Insignificant QBO-MJO Prediction Skill Relationship in the SubX and S2S Subseasonal Reforecasts

被引:32
|
作者
Kim, Hyemi [1 ]
Richter, Jadwiga H. [2 ]
Martin, Zane [3 ]
机构
[1] SUNY Stony Brook, Sch Marine & Atmospher Sci, Stony Brook, NY 11794 USA
[2] Natl Ctr Atmospher Res, POB 3000, Boulder, CO 80307 USA
[3] Columbia Univ, Dept Appl Phys & Appl Math, New York, NY USA
关键词
Madden-Julian oscillation; quasi-biennial oscillation; prediction; MADDEN-JULIAN OSCILLATION; QUASI-BIENNIAL OSCILLATION; COMMUNITY ATMOSPHERE MODEL; TELECONNECTIONS; CLIMATE;
D O I
10.1029/2019JD031416
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The impact of the stratospheric quasi-biennial oscillation (QBO) on the prediction of the tropospheric Madden-Julian oscillation (MJO) is evaluated in reforecasts from nine models participating in subseasonal prediction projects, including the Subseasonal Experiment (SubX) and Subseasonal to Seasonal (S2S) projects. When MJO prediction skill is analyzed for December to February, MJO prediction skill is higher in the easterly phase of the QBO than the westerly phase, consistent with previous studies. However, the relationship between QBO phase and MJO prediction skill is not statistically significant for most models. This insignificant QBO-MJO skill relationship is further confirmed by comparing two subseasonal reforecast experiments with the Community Earth System Model v1 using both a high-top (46-level) and low-top (30-level) version of the Community Atmosphere Model v5. While there are clear differences in the forecasted QBO between the two model top configurations, a negligible change is shown in the MJO prediction, indicating that the QBO in this model may not directly control the MJO prediction and supporting the insignificant QBO-MJO skill relationship found in SubX and S2S models.
引用
收藏
页码:12655 / 12666
页数:12
相关论文
共 37 条
  • [31] Effects of the Madden-Julian Oscillation on 2-m air temperature prediction over China during boreal winter in the S2S database
    Zhou, Yang
    Yang, Ben
    Chen, Haishan
    Zhang, Yaocun
    Huang, Anning
    La, Mengke
    CLIMATE DYNAMICS, 2019, 52 (11) : 6671 - 6689
  • [32] Atmospheric water vapour transport in ACCESS-S2 and the potential for enhancing skill of subseasonal forecasts of precipitation
    Reid, Kimberley J.
    Hudson, Debra
    King, Andrew D.
    Lane, Todd P.
    Marshall, Andrew G.
    QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2024, 150 (758) : 68 - 80
  • [33] Adapting subseasonal-to-seasonal (S2S) precipitation forecast at watersheds for hydrologic ensemble streamflow forecasting with a machine learning-based post-processing approach
    Zhang, Lujun
    Gao, Shang
    Yang, Tiantian
    JOURNAL OF HYDROLOGY, 2024, 631
  • [34] An inter-comparison performance assessment of a Brazilian global sub-seasonal prediction model against four sub-seasonal to seasonal (S2S) prediction project models
    Bruno dos Santos Guimarães
    Caio Augusto dos Santos Coelho
    Steven James Woolnough
    Paulo Yoshio Kubota
    Carlos Frederico Bastarz
    Silvio Nilo Figueroa
    José Paulo Bonatti
    Dayana Castilho de Souza
    Climate Dynamics, 2021, 56 : 2359 - 2375
  • [35] Probabilistic skill of statistically downscaled ECMWF S2S forecasts of maximum and minimum temperatures for weeks 1-4 over South Africa
    Phakula, Steven
    Landman, Willem A.
    Engelbrecht, Christien J.
    METEOROLOGICAL APPLICATIONS, 2024, 31 (01)
  • [36] Multiweek tropical cyclone prediction for the Southern Hemisphere in ACCESS-S2: Maintaining operational skill and continuity of service
    Camp, J.
    Gregory, P.
    Marshall, A. G.
    Greenslade, J.
    Wheeler, M. C.
    QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2023, 149 (757) : 3401 - 3422
  • [37] Seasonality in Prediction Skill of the Madden-Julian Oscillation and Associated Dynamics in Version 2 of NASA's GEOS-S2S Forecast System
    Lim, Young-Kwon
    Arnold, Nathan P.
    Molod, Andrea M.
    Pawson, Steven
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2021, 126 (18)