Seasonal streamflow forecast: a GCM multi-model downscaling approach

被引:6
作者
Foster, Kean L. [1 ]
Uvo, Cintia B. [1 ]
机构
[1] Lund Univ, Dept Water Resources Engn, SE-22100 Lund, Sweden
来源
HYDROLOGY RESEARCH | 2010年 / 41卷 / 06期
关键词
canonical correlation analysis; climate predictability tool; downscaling; general circulation model; PRECIPITATION; CLIMATE; MODEL; BIAS;
D O I
10.2166/nh.2010.143
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
This work investigates the predictability of seasonal to inter-annual streamflow over several river basins in Norway through the use of multi-model ensembles. As general circulation models (GCMs) do not explicitly simulate streamflow, a statistical link is made between GCM-forecast fields generated in December and average streamflow in the melting season May-June. By using the Climate Predictability Tool (CPT) three models were constructed and from these a multi-model was built. The multi-model forecast is tested against climatology to determine the quality of the forecast. Results from the forecasts show that the multi-model performs better than the individual models and that this method shows improved forecast skills if compared to previous studies conducted in the same basins. The highest forecast skills are found for basins located in the southwest of Norway. The physical interpretation for this is that stations on the windward side of the Scandinavian mountains are exposed to the prevailing winds from the Atlantic Ocean, a principal source of predictive information from the atmosphere on this timescale.
引用
收藏
页码:503 / 507
页数:5
相关论文
共 50 条
  • [1] Statistical downscaling of GCM simulations to streamflow
    Landman, WA
    Mason, SJ
    Tyson, PD
    Tennant, WJ
    JOURNAL OF HYDROLOGY, 2001, 252 (1-4) : 221 - 236
  • [2] Downscaling of GCM forecasts to streamflow over Scandinavia
    Nilsson, Patrik
    Uvo, Cintia B.
    Landman, Willem A.
    Nguyen, Tinh D.
    HYDROLOGY RESEARCH, 2008, 39 (01): : 17 - 26
  • [3] Statistical downscaling methods based on APCC multi-model ensemble for seasonal prediction over South Korea
    Kang, Suchul
    Hur, Jina
    Ahn, Joong-Bae
    INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2014, 34 (14) : 3801 - 3810
  • [4] On the NextGen-Chile Forecast System: A Calibrated Multi-Model Ensemble Approach for Seasonal Precipitation Forecasts
    Campos, Diego A.
    Cabello, Fernanda I.
    Munoz, angel G.
    INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2025, 45 (04)
  • [5] Reductions in seasonal climate forecast dependability as a result of downscaling
    Schneider, J. M.
    Garbrecht, J. D.
    TRANSACTIONS OF THE ASABE, 2008, 51 (03): : 915 - 925
  • [6] Multi-model ensemble approach for statistically downscaling general circulation model outputs to precipitation
    Sachindra, D. A.
    Huang, F.
    Barton, A. F.
    Perera, B. J. C.
    QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2014, 140 (681) : 1161 - 1178
  • [7] The Effect of Statistical Downscaling on the Weighting of Multi-Model Ensembles of Precipitation
    Wootten, Adrienne M.
    Massoud, Elias C.
    Sengupta, Agniv
    Waliser, Duane E.
    Lee, Huikyo
    CLIMATE, 2020, 8 (12) : 1 - 17
  • [8] Multi-model seasonal forecast of Arctic sea-ice: forecast uncertainty at pan-Arctic and regional scales
    Blanchard-Wrigglesworth, E.
    Barthelemy, A.
    Chevallier, M.
    Cullather, R.
    Fuckar, N.
    Massonnet, F.
    Posey, P.
    Wang, W.
    Zhang, J.
    Ardilouze, C.
    Bitz, C. M.
    Vernieres, G.
    Wallcraft, A.
    Wang, M.
    CLIMATE DYNAMICS, 2017, 49 (04) : 1399 - 1410
  • [9] Identifying the influence of hydroclimatic factors on streamflow: A multi-model data-driven approach
    Islam, Khandaker Iftekharul
    Gilbert, James Matthew
    JOURNAL OF HYDROLOGY, 2025, 652
  • [10] Statistical downscaling of pattern projection using multi-model output variables as predictors
    Hongwen Kang
    Congwen Zhu
    Zhiyan Zuo
    Renhe Zhang
    Acta Meteorologica Sinica, 2011, 25 : 293 - 302