...
【24h】

Observations and modeling of San Diego beaches during El Nino

机译:厄尔尼诺现象期间的圣地亚哥海滩观测和建模

获取原文
获取原文并翻译 | 示例
           

摘要

Subaerial sand levels were observed at five southern California beaches for 16 years, including notable El Ninos in 1997-98 and 2009-10. An existing, empirical shoreline equilibrium model, driven with wave conditions estimated using a regional buoy network, simulates well the seasonal changes in subaerial beach width (e.g. the cross-shore location of the MSL contour) during non-El Nino years, similar to previous results with a 5-year time series lacking an El Nino winter. The existing model correctly identifies the 1997-98 El Nino winter conditions as more erosive than 2009-10, but overestimates shoreline erosion during both El Ninos. The good skill of the existing equilibrium model in typical conditions does not necessarily extrapolate to extreme erosion on these beaches where a few meters thick sand layer often overlies more resistant layers. The modest over-prediction of the 2009-10 El Nino is reduced by gradually decreasing the model mobility of highly eroded shorelines (simulating cobbles, kelp wrack, shell hash, or other stabilizing layers). Over prediction during the more severe 1997-98 El Nino is corrected by stopping model erosion when resilient surfaces (identified with aerial imagery) are reached. The trained model provides a computationally simple (e.g. nonlinear first order differential equation) representation of the observed relationship between incident waves and shoreline change. (C) 2016 Elsevier Ltd. All rights reserved.
机译:在加利福尼亚南部的五个海滩上观测了地下沙尘含量达16年,其中包括1997-98年和2009-10年的著名的厄尔尼诺现象。现有的经验性海岸线平衡模型是由使用区域浮标网络估算的波浪条件驱动的,它很好地模拟了非厄尔尼诺现象期间海底海滩宽度(例如MSL等高线的跨岸位置)的季节性变化。缺少El Nino冬季的5年时间序列的结果。现有模型正确地将1997-98年厄尔尼诺现象的冬季条件确定为比2009-10年更具侵蚀性,但高估了两个厄尔尼诺现象期间的海岸线侵蚀。在典型条件下,现有平衡模型的良好技巧不一定能推论出这些海滩上的极度侵蚀,那里几米厚的沙层通常会覆盖更多的抵抗层。通过逐渐降低高度侵蚀的海岸线(模拟鹅卵石,海带残骸,贝壳哈希或其他稳定层)的模型移动性,可以减少2009-10 El Nino的适度过度预测。在达到更严重的表面(以航空影像识别)时,通过停止模型侵蚀来纠正更严重的1997-98年厄尔尼诺现象期间的过度预测。训练后的模型提供了观察到的入射波与海岸线变化之间关系的计算简单(例如非线性一阶微分方程)表示。 (C)2016 Elsevier Ltd.保留所有权利。

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