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Why SST? Why in situ analyses? A long (simply constructed) timeseries

A contribution to the problem of coupling in the western North Pacific: SST analyses from ships and buoys. Rick Danielson Oceanography, Dalhousie University, Halifax. Why SST? Why in situ analyses? A long (simply constructed) timeseries Downward impact of cyclones on SST

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Why SST? Why in situ analyses? A long (simply constructed) timeseries

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  1. A contribution to the problem ofcoupling in the western North Pacific:SST analyses from ships and buoys Rick Danielson Oceanography, Dalhousie University, Halifax • Why SST? Why in situ analyses? • A long (simply constructed) timeseries • Downward impact of cyclones on SST (with observational bias) • Upward impact on cyclones • Summary

  2. Cold SST Cold SST 17 Strong at T0 18 Ordinary Gyakum and Danielson (MWR 2000)

  3. Could define anomalies better (spectrally) if we had a long timeseries 17 Strong at T0 18 Ordinary

  4. 810 obs Dec 27-29 1998 monthly weekly daily “HadISST” (2003) “Reynolds” (2002) “Reynolds” (2007)

  5. Bucket Engine intake Buoy/hull sensor Unknown method Kent, Woodruff, and Berry (JAOT 2007)

  6. -3 -2 -1 0 1 2 3 Analysis method 3 days of ICOADS obs Delaunay triangulation 5-point smoothing 1998 December 27-29

  7. Analysis method 1998 December 27-29

  8. Analysis method 1998 December 27-29

  9. In situ HadISST -1.5 daily Reynolds (2007)

  10. Downward impact (submonthly SST) 17 Strong 18 Ordinary Wilks (JAMT 2006)

  11. Contribution by method 17 Strong (+1day) • buckets too cool by ~10% of air-sea difference • (cooling as buckets are drawn on board) • engine intake too warm by ~0.1oC before 1990 • (warming in engine intake pipes) and cool after Kent and Kaplan (JAMT 2006)

  12. Downward impact (submonthly SST) 17 Strong 18 Ordinary Wilks (JAMT 2006)

  13. Downward impact (submonthly SST) no bucket obs 17 Strong 18 Ordinary Wilks (JAMT 2006)

  14. Downward impact (submonthly SST) no bucket or unknown obs 17 Strong 18 Ordinary Wilks (JAMT 2006)

  15. climatological ocean • mixed layer depth • in March (meters) Yasuda (J.Oceanography 2003)

  16. Upward impact • bandpass the 1-6 • month SST variations • reorganize events by • season: midwinter vs • transitional (and omit • Nov. and Feb. cases) • look before T0…

  17. Summary • ICOADS SST obs appear to provide sufficient coverage to • justify their own quasi-daily analysis • The use of composite in situ SST analyses seems physically • meaningful (but need to quantify errors, like other analyses) • Separate studies of upward and • downward impacts (between SST • and cyclones) should be possible • What criteria on cyclones (and/or • anticyclones) best reveal the • coupling mechanisms?

  18. Timeseries validation • use overlapping timescales • of HadISST and Reynolds • et al. (2002) for reference • lowpass filter in situ • analyses (3-d or 7-d) • and subsample (weekly • and monthly) • raw differences:

  19. Timeseries validation • spatial correlation at annual • timescales is high (~99%) • bandpass filter all analyses • with 6-month highpass cutoff • and correlate:

  20. Composite SST Reynolds et al. (2002) no buckets or unknown in situ (subsurface)

  21. Composite SST

  22. Timeseries validation Butterworth lowpass filter f frequency fc cutoff (Nyquist)

  23. Why short timescales? Czaja and Frankignoul (2002) Observed impact of Atlantic SST anomalies on the NAO “Frankignoul and Hasselmann (1977) have pointed out that unlagged correlation between SST and atmospheric anomalies were primarily reflecting the atmospheric forcing of the ocean, so that the oceanic influence on the atmosphere can only be established by studying their covariability when the ocean is leading. In most previous studies (e.g., Namias 1964; Ratcliffe and Murray 1970; Deser and Timlin 1997), the focus was on 1-month lead and no significant oceanic impact could be detected. We believe that this reflects in part that large-scale patterns like the NAO have a significant intrinsic persistence, so that the covariability at 1-month lead is still affected by the atmosphere forcing the ocean. In a recent study, Czaja and Frankignoul (1999) systematically considered lead times longer than a month…”

  24. Why short timescales? Deser and Timlin (1997) “Atmosphere-Ocean Interaction on Weekly Timescales in the North Atlantic and Pacific” Figure 1 Figure 3

  25. Why in situ analyses? • Ratcliffe and Murray (1970) • “North Atlantic SST and • European Pressure” • Monthly SST anomalies south of • Newfoundland help forecast SLP • Peng et al. (1995) “Early • and Midwinter Atmospheric • Responses to Atlantic SST” • Response of the mean flow depends • on initial conditions (seasonality!) • Cjaza and Frankignoul (1999) • “Influence of North Atlantic • SST” (monthly lagged SVD) • First observational demonstration of • an upward impact (in fall and spring) • That the midlatitude ocean has a measurable impact has been described as a “belief” (Frankignoul 1985), an “hypothesis” (Greatbatch 2000), and a “debate” (Kushnir et al. 2002) • Contemporaneous variability is invariably indicative of a downward influence of the atmosphere forcing the ocean (Frankignoul 1985)

  26. Why short timescales? • Frankignoul and Sennechael • (2007) “Influence of North • Pacific SST Anomalies” • For timescales of 2 months and more, • there is an impact in summer and fall, • but must extract ENSO variations first • Kushnir et al. (2002) “GCM • Response to SST Anomalies” • Difficult to reconcile GCMs, but largest • response may be related to remergence • of SST anomalies in Fall, but response • needs physical explanation • Frankignoul and Kestenare • (2005) “Updated Impact on • NAO” • For timescales of 2 months and more, • the R&M centre of action is de- • emphasized, but the SST centre in • subtropics is strong • Modelling and observational • studies generally call for • work to understand physical • mechanisms • How about examining • shorter timescales?

  27. Background Petterssen, Bradbury, and Pedersen (1962) “The Norwegian Cyclone Models in relation to Heat and Cold Sources” “…much of the frontal precipitation at middle latitudes and almost all of the rainfall in the equatorial zone derive from water evaporated in the subtropical belts.”

  28. Background “In the 1960’s there developed a belief that anomalous ocean temperatures could influence the atmospheric circulation in a persistent manner” – C. Frankignoul (1985) Ratcliffe and Murray (1970)

  29. Background - Cyclone Heat Flux Impacts • Petterssen et al. (1962) “The • Norwegian Cyclone Model’s • Heat and Cold Sources” • Surface heat fluxes are mainly in the • cold sector (this damps eddies) • Danard and Ellenton (1980) • “Physical Influences on East • Coast Cyclogenesis” • Preconditioning heat fluxes help eddies • Sanders and Gyakum (1980) • “Cyclone Bomb Climatology” • Strong eddies develop near strong SST • gradients (Gulf Stream and Kuroshio) • Bosart (1981) “President’s • Day Snowstorm” • Operational forecast models should • include latent heat fluxes • Davis and Emanuel (1988) • “Evidence for the Influence • of Surface Heat Fluxes” • Potential warming by heat fluxes • correlated with poor cyclone forecasts • Roebber (1989) “Current • Meanders and Cyclones” • No correlation between strong • cyclones and warm SST anomalies

  30. Background - Cyclone Heat Flux Impacts • Kuo et al. (1991) “Surface • Fluxes in Seven Explosive • Cyclone Simulations” • Preconditioning fluxes between 1-2 • days before deepening help eddies • Perrie et al. (2005) “Sea • Spray Impacts on Cyclones” • Improved heat flux models are being • implemented • Jung and Vitart (2006) • “Forecasting with and without • an Interactive Ocean” • No benefit to coupled ocean-atmosphere • forecasts during the few days before a • strong cyclone

  31. Petterssen et al. (1962) “The • Norwegian Cyclone Model’s • Heat and Cold Sources” • Surface heat fluxes are mainly in the • cold sector (this damps eddies) • Bosart (1981) “President’s • Day Snowstorm” • Operational forecast models • should include latent heat flux • (positive impact likely) • Kuo et al. (1991) “Surface • Fluxes in Seven Explosive • Cyclone Simulations” • Preconditioning fluxes between 1-2 • days before deepening help eddies • Jung and Vitart (2006) • “Forecasting with an • Interactive Ocean” • No benefit to coupled • ocean-atmosphere forecasts • during the few days before a • strong cyclone Why in situ analyses? Upward Influence (SST on cyclones)

  32. Price (1981) and Greatbatch • (1983) “Upper ocean • response to storms” • Enhanced inertial velocities to right • of storm – entrainment and cooling • Shay et al. (2000) “Warm • core ring and Opal” • Deep warm core ring relatively • unchanged as hurricane intensifies • Ren et al. (2004) “Coupled • dynamics in midlatitudes” • Warming after the passage of Super- • storm owing to advection north plus • entrainment of warm water at depth Why in situ analyses? Downward Influence (cyclones on SST) High-frequency SST analyses needed (including pre-satellite era) to assess systematic impacts

  33. GODAE SST Reanalysis • every 12 h from 1981 • <0.4-K error • <10-km resolution • updated in real-time Bulletin of the AMS (Aug 2007)

  34. Courtney (Grade 9) Rick (Grade 19) Nicole (Grade 9)

  35. Analysis method Previous in situ analyses: • Ishii et al. (MWR 2003) performed monthly • subsurface temperature analyses from 1950 • using 3D-Var • Ishii et al. (IJC 2005) performed daily SST (and • other surface) analyses from 1900 using OI (but • then monthly averaged) • Our method may be noiser, but its simplicity • permits analyses of measurement method (e.g., set all bucket SST to 1.0 and other types to 0.0)

  36. Acknowledgements Atlantic Storm Prediction Centre Analyses on multiple CPUs Dalhousie University Spectral processing on single CPU E. Kent (Southampton) WMO Pub.47 SST observation methods B. Thomas (EC-Atlantic) Measurement method experiments F. Dupont (Dalhousie/BIO) GMT Delaunay triangulation reference NCAR ICOADS, HadISST CDC (now ESRL) Reynolds et al. (2002) SST NCDC Reynolds et al. (2007) SST GMT and GrADs software (free!) past NSERC and CFCAS funding (McGill)

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