The effect of indiscriminate nudging time in regional climate modeling of the Mediterranean basin

1. The effect of indiscriminate nudging time in regional climate modeling of the Mediterranean basin Tamara Salameh, Philippe Drobinski, Thomas Dubos and Hiba Omrani Laboratoire de Météorologie Dynamique/Ecole Polytechnique,

2. General context 1,2 0,8 0,4 0 -0,4 -0,8 By J.L. Dufresne CNRM IPSL Global climate change  Global climate models agree on: • A decrease in precipitation rate (mm/j) for scenario A1B (21st century) • Increase in extreme cold temperature • Increase in extreme precipitation (Goubanova and Li 2006) Need to know as precise as possible future climate conditions at regional scales (city, valley,…) Tamara Salameh 1/13

3. General context • Important needs in water and energy • Understanding the Mediterranean regional climate has environmental, economical and societal implications • Coupled system (ocean-atmosphere-hydrology) • Strong topographic component that induces extreme events Strong scales interaction Tamara Salameh 2/13

4. Regional dynamical modeling of the atmospheric circulation over the Mediterranean basin • Brief state of the art • Consists on forcing a regional model (limited area model, RCM) by a GCM, generally to ameliorate the realism of the modeled fields (Mass et al., 2002) • Sensitivity studies on initial and boundary conditions of the GCM (forcing resolution, frequency of update of boundary conditions), physical parameterization of the RCM (Bhaskaran et al., 1996; Seth et Giorgi, 1998; Noguer et al., 1998; Denis et al., 2002, 2003)  impact on the RCM results • High-cost calculation method but transferrable from region to another • For long regional runs, periodic reinitilization gives better results (scores) than the continuous regional run (Qian et al. 2003; Lo and Yang, 2008)  affect the temporel variability  alternative solution: nudging the RCM fields to the GCM fields (relatively less considered in the literature): 2 nudging types: temporal (Salameh et al., en révision) and spectral (Von Storch et al., 2000), both need adjustment of constants Tamara Salameh 3/13

5. Regional dynamical modeling of the atmospheric circulation over the Mediterranean basin 1 Problem: relaxing the fields of the RCM to those of the GCM by adding to the conservation equations a relaxation term to the large-scale forcing variables Challenge: evaluation of the impact of nudging on the physical processes at all scales and evaluation of the existence of an optimal nudging time that minimizes the total error committed on the large and small scales Simplified approach, one dimension, linear Example: equation to resolve for a linear approach 1D (e.g. q = PV) Small-scale source (e.g. convection, relief) The GCM problem Stationary answer to the large-scale forcing General solution Tamara Salameh 4/13

6. Regional dynamical modeling of the atmospheric circulation over the Mediterranean basin 2 1 3 Numerical diffusion induced by the discretization of conservation equations Relaxation time to the large-scale qls Problem: relaxing the fields of the RCM to those of the GCM by adding to the conservation equations a relaxation term to the large-scale forcing variables Challenge: evaluation of the impact of nudging on the physical processes at all scales and evaluation of the existence of an optimal nudging time that minimizes the total error committed on the large and small scales Simplified approach, one dimension, linear Example: equation to resolve for a linear approach 1D (e.g. q = PV) Approached equation resolved by the RCM Small-scale source (e.g. convection, relief) The GCM problem In the Fourier space Stationary answer to the large-scale forcing General solution Tamara Salameh 4/13

7. Regional dynamical modeling of the atmospheric circulation over the Mediterranean basin Exact solution Total error Large-scale error The real variability of the large-scale flow Exact solution: and Knum 0 Objective: determination of an optimal nudging time that minimizes the total error committed on the large and small scales (if it exists) The regional solution: Contribution of the small-scale Contribution of the large-scale Small-scale error Optimal nudging time minimizing the total error Tamara Salameh 5/13

8. Regional dynamical modeling of the atmospheric circulation over the Mediterranean basin Mean wind (MM5: Nov-Dec. 1998*) Real RCM’s approach =1h =2h MM5 simulations all indentic except of the nudging time =4h =3h =5h =6h Weak impact on mean wind field at 10 m but strong impact on the wind variability =12h = * Year rich in Mistral events and dense water formation Tamara Salameh 6/13

9. Regional dynamical modeling of the atmospheric circulation over the Mediterranean basin =1h =2h =1h =2h =3h =4h =3h =4h =5h =5h =6h =6h = =12h = =12h Stability of wind direction Variability of wind speed This variability has very strong impact on precipitation and extreme wind Tamara Salameh 7/13

10. Regional dynamical modeling of the atmospheric circulation over the Mediterranean basin qr=potential vorticity (PV) =1h =2h ||qls|| is the variance for  = 0 ; =3h =4h The cutoff frequency Kc = π/Δx (resolution of ERA-40) =5h =6h = =12h ||qss|| is the variance for  =  Tamara Salameh 9/13

11. Regional dynamical modeling of the atmospheric circulation over the Mediterranean basin Domination of the diffusion: Linear model ~ OK Diffusion+contribution of non linear processes: Linear model not OK Evolution of the variance dominated by the development of fine-scale structures : linear model ~ OK Tamara Salameh 10/13

12. Regional dynamical modeling of the atmospheric circulation over the Mediterranean basin Domination of the diffusion: Linear model ~ OK Diffusion+contribution of non linear processes: Linear model not OK Evolution of the variance dominated by the development of fine-scale structures : linear model ~ OK num = 10h ss = 1h Robust estimation Tamara Salameh 10/13

13. Regional dynamical modeling of the atmospheric circulation over the Mediterranean basin • Conclusions: • Strong impact of nudging on dynamical regionalization: variability of surface wind  precipitation and wind extremes • Simplified linear one dimension model • Existence of an optimal nudging time • Existence of two characteristic time scales : et • Impact of nudging on the small-scale in MM5 ~ linear model Tamara Salameh 13/13

14. Application to regional climate simulations conducted with WRF WRF forced by IPSL CM4 (LMDZ outputs) used for IPCC AR4 Wintertime periods (November to March) 1861-1871 and 1990-2000 60 km spatial resolution Tamara Salameh 11/13

15. Application to regional climate simulations conducted with WRF 1990-2000 Sim-obs CRU 0.5° (1990_2000) 1990_2000 -1861_1871 • The impact of nudging is not uniform over the domain • Nudging produces better results • The difference in averaged temperature between 1990-2000 and 1861-1871 is positive over all the domain • Increase in the precipitation rate over mountains and decreases everywhere else • WRF tends to over-estimate precipitation over the domain • Nudging produces more precipitation over the eastern basin and less over mountains No nudging Nudging time = 6 h Nudged simulation – no nudging simulation Tamara Salameh 12/13

16. The end!!!! Thank you for your attention!! Tamara Salameh

17. Regional dynamical modeling of the atmospheric circulation over the Mediterranean basin Précipitations Extreme wind (>15 m s-1) =1h =2h =1h =2h =4h =3h =3h =4h =5h =6h =5h =6h Coherent result with Lo et al. 2008 on the necessity of nudging to ameliorate precipitation =12h = = =12h Tamara Salameh 8/13