傳統潛在可預報度之分析主要以大氣環流模式（Atmospheric general circulation model；簡稱AGCM）資料作為評估的依據。然而，AGCM往往因為海洋與大氣之間並無能量交換，而高估了降水以及環流的強度，由此可知海氣交互作用所扮演之重要角色。另一方面，潛在可預報度主要在評估模式大氣對於邊界驅力的反應程度，然而，海氣耦合模式中，邊界條件與初始條件會隨著時間不斷改變，這將使利用海氣耦合模式進行潛在可預報度分析的難度提高。基於上述理由，為了釐清海氣交互作用對於潛在可預報度之影響，本研究將透過實驗設計，探討局部海氣交互作用對於潛在可預報度之影響。
研究發現，當赤道海溫變化明顯時（如ENSO期間），CTRL與MLM實驗中均顯示較高之潛在可預報度，其中又以赤道地區最為顯著；中高緯度地區，則是以PNA地區較為明顯。在季節的變化上，則是以冬季時有最高之潛在可預報度。這些結果與前人利用AGCM進行潛在可預報度分析所獲得之結論一致，換言之，即使海氣交互作用存在，大氣潛在可預報度的變化依然以ENSO年較高，所有年次之，非ENSO居後的形式呈現。由此可知，實驗中DTEP地區的海溫變化仍是主要影響全球大氣潛在可預報度的驅力。
MLM與CTRL實驗差別在於MLM實驗中允許有海氣交互作用，此作用的存在，造成二組實驗之潛在可預報度存在著些微的差距，而此些微差距透過Monte-Carlo的檢驗方式獲得信心。從變異數分析研究訊號與雜訊的結果發現，海氣交互作用的影響存在著明顯的區域性和季節變化。冬季的反應較夏季明顯。其中太平洋與大西洋的季節變化相對較大；印度洋地區則是以減弱潛在可預報度為主。
至於海氣交互作用影響潛在可預報度的運作過程，則可透過暖年減冷年合成圖進行解釋—在海氣交互作用顯著區域，大氣對於DTEP地區海溫變化一旦產生反應，局部地區的海氣交互作用即開始扮演修飾此反應的角色。修飾的作用主要有二，其一為透過熱通量之交換提供負貢獻至大氣，此作用將造成潛在可預報度之減弱；其二為維持環流強度，此作用將使MLM實驗組的潛在可預報度高於環流強度迅速減弱的CTRL實驗。
本研究比較了AGCM與耦合模式之潛在可預報度，其中使用之耦合模式為AGCM外加一混合層模式，忽略了海洋動力的影響。在未來，若能設計一組實驗，使DTEP地區以外的海洋與大氣為真正之耦合作用，將能增進海氣交互作用對於潛在可預報度影響之了解。此外，若能再加入一組AMIP方式之模擬資料，將有助於釐清海氣交互作用對於潛在可預報度之真正影響。

Alexander, M. A., J. D. Scott, and C. Deser, 2000: Processes that influence sea surface temperature and ocean mixed layer depth variability in a coupled model. J. Geophys. Res., 105, 16 823–16 842.
—, I. Blade, M. Newman, J. R. Lanzante, N.-C. Lau, and J. D. Scott, 2002: The Atmospheric Bridge: the Influence of ENSO Teleconnections on Air-Sea Interaction Over the Global Oceans. J. Climate , 15, 2205-2231.
Barsugli, J. J., and D. S. Battisti, 1998. The Basic Effects of Atmosphere-Ocean Thermal Coupling on Midlatitude Variability. J. Atmos. Sci., 55, 477-493.
Bengtsson, L., 1985: Medium-Range Forecasting－The experience of ECMWF. Bull. Amer. Meteor. Soc., 66, 1133-1146.
Bjerknes, J., 1966: A possible response of the atmospheric Hadley circulation to anomalies of ocean temperature. Tellus, 18, 820-829.
—, 1969: Atmospheric Teleconnections from the equatorial Pacific. Mon. Wea. Rev. 97, 163-172.
Brankovic, C ., and T. N. Palmer, 1997: Atmospheric Seasonal Predictability and Estimates of Ensemble Size. Mon. Wea. Rev., 125, 859-874.
Branstator, G. 1990: Low-Frequency Patterns Induced by Stationary Waves. J. Atmos. Sci., 47, 629-649.
Broccoli, A. J., and S. Manabe, 1992: The effects of orography on midlatitude Northern Hemisphere dry climates. J. Climate, 5, 1181–1201.
Cayan, D. R., 1992: Latent and sensible heat flux anomalies over the northern oceans: Driving the sea surface temperature. J. Phys. Oceanogr., 22, 859-881.
Charney, J. G., Fleagle, R. G., Riehl, H., Lally, V. E. and Wark, D. Q., 1966. The feasibility of a global observation and analysis experiment. Bull. Am. Meteorol. Soc. 47, 200–220.
Chen, W. Y., Huug M., and Van den Dool, 1997: Atmospheric Predictability of Seasonal, Annual, and Decadal Climate Means and the Role of the ENSO Cycle: A Model Study. J. Climate, 10, 1236–1254.
Chen, W. Y.. 1989: Estimate of Dynamical Predictability from NMC DERF Experiments. Mon. Wea. Rev., 117, 1227–1236.
Chervin, R. M., 1988: Predictability of time-averaged atmospheric states. Physically-Based Modelling and Simulation of Climate and Climate Change—Part II, M. E. Schlesinger, Ed., Kluwer Academic, 983–1008.
Gates, W. Lawrence, 1992: AMIP: The Atmospheric Model Intercomparison Project. Bull. Amer. Meteor. Soc., 73, 1962–1970.
—, J. S. Boyle, C. C. Covey, C. G. Dease, C. M. Doutriaux, R. S. Drach, M. Fiorino, P. J. Gleckler, J. J. Hnilo, S. M. Marlais, T. J. Phillips, G. L. Potter, B. D. Santer, K. R. Sperber, K. E. Taylor, and D. N. Williams, 1999: An overview of the results of the Atmospheric Model Intercomparison Project (AMIP I). Bull. Amer. Meteor. Soc., 80, 29-55.
Gordon, C. T., and W. Stern, 1982: A description of the GFDL global spectral model. Mon. Wea. Rev., 110, 625–644.
Hoerling, M. P., A. Kumar and Min Zhong. 1997: El Niño, La Niña, and the Nonlinearity of Their Teleconnections. J. Climate, 10, No. 8, 1769–1786.
—, and A. Kumar, 2002: Atmospheric response patterns associated with tropical forcing. J. Climate, 15, 2184–2203.
Horel, John D. and John M. Wallace. 1981: Planetary-Scale Atmospheric Phenomena Associated with the Southern Oscillation. Mon. Wea. Rev., 109, 813–829.
Klein, S. A., B. J. Soden, and N.-C. Lau, 1999: Remote sea surface variations during ENSO: Evidence for a tropical atmospheric bridge. J. Climate, 12, 917–932.
Kumar, A. and M. P. Hoerling. 1995: Prospects and Limitations of Seasonal Atmospheric GCM Predictions. Bull. Amer. Meteor. Soc., 76, 335–345.
Latif, M., Joachim Biercamp, Hans von Storch, Michael J. McPhaden and Edilbert Kirk, 1990: Simulation of ENSO Related Surface Wind Anomalies with an Atmospheric GCM Forced by Observed SST. J. Climate, 3, 509–521.
Lau, N.-C.,1985: Modeling the Seasonal Dependence of the Atmospheric Response to Observed El Niños in 1962–76. Mon. Wea. Rev., 113, 1970–1996.
—, and M. J. Nath, 1994: A modeling study of the relative roles of tropical and extratropical SST anomalies in the variability of the global atmosphere–ocean system. J. Climate, 7, 1184–1207.
—, and —, 2000: Impact of ENSO on the variability of the Asian–Australian monsoons as simulated in GCM experiments. J. Climate, 13, 4287–4309.
—, and —, 2001: Impact of ENSO on SST variability in the North Pacific and North Atlantic: Seasonal dependence and role of extratropical air–sea coupling. J. Climate, 14, 2846–2866.
—, and —, 2003: Atmosphere–Ocean Variations in the Indo-Pacific Sector during ENSO Episodes. J. Climate, 16, 1–20.
Lorenz, E. N., 1963b: The predictability of hydrodynamic flow. Trans. NY Acad. Sci., Series II, 25, 409-432.
—, 1965: A study of the predictability of a 28-variable atmospheric model. Tellus, 17, 321-333.
—, 1984: Estimates of atmospheric predictability at medium range. Predictability of Fluid Motions, G. Holloway and B. J. West, Eds., Amer. Inst. Phys., 133-139.
Madden, R. A., 1976: Estimates of the Natural Variability of Time-Averaged Sea-Level Pressure. Mon. Wea. Rev., 104, 942–952.
Manabe, S., R. J. Stouffer, M. J. Spelman, and K. Bryan, 1991: Transient responses of coupled ocean–atmosphere model to gradual changes of atmospheric CO2. Part I: Annual mean responses. J. Climate, 4, 785–818.
Miyakoda, k., G. D. Hembree, R. F. Strickler and I. Shulman, 1972: Cumulative Results of Extended Forecast Experiments I. Model Performance for Winter Cases. Mon. Wea. Rev., 100, 836–855.
—, T. Gordon, R. Caverly, W. Stern, J. Sirutis and W. Bourke. 1983: Simulation of a Blocking Event in January 1977. Mon. Wea. Rev., 111, 846–869.
Montroy, David L., Michael B. Richman and Peter J. Lamb, 1998: Observed Nonlinearities of Monthly Teleconnections between Tropical Pacific Sea Surface Temperature Anomalies and Central and Eastern North American Precipitation. J. Climate, 11, 1812–1835.
Phelps, M. W., A. Kumar and James J. O'Brien, 2004: Potential Predictability in the NCEP CPC Dynamical Seasonal Forecast System. J. Climate, 17, 3775–3785.
Reynolds, R. W. and T. M. Smith, 1994: Improved global sea surface temperature analyses. J. Climate, 7, 929-948.
Rowell, D. P., C. K. Folland, K. Maskell, and M. N. Ward, 1995: Variability of summer rainfall over tropical North Africa (1906– 92): Observations and modelling. Quart. J. Roy. Meteor. Soc., 121, 669–704.
—, 1998: Assessing Potential Seasonal Predictability with an Ensemble of Multidecadal GCM Simulations. J. Climate, 11, 109–120.
Saha, S., and H. M. Van den Dool, 1988: A measure of the practical limit of predictability. Mon. Wea. Rev., 116, 2522–2526.
Shukla, J.,1981: Dynamical Predictability of Monthly Means. J. Atmos. Sci., 38, 2547–2572.
— and D.S. Gutzler. 1983: Interannual Variability and Predictability of 500 mb Geopotential Heights over the Northern Hemisphere. Mon. Wea. Rev., 111, 1273–1279.
—, 1985: Predictability. Issues in atmospheric and oceanic modeling, Part II. Weather Dynamics. Advances in Geophysics, 28B, 87 122.
—, J. Anderson, D. Baumhefner, C. Brankovic, Y. Chang, E. Kalnay, L. Marx, T. Palmer, D. Paolino, J. Ploshay, S. Schubert, D. Straus, M. Suarez and J. Tribbia, 2000: Dynamical Seasonal Prediction. Bull. Amer. Meteor. Soc., 81, 2593–2606.
Smagorinsky, J. 1969. Problems and promises of deterministic extended range forecasting. Bull. Amer. Meteor. Soc., 50, 286–311.
Smith, T. M., R. W. Reynolds, R. E. Livezey, and D. C. Stokes, 1996: Reconstruction of historical sea surface temperatures using empirical orthogonal functions. J. Climate, 9, 1403-1420.
Trenberth, Kevin E., 1985: Potential predictability of geopotential heights over the Southern Hemisphere. Mon. Wea. Rev., 113, 54–64.
Wallace, J. M., and D. S. Gutzler, 1981: Teleconnection in thegeopotential height field during the Northern Hemisphere winter. Mon. Wea. Rev., 109, 784 - 812.
—, C. Smith, and Q.-R. Jiang, 1990: Spatial patterns of atmosphere/ocean interaction in the northern winter. J. Climate, 3, 990-998.
Wang, B., R.Wu, and X. Fu, 2000: Pacific–East Asian teleconnection: How does ENSO affect east Asian climate. J. Climate, 13, 1517– 1536.
—, Q. Ding, X. Fu, I.-S. Kang, K. Jin, J. Shukla, and F. Doblas-Reyes, 2005: Fundamental challenges in simulation and prediction of summer monsoon rainfall. Geophys. Res. Lett., 32, L15711.
Webster, P. J., 1981: Mechanisms Determining the Atmospheric Response to Large-Scale Sea Surface Temperature Anomalies. J. Atmos. Sci., 38, 554-571.
Wilks, Daniel S., 2005: Statistical Methods in the Atmospheric Sciences —— An Introduction, International geophysics series, 59, 114-146.
Wu, R., B. P. Kirtman, 2005: Roles of Indian and Pacific Ocean air–sea coupling in tropical atmospheric variability. Climate Dym., 25, 155-170.
—, —, and K. Pegion, 2006: Local air-sea relationship in observations and model simulations, J. Climate, 19, 4914-4932.
Zwiers, F. W., 1987: A potential predictability study conducted with an atmospheric general circulation model. Mon. Wea. Rev., 115, 2957–2974.
—, 1996: Interannual variability and predictability in an ensemble of AMIP climate simulations conducted with the CCC GCM2. Climate Dyn., 12, 825–848.