrid Cloud of an Idealized Tropical Cyclone at Convection-Permitting Resolution

<p>Data and analysis scripts for figures&nbsp;of Journal article (Statistics of the Subgrid Cloud of an Idealized Tropical Cyclone at Convection-Permitting Resolution)</p>

opencc-by-4.0Nov 2022View details →
zenodo32/100

Tropical Cyclone Evaluation Methodology Dataset

<p>This dataset includes Automated Tropical Cyclone Forecast (ATCF) format ASCII files. These data are a subset of files from the Hurricane Forecast Improvement project (HFIP) Stream 1.5 evaluation covering three years of retrospective forecasts from 2010-2012.&nbsp;The best track analysis (b-decks), operational baselines (a-deck), and experimental Stream1.5 model output included can be used as example data to perform tropical cyclone model forecast evaluations, following Brown et al, 2023: User-responsive diagnostic verification methods for evaluating tropical cyclone track and intensity forecasts.</p>

opencc-by-4.0Apr 2023View details →
zenodo32/100

Azimuthally averaged tangential wind and radial wind for 3D WRF tropical cyclone simulations

<p>MAT-file&nbsp;</p> <p>setup number 1 to 9: V20B0.75R75, V20B0.75R100, V20B0.75R125;&nbsp;V20B1.0R75, V20B1.0R100, V20B1.0R125;&nbsp;V30B0.75R75, V30B0.75R100, V30B0.75R125</p> <p>time: hourly output</p> <p>iradius: radial grids, radius=(iradius-1)*2 km</p> <p>Vt(setup, time, iradius): tangential wind calculated from 10-m wind</p> <p>Vr(setup, time, iradius): radial wind calculated from 10-m wind</p> <p>M(setup, time, iradius): absolute angular momentum calculated using M=Vt*r+1/2*f*r^2</p> <p>nt(setup): maximum time step, 1 h interval</p> <p>nr(setup): maximum grid for radius, starting from center (0km)&nbsp;with 2 km interval</p> <p>Vmax(setup, time): maximum 10-m tangential wind</p> <p>RMW(setup, time): radius of&nbsp;maximum 10-m tangential wind</p> <p>MRMW(setup, time): absolute angular momentum at RMW</p> <p>SL(setup, time): M*(r*) slope calculated using best linear fit</p> <p>RIstart(setup): RI onset time</p> <p>RIend(setup): RI end time</p>

opencc-by-4.0May 2023View details →
zenodo32/100

Precipitation Microphysics in Tropical Cyclones: A Global Perspective Using the NASA Global Precipitation Measurement Mission Dual-Frequency Precipitation Radar

<p>This dataset includes all files (in .npy format) that was used to plot distributions of the slopes of vertical profiles of reflectivity in the liquid phase, in the ice phase, and echo top heights using the NASA Global Precipitation Measurement mission Dual-Frequency Precipitation Radar.&nbsp;</p>

opencc-by-4.0Jul 2023View details →
zenodo32/100

Cyclone_ESS

<p>datasets for the paper &quot;Effects of solar variability on tropical cyclone activity&quot; submitted to Earth and Space science.</p>

opencc-by-4.0Jul 2023View details →
zenodo32/100

Data Used for the Publication "Use of Threshold Parameter Variation for Tropical Cyclone Tracking"

<p>Data used to produce the figures in &quot;Use of Threshold Parameter Variation for Tropical Cyclone Tracking,&quot; as submitted to GMD.</p>

opencc-by-4.0Jul 2023View details →
zenodo32/100

Assessing the improvement of Tropical Cyclone representation in the IPSL model with increasing resolution -- Data

<p>This folder contains the following data, used in the artcle &quot;Assessing the improvement of Tropical Cyclone representation in the IPSL model with increasing resolution&quot;:</p> <p>* TC tracks in all the simulations, before and after the STJ filtering</p> <p>* Composite NetCDFs</p> <p>* Large scale variables used in the GPI, and the GPI itself, in ICO-VHR and ERA5</p>

opencc-by-4.0Jul 2023View details →
zenodo32/100

Data from "Connecting large-scale meteorological patterns to extratropical cyclones in CMIP6 climate models using self-organizing maps"

<p>The following files were used as data and analysis in the article &quot;Connecting large-scale meteorological patterns to extratropical cyclones in CMIP6 climate models using self-organizing maps&quot; (<a href="https://doi.org/10.1029/2022EF003211">https://doi.org/10.1029/2022EF003211</a>).&nbsp;In the study, we applied&nbsp;self-organizing maps (SOMs) as an automated machine-learning approach to characterize the large-scale meteorological patterns (LSMP) and associated frequency and intensity of discrete extratropical cyclone (ETC)&nbsp;events over the northeastern U.S. The dominant patterns of geopotential height variability are identified through SOM analysis of five reanalysis products during 1980 -&nbsp;2019. ETC events are tracked using TempestExtremes and are integrated with SOMs to classify the accumulated cyclone activity associated with each pattern. We then evaluate the skill of CMIP6 historical experiments in simulating the LSMP&nbsp;and ETC events identified in the SOM. Please see the published paper for more details. Here we have archived:&nbsp;</p> <p>- data pre-processing scripts</p> <p>- code to run the self-organizing map analysis</p> <p>- code to&nbsp;calculate the SOM and ETC statistics</p> <p>- composites of 500-hPa geopotential&nbsp;height for each dataset as organized by the SOM</p> <p>- ETC tracking script&nbsp;and tracking output for each dataset</p> <p>- SOM output for each dataset&nbsp;</p>

openagpl-3.0-or-laterJul 2023View details →
zenodo32/100

Economic impacts of tropical cyclone-induced multiple hazards in China

<p>The data and codes will be deposited in a repository that is appropriate for my scientific domain and that it is interoperable and reusable.</p>

opencc-by-4.0Aug 2023View details →
zenodo32/100

Collection of The tropical cyclones best-track data (CMABSTdata) and the daily surface climatological stations dataset for China (V3.0) from CMA

<p>This dataset contains the tropical cyclones best-track data from the China Meteorological Administration (CMABSTdata)<strong>[1] </strong>and the daily surface climatological stations dataset for China (V3.0)<strong>[2] </strong>from 1979-2019 from China Meteorological Administration.</p> <p>[1] Y<span>ing, M., Zhang, W., Yu, H., Lu, X., Feng, J., Fan, Y., . . . Chen, D. (2014). An overview of the China Meteorological Administration tropical cyclone database.&nbsp;<em>Journal of Atmospheric and Oceanic Technology, 31</em>(2), 287-301. </span></p> <p>[2]<span>(CMA, http://data.cma.cn)</span></p>

opencc-by-4.0Aug 2023View details →
zenodo32/100

Data for "Using Convolutional Neural Network to Emulate Seasonal Tropical Cyclone Activity"

<p>The trained 600-member ensemble convolutional neural networks (CNNs) for seasonal tropical cyclone (TC) activity&nbsp;to allow future studies. Please refer Fu et al. (2023;&nbsp;<em>Using Convolutional Neural Network to Emulate Seasonal Tropical Cyclone Activity</em>) for more details.</p>

opencc-by-4.0Aug 2023View details →
ClinicalTrials.gov32/100

CYCLONES - CYClophosphamide LOw Dose and No Extra Steroid

ClinicalTrials.gov study NCT03492255. IPD Sharing: NO. Countries: 1. Publications: 16.

closedIPD-NOFeb 2026View details →
dryad32/100

Data from: Impacts and recovery from Severe Tropical Cyclone Yasi on the Great Barrier Reef

Open the record for dataset details and reuse information.

publicMar 2016View details →
dryad32/100

Data from: Globally consistent impact of tropical cyclones on the structure of tropical and subtropical forests

Open the record for dataset details and reuse information.

publicApr 2019View details →
zenodo28/100

Digitized flood location dataset during cyclone Amphan from newspaper survey

<p>A dataset of inundation location, digitized and geotagged from newspaper reports during cyclone Amphan over Bengal delta.</p> <p>Description of columns:</p> <p>1. District: Location name at 2nd administrative level</p> <p>2. Upazila: Location name at 3rd administrative level</p> <p>3. Location: Location name</p> <p>4. Lon: Longitude</p> <p>5. Lat: Latitude</p> <p>6. Type: Type of flood - Flood or Inundation</p> <p>7. Mechanism: Type of flood/inundation mechanism. Breach (Embankment breaching), Hightide (Unembanked low-land), Overtopping (Embankment overflow)</p> <p>8. Source: Source newspaper name.</p> <p>9. Date: Corresponding date of the publishing of the news.</p> <p>&nbsp;</p> <p><strong>Acknowledgement:</strong></p> <p>CNES (through the TOSCA project BANDINO) and Embassy of France in Bangladesh for financial support. Also support from French research agency (Agence Nationale de la Recherche; ANR) under the DELTA project (ANR-17-CE03-0001).</p>

opencc-by-4.0Oct 2020View details →
dryad28/100

Data for: Geography, taxonomy, extinction risk, and exposure of fully migratory birds to droughts and cyclones

<p class="MsoNormal"><strong>Aim</strong>: Anthropogenic climate change is predicted to drive unprecedented increases in the frequency and intensity of extreme climatic events, such as drought and cyclones. The impacts of these events on fully migratory species could be particularly severe and have cascading effects on the functioning of many ecosystems. We explore the relationships between geography, taxonomy, extinction risk, and the exposure of fully migratory birds to drought and cyclones.</p> <p class="MsoNormal"><strong>Location:</strong> Global.</p> <p class="MsoNormal"><strong>Time period:</strong> 1985-2014.</p> <p class="MsoNormal"><strong>Major taxa studied:</strong> 383 fully migratory bird species.</p> <p class="MsoNormal"><strong>Methods:</strong> We assessed exposure of fully migratory birds to cyclones and droughts, quantifying exposure by calculating the percentage of spatial overlap between a species' range and the extent of an extreme event within a given time series. We compared the level of cumulative exposure sustained by species among different taxonomic groups and within their breeding and wintering ranges; we also assessed whether species currently classed as 'threatened' are more cumulatively exposed than 'non-threatened' species.</p> <p class="MsoNormal"><strong>Results</strong>: We identified fully migratory bird species highly exposed to extreme climatic events and global geographic hotspots of species exposure. 4% of species were found to be highly exposed to cyclones and droughts in both their wintering and breeding ranges. Wintering ranges were, on average, more cumulatively exposed to cyclones than breeding ranges; there was no discernible difference in drought exposure between ranges. Species currently classed as threatened were shown to experience higher exposure to droughts than non-threatened ones in both ranges.</p> <p class="MsoNormal"><strong>Main conclusions:</strong> This exposure analysis provides the first step to a full global assessment of fully migratory bird species' vulnerability to extreme climatic events. Many species are at least as exposed to extreme events within their wintering ranges as in their breeding ranges, supporting calls for 'full cycle' assessment of migratory species' vulnerability to climate change. Our identification of hotspots of exposure may help to guide further monitoring, research, and management.</p>

opencc-zeroNov 2023View details →
zenodo28/100

Moat Areas Tend to Form in Tropical Cyclones with Broader Wind Fields

<p>azimuthal-mean data for CNTL and SMALL</p>

opencc-by-4.0Nov 2023View details →
zenodo28/100

Global eddy-induced variation in the intensities of tropical cyclones

Open the record for dataset details and reuse information.

opencc-by-4.0Dec 2023View details →
zenodo28/100

Datasets for Analyzing Tropical Cyclone Impacts on Hydrological Extremes in the Mid-Atlantic Region

<p>The data sets provided here were used for the climatological analysis of tropical cyclone impacts on hydrological extremes in the Mid-Atlantic region of the United States. This research was published in <em><strong>Environmental Research Letters</strong></em>&nbsp;<a href="http://doi.org/10.1088/1748-9326/ac2d6a">https://doi.org/10.1088/1748-9326/ac2d6a</a>.</p> <p>The data sets include:</p> <ul> <li><strong>hurdat_data/</strong> <ul> <li><strong>hurdat2-1950-2019_rev.txt:</strong>&nbsp;6-hourly entires of hurricane tracks for all events occurring in the Atlantic region.&nbsp;The first column HURID matches the first column in the hurdat2-1950-2019_seq.txt</li> <li><strong>hurdat2-1950-2019_seq.txt</strong>:&nbsp; <ul> <li>1st column: HURID</li> <li>2nd column: event ID. For example, AL092011 means: AL (Spaces 1 and 2) &ndash; Basin &ndash; Atlantic; 09 (Spaces 3 and 4) &ndash; ATCF cyclone number for that year; 2011 (Spaces 5-8, before the first comma) &ndash; Year;&nbsp;</li> <li>3r column: event Name, if available, or else &ldquo;UNNAMED&rdquo;&nbsp;</li> <li>4th column: number of best track entries</li> </ul> </li> </ul> </li> <li><strong>usgs_gage/</strong> <ul> <li><strong>Content:</strong>&nbsp;daily streamflow records from USGS gages over 10/01/1950-9/30/2019</li> <li><strong>Format</strong>: <ul> <li>1st column: timestamp</li> <li>2nd column: daily mean flow (in cfs)</li> </ul> </li> </ul> </li> <li><strong>usgs_gage_list</strong> <ul> <li><strong>Content</strong>:&nbsp;Summary of USGS gages used in the analysis</li> </ul> </li> <li><strong>livneh_ppt.mat</strong> <ul> <li><strong>Content</strong>:&nbsp;Summary of precipitation data used in the analysis in Matlab structure array. The array includes statistics derived from precipitation records for 2857 grid cells (1/16 degree resolution) covering the Mid-Atlantic region.&nbsp;</li> </ul> </li> </ul>

opencc-by-4.0Oct 2021View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

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abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record