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OHC comparison

OHC comparison. Purpose. Investigate relative contribution of different factors to differences in calculated ocean heat content Factors include: mapping method, XBT correction, profile data used, reference climatology. Paper Outline. Introduction: Why examine? Method (see following slides)

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OHC comparison

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  1. OHC comparison

  2. Purpose • Investigate relative contribution of different factors to differences in calculated ocean heat content • Factors include: mapping method, XBT correction, profile data used, reference climatology

  3. Paper Outline • Introduction: Why examine? • Method (see following slides) • Results: OHC Comparisons (Years 1968-2009) Done (for some groups) 1. EN3v2a database, bottle/CTD/Argo/XBT data used, Wijffels XBT corrections applied, Wijffels bottle/CTD/Argo climatology used as baseline. 2. Same as (1) except Levitus XBT corrections applied. 3. Same as (1) except Wijffels bottle/CTD/Argo/XBT climatology used as baseline Not done yet 4. Same as (1) except Cowley XBT corrections applied • Discussion: Why differences? Some exploration of geographic differences between mapping methods, how methods themselves contribute to differences • Conclusions

  4. Method (1) • Catia has calculated 1°x1° mean (potential) temperature anomaly fields using various climatologies, XBT corrections, and datasets • For each year, the anomalies are calculated for each month separately. • The mean temperature anomaly fields are averages over depths 0-300m and 300-700m at each grid square. • Catia has calculated ocean heat content using the method outlined in Domingues et al. (2008) from each set of temperature anomaly fields.

  5. Method (2) • Tim has calculated ocean heat content from the same input temperature anomaly fields using the Levitus et al. (2009) method as follows: • For each year, monthly temperature anomalies were multiplied by number of observations for that month, all available months added together, then divided by total observations for the year (in each grid square) to get a yearly temperature anomaly. • 0-300 m mean temperature anomalies were inserted as the temperature anomaly values at each of the 12 standard levels 0m to 300m • 300-700 m mean temperature anomalies were inserted at each of 4 standard levels 400m – 700m. • Temperature anomalies were objectively analyzed and used to calculate ocean heat content

  6. First Preliminary Results • Using input dataset EN3v2a + Argo only 2004-2009 • Temperature anomalies are relative to monthly climatologies. • Climatology with bottle/CTD/Argo/XBT • Ocean heat content integrals are 0-700m, 65°S to 65°N • Chose temperature anomaly sets most similar to those used for published heat content • Like Domingues et al. (2008): bottle/CTD/Argo/XBT data only, Wijffels et al. (2008) corrections • Like Levitus et al. (2009): all available data, Levitus et al. (2009) corrections.

  7. No smoothing

  8. 3-yr smoothing

  9. 11-year mean ocean heat content comparison (unsmoothed) WO8c = Wijffels et al. 2008 XBT corrections used L09c= Levitus et al. 2009 XBT/MBT corrections used D08m=Domingues et al. 2008 mapping used L09m=Levitus et al. 2009 mapping used Units=1022 Joules

  10. Observations 1 • From all 11-year time periods, XBT corrections cause the largest difference. • Differences between mapping methods for 11-year means are < 0.4 x 1022J, excepting case of Levitus corrections 1994-2004 (2.0 x 1022J).

  11. EN3v1d data set compared to EN3v2a

  12. Observations 2 • Using EN3v2a instead of EN3v1d has only small effect for most years. • The difference is larger for the Levitus mapping for most years, but still relatively small • The difference for Domingues mapping is large only for 2000-2002. Why?

  13. Using different base climatologies: Both from S. Wijffels, both using bottle/CTD/Argo, one with XBTs, one without

  14. Bottle/CTD/Argo/XBT input vs. All data [including moored buoys, gliders,drifters, other?]

  15. Observations 3 • Different climatologies have a small effect using the Levitus mapping, larger effect using Domingues mapping • additional data in the All data set makes little difference over the bottle/CTD/Argo/XBT dataset

  16. Different XBT corrections Levitus mapping

  17. Different XBT corrections Domingues mapping

  18. Different XBT corrections Lyman mappings (mean of the maps)

  19. Different XBT corrections Lyman mappings (representative mean)

  20. Different XBT corrections Ishii mapping

  21. Different XBT corrections Good mapping

  22. Different XBT corrections Levitus mapping

  23. Different XBT corrections Domingues mapping

  24. Different XBT corrections Lyman mappings (mean of the maps)

  25. Different XBT corrections Lyman mappings (representative mean)

  26. Different XBT corrections Ishii mapping

  27. Different XBT corrections Good mapping

  28. Observations 4 • Different XBT corrections have a larger effect using the Domingues mapping than the Levitus mapping

  29. Year 2009 W08 XBT corrections BCAX data EN3v2 Monthly temp. clim. (BCAX) Levitus mapping (above) Domingues mapping (below) Current Levitus mapping with WOA09 monthly temp. clim. Levitus XBT correction (above)

  30. Year 1980 W08 XBT corrections BCAX data EN3v2 Monthly temp. clim. (BCAX) Levitus mapping (above) Domingues mapping (below) Current Levitus mapping with WOA09 monthly temp. clim. Levitus XBT correction (above)

  31. Year 2001 W08 XBT corrections BCAX data Monthly temp. clim. (BCAX) Domingues mapping EN3v1d(above) Domingues mapping EN3v2a (below) Current Levitus mapping with WOA09 monthly temp. clim. Levitus XBT correction (above)

  32. Observations 5 • Domingues mapping presents much smoother geographic distribution of heat (due to EOF pattern mapping?) • This may damp mesoscale features such as cool Amazon outflow area 2009 (How important is this?) • QC is more critical to Levitus mapping (How much heat represented by anomalous features?) • EN3v1d warmer Pacific than EN3v2a (why?)

  33. Observations 6 • Lyman (representative mean) similar to Domingues/Levitus 1980s-1990s, only Domingues 2000s • Lyman (mean of t he maps) similar to Good most years, Levitus/Good in the 2000s

  34. Observations 7 • Lyman (mean of the maps) difference using different climatologies closest to 0.0 x 1022J, except 1990s • Levitus differences fairly constant for all years (~1.2 x 1022J) • Domingues differences largest in the 1970s • Lyman (representative mean) differences large in the 2000s

  35. Observations 8 • Differences between using Wijffels and Levitus corrections are similar for each mapping method, except late 1990s to 2004 where Lyman (representative mean) and Domingues differences are larger. • No XBT data used after 2004

  36. Domingues, Levitus mapped ocean heat content (left) and thermosteric sea level anomaly (right)

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