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Observation B ias and O cean R eanalyses

Session 3: Observational Data Recovery and Bias Correction Efforts. Observation B ias and O cean R eanalyses. James Carton , Gennady Chepurin, Semyon Grodsky, Tony Santorelli, and Benjamin S. Giese (TAMU) Department of Atmospheric and Oceanic Science University of Maryland. Motivation:

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Observation B ias and O cean R eanalyses

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  1. Session 3: Observational Data Recovery and Bias Correction Efforts Observation Bias and Ocean Reanalyses James Carton, Gennady Chepurin, Semyon Grodsky, Tony Santorelli, and Benjamin S. Giese (TAMU) Department of Atmospheric and Oceanic Science University of Maryland Motivation: > Bias problems in ocean observation sets: Gouretski and Koltermann, 2007, Wijffels et al. (2008); Levitus et al. (2009); Ishii and Kimoto (2010), Gouretski and Reseghetti (2010), Giese et al. (2010) > Problems interpretation of observations: Grodsky et al. (2008) > Bias problems in current surface forcing data sets: Bromwich and Fogt (2004), Large and Yeager (2008) > Model problems

  2. 1910-1919

  3. HYDRO DATA • BT History • 1944 mechanical BT developed at WHOI • 1968 Sippican gets contract to produce XBT • XBT depth = at – bt2 • 1980s Recorders change offering two drop-rate algorithms • 1995 Production moved to MX • 1996 wire coating changes; winding specifications were changed • 1999 mesh added which affects the spooling of the first few meters. Wijffels et al. (2008)

  4. Global heat content 0/700m ORIGINAL Discuss this later

  5. Heat Content anal – obsfor 7 reanalyses A-O > 0 108Jm-2

  6. Fall Rate Formulae Temp error interpreted as depth error Sippican Fall Rate: xbt depth = at – bt2 a=6.472 and b=0.00216 Hanawa (1994): a=6.691, b=0.00225 Hanawa data

  7. Temp Error Levitus et al. 2010 Temp Error after Levitus et al bias correction

  8. Global heat content 0/700m ORIGINAL Corrected

  9. Global heat content 0/700m

  10. MEAN BIAS CORRECTION LEVITUS ET AL., 2009 WIJFFELS ET AL. 2008, Ishii and Kimoto, 2010

  11. When the observations are assimilated into SODA Experiments 2.1.0 Hanawa 2.1.2 Levitus 2.1.4 Wijffels <A-O>

  12. When the observations are assimilated into SODA Too warm Hanawa Levitus et al Too warm Wijffels et al Too cold

  13. 1997/8 El Nino Correcting the BTs causes a 30cm/s change in U(z=50m) and a 0.5C change in T(z=50m)

  14. Surface drifters Memoriam: Pearn P. Niiler 1937-2010

  15. Surface Drifters:Velocity trend bias Explanations the switch to mini-drogues? orunidentified drifters missing drogues?

  16. Difference between MLT and SST

  17. Surface winds Percentage of the ocean covered by the ICOADS wind observation Wind Coverage 100% means that 120 months of 2x2 deg binned data is available during a decade

  18. Time correlation of anomalous zonal wind stress from ICOADS observations and the 20thC reanalysis for the (top) first and (bottom) second half of the 20th century

  19. Running standard deviation of monthly anomalous zonal wind stress at the Vlissingen weather station (OBS) and from the 20thC Reanalysis (REAN). This suggests that REAN underestimates the magnitude of anomalous winds by ~50% (or 75% of variance is missing). But temporal correlation of observed and reanalysis wind anomalies is high, ~0.9.

  20. Summary • Much recent attention has been devoted to identifying bias in the BT archive, discussed in two recent workshops. Ocean reanalysis offers an approach complementary to XBT-CTD comparisons. • SST is generally interpreted as MLT. In fact the two are systematically different in ways that need to be clarified. • Surface drifters have an unrealistic trend. Unraveling the cause and removing the trend requires returning to the original data, an effort underway at AOML (Lumpkin). Possible cause: unidentified undrogued drifters. • ICOADS comparisons to the 20CR offers a way to examine the accuracy of the surface winds.

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