Taking into account the gustiness due to free and deep convection for the representation of air-sea fluxes. - in the LMDZ model -

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1 Taking into account the gustiness due to free and deep convection for the representation of air-sea fluxes - in the LMDZ model - Alina Găinuşă-Bogdan, Frédéric Hourdin, Abdoul Traore, Catherine Rio, Jean-Yves Grandpeix, Jean-Louis Dufresne

2 What is gustiness? Small-scale wind variability Subgrid Redelsperger et al. (2000)

3 How can we parameterize gustiness? Free convection: Godfrey&Beljaars (1991): U eff 2 = U (βw * ) 2 Redelsperger et al. (2000): β = 0.65 Deep convection: Redelsperger et al. (2000): U g = 19.8 R R + R 2 4

4 How can we parameterize gustiness? ALE = Available lifting energy

5 How can we parameterize gustiness? Redelsperger et al. (2000): (βw * ) 2 f(r) U eff 2 = U β 2 2ALE BL + α 2ALE WK ALE = Available lifting energy

6 Simulations Old parameterization - contained ad-hoc C H enhancement at low wind speeds under unstable conditions eq.9/miller et al. (1992) No parameterization - de-activation of eq.9/miller et al. (1992) New parameterization - replacement of Miller et al. eq. 9 with full gustiness (BL+WK) 1D case TOGA

7 Simulations Old parameterization - contained ad-hoc C H enhancement at low wind speeds under unstable conditions eq.9/miller et al. (1992) No parameterization - de-activation of eq.9/miller et al. (1992) New parameterization - replacement of Miller et al. eq. 9 with full gustiness (BL+WK) Effective wind speed difference 1D case TOGA

enchancement => no effect on wind stress add proper

8 Results - fluxes none - old new - old The results are what we expect for the wind stress: removing the old C H enchancement => no effect on wind stress add proper gustiness => enhanced wind stress, following effective wind speed evolution

9 Results - fluxes none - old new - old Removing the old parameterization decreases the latent heat flux New parameterization => mostly enhanced latent heat fluxes No clear change of mean sensible heat fluxes in either case, but more variability with the new parameterization

10 Results - fluxes none - old new - old Removing the old parameterization decreases the latent heat flux New parameterization => mostly enhanced latent heat fluxes No clear change of mean sensible heat fluxes in either case, but more variability with the new parameterization...is that really so?

11 Results - fluxes none - old new - old

12 Results - fluxes none - old? new - old

13 Results - fluxes none - old new - old? old parameterization old parameterization no parameterization new parameterization

14 Results - fluxes none - old new - old? old parameterization old parameterization no parameterization new parameterization

15 Conclusions 1D experiments (TOGA) Evaluation of gustiness parameterization global statistics BUT ALSO high-frequency time evolution! (process-oriented diagnostics ideal, but not often possible)

16 Conclusions 1D experiments (TOGA) Evaluation of gustiness parameterization global statistics BUT ALSO high-frequency time evolution! (process-oriented diagnostics ideal, but not often possible) Gustiness => higher, more variable wind stress higher because of effective wind speed, NOT C D (~same mean value, lower variability); more variable simply because it takes both positive and negative values + see above

17 Conclusions 1D experiments (TOGA) Evaluation of gustiness parameterization global statistics BUT ALSO high-frequency time evolution! (process-oriented diagnostics ideal, but not often possible) Gustiness => higher, more variable wind stress higher because of effective wind speed, NOT C D (~same mean value, lower variability); more variable simply because it takes both positive and negative values + see above Gustiness => ~O(25%) higher LH than without (~O(10%) higher than old parameterization); less variability also thanks to direct effect of the effective wind speed C H actually decreases (<> old parameterization, where C H increase is the reason why LH increased compared to no parameterization) q2m increases slightly (O(5%) w.r.t. old, O(10%) w.r.t. none), but systematically

18 Conclusions 1D experiments (TOGA) Evaluation of gustiness parameterization global statistics BUT ALSO high-frequency time evolution! (process-oriented diagnostics ideal, but not often possible) Gustiness => higher, more variable wind stress higher because of effective wind speed, NOT C D (~same mean value, lower variability); more variable simply because it takes both positive and negative values + see above Gustiness => ~O(25%) higher LH than without (~O(10%) higher than old parameterization); less variability also thanks to direct effect of the effective wind speed C H actually decreases (<> old parameterization, where C H increase is the reason why LH increased compared to no parameterization) q2m increases slightly (O(5%) w.r.t. old, O(10%) w.r.t. none), but systematically Gustiness => negligible differences in mean SH; slightly less variability lower CH and ΔT compensate for higher effective wind speed?

19 Results 3D, atmosphere forced with climatological SSTs, 3 years

20 Results 3D, atmosphere forced with climatological SSTs, 3 years

21 Results 3D, atmosphere forced with climatological SSTs, 3 years

22 Results 3D, atmosphere forced with climatological SSTs, 3 years

23 Results 3D, atmosphere forced with climatological SSTs, 3 years

24 Results 3D, atmosphere forced with climatological SSTs, 3 years

25 Results 3D, coupled ocean-atmosphere model, 3 years

26 Conclusionsts 3D tests Gustiness doesn t only affect the tropics! Thank you!

27 How important is gustiness? Free convection: Godfrey&Beljaars (1991): At low wind speeds, quite! U eff 2 = U (βw * ) 2 Redelsperger et al. (2000): β = 0.65 Deep convection: Redelsperger et al. (2000): U g = 19.8 R R + R 2 4

28 How important is gustiness? Wind stress At low wind speeds, quite! Latent heat flux Sensible heat flux

29 What can we use for development? 1D case TOGA The TOGA-COARE campaign: Nov. 1 st, 1992 Feb. 28, 1993 Succession of active and suppressed convection events

30 How do we parameterize gustiness? U eff 2 = U β 2 2ALE BL + α 2ALE WK

31 How do we parameterize gustiness? U eff 2 = U β 2 2ALE BL + α 2ALE WK Scalar mean of the wind speed (Redelsperger et al., 2000) = U 0 + resolved deep convection gustiness Magnitude of the mean vector wind (Redelsperger et al., 2000) = U 0 U 0, CTRL + BL gust + WK gust U 0, CTRL + BL gust U 0, CTRL + WK gust Magnitude of the mean vector wind = U 0, CTRL comparable magnitudes lower gustiness for U 0 peaks, higher for low U 0 wind enhancement higher in Dec than Dec 1992

32 How do we parameterize gustiness? U eff 2 = U β 2 2ALE BL + α 2ALE WK Horizontal wind speed deep convection gustiness Scalar mean of the wind speed (Redelsperger et al., 2000) = U 0 + resolved deep convection gustiness Magnitude of the mean vector wind (Redelsperger et al., 2000) = U 0 Magnitude of the mean vector wind = U 0, OBS Magnitude of the mean vector wind = U 0, CTRL

33 Results 3D gustiness and turbulent exchange coefficients AMIP CPL

34 Results 3D - Precipitation AMIP CPL

35 Results 3D - Precipitation

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