Zhou Yingzhen yingzhenzhou0@outlook.com 0000-0002-9004-9224 2024 Comparison of MODIS and SGLI Albedo Retrievals Over the Sea of Okhotsk (January-May 2021) dataset https://doi.org/10.1594/PANGAEA.972834 2024-10-07T06:40:47 This dataset contains surface shortwave albedo retrieval and surface classification data derived from both MODIS and SGLI satellite sensors over the Sea of Okhotsk, covering the period from January to May 2021. The data is stored in NetCDF format and standardized on a 1-km grid, allowing for direct pixel-to-pixel comparison. The dataset consists of albedo values and surface classifications, enabling an in-depth analysis of retrieval consistency and discrepancies between the two sensors. Data were averaged over weekly time periods for valid sea-ice pixels. The specific dates for each weekly period are provided. The retrieval algorithm is described in https://doi.org/10.5194/tc-17-1053-2023. Zhou Yingzhen yingzhenzhou0@outlook.com 0000-0002-9004-9224 2024 Albedo Retrievals from MODIS Over the Sea of Okhotsk (Validation Data, 2002–2014) dataset https://doi.org/10.1594/PANGAEA.972844 Zhou Yingzhen yingzhenzhou0@outlook.com 0000-0002-9004-9224 Chen Nan 2023 Validation data of measured VIS/NIR/SW albedo derived from the ACLOUD campaign and retrieval data (sea ice surface albedo and surface classification) from MODIS dataset https://doi.org/10.1594/PANGAEA.961709 Zhou Yingzhen yingzhenzhou0@outlook.com 0000-0002-9004-9224 Li Wei wli4@stevens.edu Chen Nan Fan Yongzhen Stamnes Knut 0000-0002-8880-6070 2023 A sensor-agnostic albedo retrieval method for realistic sea ice surfaces: model and validation The Cryosphere 17(2) https://doi.org/10.5194/tc-17-1053-2023 1053-1087 135.0 165.0 40.0 64.0 150.0 52.0 2021-01-08T00:00:00 2021-05-12T00:00:00 Sea_of_Okhotsk_2021 40.0 135.0 Okhotsk Sea 2021-01-08T00:00:00 64.0 165.0 2021-05-12T00:00:00 Satellite remote sensing SAT 1.5 CC-BY-4.0 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/ The dataset includes the following variables: 1. MODIS_SW_albedo: Albedo values retrieved from the MODIS sensor using the SciML albedo retrieval algorithm. Values are provided for the period January-May 2021 on a grid with a spatial resolution of 1 km. 2. MODIS_mask: Surface classification mask for the MODIS sensor. The mask values correspond to different surface types and features: • 0: Water • 1: Sea-ice • 2: Sea-covered ice 3. SGLI_SW_albedo: Albedo values retrieved from the SGLI sensor using the the SciML albedo retrieval algorithm. These values are provided for the same time period (January-May 2021) and grid as the MODIS data. 4. SGLI_mask: Surface classification mask for the SGLI sensor. The mask uses the same classification scheme as the MODIS mask: • 0: Water • 1: Sea-ice • 2: Sea-covered ice --- Time Periods Covered: The dataset spans eight weekly time intervals, corresponding to the following periods: • 2021-01-08 ~ 2021-01-13 • 2021-01-31 ~ 2021-02-06 • 2021-02-11 ~ 2021-02-17 • 2021-03-05 ~ 2021-03-12 • 2021-03-15 ~ 2021-03-20 • 2021-04-01 ~ 2021-04-07 • 2021-04-22 ~ 2021-04-30 • 2021-05-07 ~ 2021-05-12 Each period represents a weekly aggregate of albedo and surface classification data from both sensors, averaged where valid sea-ice pixels were present. --- Format: The dataset is provided in NetCDF format (.nc), which can be read and analyzed using common geospatial and scientific data tools such as Python's xarray or Panoply. CurationLevelC Enhanced curation https://wiki.pangaea.de/wiki/Curation_levels citable Albedo Okhotsk Sea Sea ice author100574 author100575 author100576 author100577 author76539 curlevel30 event3189135 geocode1599 geocode1600 geocode1601 journal4140 license21 method11573 ref119264 refds961709 refds972844 term21436 term47389 term48200 term54455