首页> 外文会议>IUGG General Assembly >Downscaling medium-range ensemble forecasts using a neural network approach
【24h】

Downscaling medium-range ensemble forecasts using a neural network approach

机译:使用神经网络方法缩小的中等范围集合预测

获取原文

摘要

In this study, we present an application of self-organizing maps (SOMs) to downscaling weekly ensemble forecasts for probabilistic prediction of local precipitation in Japan. SOM is simultaneously employed on four elemental variables derived from the JRA55 reanalysis over area of study (Southwestern Japan), whereby a two-dimensional lattice of weather patterns (WPs) dominated during the 1958-2008 period is obtained. Down-scaling weekly ensemble forecasts to local precipitation are conducted by using the obtained SOM lattice based on the WPs of the global model ensemble forecast. A probabilistic local precipitation is easily and quickly obtained from the ensemble forecast. The predictability skill of the ensemble forecasts for the precipitation is significantly improved under the downscaling technique.
机译:在这项研究中,我们展示了自组织地图(SOM)的应用,以向日本局部降水的概率预测缩小为期每周整体预测。 SOM同时采用来自JRA55 Reany分析的四个元素变量,在研究区域(日本西南部),从而获得了在1958 - 2008年期间主导的天气模式(WPS)的二维晶格。通过使用所获得的SOM格子基于全球模型集合预测的WPS,通过使用所获得的SOM格对局限性降水进行下降的每周整合预测。概率局部降水很容易快速地从集合预测获得。在缩小技术下,沉淀的集合预测的可预测性技能显着改善。

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