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18 results for “Winter storm”
Storm Database Files for CLIMK–WINDS: A New Database of Extreme European Winter Windstorms
<p>This database is comprised of the four netCDF files containing the 50 most extreme European winter windstorms identified within the four input sources, with one netCDF file per source: ERA5 reanalysis, CCLM_ERA5_EUR-11 regional climate model simulation, COSMO-REA6 reanalysis, and CCLM_ERA5_CEU-3 regional climate model. This database was created by Clare Marie Flynn and its creation is described in the following paper: Flynn, C. M., Moemken, J., Pinto, J., Schutte, M., and Messori, G.: CLIMK–WINDS: A New Database of Extreme European Winter Windstorms, under review for final submission, Earth System Science Data, 2025.</p>
Two-wave Post-Disaster Survey on Climate Change Attitudes: Texas after Hurricane Harvey and the 2021 North American Winter Storms
<p><strong>Overview</strong></p> <p>This repository contains data needed to reproduce the analysis results from Chen et al. 2024. "Disaster Experience Mitigates the Partisan Divide on Climate Change: Evidence from Texas," <em>Global Environmental Change</em>. It is a study about climate change attitudes and experience with climate disasters across U.S. partisan groups. For details about the data, please see the published paper. Results reproduction code is available at <a href="https://github.com/tedhchen/floodStorm" target="_blank" rel="noopener">https://github.com/tedhchen/floodStorm</a>.</p> <p> </p> <p><strong>Data Set Details</strong></p> <p>`texas_climate_attitudes.csv` contains data from two waves of surveys of Democrats and Republicans living in Texas, with the following groups of variables.</p> <ul> <li>climate change attitudes</li> <li>self-reported exposure to climate disasters</li> <li>scientific information treatment condition and checks</li> <li>political leaning</li> <li>sociodemographics and residential location</li> <li>survey administration details</li> </ul> <p>`outage2021_data.RData` contains power outage data for counties and cities in Texas during Feb. 2020 and Feb. 2021.</p> <p>`outage2021_data_multithreshold.RData` contains power outage data for counties and cities in Texas during Feb. 2020 and Feb. 2021, aggregated to the county level based on different thresholds of uncertainty about which cities people live in.</p> <p>`gtrends_archive.RData` contains Google Trends data for "hurricane", "astros", and "power", in Texas between 2017 and 2021.</p> <p> </p> <p><strong>References</strong></p> <p>Please reference the original study when using this data set.</p> <p>Ted Hsuan Yun Chen, Christopher J. Fariss, Hwayong Shin, Xu Xu. 2024. "Disaster Experience Mitigates the Partisan Divide on Climate Change: Evidence from Texas." <em>Global Environmental Change</em>. <a href="https://doi.org/10.1016/j.gloenvcha.2024.102918" target="_blank" rel="noopener">doi:10.1016/j.gloenvcha.2024.102918</a>.</p>
Convection in future winter storms over Northern Europe - data
<pre><em>We provide the python code to reproduce the figures of the Environmental Research Letter entitled </em><em>"Convection in future winter storms" by S. Berthou et al.</em></pre> <p>Python library requirements:</p> <p>python 3.8.12</p> <p>pandas 1.4.1</p> <p>seaborn 0.11.2</p> <p>matplotlib 3.5.1</p> <p>numpy 1.22.3</p> <p>scipy 1.8.0</p> <p>statsmodel.api 0.13.2</p>
Рис. 2. РаспреΑеΛение трубконосых птиц (А — темноспинный аΛьбатрос, Б — гΛупыш, В — тонкокΛювый буревестник, Г — сизая качурка) в Охотском море и сопреΑеΛьных воΑах Тихого океана и Японского моря по резуΛьтатам суΑовых учетов в февраΛе — мае 2020 г. (особей/км2 на 10-минутных трансектах). СпΛошными Λиниями показаны учетные трансекты, пунктиром — 200-метровая изобата Fig. 2. Distribution of tubenoses — (А) Laysan albatross, (Б) Northern fulmar, (В) shorttailed shearwater, (Г) fork-tailed storm-petrel — in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan in February–May 2020 (birds/km2 on 10-minute transects). Solid lines indicate transects; dotted line indicates a 200 m isobath in Population of seabirds in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan during the winter-spring period of 2020
Рис. 2. РаспреΑеΛение трубконосых птиц (А — темноспинный аΛьбатрос, Б — гΛупыш, В — тонкокΛювый буревестник, Г — сизая качурка) в Охотском море и сопреΑеΛьных воΑах Тихого океана и Японского моря по резуΛьтатам суΑовых учетов в февраΛе — мае 2020 г. (особей/км2 на 10-минутных трансектах). СпΛошными Λиниями показаны учетные трансекты, пунктиром — 200-метровая изобата Fig. 2. Distribution of tubenoses — (А) Laysan albatross, (Б) Northern fulmar, (В) shorttailed shearwater, (Г) fork-tailed storm-petrel — in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan in February–May 2020 (birds/km2 on 10-minute transects). Solid lines indicate transects; dotted line indicates a 200 m isobath
Data from Zeppenfeld et al. 2023: "Winter storm risk assessment in forests with high resolution gust speed data", Eur. J. For. Res.
<p>Single-tree damage data from winter storm event "Lothar" 1999 in Baden-Wurttemberg, Germany. The data set includes the response (damage or no damage) and covariates for model parametrisation as described in Zeppenfeld et al. (2023).</p>
Northeast US Regional NEXRAD radar mosaics of winter storms from 1996-2023, part 2
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Northeast US Regional NEXRAD radar mosaics of winter storms from 1996-2023, part 1
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Responses of White-throated sparrows to simulated winter storm cues
<p class="MsoNoSpacing">These data were used in the publication "Increased frequency of exposure to simulated winter storm cues negatively affects white-throated sparrows (<em>Zonotrichia albicollis</em>)" Front. Ecol. Evol. | doi: 10.3389/fevo.2020.00222</p> <p>Climate change is causing changes in weather patterns and more frequent extreme weather events. Although birds are often able to cope with and respond to inclement weather with physiological and behavioral responses, as weather events become more severe or frequent the adaptive coping responses of many species may be pushed beyond their limits. We investigated the effects of experimental recurrent inclement winter weather cues on body composition, glucocorticoid hormones, and behavior of white-throated sparrows (<em>Zonotrichia albicollis</em>). We used a hypobaric climatic wind tunnel to simulate storms by transiently decreasing barometric pressure and temperature, and measured behavioral responses, body composition, and baseline corticosterone levels in birds exposed, or not exposed (control), to different frequencies of simulated storms. In study 1, experimental birds were exposed to one storm per week over 9 weeks. In study 2, experimental birds were exposed to two storms per week over 12 weeks. Birds exposed to one simulated storm per week had higher fat and lean masses than control birds, with no differences in the amount of time groups spent feeding. This change in body composition suggests that birds were coping by increasing energy stores. In contrast, birds exposed to two simulated storms per week had lower fat masses compared to control birds, even though they spent more time feeding. Experimental birds in study 2 also had lower baseline corticosterone levels than controls. These changes suggest that the coping response observed in study 1 was overcome in study 2. These findings provide novel experimental evidence that birds detect and respond to changes in temperature and barometric pressure independent of other storm-related cues. One simulated storm per week resulted in potentially adaptive responses of increase mass. However, increasing the frequency of storm exposure to twice per week may exceed a physiological threshold for tolerance to which these songbirds are able to cope. These results also experimentally demonstrate that repeated exposure to inclement weather cues can directly affects birds' energy reserves, with strong implications for survival as severe weather events continue to become more prevalent.</p>
Data for the figures in "In-cloud characteristics observed in US Northeast and Midwest non-orographic winter storms with implications for ice particle mass growth and residence time"
<div> <div>This repository contains data shown in the figures in Allen, L. R., Yuter, S. E., Crowe, D. M., Miller, M. A., and Thornhill, K. L.: "In-cloud characteristics observed in US Northeast and Midwest non-orographic winter storms with implications for ice particle mass growth and residence time," to be submitted to Atmospheric Chemistry and Physics.</div> <div> </div> <div> <div> <div>Description of the original data sources: All of the NASA IMPACTS data are archived by GHRC at https://ghrc.nsstc.nasa.gov/uso/ds_details/collections/impactsC.html (McMurdie et al., 2019). The NSF PLOWS 1-second flight-level data are archived by the UCAR Earth Observing Laboratory at https://data.eol.ucar.edu/dataset/113.063 (UCAR/NCAR - Earth Observing Laboratory, 2011). ERA5 hourly data on pressure levels are available from the Copernicus Climate Data Store at https://cds.climate.copernicus.eu/datasets/reanalysis-era5-pressure-levels?tab=overview (Hersbach et al., 2023b). ERA5 hourly single-level data are available from the Copernicus Climate Data Store at https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels?tab=overview (Hersbach et al., 2023a).</div> </div> </div> </div>
Data for "Hunting for gravity waves in non-orographic winter storms using 3+ years of regional surface air pressure networks and radar observations"
<p>These data are shown in the figures included with the article "Hunting for gravity waves in non-orographic winter storms using 3+ years of regional surface air pressure networks and radar observations," submitted to Atmospheric Chemistry and Physics.</p>
Data corresponding to "Disparities in disruptions to public drinking water service in Texas communities during Winter Storm Uri 2021"
<p><strong>Contents:</strong></p> <p><strong>TX_pws_data_uri_zenodo.csv</strong>: This dataset was generated by integrating information on community public water systems (PWSs) from the Texas Commission of Environmental Quality (TCEQ) and Texas Water Development Board's water service boundary viewer, weather data from the National Oceanic and Atmospheric Administration (NOAA), and demographic information from the US Census Bureau's 2010 Decennial Census. More information is available in:<br> Tomko, Brianna, 2022, Public drinking water access in Texas communities during Winter Storm Uri 2021, Bachelor Thesis, The Ohio State University, Columbus. </p> <p><strong>readme_for_TX_pws_data_uri_zenodo.txt</strong>: Explains contents of TX_pws_data_uri_zenodo.csv.</p> <p><strong>WaterOutageSurvey-PeopleOnPublicWaterSystems.xlsx</strong>: This dataset was generated as part of a cross-sectionally survey of people living in Texas during Winter Storm Uri.</p> <p>More information on all datasets is available in:</p> <p>Tomko, B., C.L. Nittrouer, X. Sanchez-Vila, and A.H. Sawyer. (2023) "Disparities in disruptions to public drinking water services in Texas communities during Winter Storm Uri 2021," provisionally accepted at PLOS Water, doi: 10.1371/journal.pwat.0000137.</p>
Responses of White-throated sparrows to simulated winter storm cues
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Data from: Winter storms drive rapid phenotypic, regulatory and genomic shifts in the green anole lizard
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Code for GMD publication - Simulated microphysical properties of winter storms from bulk-type microphysics schemes and their evaluation in WRF (v4.1.3) model during ICE-POP 2018
<p>In this repository, we include the source codes for WRF microphysics parameterization used in the GMD publication "Simulated microphysical properties of winter storms from bulk-type microphysics schemes and their evaluation in WRF (v4.1.3) model during ICE-POP 2018."</p> <p>The four 2-moment bulk microphysical parameterization codes, WDM6, WDM7, Thompson, and Morrison, are divided into 3 WDM, Thompson, and Morrison codes, and each code has been modified so that detailed microphysical processes can be checked in wrfout.</p> <p>The WDM6 and WDM7 schemes include numerical errors for ice microphysical parameterization (Kim and lim, 2021) and for cloud evaporation and melting processes (Lei et al., 2020).</p> <p>Namelist files shows the namelist.input for each case.</p> <p> </p> <p> </p>
Data for "Revisiting the reanalysis-model discrepancy in Southern Hemisphere winter storm track trends"
<p>The dataset supporting the conclusion of the submitted paper is uploaded here.</p> <p>The data are labeled after each figure. The npz files include data required to reproduce our results in python arrays.</p>
Layers of enhanced spectrum width within Northeast United States coastal winter storms
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Loss of branches due to winter storms could favor deciduousness in oaks
<p>Premise of the study. Ecologists have an incomplete understanding of the factors that select for deciduous, evergreen, and marcescent leaf habits. Evergreens have more opportunities for photosynthesis but may experience costs when abiotic conditions are unfavorable such as during ice and windstorms.</p> <p>Methods. We documented branch loss for species of oaks (<i>Quercus</i> spp) in a common garden in California during an unusual windstorm.</p> <p>Key Results. Branches of marcescent trees were more likely to break during the storm and this pattern had a negligible phylogenetic signature. Branches of evergreen and marcescent species were mostly alive prior to breaking, which likely accrued a fitness cost, while those of deciduous species were mostly already dead. One explanation for the overrepresentation of broken branches from marcescent species is that their petioles are inflexible and have greater wind loading compared to the flexible petioles of evergreen leaves and the leafless condition of deciduous branches.</p> <p>Conclusions. These results suggest that branch loss during unusual winter storms may be an important cost of a marcescent leaf habit.</p>
Loss of branches due to winter storms could favor deciduousness in oaks
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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.
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.