1. 1 Comparative Analysis of Upper Ocean Heat Content Variability from an Ensemble of Operational Ocean Analyses Yan Xue (1), Magdalena A. Balmaseda (2), Tim Boyer (6),Nicolas Ferry (3), Simon Good (4), Ichiro Ishikawa (5), Arun Kumar (1) Michele Rienecker (7), Tony Rosati (8), Yonghong Yin (9) (1) NOAA/NCEP, 5200 Auth Rd, Camp Springs, MD 20746, USA, Yan.Xue@noaa.gov, Arun.Kumar@noaa.gov (2) ECMWF, Shinfield Park, Reading RG2 9AX (UK), Magdalena.Balmaseda@ecmwf.int (3) Mercator-Océan, 8-10 rue Hermès, 31520 RAMONVILLE ST AGNE (France), Nicolas.Ferry@mercator-ocean.fr (4) Met Office Hadley Centre, FitzRoy Road, Exeter, Devon, EX1 3PB (UK), Simon.Good@metoffice.gov.uk (5) Japan Meteorological Agency, 1-3-4 Ootemachi, Chiyoda-ku, Tokyo, 100-8122 (Japan), iishikawa@met.kishou.go.jp (6) NOAA/ NESDIS/NODC, 1315 East-West Highway, Silver Spring, MD 20910, USA, Tim.Boyer@noaa.gov (7) NASA/GSFC/GMAO, Greenbelt, MD 20771 (USA), Michele.Rienecker@.nasa.gov (8) NOAA/GFDL, Princeton University, P.O. Box 308, Princeton, NJ 08542. Tony.Rosati@noaa.gov (9) CAWCR, GPO Box 1289, Melbourne, VIC 3001 (Australia), Y.Yin@bom.gov.au Workshop on Observing System Evaluation and Intercomparisons, June 13-17, 2011, Santa Cruz, CA

2. 2 GSOP Upper 300m Heat Content Comparison, Reading, 2006 (call for validation of climate signals) The North Pacific does not show a warming trend, but more of a rapid shift in the early 90’s Large uncertainty after 2000 Phase/amplitude of decadal signal is poorly resolved. Outliers. North PacificNorth Atlantic Tropical PacificTropical AtlanticTropical Indian Ocean Courtesy of Magdalena Balmaseda

3. 3 NameMethod & Forcings In Situ Data Altimetry Data ResolutionPeriodVintageReference EN3.v2aAnalysis Correction Scheme No XBT corrections No1°x 1°, 42 Levels Monthly Temp. 1950- present 2009Ingleby and Huddleston (2007) NODCObjective Analysis No XBT corrections No1°x 1°, 16 Levels, 0 to 700m Seasonal Temp. 1955- present 2010Levitus et al. (2009) GODAS3D-VAR No XBT corrections NO (Yes in real time) 1°x 1° (1/3° near Eq), 40 Levels Pentad, Monthly 1979- present 2003Behringer and Xue (2004 ECMWF (S3) OI No XBT corrections Yes1°x1° (1/3° near Eq), 29 Levels Daily, Monthly 1959- present 2007Balmaseda et al. (2008) JMA3D-VAR No XBT corrections Yes1°x1° (1/3° near Eq), 50 Levels Pentad, Monthly 1979- present 2009Usui et al. (2006) CFSR3D-VAR Partially coupled No XBT corrections No (Yes in real time) 1/2°x 1/2° (1/4° near Eq), 40 Levels Daily, Pentad, Monthly 1979- present 2010Xue et al. (2010) GFDLEnKF Fully coupled XBT corrections Yes 1°x 1° (1/3° near Eq), 50 Levels Daily, Pentad, Monthly 1970- present 2010Zhang et al. (2009) GMAOEnOI Fully coupled XBT corrections No1/2°x 1/2° (1/4° near Eq), 40 Levels Daily, Monthly 1980- present 2011Rienecker at al. (2011) MERCATOR (PSY2G2) KF-SEEKNo XBT corrections Yes2°x 2° (1/2° near Eq), 31 Levels Daily, Pentad, Monthly 1979- present 2007Drévillon et al. (2008) BOM (PEODAS) EnKFNo XBT corretions No2°x 1.5 ° (1/2° near Eq.), 25 Levels Daily, Monthly 1980- present 2009Yin et al. (2010) OceanObs09 Community White Paper by Xue et al. (2010) (call for operational monitoring of climate signals)

4. 4 In Situ Observations from Saha et al. (2010) Argo (2003-09) Altimetry (1993-2002) Pre-Altimetry (1985-1992)

5. 5 How well is the mean HC300 analyzed by operational ocean reanalysis (ORA)? What are impacts of changes in the ocean observing system on the quality of HC300 analysis? How well does operational ORA capture interannual variability, multi-decadal and long term variability in HC300? What are prospects for monitoring climate indices using an ensemble of operational ORAs? What are roles of HC300 on potential predictability of ENSO, Indian Ocean Dipole and Atlantic Nino? Questions

6. 6 Mean Heat Content in 1985-2009

7. 7 RMSD from EN3 in Different Ocean Basins

8. 8 HC300 in Equatorial Pacific (2 o S-2 o N) 1993 1999 2003

9. 9 HC300 in Equatorial Indian Ocean (2 o S-2 o N) 2003 1997

10. 10 HC300 in Equatorial Atlantic (2 o S-2 o N) 2005

11. 11 HC300 Anomaly Correlation with EN3

12. 12 HC300 Anomaly Correlation with OI SST

13. 13 E. PacW. Pac.S.E. Ind.S.W. Ind.E. Atl. EN3 0.800.390.160.420.57 NODC 0.740.370.160.420.47 GODAS 0.780.390.250.410.46 ECMWF 0.780.410.320.480.58 JMA 0.770.380.360.510.45 CFSR 0.750.370.300.400.35 GFDL 0.760.380.240.450.60 GMAO 0.770.360.290.420.48 MERCATOR 0.780.410.390.470.56 BOM 0.790.390.340.450.47 mean 0.770.390.280.440.50 Spread/mean 5%11%29%11%18% Table 3. Anomaly correlation between HC300 and SST in 1982-2009 averaged in various ocean basins drawn as boxes in Fig. 8. Correlations less than 0.4 are in bold. Anomaly Correlation between HC300 and SST

14. 14 HC300 Anomaly Indices for ENSO, IOD and Atlantic Nino ENSO IOD Atlantic Nino

15. 15 Linear Trend of HC300 Anomaly in 1993-2009

16. 16 1995 2004 1999 HC300 Anomaly Indices for Multi-decadal Variability

17. 17 HC300 and HC300 Anomaly Average in 70 o S-70 o N El Chichon Mt. Pinatubo 2003

18. 18 Impacts of HC300 on SST Anomaly

19. 19 Role of HC300 for Predictability of ENSO -Equatorial western Pacific HC300a leads NINO3.4 by 10-12 months. - The lead/lag relationship between HC300a and NINO3.4 is consistently analyzed by all ORAs. - NODC is too noisy near the equator. - The peak correlation between HC300a and NINO3.4 in CFSR is lower than others.

20. 20 Role of HC300 for Predictability of Atlantic Nino -Equatorial eastern Atlantic HC300a leads Atlantic Nino by 4-6 months. -Equatorial western Atlantic HC300a leads Atlantic Nino by 8-12 months. -Differences in the lead/lag correlation are quite large.

21. 21 Role of HC300 for Predictability of IOD - Southeastern Indian Ocean HC300a leads IOD by 2 months. - Southwestern Indian Ocean HC300a leads IOD by 8-12 months. - Differences in the lead/lag correlation are quite large.

22. 22 Summary Consistency in mean HC300 is generally high south of 30 o S except near the Gulf Stream and Kuroshio-Oyashio Extension (KOE), in the tropical Atlantic, and some regional seas such as Gulf of Mexico and South China Sea. Consistency, measured by root-mean-square differences from EN3, tends to increase with time, particularly in the tropical Pacific, the tropical Indian Ocean and extra-tropical southern oceans, which are partly due to constraints from a dense observational network from tropical mooring arrays and Argo floats. Consistency in the equatorial Pacific HC300 increased significantly after 1993 when the TAO mooring array was fully implemented. Consistency in the equatorial Indian Ocean HC300 increased significantly around 2003 when the two RAMA mooring lines were implemented at 80.5 o E and 90 o E. All model-based HC300 are too cold relative to EN3 in the eastern tropical Indian Ocean before 1997. Consistency in the equatorial Atlantic HC300 is much lower than that in the equatorial Pacific and Indian Ocean, but it improved significantly after 2006.

23. 23 Summary HC300 anomalies (HC300a) associated with ENSO are highly consistent among ORAs; HC300a associated with IOD are moderately consistent, and model-based analyses are superior to in situ-based analyses in the eastern pole of the IOD; HC300a associated with the Atlantic zonal mode have considerable uncertainties among ORAs, which are comparable to signals. Large multi-decadal variability and long-term trends exist in HC300. The consensus among ORAs suggests that the mean HC300 in 70 o S- 70 o N has brief cooling periods during early 1980s and 1992-1993 related to the volcanic eruptions of the El Chichon and Mt. Pinatubo, and a short warming in 1985-1991, and then a continuous warming in 1994-2003, followed by a persistence or weak cooling in 2004- 2009. Despite of many advances in ORAs in the past decade, uncertainties in HC300 are still large near western boundary currents, in the tropical Atlantic and extra-tropical southern oceans. To improve HC300 analysis in those regions, additional advances, such as improving surface fluxes, model physics, model resolution and data assimilation schemes, will be needed in conjunction with maintaining and enhancing ocean observing systems in those regions.