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1,121 results for “weathering”
Climatological analysis of vegetation response to weather conditions in Emilia Romagna region (OAL-IT)
<p>The ambition of H2020 OPERANDUM project is to develop and document Nature Based Solutions (NBS) to mitigate risks associated with hydro-meteorological (HM) hazards. NBS mitigate risks by reducing the vulnerability of a particular system. The aim of this work is to demonstrate the use of multisource remote sensing data in documenting the impact of extreme HM events to advance knowledge on vulnerability and exposure. In particular the focus is to document past impacts due to extreme events selected from a characterization of recent (30 years) HM events in 11 Open Air Laboratories (OALs) where co-design, co-development and deployment of NBS are taking place. The impacts were documented by applying a wide spectrum of satellite image data and other, close – range, remote sensing techniques. A better understanding of the consequences due to extreme HM events in a particular area (OALs) is essential to identify elements at risk and expected to provide a reference to evaluate the reduction of vulnerability and mitigation of risks past the completion of NBS.</p> <p>This dataset contains Remote Sensing observations for the OAL-ITALY , notably:</p> <p>- Time series of daily MODIS Land Surface Temperature (original and reconstruction with Harmonic Analysis of Time Series (HANTS) from 2001 to 2017. </p> <p>- Time series of 8 days MODIS Normalized Difference Vegetation Index (NDVI) from 2001 to 2017 (original and reconstruction (daily) with Harmonic Analysis of Time Series (HANTS) ). </p> <p>- Time series of daily normalized NDVI anomalies calculated from 2001 to 2017. </p> <p>- Time series of daily normalized LST anomalies calculated from 2001 to 2017. </p> <p>- Time series of daily Normalized Drought Anomaly Index calculated from 2001 to 2017. </p> <p> </p> <p> </p> <p> </p>
Surface weather stations and lightning data
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Average monthly weather summaries (air temperature and precipitation) at airport Lindbergh Field, San Diego, CA, 1850 - ongoing.
Data obtained as monthly values from National Ocean and Atmosphere (NOAA) National Weather Service web site for San Diego WSO Airport, California (047740). The data, presented as two sets from 1850-1913 and from 1914-ongoing, are obtained and combined on a monthly basis and re-published.
Space-weather HMI Active Region Patch (SHARP)
SHARP stands for Space-weather HMI Active Region Patch. A SHARP is a DRMS series that contains (1) various space-weather quantities calculated from the photospheric vector magnetogram data and stored as FITS header keywords, and (2) 31 data segments (described in detail below), including each component of the vector magnetic field, the line-of-sight magnetic field, continuum intensity, doppler velocity, error maps and bitmaps. The data segments are not full-disk; rather, they are partial-disk, automatically-identified active region patches. SHARPs are calculated every 12 minutes. Often, there is more than one active region on the solar disk at any given time. Thus, SHARPs are indexed by two prime keys: time, T_REC, and HMI Active Region Patch Number, HARPNUM.
Aviation Safety Reporting System: Inflight Weather Encounters
A sampling of reports from both air carrier flight crews and GA pilots referencing encounters with severe or unforecast weather.
UNDERSTANDING SEVERE WEATHER PROCESSES THROUGH SPATIOTEMPORAL RELATIONAL RANDOM FORESTS
UNDERSTANDING SEVERE WEATHER PROCESSES THROUGH SPATIOTEMPORAL RELATIONAL RANDOM FORESTS AMY MCGOVERN, TIMOTHY SUPINIE, DAVID JOHN GAGNE II, NATHANIEL TROUTMAN, MATTHEW COLLIER, RODGER A. BROWN, JEFFREY BASARA, AND JOHN K. WILLIAMS Abstract. Major severe weather events can cause a significant loss of life and property. We seek to revolutionize our understanding of and ability to predict such events through the mining of severe weather data. Because weather is inherently a spatiotemporal phenomenon, mining such data requires a model capable of representing and reasoning about complex spatiotemporal dynamics, including temporally and spatially varying attributes and relationships. We introduce an augmented version of the Spatiotemporal Relational Random Forest, which is a Random Forest that learns with spatiotemporally varying relational data. Our algorithm maintains the strength and performance of Random Forests but extends their applicability, including the estimation of variable importance, to complex spatiotemporal relational domains. We apply the augmented Spatiotemporal Relational Random Forest to three severe weather data sets. These are: predicting atmospheric turbulence across the continental United States, examining the formation of tornadoes near strong frontal boundaries, and understanding the translation of drought across the southern plains of the United States. The results on such a wide variety of real-world domains demonstrate the extensive applicability of the Spatiotemporal Relational Random Forest. Our long-term goal is to significantly improve the ability to predict and warn about severe weather events.
High Mountain Asia Langtang Automatic Weather Station Measurements V001
This data set contains meteorological data, such as air temperature, pressure, rainfall intensity, relative humidity, and wind direction/speed measured by the International Centre for Integrated Mountain Development (ICIMOD).
Weather Research and Forecasting (WRF) Model IMPACTS V1
The Weather Research and Forecasting (WRF) Model IMPACTS dataset includes model data simulated by the Weather Research and Forecasting (WRF) model for the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. IMPACTS was a three-year sequence of winter season deployments conducted to study snowstorms over the U.S Atlantic Coast (2020-2022). The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. The WRF model provided simulations of the precipitation events that were observed during the campaign using initial and boundary conditions from the Global Forecast System (GFS) model and the North American Mesoscale Forecast System (NAM). The WRF IMPACTS dataset files are available from January 12 through March 7, 2020 in netCDF-3 format.
MuFoRa – A Multimodal Dataset of Traffic Elements Under Controllable and Measured Adverse Weather Conditions of Fog and Rain
<div> <p>This is a novel multimodal dataset of traffic elements consisting of image and point cloud files in typical adverse weather situations especially suited for autonomous driving sensors and algorithms performance characterization. The specialty of this dataset arises from parametric acquisition under controllable and measured fog (quantified as visibility) and rain intensity conditions in the indoor test facility of CARISMA - THI in collaboration with HM. </p> <p> </p> </div>
Data collected from solar and weather stations over a day
<p>Scientific data of EnergyLAB. These data come from solar and meteorological stations present on the following territories: Comoros, Madagascar, Mauritius, Seychelles. This server was created as part of the IOS-net project which aims to study the solar field and the optimization of solar intelligent energy systems in the countries of the IOC (Indian Ocean Commission). These data are served by Unidata's Thematic Realtime Environmental Distributed Data Services (THREDDS) Data Server (TDS) in a variety of interoperable data services and output formats.</p>
Lunar Space Weathering Maps Bundle
Lunar Space Weathering Maps
Mercury Space Weathering Maps Bundle
Mercury Space Weathering Maps
Cardiff Weather Dataset
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Mueller Ice Cap weather data
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Cycles agroecosystem model weather files under nuclear winter scenarios
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Dataset for: Brassica plants promote Apis mellifera visitation to Japanese apricot under cold weather conditions
<p>Dataset for our paper named "<strong><em>Brassica</em></strong><strong> plants promote <em>Apis mellifera</em> visitation to Japanese apricot under cold weather conditions</strong>".</p>
Mirador - Weather
Earth Science data access made simple. Our weather system includes the dynamics of the atmosphere and its interaction with the oceans and land. The improvement of our understanding of weather processes and phenomena is crucial in gaining an understanding of the Earth system.
MeteoSwiss ensemble weather forcing data (2019)
<p>MeteoSwiss CosmoE weather ensemble predictions for 2019, which were used for the calibration of the hydrodynamic model of Lake Geneva. The original dataset was modified to only contain the relevant pixels over the lake to reduce the total size of the dataset.</p>
A contribution to real-time space weather monitoring based on scintillation observations and IoT
<p>Here, all field measurements acquired for the article entitled: ''A contribution to real-time space weather monitoring based on scintillation observations and IoT'', by Santos Freitas et al (2022) in Advances in Space Research are made available. The Scintapp is also available for download. Details on the data format can be found in section 2 of the aforementioned article.</p>
weather-benchmark-test
<p>Geopotential and constants file.</p> <p>Version 2: Now as float32 and with attributes.</p> <p>Version 3: Now 2.8125 degrees and different latitude coordinates (32x64 and 64x128) </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.