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Understanding the Tropical Biases in GCMs: Double-ITCZ, ENSO, MJO and Convectively Coupled Equatorial Waves

Understanding the Tropical Biases in GCMs: Double-ITCZ, ENSO, MJO and Convectively Coupled Equatorial Waves. The tropical biases: One of the main bottlenecks for climate modeling. The major difficulties for understanding and alleviating these tropical biases.

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Understanding the Tropical Biases in GCMs: Double-ITCZ, ENSO, MJO and Convectively Coupled Equatorial Waves

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  1. Understanding the Tropical Biases in GCMs:Double-ITCZ, ENSO, MJO and Convectively Coupled Equatorial Waves

  2. The tropical biases: One of the main bottlenecks for climate modeling

  3. The major difficulties for understanding and alleviating these tropical biases • They all involve some forms of feedback, such as the ocean-atmosphere feedback and the wave-heating feedback, making it difficult to determine the real cause of the bias; • The biases need to be traced back to specific model characteristics, such as certain aspect of the physical parameterizations, in order to provide useful guidance on how to improve the model simulations.

  4. How to attack the problem? Difficult to understand the success of some schemes/ parameters Difficult to try all combinations of schemes/parameters Possible missing physics in all existing schemes Simulations and Predictions Model Improvement (Treatments) Structure Analysis (Symptoms) Feedback and Physical Relationship Analysis (Mechanisms)

  5. GCMs analyzed: 27 models including almost all the major GCMs used for predictions and projections • 22 IPCC AR4 coupled GCMs (IPCC Fourth Assessment Report to be released in 2007; from PCMDI data archive) • NCEP operational GFS and CFS (in collaboration with Wanqiu Wang of NCEP) • ECMWF model (from DEMETER archive) • NASA GMAO GEOS5 GCM currently under development (in collaboration with Siegfried Schubert, Max Suarez, Julio Bacmeister of NASA GMAO) • GFDL next generation GCM currently under development (in collaboration with Leo Donner of GFDL) • Seoul National University GCM (in collaboration with Myong-In Lee of NASA GMAO)

  6. The double-ITCZ problem: Symptoms (1) Excessive (insufficient) precipitation over much of tropics (equatorial western Pacific); (2) Cold SST bias over much of tropics Obs NCAR GFDL Double-ITCZ Shading: SST Contours: precipitation From Lin (2006a)

  7. The double-ITCZ problem: Mechanisms (1) Biases in AGCM’s climatology initiate the biases in the coupled runs; (2) Biases in ocean-atmosphere feedback parameters amplify or suppress the initial problems. SST gradient - trade wind (Bjerknes) feedback (e.g. Bjerknes 1969, Neelin and Dijkstra 1995; Pierrehumbert 1995; Sun and Liu 1996; Jin 1996; Clement et al. 1996; Liu 1997; Cai 2003) SST - LHF feedback (e.g. Wallace 1992; Liu et al 1994; Zhang et al. 1995) SST - SWF feedback (e.g. Ramanathan and Collins 1991) Neelin and Dijkstra (1995) showed that any excessive positive feedback (or insufficient negative feedback) tends to shift the whole system westward, leading to a double-ITCZ pattern. However, few previous studies have evaluated quantitatively the feedback parameters in GCMs. From Lin (2006a)

  8. The double-ITCZ problem: Mechanisms(1) Excessive tropical precipitation in AGCMs leads to enhanced Walker circulation and surface flux cooling Precipitation Latent heat flux Excessive Excessive Surface zonal wind stress Surface downward shortwave flux Overly strong Insufficient Annual mean along the equator (5N-5S)

  9. The double-ITCZ problem: Mechanisms(2) Overly positive ocean-atmosphere feedback parameters Bjerknes x vs SST Precip vs SST Overly positive SST-LHF LHF vs SST Qair vs SST Overly positive SST-SWF SWF vs SST Cld vs SST Insufficiently negative Linear regression for 5N-5S averaged monthly data

  10. The ENSO problem: Symptoms(1) Large scatter in ENSO variance (2) Too-short ENSO period in many models Interannual variance of SST along the equator (5N-5S) CCSM3 Normalized spectrum of Nino3 SST CCSM3 From Lin (2006b)

  11. Existing ENSO theories (6) Stochastic forcing theory (McWilliams and Gent 1978, Lau 1985, Penland and Sardeshmukh 1995, Blanke et al. 1997, Kleeman and Moore 1997, Eckert and Latif 1997) (1) Slow coupled mode theory (Philander et al. 1984, Gill 1985, Hirst 1986, Neelin 1991, Jin and Neelin 1993, Wang and Weisberg 1996) (2) Delayer oscillator theory (Suarez and Schopf 1988, Battisti and Hirst 1989) (3) Advective-reflective oscillator theory (Picaut et al 1997) (4) Western Pacific oscillator theory (Weisberg and Wang 1997) Quasi-standing oscillation within Pacific basin triggered or forced by free oceanic waves (5) Recharge oscillator theory (Jin 1997a,b) From Lin (2006c)

  12. A new observation-based mechanism for ENSO: The coupled wave oscillator (Lin 2006c,d) ENSO amplitude and period are determined by circum-equatorial coupled equatorial waves, and their interactions with the off-equatorial Rossby waves

  13. The ENSO Problem: MechanismIncorrect representation of the coupled wave oscillator Too-fast phase speed Realistic phase speed SSH SSH x x CCSM3 ENSO Period=2.5 yrs MPI ENSO Period=4 yrs

  14. The MJO and CCEW problems: SymptomsOnly half of the models have the waves, but usually with too weak variances and too fast phase speeds Obs GFDL NCAR

  15. The MJO and CCEW problems: SymptomsThe problem is especially severe for MJO, with very weak variance, no coherent eastward propagation, and no significant spectral peak All season Asian summer monsoon CCSM3 Spectrum of precipitation at 0N85E North American monsoon West African monsoon (Lin et al. 2006a,b,c, Lin 2007)

  16. The MJO and CCEW problems: Mechanisms Vertical heating profile In collaboration w/ Leo Donner Stratiform heating In collaboration w/ Myong-In Lee Moisture pre-conditioning Column-integrated diabatic heating has six major components (Mean state and higher-frequency modes affect the MJO through the nonlinear terms) In collaboration w/ Ping Liu Shallow/midtop convection In collaboration w/ Myong-In Lee Radiation feedback Model resolution In collaboration w/ Wanqiu Wang IPCC runs Air-sea coupling

  17. The MJO and CCEW problems: Treatments Moisture trigger often significantly enhances the variances of CCEWs, and sometimes slows down the phase speeds No convection Strong trigger Weak trigger No trigger Effect on MJO is not monotonic Lin, Lee. Kim, Kang (2006d)

  18. The MJO and CCEW problems: Treatments Moisture trigger significantly enhances the fraction of large-scale precipitation No convection Strong trigger Weak trigger No trigger Lin, Lee, Kim, Kang (2006d)

  19. Recommendation: A model development strategy for alleviating the tropical biases Difficult to understand the success of some schemes/ parameters Difficult to try all combinations of schemes/parameters Possible missing physics in all existing schemes Simulations and Predictions Model Improvement (Treatments) Structure Analysis (Symptoms) Feedback and Physical Relationship Analysis (Mechanisms) Understand the reasons of past successes/failures Save time and computer resources in testing parameters Know the directions of future improvements

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