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OGCM sensitivity experiments on the annual cycle of Western Hemisphere Warm Pool (WHWP)

OGCM sensitivity experiments on the annual cycle of Western Hemisphere Warm Pool (WHWP). By S.-K. Lee (CIMAS/UM), D. Enfield (AOML/NOAA), C. Wang (AOML/NOAA), and G. Halliwell Jr. (RSMAS/UM) Objectives:

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OGCM sensitivity experiments on the annual cycle of Western Hemisphere Warm Pool (WHWP)

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  1. OGCM sensitivity experiments on the annual cycle of Western Hemisphere Warm Pool (WHWP) • By S.-K. Lee (CIMAS/UM), D. Enfield (AOML/NOAA), C. Wang (AOML/NOAA), and G. Halliwell Jr. (RSMAS/UM) • Objectives: • To assess the appropriateness of commonly used surface heat flux data sets in driving HYCOM simulation of WHWP • To assure that the model will optimally simulate the warm pool behavior (i.e, fine-tuning). • To understand the annual cycle of the WHWP heat budget (i.e, forcing and damping mechanisms)

  2. Outline • What is WHWP and why do we want to study it? • HYCOM configuration • 16 Numerical experiments • Two important numerical issues (a) Heat budget analysis using HYCOM? (b) Synoptic variability of surface turbulent heat flux • Model-Data and Model-Model comparisons • Conclusion and Discussion

  3. What is WHWP and why do we want to study it? • Importance of WHWP: • A heating source for the summer Atlantic Hadley circulation (Wang and Enfield, 2003) • A source of moisture for North America, affecting summer rainfall in the US, Caribbean, Central & South America (Bosilovich et al. 2002; Mestas-Nunez et al., 2005) • Important for Atlantic Hurricanes (Wang et al., 2005) • Interannual variability large, a part of ENSO-Atlantic bridge signal

  4. OGCM simulation Model: Hybrid Coordinate Ocean Model (version 2.1.27) Model domain: contains both Pacific and Atlantic (100oE- 20oE, 35oS-65oN) Resolution: uniform 1o in zonally and variable in meridional direction; 0.5o at the equator increasing linearly to 1o at 40o latitude and 1o poleward of 40o; 22 hybrid layers Miscs.: T-S are advected; Levitus climatology used for initial condition, also for relaxation at the southern boundary.

  5. Numerical experiments

  6. Two important numerical issues • Issue-1: Heat budget analysis using HYCOM? • Hybrid grid generator acts like an upstream vertical advection operator (Bleck, 2002), contributing in ocean heat budget • A practical solution is to enforce the surface layers (~50m) to be in purely z-coordinate (the problem still exist in hybrid layers, but not in purely z-coordinate or isopycnal layers). • Use unrealistically small target density for the upper layers to enforce the surface layers (~50m) to be in purely z-coordinate (Bleck, 2002) • PCM scheme do nothing in z-coordinate layers, but PLM (HYCOM default) still operate in purely z-coordinate layers. • Heat budget computation routine is implemented in the codes. Using archive data is not a good idea.

  7. Issue-1: Heat budget analysis using HYCOM?

  8. Issue-2: Synoptic variability of surface turbulent heat flux

  9. Issue-2: Synoptic variability of surface turbulent heat flux • Synoptic variability in the surface turbulent heat fluxes (anisotropic heat flux term) is significant over the WHWP (~50W/m2). • Anisotropic heat flux is independent from the mean fluxes, thus can not be parameterized (Gulev, 1979). • When monthly heat flux data sets are used to force HYCOM, anisotropic heat flux must be treated separately. • A practical way is to estimate the anisotropic heat flux for each surface heat flux climatology, then use it as an additional heat flux in HYCOM.

  10. Surface net heat flux in the eight data sets

  11. Air-sea heat (moisture) transfer coefficeint

  12. Quick evaluation of the eight flux datasets (EPIC)

  13. Quick evaluation of the eight flux datasets (PIRATA)

  14. SHC-KPP & OBH-KPP

  15. SHU-KPP & DSU-KPP

  16. NCEP1-KPP & NCEP2-KPP

  17. ERA15-KPP & ERA40-KPP

  18. Model SST bias versus surface net heat flux (QNET)

  19. QNET (DSU – ERA15)

  20. Simulated vs. observed subsurface temperature profile

  21. Summary • The simulated SST is closest to the observations when Southampton constrained (SHC) data is used to force HYCOM; unrealistically high when forced with unconstrained in-situ data products (SHU, DSU) and unrealistically low when forced with model-based reanalysis products (NCEP1, NCEP2, ERA15 and ERA40). • The model SST bias is minimized when monthly KPAR climatology is used. For reasonable variations of the critical Richarson number (0.25 ~ 1.00) in two different mixing models (KPP and GISS), there is no significant impact on the results. Heat flux bias is too high to make any conclusion. • Yes, HYCOM can be used for mixed layer heat budget studies, but the numerical diffusion due to hybrid-grid generator must be properly dealt with, and the heat budget computation routine must be implemented in the codes. • When monthly heat flux data sets are used to force HYCOM, synoptic variability of the QLAT and QSENmust beincorporatedin HYCOM.

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