This paper proposes a method, which involves the interpolation of surface pressure and temperature fields obtained from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2(CFSv2)6-hourly products to derive these site-specific meteorological data. In addition...
CFSv2A detailed analysis of sensitivity to the initial condition for the simulation of the Indian summer monsoon using retrospective forecast by the latest version of the Climate Forecast System version-2 (CFSv2) is carried out. This study primarily focuses on the tropical region of Indian and ...
摘要:春季欧亚大陆积雪与中国夏季降水有显著的相关关系,但由于缺乏在气候预报模式中春季欧亚大陆积雪与中国夏季降水关系的研究,使得在我国夏季降水的气候预测中很少关注欧亚大陆春季积雪异常这个信号,从而影响了我国汛期降水业务预测成功率。鉴于此,本项目利用美国国家环境预测中心(NCEP)最新的气候预报系统(CFSv2)的后报资料...
本文利用NCEP气候预报系统第二版(Climate Forecast System version 2,CFSv2)逐月积雪覆盖率和雪水当量后报资料,分析了该模式对于欧亚大陆积雪的预测能力和可预测性。主要结论如下:CFSv2能够基本再现观测到的欧亚大陆积雪的季节循环。整体来看,模式对于积雪覆盖率的模拟能力好于雪水当量。由于积雪累积期与消融期积雪覆盖率...
Results show that the NCEP-CFSv2 model can skillfully predict the Siberian high intensity only in November, the reasons for which are that the local thermal process, dynamic process, and Siberian snow cover extent mainly affect the Siberian high intensity in November. In terms of the thermal ...
In this paper the hindcast precipitation fields of the NCEP's second-generation climate prediction system (CFSv2) and the observed precipitation data of 182 meteorological stations in Sichuan and Chongqing from 2000 to 2009 were utilized. Sub-seasonal forecastin...
Saha, SK, Pokhrel, S, Chaudhari, HS (2013) Influence of Eurasian snow on Indian summer monsoon in NCEP CFSv2 free run. Clim Dyn 41: pp. 1801-1815Saha SK, Pokhrel S, Chaudhari H (2013b) Influence of Eurasian snow on Indian summer monsoon in NCEP CFSv2 freerun. Clim Dyn 41:1801–...
Shin, Chul-SuGeorge Mason UnivHuang, BohuaGeorge Mason UnivClimate dynamicsShin, C.; Huang, B. Slow and fast annual cycles of the Asian summer monsoon in the NCEP CFSv2. Clim. Dyn. 2016, 47, 529-553. [CrossRef]
We apply the ensemble averaging of both single- and three-hidden-layer neural networks on the NCEP CFSv2 SST forecast. They can correct the identified SST error, though ANN3 performs relatively better than that of ANN1. Thus, ensemble-based ANN3 is a useful SST bias correction approach....
Zuo Z, Yang S, Zhang R, Xiao D, Guo D, Ma L. 2014. Response of summer rainfall over China to spring snow anomalies over Siberia in the NCEP CFSv2 reforecast. Q. J. R. Meteorol. Soc. 141: 939-944, doi: 10.1002/qj.2413....