David Zermeño Advisor: Chidong Zhang

1. Student SeminarOn the Tropical Atlantic Model Biases and the Vertical Heating Structure over the Amazon David Zermeño Advisor: Chidong Zhang

2. Introduction • The climate variability of the Tropical Atlantic (TA) displays important bias in in most of the Atmospheric Oceanic General Circulation Models (AOGCMs). • This errors have prevailed trough significant model improvements. • Besides the scientific importance of addressing this issue, improving model reliability is beneficial for reducing climate vulnerability, in this case for the South American and West African regions.

3. Important biases From coupled Models that participated in the AR4 Observed climatology (top figures) and model bias (bottom figures): CMIP ensemble “minus” observed Reversed SST gradient Westerly (arrows) and SST bias in C and D Figures form Richter et al, 2011

4. Some hypothesis • Richter et al. (2008) suggest that the triggering factor of these biases should be in the atmospheric component of the AOGCMs, as these errors persist in simulations even if observed SST is prescribed. • Convection is likely to play an important role. Richter et al.(2008) hypothesized that the dipole of rainfall deficit over equatorial South America and excess over tropical Africa is responsible for the westerly wind biases. • Other hypothesis is that models underestimate the stratocumulus deck in the east TA, so more incoming radiation leads to warm SST bias in this side of the basin (E.g. Large andDanabasoglu 2006). • Other authors suggest that the ocean model is the one responsible for the SST bias. E. g. Breugemet al. (2008): model spurious barrier layers in the eastern TA basin suppress vertical entrainment of sub-thermocline water into the mixed layer, causing a gradual heating. • The relatively small size of the TA suggests that regional details are very important for alleviating the model biases. Currently, no hypothesis can satisfactorily explain the biases either in the atmospheric or oceanic components, or in the coupled system.

5. Our approach We ask, to what extend the vertical heat structure over the Amazon induces a dynamic response over the TA? Particularly: ¿More shallow convection (bottom-heavy heating profiles) would improve westerly bias? Models tends to produce insufficient shallow convection Idealized scheme of our hypothesis. A profile like the green one will be referred as “bottom heavy”, and like the red one as “top heavy” Dynamic response

6. Getting suitable experiments To test this idea we used the WRF model (a regional atmospheric model) Experiments with different cumulus parameterizations How to assess sensitivity to the shape of the profile and not to its strength? (looking for well defined and equal area bottom and top heavy profiles)

7. Our approach was by making idealized experiments: Artificially reshaping the vertical heating profile WRF experiment domain in black, 0.5 degrees resolution The reshaping is applied at 90% power in the red region and then relaxed towards the original profile in the yellow zone The way of reshaping the profile is the following: (Based on the work of Li C. et al 2009) The new reshaped profile Any given profile Reduced by 70% The heat taken Morphed In an arbitrary shape + = = B A Area under the curve of A = Area under the curve of B

8. Finally idealized experiments originally Same area and a well defined peak reshaped forced (Most of my effort was deposited in this process)

9. Results ofcomparing the top-heavy profile simulation with the reference one Vertical section of u wind component Top-heavy profile Difference in u: Top-heavy “minus” reference Reference (unperturbed) Longitude Wind difference: Top-heavy “minus” reference m/s Averaged area Red: westerly bias in the top-heavy simulation Blue: easterly bias Up to 3 m/s Longitude m/s Longitude

10. u at 10m wind bias in WRF(An example) Difference of the model simulation and Reanalysis Simulated with WRF reference Latitude Longitude Latitude Longitude May 2005 Simulation U at 10m difference: Top-heavy “minus” reference m/s Reanalysis Westerly bias associated with a top-heavy heating profile  Mesoscale processes? Land sea breeze in NE Brazil? m/s

11. Now the bottom-heavy profile experiment and the reference one Vertical section of u wind component Difference in u: bottom-heavy “minus” reference A bottom-heavy profile weakens the westerly bias, but very weakly at surface Longitude Latitude Averaged area m/s Longitude

12. Now the bottom-heavy profile experiment and the reference one Accumulated rain (month of May 2005) Bottom-heavy Vertical section of u wind component Difference in u: bottom-heavy “minus” reference A bottom-heavy profile weakens the westerly bias, but very weakly at surface Latitude Top-heavy Reference (unperturbed) Averaged area longitude Latitude A top heavy profile increases rain whereas a bottom-heavy profile diminishes it. m/s mm Longitude

13. Now the bottom-heavy profile experiment and the reference one Accumulated rain (month of May 2005) Bottom-heavy Vertical section of u wind component Difference in u: bottom-heavy “minus” reference A bottom-heavy profile weakens the westerly bias, but very weakly at surface Latitude Top-heavy Reference (unperturbed) longitude Recall that these are highly idealized experiments but highlight key issues for further improvement A top heavy profile increases rain whereas a bottom-heavy profile diminishes it. m/s mm

14. Summary • Misrepresentation of the vertical heating structure over the Amazon is associated with westerly bias over the Tropical Atlantic. • A top-heavy profile strengthens the westerly bias, a bottom-heavy profile is likely to reduce the bias. • Rain is increased for a bottom heavy profile, whereas for a bottom-heavy profile rain is diminished. Future Work • It is to be evaluated how TA wind is influenced by the convection over West Africa. • Some studies suggest that improving equatorial wind stress would improve the SST gradient bias (E. g. Dewitt D. 2005). So it is necessary to evaluate the coupled, atmosphere-ocean, response to top-heavy and bottom heavy profiles.

15. Thank you!

16. Bibliography -BreugemWP, Chang P, Jang CJ, Mignot J, Hazeleger W (2008) Barrier layers and tropical Atlantic SST biases in coupled GCMs. Tellus 60A:885–897. -ChongyinLi, XiaolongJia, Jian Ling, Wen Zhou and Chidong Zhang (2008) Sensitivity of MJO simulations to diabatic heating profiles. Climate Dynamics (2009) 32:167–187. DOI 10.1007/s00382-008-0455-x. -DeWitt David G. (2005) Diagnosis of the Tropical Atlantic near-equatorial SST bias in a directly coupled atmosphere-ocean general circulation model. Geophysical research letters, vol 32.doi 10.1029/2004GL021707. -Davey MK, Coauthors (2002) STOIC: A study of coupled model climatology and variability in tropical ocean regions. ClimDyn 18:403–420. -Large WG, Danabasoglu G (2006) Attribution and impacts of upper-ocean biases in CCSM3. J Clim 19:2325–2346. -Richter Ingo and Shang-Ping Xie (2008) On the origin of equatorial Atlantic Biases in Coupled General Circulation Models. ClimDyn (2008) 31:587–598. DOI 10.1007/s00382-008-0364-z. -Richter Ingo, Shang-Ping Xie, Andrew T. Wittemberg and Yukio Masumoto (2011) Tropical Atlantic Biases and their relation to Surface Wind Stress and Terrestrial Precipitation.Accepted in Climate Dynamics on February 21, 2011.