...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of hydrometeorology >Quantifying Snow Mass Mission Concept Trade-Offs Using an Observing System Simulation Experiment
【24h】

Quantifying Snow Mass Mission Concept Trade-Offs Using an Observing System Simulation Experiment

机译：使用观察系统仿真实验量化雪地质量概念概念权衡

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Because of its location, Canada is particularly affected by snow processes and their impact on the atmosphere and hydrosphere. Yet, snow mass observations that are ongoing, global, frequent (1-5 days), and at high enough spatial resolution (kilometer scale) for assimilation within operational prediction systems are presently not available. Recently, Environment and Climate Change Canada (ECCC) partnered with the Canadian Space Agency (CSA) to initiate a radar-focused snow mission concept study to define spaceborne technological solutions to this observational gap. In this context, an Observing System Simulation Experiment (OSSE) was performed to determine the impact of sensor configuration, snow water equivalent (SWE) retrieval performance, and snow wet/dry state on snow analyses from the Canadian Land Data Assimilation System (CaLDAS). The synthetic experiment shows that snow analyses are strongly sensitive to revisit frequency since more frequent assimilation leads to a more constrained land surface model. The greatest reduction in spatial (temporal) bias is from a 1-day revisit frequency with a 91% (93%) improvement. Temporal standard deviation of the error (STDE) is mostly reduced by a greater retrieval accuracy with a 65% improvement, while a 1-day revisit reduces the temporal STDE by 66%. The inability to detect SWE under wet snow conditions is particularly impactful during the spring meltdown, with an increase in spatial RMSE of up to 50 mm. Wet snow does not affect the domain-wide annual maximum SWE nor the timing of end-of-season snowmelt timing in this case, indicating that radar measurements, although uncertain during melting events, are very useful in adding skill to snow analyses.
机译：由于其位置，加拿大受到雪过程的影响及其对大气和水圈的影响。然而，目前无法在操作预测系统内进行持续，全局，频繁（1-5天）和高足够空间分辨率（公正）和高足够的空间分辨率（公正）的雪地质量观测。最近，环境和气候变化加拿大（ECCC）与加拿大航天局（CSA）合作，启动雷达集中的雪位使命概念研究，以定义这种观察间隙的星载技术解决方案。在这种情况下，进行了观察系统仿真实验（OSSE）以确定传感器配置，雪水等效（SWE）检索性能和雪湿/干燥状态从加拿大土地数据同化系统（Caldas）的雪分析。合成实验表明，雪分析对重新审视频率非常敏感，因为更频繁的同化导致更受约束的陆地面模型。空间（时间）偏差的最大减少是从1天的Revisit频率从91％（93％）改善。误差（STDE）的时间标准偏差大多通过提高65％的检索精度来减少，而1天的Revisit将时间STDE减少66％。在湿雪条件下无法检测SWE在弹簧熔化期间特别有影响，在空间RMSE增加到50毫米。在这种情况下，湿雪不会影响域名的年度最大SWE，也不影响季节昼夜雪花时机的时间，表明雷达测量虽然在熔化事件期间不确定，但在为雪分析中添加技术非常有用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号