Linear Kinematic Features (leads & pressure ridges) detected and tracked in sea-ice deformation simulated in an Arctic configuration of MITgcm using a 2-km horizontal grid spacing from 1997 to 2008
Leads and pressure ridges are dominant features of the Arctic sea ice cover. Not only do they affect heat loss and surface drag, but also provide insight into the underlying physics of sea ice deformation. Due to their elongated shape they are referred as Linear Kinematic Features (LKFs). This data-...
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| Format: | Dataset |
| Language: | English |
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PANGAEA - Data Publisher for Earth & Environmental Science
2019
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| Online Access: | https://dx.doi.org/10.1594/pangaea.909636 https://doi.pangaea.de/10.1594/PANGAEA.909636 |
| Summary: | Leads and pressure ridges are dominant features of the Arctic sea ice cover. Not only do they affect heat loss and surface drag, but also provide insight into the underlying physics of sea ice deformation. Due to their elongated shape they are referred as Linear Kinematic Features (LKFs). This data-set includes LKFs that were detected and tracked in sea ice deformation simulated in an Arctic configuration of MITgcm using a 2-km horizontal grid spacing. The model data is sampled for the entire observing period of the RADARSAT Geophysical Processor System (RGPS). The data-set spans the winter month (November to May) from 1997 to 2008 and covers the entire Arctic Ocean. A detailed description of the model configuration and the data-set is provided in: Hutter, N. and Losch, M.: Feature-based comparison of sea-ice deformation in lead-resolving sea-ice simulations, The Cryosphere, https://doi.org/10.5194/tc-2019-88, accepted for publication, 2019. A detailed description of the algorithms deriving the data set is provided in: Hutter, N., Zampieri, L., and Losch, M.: Leads and ridges in Arctic sea ice from RGPS data and a new tracking algorithm, The Cryosphere, 13, 627-645, https://doi.org/10.5194/tc-13-627-2019, 2019. : Data Description:The data set covers all RGPS winter data, i.e. November to May for the years 1996/97 to 2007/08. The LKFs of each winter season are saved in one TAB-delimited text-file (ASCII). In total the data-set contains in 12 files.In the csv-file each row corresponds to one pixel of an LKF in this year. In individual pixels are sorted by date and LKF. Each LKF gets a identifier number (LKF No.) that is unique in this winter. For track features the LKF No.(s) of parent LKF(s) from the previous RGPS time record are provided. The columns of the csv-files are structured in the following way:Start Year, Start Month, Start Day, End Year, End Month, End Day, Date(RGPS format), LKF No., Parent LKF No., lon, lat, ind_x, ind_y, divergence rate, shear rateSpecific comments:Start Year, Start Month, Start Day -> Start date of the RGPS time record in which LKFs are detectedEnd Year, End Month, End Day -> End date of the RGPS time record in which LKFs are detectedDate in original RGPS format -> RGPS format of date (first for digits are the year, the last three digits are the number of days). This format is used as filename by RGPS.LKF No. -> each LKF in one winter has its unique identifier number that can be used to track the featureParent LKF No. -> LKF No. of the LKF from the previous time records, for that this LKF is a temporal continuation determined by the tracking algorithm. This entry can contain multiple numbers if the current LKF was formed from multiple LKFs. '0' is used as a fill value, if there is no parent LKF.ind_x,ind_y -> Indexes of the LKF pixel in original RGPS data that can be used to index original RGPS fieldslon, lat -> position of LKF pixeldivergence and shear rate -> The divergence and shear rate of RGPS deformation data at LKF pixel. The divergence rate can be used to distinguish leads and pressure ridges in the data-set, please see Hutter et al. (2019). |
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