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datasets available to search
ShareScore release 0.9.0
Dataset results
11 results for “extreme weather events”
Supply Chain Shocks due to extreme weather events
<p>Projected supply chain shocks due to extreme weather events measured in annual percentage change in a country-sector's export activity compared to the baseline period</p>
Extreme Weather Event database over Aotearoa New Zealand
<p><strong>The Aotearoa New Zealand (ANZ) Extreme Weather Events (EWE) database </strong>(EWE_database_V1.0.0.xlsx)<strong> is a comprehensive record of extreme weather events in ANZ. The events listed in this database have been carefully assessed and categorized based on their meteorological significance, considering their rarity and whether they broke records or triggered official weather warnings. Some of the metrics used to classify each event rely on subjective judgment and expert opinions. The database captures meteorologically significant events, including those that have caused substantial damage to properties or led to casualties, and, in some cases, includes supplementary information about their socioeconomic impacts. The information in the EWE database is primarily sourced from the Meteorological Service of New Zealand Ltd (MetService) and the National Institute of Water and Atmospheric Research (NIWA). Additional impact data have been added from various media sources, with insured loss data for some events sourced from the Insurance Council of New Zealand (ICNZ).</strong></p> <p>Note - For more information about the database and the other additional files, please look into the Metadata (Metadata_EWE_V.1.0.0.docx) and the supplementary document (Supplementary document on EWE_V.1.0.0.docx).</p>
Extreme weather events threaten biodiversity and functions of river ecosystems: dataset for conducting the meta-analysis
<p>This repository contains the code and dataset to replicate the meta-analysis conducted by Sabater et al. entitled "Extreme weather events threaten biodiversity and functions of river ecosystems: evidence from a meta-analysis"</p> <p>Metadata:</p> <p>- metaanalysis_GlobalEvidenceRivers_Rscript.R - R Script to conduct the meta-analysis</p> <p>- structural_resp.csv - table with data to perform the species richness, density, and biomass meta-analysis. It includes the mean, SD (or SE), and sample number of the studies included in the meta-analysis, as well as information on the paper authors, year of publication, and type of study (experimental or observational). It also includes co-variates and the author who subtracts the information from the paper.</p> <p>- functional_resp.csv - table with data to perform the primary productivity, respiration, and decomposition meta-analysis. It includes the mean, SD (or SE), and sample number of the studies included in the meta-analysis, as well as information on the paper authors, year of publication, and type of study (experimental or observational). It also includes co-variates and the author who subtracts the information from the paper.</p> <p>-refMap.csv - Geographical information of the papers included in the meta-analysis.</p>
Socio-Technical Approach for the Assessment of Critical Infrastructure Systems Resiliency in Extreme Weather Events
<p>Datasets generated during and/or analyzed during the Socio-Technical Approach for the Assessment of Critical Infrastructure Systems Resiliency in Extreme Weather Events.</p>
Radiation Effects on Satellites during Extreme Space Weather Events (pre-publication dataset)
<p>Data for submitted paper entitled "Radiation Effects on Satellites during Extreme Space Weather Events".</p> <p>Submitted to AGU Space Weather.</p> <p> </p>
Supplementary figures for 'Domino: A new framework for the automated identification of weather event precursors, demonstrated for European extreme rainfall.'
<p>Supplementary dynamics and skill plots for the paper 'Domino: A new framework for the automated identification of weather event precursors, demonstrated for European extreme rainfall', submitted to QJRMS.</p>
Extreme Weather Event Real-time Attribution Machine (EWERAM) forecasts for Cyclone Gabrielle
<p>These files contain the hourly precipitation, wind, humidity, and pressure data as well as the land-sea mask, orography, and regional council data supporting the investigation into the human role in Cyclone Gabrielle performed by the EWERAM (Extreme Weather Event Real-time Attribution Machine) consortium. The EWERAM experiment design is outline by Tradowsky and co-authors (2023, 10.1088/2752-5295/acf4b4).</p> <p>Directory and data format follows the conventions of the Climate of the 20th Century Plus Detection and Attribution (C20C+ D&A) Project. Details are provided at https://portal.nersc.gov/c20c/experiment.html and in Stone and co-authors (2019, 10.1016/j.wace.2019.100206).</p>
Ecological resilience and resistance to extreme weather events - review data
<p>Extreme weather events (EWEs) are expected to increase in stochasticity, frequency, and intensity due to climate change. Documented effects of EWEs, such as droughts, hurricanes, and temperature extremes, range from shifting community stable states to species extirpations. To date, little attention has been paid to how populations resist and/or recover from EWEs through compensatory (behavioural, demographic or physiological) mechanisms; limiting the capacity to predict species responses to future changes in EWEs. Here, we systematically reviewed the global variation in species' demographic responses, resistance to, and recovery from EWEs across weather types, species, and biogeographic regions. Through a literature review and meta-analysis, we <span>tested the prediction that population abundance and probability of persistence will decrease in populations after an EWE and how compensation affects that probability. Across 524 species population responses to EWEs reviewed (27 articles), we noted large variation in responses, such that, on average, the effect of EWEs on population demographics was not negative as predicted. The majority of species populations (80.4%) demonstrated compensatory mechanisms during events to reduce their deleterious effects. However, for populations that were negatively impacted, the demographic consequences were severe. Nearly 20% of the populations monitored experienced declines of over 50% after an EWE</span>, and 6.8% of populations were extirpated. Population declines were reflected in a <span>reduction in survival. Further, resilience was not common, as 80.0% of populations that declined did not recover to before EWE levels while monitored. </span>However, average monitoring time was only two years with over a quarter of studies tracking recovery for less than the study species generation time. We conclude that EWEs have positive and negative impacts on species demography, and this varies by taxa. Species population recovery over short time intervals is rare, but long-term studies are required to accurately assess species resilience to current and future events.</p>
Data from: Interaction between extreme weather events and mega‐dams increases tree mortality and alters functional status of Amazonian forests
Open the record for dataset details and reuse information.
Ecological resilience and resistance to extreme weather events - review data
Open the record for dataset details and reuse information.
Network Analysis to Identify Critical Links for Relief Activities During Extreme Weather Events
<p>As one of the principal lifeline systems, transportation networks are crucial for evacuation and delivering essential resources and services during the response and recovery phases of extreme weather events and must remain intact to enhance regional resiliency. The conventional evaluation measures that estimate the vulnerability or criticality of road network based on travel time or link volumes do not capture the community impacts due to disruptions. This study seeks to develop a framework to evaluate road network infrastructure criticality during extreme weather events by introducing measures that evaluate the vulnerability of roads users, rather than the physical aspects of link importance. The research develops an innovative approach that integrates three important concepts including hurricane evacuation behavior, community impacts, and road criticality to identify the critical links. Results show that the critical links for vulnerable populations during evacuation do not always align with conventional link-based measures. This highlights the importance of using a performance measure that takes the social vulnerability of road users into consideration when identifying the criticality of a road network and planning for fortification of links to avoid irreversible consequences for vulnerable population groups. Furthermore, decision-making that considers the risks to different communities may lead to a more effective distribution of resources and help support a timely and safe evacuation from disaster events by strengthening the preservation of critical infrastructure links.</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.