...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Weather and forecasting >An Initial Assessment of Radar Data Assimilation on Warm Season Rainfall Forecasts for Use in Hydrologic Models
【24h】

An Initial Assessment of Radar Data Assimilation on Warm Season Rainfall Forecasts for Use in Hydrologic Models

机译：暖季降雨预报中雷达数据同化的初步评估，用于水文模型

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

The effect of introducing radar data assimilation into the WRF Model to improve high-resolution rainfall forecasts that are used for flash flood forecasting is analyzed. The authors selected 12 heavy rainfall events and performed two WRF 24-h simulations that produced quantitative precipitation forecasts (QPFs) for each, one using the standard configuration in forecast mode (QPF-Cold) and one using radar data assimilated at initialization (QPF-Hot). Simulation outputs are compared with NWS stage IV QPEs for storm placement, area over threshold coverage, and equitable threat scores. The two QPF products and stage IV data are used to force the distributed hydrological model CUENCAS for the same 800 km x 800 km domain centered over Iowa (and to calculate peak flows across the river network). The hydrological model responses to the three products are compared in terms of spatial location and flood intensity. In general, QPF-Hot outperformed QPF-Cold in replicating stage IV QPE statistics. However, QPF-Hot was too wet in the first 2 h of the event, and storms created by the radar-assimilation techniques dissipated quickly, with rainfall forecasts resembling QPF-Cold after 12 h. Flash flooding predicted by CUENCAS using QPF-Hot was more consistent with stage IV in terms of placement and intensity; however, results were not consistent for all events evaluated. The most encouraging result is that expected flash flooding was indeed predicted in all 12 cases using QPF-Hot and not QPF-Cold even though placement and intensity were not a perfect match. The initial results of this study indicate that radar assimilation improves WRF's ability to capture the character of storms, promising more accurate guidance for flash flood warnings.
机译：分析了将雷达数据同化引入WRF模型以改善用于山洪预报的高分辨率降雨预报的效果。作者选择了12次强降雨事件，并进行了两次WRF 24小时模拟，每个模拟都产生了定量降水预报（QPF），一种使用了预报模式下的标准配置（QPF-Cold），另一种使用了初始化时得到的雷达数据（QPF-热）。将模拟输出与NWS第四阶段QPE进行比较，以了解风暴的位置，超过阈值的区域和公平的威胁评分。这两个QPF产品和IV期数据用于强制以爱荷华州为中心的800 km x 800 km区域内的分布式水文模型CUENCAS（并计算整个河网的峰值流量）。比较了三种产品的水文模型响应的空间位置和洪水强度。通常，在复制IV期QPE统计数据时，QPF-Hot优于QPF-Cold。但是，在事件的前2小时，QPF-Hot太潮湿，雷达同化技术造成的暴风迅速消散，而12小时后的降雨预报类似于QPF-冷。 CUENCAS使用QPF-Hot预测的山洪泛滥在位置和强度方面与IV期更加一致。但是，所有评估事件的结果均不一致。最令人鼓舞的结果是，即使放置和强度都不是完美的匹配，使用QPF-Hot而不是QPF-Cold的情况下，在所有12个案例中的确确实预测了预期的山洪泛滥。这项研究的初步结果表明，雷达同化提高了WRF捕获风暴特征的能力，有望为山洪预警提供更准确的指导。

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