2017 , Vol. 32 >Issue 4: 382 - 395
DOI: https://doi.org/10.11867/j. issn. 1001-8166.2017.04.0382
Seasonal Dependence of the North Pacific and North Atlantic SST Predictability and Forecast Skill
First author:Rong Xinyao(1979-), male, Sanya City, Hainan Province, Associate professor. Research areas include climate numerical simulation and prediction.E-mail:rongur@camscma.cn
Received date: 2016-10-19
Revised date: 2017-01-20
Online published: 2017-04-20
Supported by
Foundation item:Project supported by the R&D Special Fund for Public Welfare Industry (Meteorology) “Development and research of ensemble decadal climate prediction system based on global climate models FGOALS-s, CAMS and CESM”(No.GYHY201506012);The National Basic Research Program of China (No.2012CB955201)
Copyright
In this paper, the decadal predictability and forecast skill of the Sea Surface Temperature Anomalies (SSTA) in the North Pacific and North Atlantic Ocean were investigated by conducting three sets of perfect model forecast experiments using a global coupled general circulation model. The results show that the annual mean SSTA in the North Pacific is less predictable on decadal time scale, with the forecast skill notably weaker than that of the North Atlantic. By analyzing the predictability and forecast skill of seasonal mean SSTA, it is found that the decadal predictability and forecast skill of the winter mean (JFM) SSTA in the central and western North Pacific are significantly higher than those of other seasons, and the magnitude is comparable with that of the North Atlantic. The predictability and forecast skill of the North Atlantic SSTA also show seasonal variations. Further analysis indicates that the seasonal dependence of the SSTA decadal predictability and forecast skill in the North Pacific is due to the winter-to-winter reemergence mechanism of SSTA in the North Pacific, which results from the seasonal variation of the mixed layer depth of the North Pacific Ocean. While the seasonal dependence of the North Atlantic SSTA predictability and forecast skill might be related to seasonal variations of other processes, such as the Atlantic Decadal Oscillation. The results of this paper suggest that for decadal climate prediction, if the forecast skill of the seasonal mean is taken into account, we might obtain higher than annual mean forecast skill for some seasons.
Key words： North Pacific; North Atlantic; Decadal prediction; Seasonal dependence; Coupled GCM.
Xinyao Rong , Zhengyu Liu , Yun Liu , Wansuo Duan . Seasonal Dependence of the North Pacific and North Atlantic SST Predictability and Forecast Skill[J]. Advances in Earth Science, 2017 , 32(4) : 382 -395 . DOI: 10.11867/j. issn. 1001-8166.2017.04.0382
| [1] | Meehl G A, Goddard L, Murphy J, et al.Decadal prediction: Can it be skillful?[J]. Bulletin of the American Meteorological Society, 2009, 90(10): 1 467-1 485. |
| [2] | Mantua N J, Hare S R, Zhang Y, et al.A Pacific interdecadal climate oscillation with impacts on salmon production[J]. Bulletin of the American Meteorological Society, 1997, 78(6): 1 069-1 079. |
| [3] | Power S, Casey T, Folland C, et al.Interdecadal modulation of the impact ofENSO on Australia[J]. Climate Dynamics, 1999, 15(5): 319-324. |
| [4] | Kushnir Y.Interdecadal variations in North Atlantic sea surface temperature and associated atmospheric conditions[J]. Journal of Climate, 1994, 7(1): 141-157. |
| [5] | Delworth T L, Mann M E.Observed and simulated multidecadal variability in the Northern Hemisphere[J]. Climate Dynamics, 2000, 16(9): 661-676. |
| [6] | Boer G.A study of atmosphere-ocean predictability on long time scales[J]. Climate Dynamics,2000, 16(6): 469-477. |
| [7] | Boer G.Long time-scale potential predictability in an ensemble of coupled climate models[J]. Climate Dynamics, 2004, 23(1): 29-44. |
| [8] | Griffies S M, Bryan K.A predictability study of simulated North Atlantic multidecadal variability[J]. Climate Dynamics, 1997, 13(7/8): 459-487. |
| [9] | Collins M.Climate predictability on interannual to decadal time scales: The initial value problem[J]. Climate Dynamics, 2002, 1(8): 671-692. |
| [10] | Kumar A, Peng P, Chen M.Is there a relationship between potential and actual skill?[J]. Monthly Weather Review, 2014, 142(6): 2 220-2 227. |
| [11] | Smith D, Cusack S, Colman A, et al.Improved surface temperature prediction for the coming decade from a global circulation model[J]. Science, 2007, 317(5 839): 796-799. |
| [12] | Keenlyside N, Latif M, Jungclaus J, et al.Advancing decadal-scale climate prediction in the North Atlantic sector[J]. Nature, 2008, 453(7 191): 84-88. |
| [13] | Newman M.An empirical benchmark for decadal forecasts of global surface temperature anomalies[J]. Journal of Climate, 2013, 26(14): 5 260-5 269. |
| [14] | Torrence C, Webster P J.The annual cycle of persistence in the El Niño/Southern Oscillation[J]. Quarterly Journal of the Royal Meteorological Society, 1998, 124(550): 1 985-2 004. |
| [15] | Mu M, Duan W S, Wang B.Season-dependent dynamics of nonlinear optimal error growth and El Niño-Southern Oscillation predictability in a theoretical model[J]. Journal of Geophysical Research,2007,112:D10113,doi:10.1029/2005JD006981. |
| [16] | Duan W S, Wei C.The “spring predictability barrier” for ENSO predictions and its possible mechanism: Results from a fully coupled model[J]. International Journal of Climatology, 2012, 33(5): 1 280-1 292. |
| [17] | Namias J, Born R M.Temporal coherence in North Pacific sea surface temperature patterns[J]. Journal of Geophysical Research, 1970, 75(30): 5 952-5 955. |
| [18] | Namias J, Born R M.Further studies of temporal coherence in North Pacific sea surface temperature patterns[J]. Journal of Geophysical Research, 1974, 79(6): 797-798. |
| [19] | Deser C, Phillips A S, Hurrell J W.Pacific interdecadal climate variability: Linkages between the tropics and North Pacific in boreal winter since 1990[J]. Journal of Climate, 2004, 17(16): 3 109-3 124. |
| [20] | An S I, Wang B.The forced and intrinsic low-frequency modes in the North Pacific[J]. Journal of Climate, 2005, 18(6): 876-885, doi:10.1175/JCLI-3298.1. |
| [21] | Ding R Q, Li J P.Decadal and seasonal dependence of North Pacific SST persistence[J]. Journal of Geophysical Research, 2009, 114:D01105, doi: 10.1029/2008JD010723. |
| [22] | Watanabe M, Kimoto M.On the persistence of decadal SST anomalies in the North Atlantic[J]. Journal of Climate, 2000, 13(16): 3 017-3 028. |
| [23] | Timlin M S, Alexander M A, Deser C.On the reemergence of North Atlantic SST anomalies[J]. Journal of Climate, 2002, 15(181): 2 707-2 712. |
| [24] | Alexander M A, Deser C.A mechanism for the recurrence of wintertime midlatitude SST anomalies[J]. Journal of Physical Oceanography, 1995, 25(1): 122-137. |
| [25] | Wen C H, Xue Y, Kumar A.Seasonal Prediction of North Pacific SSTs and PDO in the NCEP CFS Hindcasts[J]. Journal of Climate, 2012, 25(171): 5 689-5 710. |
| [26] | Duan W S, Wu Y J.Season-dependent predictability and error growth dynamics of Pacific Decadal Oscillation-related sea surface temperature anomalies[J]. Climate Dynamics, 2015, 44(314): 1 053-1 072,doi: 10.1007/s00382-014-2364-5. |
| [27] | Wu Y, Duan W, Rong X.Seasonal predictability of sea surface temperature anomalies over the Kuroshio-Oyashio extension: Low in summer and high in winter[J]. Journal of Geophysical Research, 2016, 121(9), doi:10.1002/2016JC011887. |
| [28] | Jacob R.Low Frequency Variability in A Simulated Atmosphere ocean System[D]. Wisconsin,USA:University of Wisconsin, 1997. |
| [29] | Tobis M, Schafer C, Foster I, et al.FOAM: Expanding the horizons of climate modeling[C]∥Supercomputing, ACM/IEEE 1997 Conference, Supercomputing, ACM/IEEE 1997 Conference.1997. |
| [30] | Liu Z, Kutzbach J, Wu L.Modeling climate shift of El Niño variability in the Holocene[J]. Geophysical Research Letters, 2000, 27(15): 2 265-2 268. |
| [31] | Wu L, Liu Z, Gallimore R, et al.Pacific decadal variability: The tropical mode and the North Pacific mode[J]. Jouranl of Climate, 2003, 16(8): 1 101-1 120. |
| [32] | Liu Z, Liu Y, Wu L, et al.Seasonal and long-term atmospheric responses to reemerging North Pacific Ocean variability: A combined dynamical and statistical assessment[J]. Jouranl of Climate, 2007, 20(6): 955-980. |
| [33] | Liu Y, Liu Z, Zhang S, et al.Ensemble-based parameter estimation in a coupled GCMusing the adaptive spatial average method[J]. Jouranl of Climate, 2014, 27(11): 4 002-4 014. |
| [34] | Lu F, Liu Z, Liu Y, et al.Understanding the control of extratropical atmospheric variability on ENSO using a coupled data assimilation approach[J]. Climate Dynamics, 2016, doi:10.1007/s00382-016-3256-7. |
| [35] | Anderson J L.An ensemble adjustment Kalman filter for data assimilation[J]. Monthly Weather Review, 2001, 129(12): 2 884-2 903. |
| [36] | Anderson J L.A local least squares framework for ensemble filtering[J]. Monthly Weather Review, 2003, 131(4): 634-642. |
| [37] | White W B.Design of a global observing system for gyrescale upper ocean temperature variability[J]. Progress in Oceanography, 1995, 36(3): 169-217. |
| [38] | Carton J A, Giese B S.A reanalysis of ocean climate using Simple Ocean Data Assimilation (SODA)[J]. Monthly Weather Review, 2008, 136(8): 2 999-3 017. |
/
| 〈 |
|
〉 |
甘公网安备62010202000687
