Regional probabilistic climate forecasts from a multithousand, multimodel ensemble of simulations

被引:12
|
作者
Piani, C. [1 ]
Sanderson, B. [2 ]
Giorgi, F. [1 ]
Frame, D. J. [3 ]
Christensen, C. [2 ]
Allen, M. R. [2 ]
机构
[1] Abdus Salam Int Ctr Theoret Phys, I-34014 Trieste, Italy
[2] Univ Oxford, Dept Phys, Oxford OX1 3PU, England
[3] Univ Oxford, Environm Change Inst, Oxford OX1 3QY, England
关键词
D O I
10.1029/2007JD008712
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
A methodology for constraining climate forecasts, developed for application to the multithousand member perturbed physics ensemble of simulations completed by the distributed computing project ClimatePrediction. net, is here presented in detail. The methodology is extended to produce constrained forecasts of mean surface temperature and precipitation within 21 land-based regions and is validated with climate simulations from other models available from the IPCC (AR4) data set. The mean forecasted values of temperature and precipitation largely confirm prior results for the same regions. In particular, precipitation in the Mediterranean basin is shown to decrease and temperature over northern Europe is shown to increase with comparatively little uncertainty in the forecast (i.e., with tight constraints). However, in some cases the forecasts show large uncertainty, and there are a few cases where the forecasts cannot be constrained at all. These results illustrate the effectiveness of the methodology and its applicability to regional climate variables.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Multimodel ensemble forecasts for weather and seasonal climate
    Krishnamurti, TN
    Kishtawal, CM
    Zhang, Z
    LaRow, T
    Bachiochi, D
    Williford, E
    Gadgil, S
    Surendran, S
    [J]. JOURNAL OF CLIMATE, 2000, 13 (23) : 4196 - 4216
  • [2] Evaluation of the Added Value of Probabilistic Nowcasting Ensemble Forecasts on Regional Ensemble Forecasts
    Lu YANG
    Cong-Lan CHENG
    Yu XIA
    Min CHEN
    Ming-Xuan CHEN
    Han-Bin ZHANG
    Xiang-Yu HUANG
    [J]. Advances in Atmospheric Sciences, 2023, 40 (05) : 937 - 951
  • [3] Evaluation of the Added Value of Probabilistic Nowcasting Ensemble Forecasts on Regional Ensemble Forecasts
    Lu Yang
    Cong-Lan Cheng
    Yu Xia
    Min Chen
    Ming-Xuan Chen
    Han-Bin Zhang
    Xiang-Yu Huang
    [J]. Advances in Atmospheric Sciences, 2023, 40 : 937 - 951
  • [4] Evaluation of the Added Value of Probabilistic Nowcasting Ensemble Forecasts on Regional Ensemble Forecasts
    Yang, Lu
    Cheng, Cong-Lan
    Xia, Yu
    Chen, Min
    Chen, Ming-Xuan
    Zhang, Han-Bin
    Huang, Xiang-Yu
    [J]. ADVANCES IN ATMOSPHERIC SCIENCES, 2023, 40 (05) : 937 - 951
  • [5] Probabilistic Seasonal Forecasts in the North American Multimodel Ensemble: A Baseline Skill Assessment
    Becker, Emily
    van den Dool, Huug
    [J]. JOURNAL OF CLIMATE, 2016, 29 (08) : 3015 - 3026
  • [6] Probabilistic aspects of meteorological and ozone regional ensemble forecasts
    Delle Monache, Luca
    Hacker, Joshua P.
    Zhou, Yongmei
    Deng, Xingxiu
    Stull, Roland B.
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2006, 111 (D24)
  • [7] Using probabilistic climate change information from a multimodel ensemble for water resources assessment
    Manning, L. J.
    Hall, J. W.
    Fowler, H. J.
    Kilsby, C. G.
    Tebaldi, C.
    [J]. WATER RESOURCES RESEARCH, 2009, 45
  • [8] A Multimodel Approach for Improving Seasonal Probabilistic Forecasts of Regional Arctic Sea Ice
    Dirkson, A.
    Denis, B.
    Merryfield, W. J.
    [J]. GEOPHYSICAL RESEARCH LETTERS, 2019, 46 (19) : 10844 - 10853
  • [9] US regional climate simulations and seasonal forecasts
    Roads, J
    Chen, SC
    Kanamitsu, M
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2003, 108 (D16)
  • [10] Multimodel ensemble forecasts for precipitations in China in 1998
    Zongjian Ke
    Wenjie Dong
    Peiqun Zhang
    [J]. Advances in Atmospheric Sciences, 2008, 25 : 72 - 82