Interannual-decadal variability of wintertime mixed layer depths in the North Pacific detected by an ensemble of ocean syntheses
The interannual-decadal variability of the wintertime mixed layer depths (MLDs) over the North Pacific is investigated from an empirical orthogonal function (EOF) analysis of an ensemble of global ocean reanalyses. The first leading EOF mode represents the interannual MLD anomalies centered in the eastern part of the central mode water formation region in phase opposition with those in the eastern subtropics and the central Alaskan Gyre. This first EOF mode is highly correlated with the Pacific decadal oscillation index on both the interannual and decadal time scales. The second leading EOF mode represents the MLD variability in the subtropical mode water (STMW) formation region and has a good correlation with the wintertime West Pacific (WP) index with time lag of 3 years, suggesting the importance of the oceanic dynamical response to the change in the surface wind field associated with the meridional shifts of the Aleutian Low. The above MLD variabilities are in basic agreement with previous observational and modeling findings. Moreover the reanalysis ensemble provides uncertainty estimates. The interannual MLD anomalies in the first and second EOF modes are consistently represented by the individual reanalyses and the amplitudes of the variabilities generally exceed the ensemble spread of the reanalyses. Besides, the resulting MLD variability indices, spanning the 1948–2012 period, should be helpful for characterizing the North Pacific climate variability. In particular, a 6-year oscillation including the WP teleconnection pattern in the atmosphere and the oceanic MLD variability in the STMW formation region is first detected.
KeywordsOcean reanalysis Mixed layer depth North Pacific Mode water Pacific decadal oscillation West Pacific teleconnection pattern
We thank three anonymous reviewers for their constructive comments. Thanks are extended to Dr. H. Tsujino and Dr. K. Sakamoto for their kind and valuable advices. This work was partly supported by the Research Program on Climate Change Adaptation (RECCA) of the Ministry of Education, Culture, Sports, Science and Technology of the Japanese government (MEXT), by the Data Integration and Analysis System (DIAS) of the MEXT, by the joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101), by the UK Public Weather Service Research Programme, and by the European Commission funded projects MyOcean (FP7-SPACE-2007-1) and MyOcean2 (FP7-SPACE-2011-1). During the preparation of this article, our co-author Nicolas Ferry passed away. He was an active and supportive member of the ORA-IP and CLIVAR-GSOP activities.
- Balmaseda MA, Hernandez F, Storto A, Palmer MD, Alves O, Shi L, Smith GC, Toyoda T, Valdivieso M, Barnier B, Behringer D, Boyer T, Chang YS, Chepurin GA, Ferry N, Forget G, Fujii Y, Good S, Guinehut S, Haines K, Ishikawa Y, Keeley S, Köhl A, Lee T, Martin M, Masina S, Masuda S, Meyssignac B, Mogensen K, Parent L, Peterson KA, Tang YM, Yin Y, Vernieres G, Wang X, Waters J, Wedd R, Wang O, Xue Y, Chevallier M, Lemieux JF, Dupont F, Kuragano T, Kamachi M, Awaji T, Caltabiano A, Wilmer-Becker K, Gaillard F (2015) The Ocean Reanalyses Intercomparison Project (ORA-IP). J Oper Oceanogr 8:s80–s97. doi: 10.1080/1755876X.2015.1022329 CrossRefGoogle Scholar
- Hanawa K, Talley LD (2001) Mode waters. In: Sielder G, Chruch JJ, Gould J (eds) Ocean circulation and climate. Academic Press, NewYork, pp 373–386Google Scholar
- Kawasaki T (1991) Long-term variability in the pelagic fish populations. In: Kawasaki T, Tanaka S, Toba Y, Taniguchi A (eds) Long-term variability of pelagic fish populations and their environment. Pergamon Press, New YorkGoogle Scholar
- Large WG, Yeager SG (2004) Diurnal to decadal global forcing for ocean and sea-ice models: the data sets and flux climatologies. Technical note TN-460 + STR, NCAR, Boulder, Colorado, USAGoogle Scholar
- Levitus S (1982) Climatological atlas of the world ocean. NOAA/ERL GFDL, Princeton, New JerseyGoogle Scholar
- Masuzawa J (1969) Subtropical mode water. Deep Sea Res 16:463–472Google Scholar
- Monterey G, Levitus S (1997) Seasonal variability of mixed layer depth for the world ocean. NOAA Atlas NESDIS 14. U.S. Government Printing Office, Washington, DC, USAGoogle Scholar
- Pedlosky J (1996) Ocean circulation theory. Springer, Berlin. doi: 10.1007/987-3-662-03204-6
- Press WG, Teukolsky SA, Vetterling WT, Flannery BP (1992) Numerical recipes in FORTRAN: the art of scientific computing, 2nd edn. Cambridge University Press, CambridgeGoogle Scholar
- Storto A, Masina S, Balmaseda M, Guinehut S, Xue Y, Szekely T, Fukumori I, Forget G, Chang Y-S, Good SA, Köhl A, Vernieres G, Ferry N, Peterson KA, Behringer D, Ishii M, Masuda S, Fujii Y, Toyoda T, Yin Y, Valdivieso M, Barnier B, Boyer T, Lee T, Gourrion J, Wang O, Heimback P, Rosati A, Kovach R, Hernandez F, Martin MJ, Kamachi M, Kuragano T, Mogensen K, Alves O, Haines K, Wang X (2015) Steric sea level variability (1993–2010) in an ensemble of ocean reanalyses and objective analyses. Clim Dyn. doi: 10.1007/s00382-015-2554-9 Google Scholar
- Toyoda T, Awaji T, Masuda S, Sugiura N, Igarashi H, Mochizuki T, Ishikawa Y (2011) Interannual variability of North Pacific eastern subtropical mode water formation in the 1990s derived from a 4-dimensional variational ocean data assimilation experiment. Dyn Atmos Oceans 51:1–25. doi: 10.1016/j.dynatmoce.2010.09.001 CrossRefGoogle Scholar
- Toyoda T, Fujii Y, Kuragano T, Kamachi M, Ishikawa Y, Masuda S, Sato K, Awaji T, Hernandez F, Ferry N, Guinehut S, Martin M, Peterson KA, Good S, Valdivieso M, Haines K, Storto A, Masina S, Köhl A, Zuo H, Balmaseda M, Yin Y, Shi L, Alves O, Smith G, Chang YS, Vernieres G, Wang X, Forget G, Heimbach P, Wang O, Fukumori I, Lee T (2015) Intercomparison and validation of the mixed layer depth fields of global ocean syntheses. Clim Dyn. doi: 10.1007/s00382-015-2637-7 Google Scholar