Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
3
datasets available to search
ShareScore release 0.9.0
Dataset results
3 results for “snow index”
Snow Index
<p>Snow indexes are indicators of the snow present in the alps mountains. The indexes are calculated with an image processing pipeline.<br> <br> The dataset is a CSV file providing: snow index, snow percentage, latitude, longitude and date.</p> <p> </p> <p>THIS WORK IS SHARED UNDER THE FOLLOWING LICENSE CREATIVE COMMONS ATTRIBUTION-SHAREALIKE 4.0 INTERNATIONAL (CC BY-SA 4.0) <a href="https://creativecommons.org/licenses/by-sa/4.0/">https://creativecommons.org/licenses/by-sa/4.0/</a></p>
Annual Snow Timing Index Rasters for the Western US and Alaska, WY2001-2019
<p>Here, a collection of rasters describing annual snow onset (SO), snow cover duration (SCD), and day of snow disappearance (DSD) for WY2001-2019 over Alaska, Canada, and the Western United States (boundary box: -152W, -100W, 32N, 68N) are available. Units are in calendar Day of Year (DOY) for SO and DSD, and in days for SCD. Filenames follow the convention, "index_west_threshold_spatialsubdomain.tif". For example, "SCD_west_5-0000005376-0000005376.tif" indicates the file contains snow cover duration raster data obtained using a 5% threshold. Spatial subdomain naming convention is described below.</p> <p>These data accompany a manuscript entitled, "Investigating the Relationship Between Peak Snow-Water Equivalent and Snow Timing Indices in the Western U.S. and Alaska". A diagnostic model of peak SWE as a function of remotely sensed snow timing indices (the dataset provided here) was developed in the course of this study to address the following questions: 1) Are peak SWE and snow timing related?; 2) How does this relationship vary across the western United States?; and 3) What meteorological and topographical conditions affect this relationship?</p> <p>These rasters were created in the Google Earth Engine (GEE) from the MODIS MOD10A1 v006 product (MODIS/Terra Snow Cover Daily L3 Global 500m SIN Grid, Version 6). From the initial daily fSCA product, a moving median window (i.e., a low-pass filter) of filter length k=25 days was applied to obtain a binary snow cover series using fractional cover threshold of 1%, 5%, 10%, 20%, and 30% such that the timing indices may be extracted. The filter length smooths out small-scale short-lived snow deposition events that obscure snow timing. Pixels without seasonal snowpack (i.e., persistent year-round snow or little to no snow) were masked: within a given water year, pixels that 1) show no onset of snow between the 272nd day of year and end of calendar year (corresponding with the typical N. hemisphere timeframe for the start of snow accumulation), and/or 2) do not melt out between start of calendar year and the 272nd day of year (typical timeframe for the end of snowmelt) were masked. SCD was calculated as (DSD + 365 days - SO). Because of the large file size, rasters were split up spatially into multiple files by the GEE, and follow the naming convention for large file exports listed here: https://developers.google.com/earth-engine/guides/exporting. As stated, "the filename of each tile will be in the form baseFilename-yMin-xMin where xMin and yMin are the coordinates of each tile within the overall bounding box of the exported image." Each band represents a different water year and is labeled as such, e.g. "DSD_2001". </p>
A Global Dataset of Standardized Moisture Anomaly Index Incorporating Snow Dynamics (SZIsnow) from 1948 to 2010
<p>The SZI<sub>snow</sub> dataset was calculated based on systematic physical fields from the Global Land Data Assimilation System Version 2 (GLDAS-2) with the Noah land surface model. This SZI<sub>snow</sub> dataset considers different physical water-energy processes, especially snow processes. The evaluation shows the dataset is capable of investigating different types of droughts across different timescales. The assessment also indicates that the dataset has an adequate performance to capture droughts across different spatial scales. The consideration of snow processes improved the capability of SZI<sub>snow</sub>, and the improvement is evident over snow-covered areas (e.g., Arctic region) and high-altitude areas (e.g., Tibet Plateau). Moreover, the analysis also implies that SZI<sub>snow</sub> dataset is able to well capture large-scale drought events across the world. This drought dataset has high application potential for monitoring, assessing, and supplying information on drought, and also can serve as a valuable resource for drought studies.</p>
ScienceDex guides
Understand access before you commit
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.