A Lagrangian Snow-Evolution System for Sea-Ice Applications (SnowModel-LG): Part I-Model Description.
A Lagrangian Snow-Evolution System for Sea-Ice Applications (SnowModel-LG): Part I-Model Description.
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DOI：
10.1029/2019jc015913
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发表时间：
2020-10
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影响因子：
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通讯作者：
Elder K
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文献类型：
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作者：
Liston GE;Itkin P;Stroeve J;Tschudi M;Stewart JS;Pedersen SH;Reinking AK;Elder K
使用拉格朗日雪演变模型（SnowModel-LG）在25 × 25 km网格上生成1980年8月1日至2018年7月31日（38年）的每日泛北极海冰上的雪属性分布。该模型采用了美国宇航局的现代研究和应用回顾分析第2版（MERRA-2）和欧洲中期天气预报中心（ECMWF）再分析-第5代（ERA 5）大气再分析，以及国家冰雪数据中心（NSIDC）海冰包裹浓度和轨迹数据集（约61，000，14 × 14-km包裹）。模拟进行全面的表面和内部的能量和质量平衡内的多层积雪演变系统。过程和特征包括降雨，降雪，静态表面和吹雪的升华，雪融化，雪密度演变，雪温度分布，积雪内的能量和质量转移，叠加冰和冰动力学。模拟产生的水平雪空间结构可能存在于自然系统中，但在以前的研究中没有发现这些空间和时间域。吹雪升华对积雪质量预算做出了重大贡献。叠加的冰层是最小的，在过去的四十年里减少了。雪携带到下一个积累季节是最小的，对融化季节的大气强迫敏感（例如，平均夏季融化期为3周或50%以上，ERA 5强迫比MERRA-2强迫）。观测到的冰动力学控制了冰的年龄（以天为单位），而冰的年龄对雪的性质演变产生了一阶控制。拉格朗日海冰上的雪模拟揭示了与冰运动相关的高分辨率雪特性空间结构与冰动力学相关的冰期强烈控制了雪特性的空间分布和时间演变一种新的高分辨率雪深度和密度产品可用于北极雪和海冰研究和应用
A Lagrangian snow‐evolution model (SnowModel‐LG) was used to produce daily, pan‐Arctic, snow‐on‐sea‐ice, snow property distributions on a 25 × 25‐km grid, from 1 August 1980 through 31 July 2018 (38 years). The model was forced with NASA's Modern Era Retrospective‐Analysis for Research and Applications‐Version 2 (MERRA‐2) and European Centre for Medium‐Range Weather Forecasts (ECMWF) ReAnalysis‐5th Generation (ERA5) atmospheric reanalyses, and National Snow and Ice Data Center (NSIDC) sea ice parcel concentration and trajectory data sets (approximately 61,000, 14 × 14‐km parcels). The simulations performed full surface and internal energy and mass balances within a multilayer snowpack evolution system. Processes and features accounted for included rainfall, snowfall, sublimation from static‐surfaces and blowing‐snow, snow melt, snow density evolution, snow temperature profiles, energy and mass transfers within the snowpack, superimposed ice, and ice dynamics. The simulations produced horizontal snow spatial structures that likely exist in the natural system but have not been revealed in previous studies spanning these spatial and temporal domains. Blowing‐snow sublimation made a significant contribution to the snowpack mass budget. The superimposed ice layer was minimal and decreased over the last four decades. Snow carryover to the next accumulation season was minimal and sensitive to the melt‐season atmospheric forcing (e.g., the average summer melt period was 3 weeks or 50% longer with ERA5 forcing than MERRA‐2 forcing). Observed ice dynamics controlled the ice parcel age (in days), and ice age exerted a first‐order control on snow property evolution. Lagrangian snow‐on‐sea‐ice simulations revealed high‐resolution, snow property spatial structures associated with ice motion Ice age, associated with ice dynamics, strongly controlled the spatial distributions and temporal evolution of snow properties A new, high resolution snow depth and density product is available for Arctic snow and sea ice studies and applications