Seasonal prediction of Korean regional climate from preceding large-scale climate indices

被引:22
|
作者
Kim, Maeng-Ki [1 ]
Kim, Yeon-Hee [1 ]
Lee, Woo-Seop [1 ]
机构
[1] Kongju Natl Univ, Dept Atmospher Sci, Gongju 314701, South Korea
关键词
seasonal prediction; climate index; multivariate linear regression; predictor; Korea;
D O I
10.1002/joc.1448
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
On the basis of multivariate linear regression with an adaptive choice of climate indices as predictors, a seasonal forecast with a lead time of 2 months was applied to Korea on a monthly basis, and leave-one-out cross-validation was applied to obtain forecasting skill at the 1% significance level. The monthly ACC (anomaly correlation coefficient) skill was 0.42-0.65 for temperature and 0.35-0.63 for precipitation. COD (coefficient of determination) was 18-42% for temperature and 14-39% for precipitation. The first coupled SLP pattern related to Korean climate is very similar to the correlation pattern between the preceding climate index and SLP at the target month, indicating that preceding climate indices can be dynamically linked to Korean climate. For example, the PNA index at a lead time of 5 months prior to October is closely related to a circulation anomaly with weak negative correlation over the Okhotsk Sea to East Sea and strong positive correlation over a broad band from Lake Baikal to China. This SLP pattern provides conditions that can dynamically induce cold advection from northwestern Asia around Lake Baikal toward the Korean Peninsula, resulting in cooling over Korea. Copyright (c) 2006 Royal Meteorological Society.
引用
收藏
页码:925 / 934
页数:10
相关论文
共 50 条
  • [1] Seasonal prediction of monthly precipitation in china using large-scale climate indices
    Kim, Maeng-Ki
    Kim, Yeon-Hee
    [J]. ADVANCES IN ATMOSPHERIC SCIENCES, 2010, 27 (01) : 47 - 59
  • [2] Seasonal Prediction of Monthly Precipitation in China Using Large-Scale Climate Indices
    Maeng-Ki KIM
    Yeon-Hee KIM
    [J]. Advances in Atmospheric Sciences, 2010, 27 (01) : 47 - 59
  • [3] Seasonal prediction of monthly precipitation in china using large-scale climate indices
    Maeng-Ki Kim
    Yeon-Hee Kim
    [J]. Advances in Atmospheric Sciences, 2010, 27 : 47 - 59
  • [4] Improved seasonal prediction of harmful algal blooms in Lake Erie using large-scale climate indices
    Tewari, Mukul
    Kishtawal, Chandra M.
    Moriarty, Vincent W.
    Ray, Pallav
    Singh, Tarkeshwar
    Zhang, Lei
    Treinish, Lloyd
    Tewari, Kushagra
    [J]. COMMUNICATIONS EARTH & ENVIRONMENT, 2022, 3 (01):
  • [5] Improved seasonal prediction of harmful algal blooms in Lake Erie using large-scale climate indices
    Mukul Tewari
    Chandra M. Kishtawal
    Vincent W. Moriarty
    Pallav Ray
    Tarkeshwar Singh
    Lei Zhang
    Lloyd Treinish
    Kushagra Tewari
    [J]. Communications Earth & Environment, 3
  • [6] Prediction of Seasonal Forest Fire Severity in Canada from Large-Scale Climate Patterns
    Shabbar, Amir
    Skinner, Walter
    Flannigan, Mike D.
    [J]. JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY, 2011, 50 (04) : 785 - 799
  • [7] Using large-scale climate indices in climate change ecology studies
    Forchhammer, MC
    Post, E
    [J]. POPULATION ECOLOGY, 2004, 46 (01) : 1 - 12
  • [8] Global Within-Season Yield Anomaly Prediction for Major Crops Derived Using Seasonal Forecasts of Large-Scale Climate Indices and Regional Temperature and Precipitation
    Iizumi, Toshichika
    Takaya, Yuhei
    Kim, Wonsik
    Nakaegawa, Toshiyuki
    Maeda, Shuhei
    [J]. WEATHER AND FORECASTING, 2021, 36 (01) : 285 - 299
  • [9] Regional and large-scale influences on Antarctic peninsula climate
    Simmonds, I
    [J]. ANTARCTIC PENINSULA CLIMATE VARIABILITY: HISTORICAL AND PALEOENVIRONMENTAL PERSPECTIVES, 2003, 79 : 31 - 42
  • [10] Low flows in France and their relationship to large-scale climate indices
    Giuntoli, I.
    Renard, B.
    Vidal, J. -P.
    Bard, A.
    [J]. JOURNAL OF HYDROLOGY, 2013, 482 : 105 - 118