首页> 外文期刊>Russian meteorology and hydrology >Application of Statistical Downscaling in GCMs at Constructing the Map of Precipitation in the Mekong River Basin
【24h】

Application of Statistical Downscaling in GCMs at Constructing the Map of Precipitation in the Mekong River Basin

机译:统计降尺度法在湄公河流域降水图编制中的应用。

获取原文
获取原文并翻译 | 示例
       

摘要

This study used the Statistical Downscaling Model (SDSM) to increase the resolution of the Global Circulation Model (GCM) at forecasting the amount of precipitation in the Mekong River basin. The model was initially calibrated using the reanalysis data by National Centers for Environmental Prediction (NCEP) and the data on observed precipitation. The results of comparison between the SDSM calculations and the observational data were used to generate the distribution of precipitation until 2099 using HadCM3, SRES A2 and B2 scenarios. After total annual precipitation had been downscaled, the percentage change in precipitation was interpolated among the selected stations in order to create precipitation maps. Both A2 and B2 scenario indicate the possibility of remarkable increase in annual precipitation in the Mekong basin, which may amount to 150 and 110%, respectively. The December-January-February precipitation is likely to increase significantly in the most part of the region, and in some areas, almost by three times. On the contrary, the June-July-August precipitation will remarkably decrease in the different parts of the territory under study. As the water resource sector is the backbone of the economics of this region including hydropower and agricultural sector, the changes in the amount of precipitation and its interannual variability can put the usual water business into stress. Thus, proper adaptive measures should be applied both at local and at regional levels for the benefit of all associated countries utilizing the resource of the Mekong River.
机译:这项研究使用统计缩减模型(SDSM)来提高全球环流模型(GCM)的分辨率,以预测湄公河流域的降水量。最初使用美国国家环境预测中心(NCEP)的再分析数据和观测降水数据对模型进行了校准。 SDSM计算结果和观测数据之间的比较结果被用于使用HadCM3,SRES A2和B2情景产生直到2099年的降水分布。在年度总降水量缩减之后,在选定的站点之间对降水量的百分比变化进行插值,以创建降水量图。 A2和B2情景均表明湄公河流域年降水量可能显着增加的可能性,分别可能达到150%和110%。在该地区大部分地区和某些地区,12月至1月至2月的降水量可能会显着增加,几乎增加了三倍。相反,在所研究领土的不同地区,6月-7月-8月的降水量将明显减少。由于水资源部门是该地区包括水力发电和农业部门在内的经济支柱,因此降水量的变化及其年际变化会给通常的供水业务带来压力。因此,应当在地方和区域两级都采取适当的适应措施,以使所有利用湄公河资源的联系国家受益。

著录项

  • 来源
    《Russian meteorology and hydrology》 |2014年第4期|271-282|共12页
  • 作者

    K. Parajuli; K. Kang;

  • 作者单位

    Asian Institute of Technology (AIT), P.O. Box 4, Klong Luang, Pathumthani, 12120 Thailand;

    Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul, Republic of Korea;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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