Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Data used for the publication Eiselt and Graversen: Predicting avalanche danger in northern Norway using statistical models, published as a preprint here: https://doi.org/10.5194/egusphere-2024-2865
The datasets were produced from NORA3 (as well as seNorge based on NORA3) downloaded from: https://thredds.met.no/thredds/catalog/nora3_subset_atmos/catalog.html
The metocean-api was used to download the data: https://github.com/MET-OM/metocean-api
The Python scripts to calculate the predictive features are published here: https://doi.org/10.5281/zenodo.14528117
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
http://inspire.ec.europa.eu/metadata-codelist/LimitationsOnPublicAccess/noLimitationshttp://inspire.ec.europa.eu/metadata-codelist/LimitationsOnPublicAccess/noLimitations
GEMS Survey Ltd. (GEMS) was awarded a contract by Channel Energy Limited to undertake metocean data collection in the Bristol Channel as part of the Atlantic Array wind farm development project. The scope of work includes the deployment of two acoustic wave and current (AWAC) units and one Directional Waverider Buoy. Ancillary work includes water and sediment sampling and water profiling. Following non-recovery of AWAC devices, TRIAXYS Directional Wave buoys were utilised for the rest of the survey. This series contains both reports and datasets associated with the Metocean Assessment.
Forecast, Real time and historical metocean data for the spanish waters
http://spdx.org/licenses/CC0-1.0http://spdx.org/licenses/CC0-1.0
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This dataset consists of three MetOcean SVP (Surface velocity profilers, MetOcean 2014) buoys deployed on Arctic sea ice during the CIRFA 2022 cruise in western Fram Strait (see Figure 1). At the time of the deployment the sea ice was stationary (fast ice) due to connection to grounded icebergs. Later (June 5, 2022, for SVP #1; June 20, 2022, for SVP #2 and SVP #3) the fast ice disconnected and started drifting. Each SVP includes a GPS, air pressure and temperature sensors connected to an Iridium modem and mounted inside a waterproof ruggedized buoy.
Data are time series and include time, latitude, longitude, air temperature inside buoy (°C), air pressure (mbar), pressure tendency (mbar), and battery voltage (V) for each of the three buoys after they were deployed (see Table 1). The measurement interval was initially 60 minutes, then changed in July 2022 to 30 minutes, later in November 2022 changed to one reading per 24 hours or 48 hours (see Table 2). The time series ended when the buoys became stationary (75.1°N for SVP #1, Sep 26, 2022; 65.8°N for SVP #2, Oct 30, 2022) or reached positions further south than 52.3°N for SVP #3 (Jan 17, 2023) / reaching 58.1°N f (Mar 29, 2023).
The average snow depth upon installation was 29 cm for SVP #1 site, 26 cm for SVP #2 site, and 12 cm for SVP #3 site. Temperature might be biased because of solar radiation; the sensor is neither ventilated nor placed in a radiation shield. SVP #1 IMEI 300234064770040; SVP #2 IMEI 300234064772040; SVP #3 IMEI 300234064776030.
https://api.npolar.no/dataset/ab9371f7-542f-4e07-beb0-3d2771d1d111/_file/92a36320069a227bd1685020739dab61?key=044ab37a19834f255acd662512973705+uflj8aG_UBkgFoVkekX7OfmSKRrKk6mK" alt="buoys_map.png">
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Data used for the publication Eiselt and Graversen: Predicting avalanche danger in northern Norway using statistical models, published as a preprint here: https://doi.org/10.5194/egusphere-2024-2865
The datasets were produced from NORA3 (as well as seNorge based on NORA3) downloaded from: https://thredds.met.no/thredds/catalog/nora3_subset_atmos/catalog.html
The metocean-api was used to download the data: https://github.com/MET-OM/metocean-api
The Python scripts to calculate the predictive features are published here: https://doi.org/10.5281/zenodo.14528117