Arctic Sea Ice Variability in the 20th and Early 21st Centuries: Synthesis of Observations and Models

20 世纪和 21 世纪初期的北极海冰变化：观测和模型的综合

• 批准号: 1203425
• 负责人: Axel Schweiger
• 金额: $ 69.49万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1203425&HistoricalAwards=false
• 关键词: Arctic; Sea; Ice; Variability; 20th

Much of the uncertainty in the pre-satellite sea ice record stems from the difficulty establishing a consistent record of sea ice variability that covers the entire Arctic from historical observations such as ship logs, reconnaissance flights, etc. These observations are scattered in space and time and the primary challenge in constructing a representative picture of sea ice variability from these records is to adequately sample the strong seasonal cycle and high spatial variability of sea ice in the Arctic. Sea ice reconstructions must therefore rely on interpolation in time and space, which is made difficult by the dynamic nature of sea ice. For some critically important climate variables, such as sea ice thickness and total arctic sea ice volume, no historical data exist. The PIs will conduct a Century-scale Arctic Sea Ice Reanalysis (CASIR) that synthesizes observations and models from 1872 to the present to produce a long-term record of arctic sea ice extent, concentration, thickness, and volume. Advances in atmospheric reanalysis, sea ice modeling, and recovery of historical data make CASIR possible. To construct CASIR, they will recover and collect new and existing historical sea ice observations as far back as the late 1800s and integrate them into a model validation and assimilation framework based on the Pan-arctic Ice-Ocean Modeling and Assimilation System (PIOMAS). This will include the extraction of sea ice variables from historical Revenue Service/Coast Guard ship logs that are now being transcribed and promise to fill important gaps in the Pacific sector of the Arctic. Through data assimilation and model calibration and validation, the observational record will be integrated into PIOMAS to generate CASIR. An ensemble of atmospheric forcing data for CASIR will be extracted from atmospheric reanalysis projects for the 20th century that are completed or currently underway. This ensemble, in addition to comparisons with observations, will be used to determine uncertainties in CASIR sea ice variables. The PIs will analyze CASIR ice extent, concentration, thickness, and volume, to characterize 20th century temporal and spatial variability, improve understanding of the mechanisms driving this variability, and place the recent sea ice decline in a longer term context.

卫星前海冰记录的大部分不确定性源于难以通过历史观测（例如船舶日志、侦察飞行等）建立覆盖整个北极的海冰变化的一致记录。这些观测分散在空间和时间上，从这些记录构建海冰变化代表性图的主要挑战是充分采样北极海冰的强季节性周期和高空间变化。因此，海冰重建必须依赖于时间和空间的插值，而海冰的动态性质使得这变得困难。对于一些极其重要的气候变量，例如海冰厚度和北极海冰总体积，不存在历史数据。 PI 将进行百年规模的北极海冰再分析 (CASIR)，综合 1872 年至今的观测结果和模型，生成北极海冰范围、浓度、厚度和体积的长期记录。大气再分析、海冰建模和历史数据恢复方面的进步使 CASIR 成为可能。为了构建CASIR，他们将恢复和收集早在1800年代末期的新的和现有的历史海冰观测结果，并将它们整合到基于泛北极冰海建模和同化系统（PIOMAS）的模型验证和同化框架中。这将包括从历史税务局/海岸警卫队船舶日志中提取海冰变量，这些变量现在正在转录，并有望填补北极太平洋地区的重要空白。通过数据同化和模型校准和验证，观测记录将集成到PIOMAS中生成CASIR。 CASIR 的大气强迫数据集合将从已完成或目前正在进行的 20 世纪大气再分析项目中提取。除了与观测结果进行比较之外，该集合还将用于确定 CASIR 海冰变量的不确定性。 PI 将分析 CASIR 冰的范围、浓度、厚度和体积，以表征 20 世纪的时间和空间变化，加深对驱动这种变化的机制的理解，并将最近的海冰减少放在更长期的背景下。