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Using a novel coupled-model framework to reduce tropical rainfall biases

Using a novel coupled-model framework to reduce tropical rainfall biases. Nicholas Klingaman Steve Woolnough, Linda Hirons National Centre for Atmospheric Science-Climate Department of Meteorology, University of Reading. Outline. Introduction to tropical biases in the MetUM

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Using a novel coupled-model framework to reduce tropical rainfall biases

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  1. Using a novel coupled-model framework to reduce tropical rainfall biases Nicholas KlingamanSteve Woolnough, Linda HironsNational Centre for Atmospheric Science-ClimateDepartment of Meteorology, University of Reading

  2. Outline • Introduction to tropical biases in the MetUM • Biases in mean rainfall • Biases in intra-seasonal variability (Madden-Julian Oscillation) • Introduction to the MetUM-GOML atmosphere—ocean-mixed-layer model • Using MetUM-GOML to explore the sensitivity of tropical biases to coupling in the tropics andextra-tropics • Summary and conclusions

  3. Tropical rainfall biases in the MetUM TRMM DJFM precipitation MetUM DJFM precipitation MetUM bias (MetUM-TRMM) The MetUM produces a strong and southward displaced ITCZ in DJFM.

  4. Tropical rainfall biases in the MetUM TRMM JJAS precipitation MetUM JJAS precipitation MetUM bias (MetUM-TRMM) Large wet biases over tropical oceans in JJAS, with dry biases over tropical land, particularly India.

  5. Madden-Julian oscillation Composites of observed OLR (shading) and 850 hPa winds (vectors) for each MJO phase (Source: Wheeler and Hendon, 2004) • The MJO is the dominant mode of sub-seasonal (30-60 day) variability in the tropics. • Events often form in the Indian Ocean, before propagating east to the Maritime Continent and the West Pacific. • Suppressed convection precedes and follows each active event. • In DJF (JJA) the MJO modulates the Australian (Asian, African) monsoon.

  6. Tropical rainfall biases in the MetUM NOAA CIRES observations Regressions of 20-100 day filtered OLR on a base point at 70°E. The MetUM produces no eastward propagation in tropical convection, with very weak anomalies on sub-seasonal timescales. MetUM Control

  7. Effects of convective entrainment NOAA CIRES observations Increasing entrainment and detrainment by 50% in the MetUM produces some eastward propagation. Klingaman and Woolnough (2014a, QJRMS) MetUM 1.5x entrainment MetUM Control

  8. Effects of convective entrainment 1.5x entrainment minus control MetUM 1.5x entrainment JJAS Control bias against TRMM 1.5x entrainment bias against TRMM See also Klingaman and Woolnough (2014a, QJRMS) and Bush et al. (2014, QJRMS).

  9. MetUM-GOML (Ocean Mixed Layer) model • Key advantages: • Cheap: < 5% of the cost of the atmosphere, allowing high (1 metre) ocean vertical resolution. • Controllable: Easily constrainable to any desired ocean state (small SST biases). • Flexible: Air-sea coupling can be applied selectively in space and time to explore the role of coupling in a range of phenomena. • Adaptable: Works easily with any GCM configuration or grid. MetUM AtmosphericGCM OASIS coupler(sub-daily) MC-KPP one-dimensional ocean model • Climatological three-dimensional heat and salt tendencies are applied to represent • (a) the mean advection in the ocean • (b) corrections for biases in atmospheric surface fluxes

  10. MetUM-GOML (Ocean Mixed Layer) model MetUM-GC (NEMO 3D ocean) MetUM-GOML (KPP 1D ocean) By using climatological heat and salt corrections, MetUM-GOML produces much smaller mean SST biases than a fully coupled GCM. Biases are typically smaller than +/- 0.5K. The disadvantage is the lack of interactive ocean dynamics in MetUM-GOML, which are important for certain applications (e.g., ENSO)

  11. MetUM-GOML (Ocean Mixed Layer) model (5) Near-global Because the MC-KPP columns do not communicate, there is complete flexibility (except near sea ice) in where the atmosphere and ocean are coupled. (4) 50N-50S (2) Warm Pool (3)Tropics- Wide (1) Indian Ocean (4) 50N-50S (5) Near-global

  12. Experiments • All experiments use MetUM GA3.0 atmosphere with +50% to entrainment and detrainment for deep and mid-level convection. • At least 25 years of data are analysed for each experiment.

  13. Impacts on the Madden-Julian oscillation NOAA A-OBS K-30 K-50

  14. Impacts on the Madden-Julian oscillation NOAA K-50 A-50(clim) A-50(15day)

  15. Effect of tropical coupling K-30 minus A-OBS (tropical coupling) K-30 JJAS precipitation A-OBS bias against TRMM K-30 bias against TRMM

  16. Effect of extra-tropical coupling K-50 minus K-30 K-50 JJAS precipitation K-30 bias against TRMM K-50 bias against TRMM

  17. Effect of coupling 50N-50S (vs. clim SST) K-50 minus A-K50(clim) K-50 JJAS precipitation A-K50(clim) bias against TRMM K-50 bias against TRMM

  18. Effect of coupling 50N-50S (vs. 15-day SST) K-50 minus A-K50(15 day) K-50 JJAS precipitation A-K50(15 day) bias against TRMM K-50 bias against TRMM

  19. Distributions of JJAS-mean all-India rainfall Extra-tropical coupling (red, orange) consistently produces stronger monsoons than tropical coupling (brown) or atmosphere-only (purple, blue). Mean seasonal cycle of all-India rainfall The strongest increases in rainfall come shortly after monsoon onset in June. All other configurations have a delayed and weak monsoon onset.

  20. A-K50(15 day) bias against TRMM and ERA-Int • JJAS means of: • Colours: Precipitation • Vectors: 850-hPa winds • Contours: MSLP K-50 minus A-K50(15 day) A-K50 has a strong cyclonic bias with low MSLP in the West Pacific, both of which are reduced considerably in K-50.

  21. A-K50(15 day) bias against TRMM and ERA-Int • April means of: • Colours: Precipitation • Vectors: 850-hPa winds • Contours: MSLP K-50 minus A-K50(15 day) In April, coupling prevents the erroneous northward migration of the Pacific ITCZ, focusing convection instead on the equator.

  22. A-K50(15 day) bias against TRMM and ERA-Int • May means of: • Colours: Precipitation • Vectors: 850-hPa winds • Contours: MSLP K-50 minus A-K50(15 day) In May, coupling produces a strong extra-tropical Pacific jet and inhibits development of strong rainfall and cyclonic anomalies near the Philippines.

  23. A-K50(15 day) “Wet India” composite A-K50(15 day) “Wet minus dry” K-50 “Wet India” composite K-50 “Wet minus dry”

  24. Summary and conclusions • MetUM-GOML is an ideal framework for examining sensitivities to tropical and extra-tropical coupling. • Heat and salt corrections maintain the observed mean SST. • Allows effects of regional coupling to be isolated in a model with very small SST biases. • The MJO improves with tropical coupling, through better SST—surface-flux—rainfall relationships. • Tropical rainfall biases reduce with extra-tropical coupling, through strengthening the subtropical high and delaying the seasonal progression of the ITCZ.

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