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TVC Experiment 2018/19: Snow field measurements
Zenodo
Montpetit, Benoit; King, Joshua; Toose, Peter; Silis, Arvids; Derksen, Chris; Brady, Mike — 2024-03-07 This dataset contains in situ snow measurements recorded as part of Environment and Climate Change Canada's 2018-2019 Trail Valley Creek Snow Experiment (TVC Experiment 18/19). These measurements were collected to evaluate coincident airborne and satellite radar measurements to better understand snow-radar interactions in a tundra environment. The measurements were recorded 50 km north of the town of Inuvik, Northwest Territories around the Trail Valley Creek research station (https://www.trailvalleycreek.ca/). Three periods of measurement took place in November 2018, January 2019, and March 2019 . Measurements and observations were recorded in handwritten snow pit sheets before being transcribed to electronic sheets. The dataset is organized by surveyed site and includes: 1) manual snowpit measurements of the following parameters: Total snow depth, vertical profiles of snow temperature, snow density, stratigraphy and grain size and notes on site characteristics and environmental conditions. 2) distributed snow depth measurements around the surveyed sites recorded with an automatic snow depth probe (magnaprobe), 3) SnowMicroPenetrometer (SMP) force profiles coincident with the snowpit measurements and distributed along the magnaprobe transects with its metadata file, and 4) snow microstructure profiles measuring specific surface area (SSA) using the IceCube instrument. All geographic coordinates were recorded with Garmin GPS units using the geographic coordinate system: WGS 84 (EPSG: 4236). There are four type of data files: snow pit sheets, magnaprobe data, SMP-derived snow parameters and raw SMP penetration force profiles. Snow pit sheets and magnaprobe data are provided as Microsoft Excel (.xlsx) files. SMP-derived snow parameters are provided in comma-separated value (.csv) files. The raw SMP force profiles are binary (.pnt) files. A synthesized version of the magnaprobe snow depth data extracted and associated with a specific snow pit was previously published here https://doi.org/10.5281/zenodo.8350643 . https://open.canada.ca/en/open-government-licence-canada
Zenodo Translation missing: fr.blacklight.search.logo
TVC Experiment 2018/19: UMass Airborne Ku-Band SAR data
Zenodo
Montpetit, Benoit; King, Joshua; Siqueira, Paul; Adam, J. Max; Toose, Peter; Derksen, Chris; Brady, Mike — 2024-03-07 This dataset contains the processed, backscatter data from the airborne UMass Ku-Band SAR data, as part of Environment and Climate Change Canada's 2018-2019 Trail Valley Creek Snow Experiment (TVC Experiment 18/19). These measurements were collected to evaluate coincident ground snow data, airborne and satellite radar measurements to better understand snow-radar interactions in a tundra environment. The measurements were acquired around the Trail Valley Creek research station (https://www.trailvalleycreek.ca/) in Northwest Territories, Canada. Three periods of ground measurement, coincident with these airborne measurements, took place in November 2018, January 2019, and March 2019. The dataset consists of processed imagery with 100m averaged backscatter data and incidence angle data around all surveyed sites. Flight information and coincident field measurement metadata are also included. https://open.canada.ca/en/open-government-licence-canada
Zenodo Translation missing: fr.blacklight.search.logo
TVC Experiment 2018/19: LiDAR processed soil roughness
Zenodo
Montpetit, Benoit; King, Joshua; Toose, Peter; Derksen, Chris; Brady, Mike — 2024-03-07 This dataset contains the processed LiDAR data of Lange et al. (2021) (https://doi.pangaea.de/10.1594/PANGAEA.934387), as part of Environment and Climate Change Canada's 2018-2019 Trail Valley Creek Snow Experiment (TVC Experiment 18/19). These measurements were collected to evaluate soil roughness impacts on airborne and satellite radar measurements to better understand snow-radar interactions in a tundra environment. The measurements were around the Trail Valley Creek research station (https://www.trailvalleycreek.ca/) in Northwest Territories, Canada. Three periods of ground measurement took place in November 2018, January 2019, and March 2019. The dataset consists of LiDAR estimates of surface roughness statistics including the Root Mean Square (RMS) height and correlation length for a 100 m footprint around all in situ snowpit survey sites. The original dataset was collected by Lange et al. (2021) and can be retrieved here: https://doi.pangaea.de/10.1594/PANGAEA.934387 https://open.canada.ca/en/open-government-licence-canada
Zenodo Translation missing: fr.blacklight.search.logo
Canadian historical Snow Water Equivalent dataset (CanSWE, 1928-2023)
Zenodo
Vionnet, Vincent; Mortimer, Colleen; Brady, Mike; Arnal, Louise; Brown, Ross — 2024-03-18 Description (in English, French follows) The Canadian historical Snow Water Equivalent dataset (CanSWE) includes manual and automated pan-Canadian observations of Snow Water Equivalent (SWE) collected by national, provincial and territorial agencies, hydropower companies and their partners, as well as academic institutions. Snow depth and derived bulk snow density are also included when available. A code describes the SWE measurement method for each site following World Meteorological Organization (WMO) standards (WMO, 2019). This new dataset supersedes the most recent update of the Canadian Historical Snow Survey (CHSSD) dataset published by Brown et al. (2019) and available at https://doi.org/10.18164/cf337b6b-9a87-4ffd-a8e5-41e6498b1474. The creation of CanSWE used the 2019 CHSSD update as a starting point and involved three main steps: (i) correction and cleaning of the 2019 CHSSD update (correction of metadata, removal of duplicates), (ii) update of this cleaned dataset until July 2020 and addition of snow data from new stations and agencies, and (iii) consistent quality control of the final dataset. The version 6 of CanSWE includes over one million SWE measurements from 2921 different locations across Canada over the snow seasons 1928 – 2023 where a snow season is defined as starting August 01 and ending July 31. CanSWE is described in detail in Vionnet et al. (2021). The data are distributed in 2 formats: a NetCDF file (CanSWE-CanEEN_1928-2023_v6.nc) and a zip file containing a csv version of CanSWE (CanSWE-CanEEN_1928-2023_v6.zip). More details about the dataset, the file format and the update made in CanSWEv6 are given in the files ReadMe_CanSWE_v6.pdf (in English) and LisezMoi_CanEEN_v6.pdf (in French). Description (Francais) La base données historiques canadiennes d’Equivalent en Eau de la Neige (CanEEN) comprend des observations manuelles et automatiques de l’Equivalent en Eau de la Neige (EEN) à l’échelle du Canada collectées par des agences nationales, provinciales et territoriales, des compagnies productrices d’hydroélectricité et leurs partenaires ainsi que par des universités. Les informations sur la hauteur de neige et la masse volumique moyenne du manteau neigeux sont incluses lorsqu’elles sont disponibles. Un code qui suit les règles de l’Organisation Mondiale de la Météorologie (OMM, 2019) décrit la méthode de mesure de l’EEN pour chaque site. Cette nouvelle base de données remplace le jeu de données des Relevés Nivométriques Canadiens (RNC) publié par Brown et al. (2019) et disponible à l’adresse : https://doi.org/10.18164/cf337b6b-9a87-4ffd-a8e5-41e6498b1474. La création de CanEEN se base sur la version de 2019 des RNC et se décompose en 3 étapes principales : (i) correction et nettoyage de la version 2019 des RNC (correction des métadonnées, suppression des duplicata), (ii) mise à jour de ce jeu de données nettoyé avec des données disponibles jusqu’en Juillet 2020 et ajout de données historiques provenant de nouvelles stations et de nouveaux partenaires, (iii) contrôle qualité appliqué à l’ensemble du jeu de données. La version 6 de CanEEN inclut plus d’un million de mesures de l’EEN collectées dans 2921 stations à travers le Canada pour les années nivologiques 1928 à 2023 où une année nivologique est définie pour la période allant du 1 août au 31 juillet. CanEEN est décrit en détail dans Vionnet et al. (2021). Les données sont distribuées sous deux formats: un fichier au format NetCDF (CanSWE-CanEEN_1928-2023_v6.nc) et une archive zip contenant un fichier au format csv (CanSWE-CanEEN_1928-2023_v6.csv). Des informations complémentaires sur le jeu de données, leur format ainsi que les modifications apportées dans la version 6 sont fournies dans les fichiers ReadMe_CanSWE_v6.pdf (en Anglais) et LisezMoi_CanEEN_v6.pdf (en Francais). References/Références: Brown, R. D., Fang, B., and Mudryk, L.: Update of Canadian historical snow survey data and analysis of snow water equivalent trends, 1967–2016. Atmos. Ocean, 57, 149 156, https://doi.org/10.1080/07055900.2019.1598843, 2019 Vionnet, V., Mortimer, C., Brady, M., Arnal, L., and Brown, R.: Canadian historical Snow Water Equivalent dataset (CanSWE, 1928–2020), Earth Syst. Sci. Data, 13, 4603–4619, https://doi.org/10.5194/essd-13-4603-2021, 2021. WMO (World Meteorological Organization): Global Cryosphere Watch: Improvements in the international reporting of Snow Depth, WIGOS Newsletter, 5, 3-4, https://community.wmo.int/wigos-newsletters-archive, 2019 https://open.canada.ca/en/open-government-licence-canada
Zenodo Translation missing: fr.blacklight.search.logo
TVC Experiment 2018/19: Radarsat-2 backscatter data
Zenodo
Montpetit, Benoit; King, Joshua; Toose, Peter; Derksen, Chris; Brady, Mike — 2024-03-07 This dataset contains the processed, backscatter data from Radarsat-2 (RSAT-2) satellite data, as part of Environment and Climate Change Canada's 2018-2019 Trail Valley Creek Snow Experiment (TVC Experiment 18/19). These RSAT-2 data were collected and processed evaluate against a network of Steven’s HydraProbe soil monitoring sensors, and coincident in situ snowpit measurements, airborne radar, and other satellite radar data to better understand soil-snow-radar interactions in a tundra environment. The RSAT-2 data was ordered to provide wintertime coverage from September 2018 to July 2019, over the Trail Valley Creek research station (https://www.trailvalleycreek.ca/) in Northwest Territories, Canada. Three periods of in situ snow measurement took place in November 2018, January 2019, and March 2019. RSAT-2 data was acquired in Wide Fine Quad mode HH+HV+VH+VV. The RSAT-2 products were processed using the European Space Agency’s (ESA), Sentinel Application Platform (SNAP) software which included image calibration to sigma nought and orthorectification. An average of the calibrated backscatter and incidence angles was then calculated for an area 100 x 100 meters surrounding the geographic coordinates of each snowpit. RADARSAT-2 Data and Products © MacDonald, Dettwiler and Associates Ltd. (2018) – All Rights Reserved. RADARSAT is an official trademark of the Canadian Space Agency. https://open.canada.ca/en/open-government-licence-canada
Zenodo Translation missing: fr.blacklight.search.logo
Sea ice deformation and rotation rates (SIDRR) from the ECCC-ASITS
Zenodo
Plante, Mathieu; Lemieux, Jean-François; Tremblay, L. Bruno; Bouchat, Amélie; Ringeisen, Damien; Blain, Philippe; Howell, Stephen; Brady, Mike; Alexander, Komarov; Duval, Beatrice; Yakuden, Lekima; Labelle, Frédérique — 2024-10-15 Description: This dataset offers pan-Arctic sea ice deformation and rotation rates (SIDRR) computed from Sentinel1 (S1) or the Radarsat Constellation Mission (RCM) Synthetic Aperture Radar (SAR) imagery, based on Sea Ice Motion (SIM) vector outputs from the Environment and Climate Change Canada Automated Sea Ice tracking System (ECCC-ASITS, Howell et al., 2022). The ASITS produces lists of sea ice motion vectors derived by tracking recognizable features in overlapping pairs of SAR images (Komarov and Barber, 2014). The tracked features from each SAR image pair are triangulated, and the SIDRRs computed using a line integral method (Bouchat et al., 2020, 2022) based on the velocity and start location of each vertex.   Format: The raw SIDRR data from multiple SAR images are stacked in daily netcdf output files, based on the acquisition time of the earliest image in the pair. The netcdf files thus include data from variable time and space resolutions depending on the triangulation and images acquisition time, in the ranges of 4 - 20 km and 12 h - 6 days. Each file is named with the convention “SIDRR_YYYYMMDD.nc”. For example, “SIDRR_20210101.nc” contains data from pairs with the first image acquisition time on January 1st, 2021. Dimension and variable names: Dimensions:         n                           triangle ID number                              npts                     number of triangulated tracked points   Variables:              idpair (n)                  SAR scene pair ID number                              pts_idpair (npts)       SAR scene pair ID number                              ids1 (n)                     ID of triangle vertex 1                              ids2 (n)                     ID of triangle vertex 2                              ids3 (n)                     ID of triangle vertex 3                              start_time (n)            Acquisition time, SAR image #1                    (hrs since ref. time)                              end_time (n)             Acquisition time, SAR image #2                    (hrs since ref. time)                              start_lat (npts)          Tracked points start latitude                          (ºN)                              start_lon (npts)         Tracked points start longitude                       (ºE)                              end_lat (npts)           Tracked points end latitude                            (ºN)                              end_lon (npts)          Tracked points end longitude                         (ºE)                              A (n)                          Start triangle Area                                          (m2)                              errA (n)                     Propagation of tracking error on A                (m2)                              dudx (n)                    x-direction divergence rate                            (day-1)                              dvdy (n)                    y-direction divergence rate                            (day-1)                              dvdx (n)                    x-direction shear rate                                     (day-1)                              dudy (n)                    y-direction shear rate                                    (day-1)                              vrt (n)                        vorticity                                                         (day-1)                              err_vrt (n)                  Propagation of tracking error on vrt             (day-1)                              div (n)                       Divergent deformation rate                           (day-1)                              err_div (n)                 Propagation of tracking error on div             (day-1)                              shr (n)                       Shear deformation rate                                 (day-1)                              err_shr (n)                 Propagation of tracking error on shr            (day-1)                              s2n (n)                      Total deformation’s signal to noise ratio https://creativecommons.org/licenses/by/4.0/legalcode
Zenodo Translation missing: fr.blacklight.search.logo
TVC Experiment 2018/19: TerraSAR-X backscatter data
Zenodo
Montpetit, Benoit; Wendleder, Anna; King, Joshua; Toose, Peter; Derksen, Chris; Brady, Mike — 2024-03-07 This dataset contains the processed, backscatter data from TerraSAR-X (TSX) satellite data, as part of Environment and Climate Change Canada's 2018-2019 Trail Valley Creek Snow Experiment (TVC Experiment 18/19). These TSX data were collected and processed to evaluate against a network of Steven’s HydraProbe soil monitoring sensors, and coincident in situ snowpit measurements, airborne radar, and other satellite radar data to better understand soil-snow-radar interactions in a tundra environment. The TSX data was ordered to provide a wintertime series of repeat overpasses from September 2018 to June 2019, over the Trail Valley Creek research station (https://www.trailvalleycreek.ca/) in Northwest Territories, Canada. Three periods of in situ snow measurement took place in November 2018, January 2019, and March 2019. TSX data was acquired from two stripmap orbits, one in HH/HV and the other in VV/VH. The TSX products were processed using the European Space Agency’s (ESA), Sentinel Application Platform (SNAP) software which included image calibration to sigma nought and orthorectification. An average of the calibrated backscatter and incidence angles was then calculated for an area 100 x 100 meters surrounding the geographic coordinates of each snowpit. The TerraSAR-X data are available through the DLR (© DLR 2019). https://open.canada.ca/en/open-government-licence-canada

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