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Seasonal variability of the relationship between SST and OLR in the Indian Ocean and its implications for initialization in a CGCM with SST nudging

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Abstract

Correlations between sea surface temperature (SST) and outgoing longwave radiation (OLR) anomalies and their implication for seasonal prediction are discussed. The observed correlations exhibit robust seasonality with the maximum (minimum) in boreal spring (autumn) in the eastern equatorial Indian Ocean (EEIO). This relationship is investigated in initial conditions that have been produced with SST nudging for seasonal predictions by a coupled model. It is found that the observed positive correlations in the EEIO cannot be reproduced by the model, despite its success in the Pacific. Thus, the SST nudging is not suitable for initialization of dynamical seasonal forecast for the Indian Ocean.

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References

  • Ashok K, Guan Z, Yamagata T (2001) Impact of the Indian Ocean Dipole on the relationship between the Indian Monsoon rainfall and ENSO. Geophys Res Lett 28:4499–4502

    Article  Google Scholar 

  • Balmaseda M, Anderson D (2009) Impact of initialization strategies and observations on seasonal forecast skill. Geophys Res Lett 36:L01701. doi:10.1029/2008GL035561

    Article  Google Scholar 

  • Balmaseda MA, Mogensen K, Weaver AT (2013) Evaluation of the ECMWF ocean reanalysis system ORAS4. Quart J Roy Meteorol Soc 139:1132–1161

    Article  Google Scholar 

  • Behera SK, Luo JJ, Masson S, Delecluse P, Gualdi S, Navarra A, Yamagata T (2005) Paramount impact of the Indian Ocean Dipole on the East African short rains: a CGCM study. J Clim 18:4514–4530

    Article  Google Scholar 

  • Behera S, Ratnam JV, Masumoto Y, Yamagata T (2013) Origin of extreme summers in Europe: the Indo-Pacific connection. Clim Dyn 41:663–676

    Article  Google Scholar 

  • Behringer DW, Xue Y (2004) Evaluation of the global ocean data assimilation system at NCEP: the Pacific Ocean. In: Eighth symposium on integrated observing and assimilation systems for atmosphere, oceans, and land surface, AMS 84th annual meeting, Washington State Convention and Trade Center, Seattle, Washington, pp 11–15

  • Bjerknes J (1969) Atmospheric teleconnections from the equatorial Pacific. Mon Weather Rev 97:163–172

    Article  Google Scholar 

  • Bretherton CS, Widmann M, Dymnikov VP, Wallace JM, Bladé I (1999) The effective number of spatial degrees of freedom of a time-varying field. J Clim 12:1990–2009

    Article  Google Scholar 

  • Chan SC, Behera SK, Yamagata T (2008) Indian Ocean Dipole influence on South American rainfall. Geophys Res Lett 35:L14S12. doi:10.1029/2008GL034204

  • Chen D, Zebiak SE, Cane MA, Busalacchi AJ (1997) Initialization and predictability of a coupled ENSO forecast model. Mon Weather Rev 125:773–788

    Article  Google Scholar 

  • Chen D, Cane M, Kaplan A, Zebiak SE, Huang D (2004) Predictability of El Niño over the past 148 years. Nature 428:733–736

    Article  Google Scholar 

  • Dee D et al (2011) The ERA-interim reanalysis: configuration and performance of the data assimilation system. Quart J Roy Meteorol Soc 137:553–597

    Article  Google Scholar 

  • Doi T, Tozuka T, Yamagata T (2010) The Atlantic meridional mode and its coupled variability with the Guinea Dome. J Clim 23:455–475

  • Fischer AS, Terray P, Guilyardi E, Gualdi S, Delecluse P (2005) Two independent triggers for the Indian Ocean Dipole/Zonal Mode in a coupled GCM. J Clim 18:3428–3449

    Article  Google Scholar 

  • Gadgil S, Joseph PV, Joshi NV (1984) Ocean–atmosphere coupling over monsoon regions. Nature 312:141–143

    Article  Google Scholar 

  • Graham NE, Barnett TP (1987) Sea surface temperature, surface wind divergence, and convection over tropical oceans. Science 238:657–659

    Article  Google Scholar 

  • Guan Z, Yamagata T (2003) The unusual summer of 1994 in East Asia: IOD teleconnections. Geophys Res Lett 30:1544. doi:10.1029/2002GL016831

    Article  Google Scholar 

  • Guan Z, Iizuka S, Chiba M, Yamane S, Ashok K, Honda M, Yamagata T (2000) Frontier atmospheric general circulation model version 1.0 (FrAM1.0): model climatology. Technical Report FTR-1

  • Han W, Liu WT, Lin J (2006) Impact of atmospheric sub-monthly oscillations on sea surface temperature of the tropical Indian Ocean. Geophys Res Lett 33:L03609. doi:10.1029/2005GL025082

    Google Scholar 

  • Hurrell JW, Hack JJ, Shea D, Caron JM, Rosinski J (2008) Sea surface temperature and sea ice boundary dataset for the Community Atmosphere Model. J Clim 21:5145–5153

    Article  Google Scholar 

  • Kalnay E et al (1996) The NCEP/NCAR 40-year reanalysis project. Bull Amer Meteor Soc 77:437–470

    Article  Google Scholar 

  • Kataoka T, Tozuka T, Behera SK, Yamagata T (2014) On the Ningaloo Niño/Niña. Clim Dyn 43:1463–1482

    Article  Google Scholar 

  • Keenlyside N, Latif M, Botzet M, Jungclaus J, Schulzweida U (2005) A coupled method for initializing El Niño-Southern Oscillation forecasts using sea surface temperature. Tellus 57A:340–356

    Article  Google Scholar 

  • Klein SA, Soden BJ, Lau NC (1999) Remote sea surface temperature variations during ENSO: evidence for a tropical atmosphere bridge. J Clim 12:917–932

    Article  Google Scholar 

  • Kumar A, Chen M, Wang W (2013) Understanding prediction skill of seasonal mean precipitation over the Tropics. J Clim 26:5674–5681

    Article  Google Scholar 

  • Kumar A, Wang H, Xue Y, Wang W (2014) How much of monthly subsurface temperature variability in the equatorial Pacific can be recovered by the specification of sea surface temperatures? J Clim 27:1559–1577

    Article  Google Scholar 

  • Levitus S, Boyer TP (1994) World ocean atlas 1994, vol. 4, temperature, NOAA Atlas NESDIS 4, NOAA, Silver Spring, Md

  • Levitus S, Burgett R, Boyer TP (1994) World ocean atlas 1994, vol. 5, salinity, NOAA Atlas NESDIS 3, NOAA, Silver Spring, Md

  • Liebmann B, Smith CA (1996) Description of a complete (interpolated) outgoing longwave radiation dataset. Bull Amer Meteor Soc 77:1275–1277

    Google Scholar 

  • Luo JJ, Masson S, Behera S, Delecluse P, Gualdi S, Navarra A, Yamagata T (2003) South Pacific origin of the decadal ENSO-like variation as simulated by a coupled GCM. Geophys Res Lett 30:2250. doi:10.1029/2003GL018649

    Article  Google Scholar 

  • Luo JJ, Masson S, Roeckner E, Madec G, Yamagata T (2005) Reducing climatology bias in an ocean–atmosphere CGCM with improved coupling physics. J Clim 18:2344–2360

    Article  Google Scholar 

  • Luo JJ, Masson S, Behera S, Yamagata T (2007) Experimental forecasts of Indian Ocean Dipole using a coupled OAGCM. J Clim 20:2178–2190

    Article  Google Scholar 

  • Luo JJ, Masson S, Behera SK, Yamagata T (2008a) Extended ENSO prediction using a fully coupled ocean–atmosphere model. J Clim 21:84–93

    Article  Google Scholar 

  • Luo JJ, Behera S, Masumoto Y, Sakuma H, Yamagata T (2008b) Successful prediction of the consecutive IOD in 2006 and 2007. Geophys Res Lett 35:L14S02. doi:10.1029/2007GL032793

  • Masumoto Y, Hase H, Kuroda Y, Matsuura H, Takeuchi K (2005) Intraseasonal variability in the upper layer currents observed in the eastern equatorial Indian Ocean. Geophys Res Lett 32:L02607. doi:10.1029/2004GL021896

    Article  Google Scholar 

  • Oberhuber JM, Roeckner E, Christoph M, Esch M, Latif M (1998) Predicting the 97 El Niño event with a global climate model. Geophys Res Lett 25:2273–2276

    Article  Google Scholar 

  • Pacanowski RC, Griffies SM (1999) MOM 3.0 manual. NOAA/GFDL, pp 680

  • Pourasghar F, Tozuka T, Jahanbakhsh S, Sari Sarraf B, Ghaemi H, Yamagata T (2012) The interannual precipitation variability in the southern part of Iran as linked to large-scale climate modes. Clim Dyn 39:2329–2341

    Article  Google Scholar 

  • Rao SA, Yamagata T (2004) Abrupt termination of Indian Ocean dipole events in response to intraseasonal disturbances. Geophys Res Lett 31:L19306. doi:10.1029/2004GL020842

    Article  Google Scholar 

  • Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Kaplan A (2003) Global analysis of SST, sea ice and night marine air temperature since the late nineteenth century. J Geophys Res 108:4407. doi:10.1029/2002JD002670

    Article  Google Scholar 

  • Reynolds RW, Rayner NA, Smith TM, Stokes DC, Wang W (2002) An improved in situ and satellite SST analysis for climate. J Clim 15:1609–1625

    Article  Google Scholar 

  • Rosati A, Miyakoda K (1988) A general circulation model for upper ocean simulation. J Phys Oceanogr 18:1601–1626

    Article  Google Scholar 

  • Rosati A, Miyakoda K, Gudgel R (1997) The impact of ocean initial conditions on ENSO forecasting with a coupled model. Mon Weather Rev 125:754–772

    Article  Google Scholar 

  • Saji NH, Yamagata T (2003) Possible impacts of Indian Ocean Dipole mode events on global climate. Clim Res 25:151–169

    Article  Google Scholar 

  • Saji NH, Goswami BN, Vinayachandran PN, Yamagata T (1999) A dipole mode in the tropical Indian Ocean. Nature 401:360–363

    Google Scholar 

  • Schott FA, Xie SP, McCreary JP (2009) Indian Ocean circulation and climate variability. Rev Geophys 47:RG1002. doi:10.1029/2007RG000245

  • Shi L, Hendon HH, Alves O, Luo JJ, Balmaseda M, Anderson D (2012) How predictable is the Indian Ocean Dipole? Mon Weather Rev 140:3867–3884

    Article  Google Scholar 

  • Tozuka T, Miyasaka T, Chakraborty A, Mujumdar M, Behera SK, Masumoto Y, Nakamura H, Yamagata T (2006) University of Tokyo coupled general circulation model (UTCM1.0). Ocean Atmos Res Rep 7:44

  • Tozuka T, Doi T, Miyasaka T, Keenlyside N, Yamagata T (2011) Key factors in simulating the equatorial Atlantic zonal SST gradient in a coupled GCM. J Geophys Res 116:C06010. doi:10.1029/2010JC006717

    Google Scholar 

  • Tozuka T, Abiodun BJ, Engelbrecht FA (2014a) Impacts of convection schemes on simulating tropical-temperate troughs over southern Africa. Clim Dyn 43:433–451

    Article  Google Scholar 

  • Tozuka T, Kataoka T, Yamagata T (2014b) Locally and remotely forced atmospheric circulation anomalies of Ningaloo Nino/Nina. Clim Dyn 43:2197–2205

    Article  Google Scholar 

  • Tozuka T, Qu T, Yamagata T (2015) Impacts of South China Sea throughflow on the mean state and El Niño/Southern Oscillation as revealed by a coupled GCM. J Oceanogr 71:105–114

    Article  Google Scholar 

  • Ummenhofer CC, England MH, McIntosh PC, Meyers GA, Pook MJ, Risbey JS, Sen Gupta A, Taschetto AS (2009) What causes southeast Australia’s worst droughts? Geophys Res Lett 36:L04706. doi:10.1029/2008GL036801

    Article  Google Scholar 

  • Wang B, Ding Q, Fu X, Kang IS, Jin K, Shukla J, Doblas-Reyes F (2005) Fundamental challenge in simulation and prediction of summer monsoon rainfall. Geophys Res Lett 32:L15711. doi:10.1029/2005GL022734

    Article  Google Scholar 

  • Webster PJ, Magaña VO, Palmer TN, Shukla J, Tomas RA, Yanai M, Yasunari T (1998) Monsoons: processes, predictability, and the prospects for prediction. J Geophys Res 103:14451–14510

    Article  Google Scholar 

  • Wu R, Kirtman BP (2007) Regimes of seasonal air–sea interaction and implications for performance of forced simulations. Clim Dyn 29:393–410

    Article  Google Scholar 

  • Wu R, Kirtman BP, Pegion K (2006) Local air–sea relationship in observations and model simulations. J Clim 19:4914–4932

    Article  Google Scholar 

  • Yang J, Liu Q, Xie SP, Liu Z, Wu L (2007) Impact of the Indian Ocean SST basin mode on the Asian summer monsoon. Geophys Res Lett 34:L02708. doi:10.1029/2006GL028571

    Google Scholar 

  • Zhu J, Kumar A, Wang H, Huang B (2015) Sea surface temperature predictions in NCEP CFSv2 using a simple ocean initialization scheme. Mon Weather Rev 143:3176–3191

    Article  Google Scholar 

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Acknowledgments

We thank two anonymous reviewers for providing constructive comments. The CGCM was run on the supercomputers of the Information Technology Center, the University of Tokyo under the cooperative research with Atmosphere and Ocean Research Institute, the University of Tokyo. The present research is supported by the Japan Society for Promotion of Science through Grant-in-Aid for Exploratory Research 24654150.

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Correspondence to Tomoki Tozuka.

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Kohyama, T., Tozuka, T. Seasonal variability of the relationship between SST and OLR in the Indian Ocean and its implications for initialization in a CGCM with SST nudging. J Oceanogr 72, 327–337 (2016). https://doi.org/10.1007/s10872-015-0329-x

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  • DOI: https://doi.org/10.1007/s10872-015-0329-x

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