Recent Progresses in Climate Predictions of the Indian Ocean Sector Swadhin Behera, Jing-Jia Luo, Yukio Masumoto and Toshio Yamagata Research Institute for Global Change/JAMSTEC, Yokohama, Japan Application Laboratory, JAMSTEC, Yokohama, Japan School of Science, The University of Tokyo, Tokyo, Japan Dept. of Ocean Technology, Policy, and Environment, The University of Tokyo, Japan behera@jamstec.go.jp

First two EOF modes of surface temperature from CTRL Experiment and non-ENSO Experiment Behera et al. 2005, J. Clim.

The Indian Ocean Pressure Oscillation Caused by IOD and its role in Southern Oscillation Behera and Yamagata 2003 Izumo et al. 2009 Nature Geo Science.

IOD Influence on South American Rainfall Observed SINTEX-F model Teleconnection Observed climatology Model climatology Nov. 2008: Santa Catarina suffered constant rainfalls for over two months (during late September, October, and November) and associated land slide and flooding affected 60 towns and over 1.5 million people Chan et al. 2008, GRL

Historical records of SST Dipole Index and Rainfall Dipole Index noENSO Obs CTRL Behera et al. 2008

SINTEX-F1 Coupled GCM Prediction System OCEAN: OPA8.2 ORCAR2 Grid 20X1.50 Eq-0.5 Level 31 ATMOSPHERE: ECHAM4 T106 L19 T106L19 5 Non-flux adjustment Every 2 hrs 2.2 The Earth Simulator

JAMSTEC seasonal prediction system: semi-multi-model ensemble 9-member ensemble hindcast experiments Three models with different coupling physics: (Each model has realistic ENSO & IOD simulations, Luo et al. 2005a) m1: Ocean surface is solid to atmosphere. (|Ua| Ua for Tau & heat flux) 　m2: Ocean surface current momentum is passed to atmosphere. (|Ua-Uo| (Ua-Uo) for Tau & heat flux) 　m3: Ocean surface is solid to atmosphere, but (|Ua-Uo| (Ua-Uo) for Tau) 2. Three initial conditions for each model: • Model spin-up (1971-1981) • A simple coupled SST-nudging initialization scheme • １day, 2 days, 3 days (weekly NCEP Reynolds data) Based on this model, we have designed a kind of semi-multi-model ensemble prediction scheme. We perturb the model coupling physics in three different ways to measure the large uncertainty in wind stress estimation. And for each model we use three initial conditions generated by a simple coupled nudging scheme and assimilating SST information only. This scheme produces realistic and ocean-atmosphere well-balanced initial conditions, which appear to be very important to long-lead predictions. It works well for ENSO prediction because ENSO is mainly determined by air-sea coupling. But for the Indian Ocean prediction, assimilating subsurface important can be very important because of strong stochastic and influential intraseasonal disturbances there. Forecast: 12 months from 1st day of every month during 1982-2004.

based on a semi-multimodel ensemble prediction system 9-member mean (1982-2004) based on a semi-multimodel ensemble prediction system >0.9 Luo et al., J. Climate, 2005b.

ENSO prediction skill of 10 coupled GCMs Nino3.4 index (1982-2004) Adapted from Jin et al. 2008, APCC CliPAS

Indian Ocean Dipole Predictability Both winter and spring barrier exist Difficulties Large deficiencies of current coupled GCMs in simulating Indian Ocean climate Sparse subsurface observations in the Indian Ocean Chaotic and active ISOs (initial conditions & predictions) Strong monsoon influence (seasonal & interannual) ENSO influence (require correct ENSO onset prediction) (90º-110ºE, 10ºS-0º) 0.5 9-member ensemble hindcasts (1982-2004) Predictable up to ~2 seasons ahead. Luo et al., J. Climate, 2007, 2178-2190.

Decoupled Hindcast Experiments El Niño and IOD Interaction dPO: No air-sea coupling in the tropical Pacific (observed SST climatology is specified). dIO: No air-sea coupling in the tropical Indian Ocean (observed SST climatology is specified). (9-member, 12-month lead, 1982-2006)

Prediction plumes (9-member mean): dIO (no Indian Ocean) 1994/95 Nino3.4 SSTA (190º-240ºE, 5ºS-5ºN) dIO (no Indian Ocean) 1994/95 1997/98 2006/07 CTL 0.5

Prediction plumes: CTL dPO (no El Niño) 1994 1997 2006 EIO SSTA (90º-110ºE, 10ºS-0º) CTL dPO (no El Niño) 1994 1997 2006

ACC RMSE Extended ENSO prediction: Nino3.4 SSTA prediction Ensemble mean Persistence ACC RMSE 0.5 Each member Nino3.4 SSTA prediction (120º-170ºW, 5ºS-5ºN) Luo et al., J. Climate, 2008, 84-93.

Nino3.4 SSTA forecast up to 2-year ahead (9-member) 1 Sep. 2006 Ensemble mean The La Nina condition would be long-lived according to the model forecast. 1 Jan. 2007 Presented at WCRP Workshop on Seasonal Prediction Barcelona Spain June 2007 1 May 2007

terrestrial 2-m air temperature anomaly Extended ENSO prediction: SSTA & terrestrial 2-m air temperature anomaly Contour interval is 0.3ºC Consistent with classical ENSO theory Luo et al., J. Climate, 2008.

Role of Warming Trend on SIP Detrended global mean surface air temperature (5-month running mean) (60S-75N) Trend (1982-2008) practical (potential) predictability of the non-detrended and detrended global mean T2m anomalies (lines with and without closed circle mark). Red (blue) short-dashed lines show the predictability if a perfect warming trend of the NCEP observations (model ensemble mean ICs) were predicted at all lead times. Black (gray) thin long-dashed lines with open circles are the persistence forecasts for the non-detrended observations (model ICs). perfect warming trend Skills for original, detrended, and “perfect trend” time series potential persistence Lead time (months) Luo et al. 2010

http://www. jamstec. go. jp/frcgc/research/d1/iod/index http://www.jamstec.go.jp/frcgc/research/d1/iod/index.html Latest Predictions - SINTEX-F SON Precipitation DJF Precipitation

Refer to http://www. jamstec. go. jp/frcgc/research/d1/iod/index Refer to http://www.jamstec.go.jp/frcgc/research/d1/iod/index.html for our experimental real time forecasts updated every month:

Real time forecasts (27-member) 　23 Apr 2008, The 　　 　Weekly Times Forecasts from 1 April 2008 24 Oct 2007, The Weekly Times Societal impacts of IOD forecasts Press Release October 16, 2006 「The World‘s First Successful Prediction of the Indian Ocean Dipole Mode (IOD) - Alleviate Social Loss Caused by Floods and Drought -」 http://www.jamstec.go.jp/jamstec-e/PR/0610/1016/index.html 10／17　読売新聞　 10／17　日本経済新聞　 10／17　日刊工業新聞 10／17　毎日新聞　 10／17　時事通信 10／17　朝日新聞　 10／18　日本海事新聞 10／30 シンガポール聯合早報 11／10 THE ASAHI SHIMBUN …. Real time forecasts (27-member) http://www.jamstec.go.jp/frcgc/research/d1/iod/index.html (90º-110ºE, 10ºS-0º) (190º-240ºE, 5ºS-5ºN) 2005 Jul Jan Luo et al. GRL2008, highlighted

Summary IOD has its own predictability, more or less independent of El Niño. IOD can fully drive El Niño-like signal as in 1994. Intrinsic interaction between El Niño and IOD exists through the atmospheric Walker circulation. crucial to the development (in particular, onset) of both El Niño and IOD. El Niño-IOD interaction provides a new hope for enhanced prediction skill of the both. IOD change needs to be considered for the future projection of ENSO under global warming.

Outstanding issues: IOD and ENSO triggering and terminations – biases in models Role of subsurface ocean (particularly the IO) – data assimilations, initializations… IOD and ENSO teleconnections in model predictions Extended ENSO predictions, role of warming trend Decadal predictions – initialization, processes…

The Evolution of 2006 IOD in SINTEX-F and POAMA Predictions The dotted lines indicate predictions for June and January DMI starting from initial months. SINTEX-F consistently predicts the 2006 IOD from November 2005. Observed DMI

The Evolution of 1994 IOD in SINTEX-F and POAMA Predictions