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The Impact of Air-Sea Interaction on the Potential Predictability

The Impact of Air-Sea Interaction on the Potential Predictability. Jung-Lien Chu Cheng-Ta Chen National Taiwan Normal University. Outline. Introduction Data and methods Results Summary. ENSO through ‘atmospheric bridge’ process strongly affects the global climate variability.

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The Impact of Air-Sea Interaction on the Potential Predictability

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  1. The Impact of Air-Sea Interaction on the Potential Predictability Jung-Lien Chu Cheng-Ta Chen National Taiwan Normal University

  2. Outline • Introduction • Data and methods • Results • Summary

  3. ENSO through ‘atmospheric bridge’ process strongly affects the global climate variability Klein et al. 1999 Lau et al. 1994 Alexander et al. 2002 Air-sea interaction plays important role in ENSO teleconnections

  4. Wang 2005 AMIP-type simulation lead to probelm in simulating summer monsoon rainfall

  5. Wu and Kirtman 2005 Air-sea coupling provides a local negative feedback to reduce the tropical atmospheric variability

  6. What is Climate Potential Predictability ? • The mechanisms for the inter-annual variability of monthly mean can be categorized into 2 parts: Internal dynamics: effects of instabilities, nonlinear interaction ……etc. Boundary forcings: fluctuations of SST, sea ice/snow, soil moisture and other slowly varying boundary conditions. …………… (Shukla 1981)

  7. What is Climate Potential Predictability ? (cont.) • To evaluate the response of model runs to a boundary forcing => (Signal) • To evaluate the differences in between model members, which are caused by the shift of initial condition and long-term integration => (Noise) • The ratio of Signal to Noise=> Potential Predictability (PPD.)

  8. Climate potential Predictability ENSO SST

  9. AMIP • PROVOST Kumar 1995

  10. Rowell 1998 Fig. 3. Percentage variance of seasonal mean MSLP due to oceanic forcing computed from the ensemble of six 1949–93 runs. Results for each of four standard seasons are shown. The contour interval is 10%, and white areas show where values do not significantly exceed zero at the 5% significance level. Many previous assessments on potential seasonal predictability are based on AMIP-type ensemble simulations

  11. Questions ? Whether local SST and air-sea interaction enhance or reduce the climate potential predictability due to remote ENSO forcing? Does this local impact have seasonality or change with the amplitude and phase of ENSO?

  12. MSLP potential predictability (signal-to-noise ratio) MLM CTRL

  13. Monte-Carlo approach for comparison To generate 1000 samples by randomly selected 8 members from the 16 ensemble members of MLM experiment for the calculation of climate potential predictability to facilitate the comparison between CTRL and MLM experiments.

  14. The Difference of PPD. between MLM and CTRL

  15. CTRL => AGCM only => PPD. Signal stronger MLM => Ocean-Atmosphere coupled scheme => PPD. Signal weaker Air-sea interaction tends to suppress the Potential Predictability over the north Pacific ocean

  16. How does air-sea interaction affect the Potential Predictability ?

  17. Potential predictability => the inter-annual variability The method of “ Warm minus Cold” composite Warm year : 1957、1972、1982、1991、1997 Cold year : 1955、1970、1973、1975、1988 (Lau et al. 2003)

  18. Warm-Cold composite-----CTRL Contour: MSLP Shadow: Net heat flux

  19. Warm-Cold composite-----MLM Contour: MSLP Shadow: Net heat flux

  20. Warm-Cold composite-----(MLM-CTRL) Contour: MSLP Shadow: Net heat flux

  21. Upward net heat flux and Low pressure anomaly over the north Pacific ocean=> MLM and CTRL • Upward net heat flux and Low pressure anomaly over the north Pacific ocean=> Weaker in MLM => “+” is found in (MLM-CTRL)

  22. 140E~160W; 30N~45N • Warm SST ano. (Winter time) • Lower pressure anomaly • stronger surface wind • upward LH and SH (ocean to atmos.) increasing • PPD (MLM < CTRL ) Warm SST ano. ( after Winter) • surface winddecreasesuddenly in CTRL run • The strength of wind speed is maintained in MLM run • PPD (MLM>CTRL)

  23. Air-sea interaction Stronger cyclonic circulation enhanced surface wind Remote forcing upward LH and SH is damped Weak inter-annual variability PPD. suppression Summary Negative feedback • ENSO remote forcing is still a dominate factor for PPD. • PPD. Changes seasonally and regionally. • Local air-sea interaction tends to damp and modify the response of MSLP to the remote tropical forcing • Climate potential predictability is suppressed by local air-sea interaction over the north Pacific ocean

  24. Thank you very much !!

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