1. An ensemble study of HyMeX IOP6 and IOP7a Alan Hally (1,2), Evelyne Richard (1), Véronique Ducrocq (2) (1)LA, University of Toulouse, France (2)CNRM, Météo-France, Toulouse, France WWOSC2014, 16 th -21 th August 2014, Montreal - Canada

2. Motivations Numerical forecasting of heavy precipitation events (HPEs) has progressed immensely, but accurate and timely precipitation forecast for flash-flood prediction still remains a challenge Initial and boundary conditions have great importance Errors in the parameterisation of physical processes can lead to incorrect descriptions of convection Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties

3. Methodology (1) All simulations undertaken with Meso-NH Initial (IC) and boundary condition (BC) uncertainties investigated using 4 different sets of conditions –Météo-France AROME analyses (2.5km)(Label – AR) –HyMeX-dedicated AROME-WMED analyses (2.5km)(WM) –ECMWF analyses (~16km)(WF) – ARPEGE analyses (10.5km over France)(AP) Ensembles labelled ICBC(6)(7a) depending on the IOP Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties

4. Methodology (2) Perturbations are introduced upon the microphysical time tendencies as follows Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties Microphysical time tendency of any water specie Random multiplication factor Source/sink of microphysical process perturbed Ice Snow Graupel Cloud droplets Raindrops Source and sink of each warm microphysical process perturbed by same factor

5. Methodology (3) r has a value in the range 0.5 – 1.5 for perturbing microphysics and turbulence tendencies Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties Perturbations are introduced upon the turbulent tendency of any state variable X as follows Turbulent time tendency of state variable XRandom multiplication factor Turbulent flux of X Each turbulent flux term perturbed by same perturbing factor

6. Physical process ensembles contained 10 perturbed members + CTRL run The most accurate member of the ICBC ensemble served as CTRL run for physical process ensembles Warm microphysical processes perturbed in ensembles labelled WA(6)(7a) Warm and cold microphysical processes simultaneously perturbed in WC(6)(7a) ensembles Warm and cold microphysical and turbulence processes simultaneously perturbed in MT(6)(7a) ensembles Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties Description of Ensembles

7. Model & Simulation set-up Meso-NH –288 x 288 point grid –2.5km horizontal resolution –4s time step –ICE3 microphysics –1D turbulence (Cuxart et al.) IOP6 –Simulations initialised 23 rd Sept at 18UTC –24 h simulation period IOP7a –Simulations initialised 26 th Sept at 00UTC –24 h simulation period Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties

8. Description of Case Studies – IOP6 On the evening of the 23 rd of September and into the early hours of the 24 th, a trough led to low-level conditions favorable to convection over the SE Massif Central mountains with moderate to weak low-level flow. This instigated an intense and fast-moving convective line, with a convective rainfall peak at 02UTC. Z + T 500hPa (18UTC)θ and winds at 950hPa (18UTC) Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties

9. Description of Case Studies – IOP7a In the early hours of the 26 th of September, a cold front approached Western Mediterranean areas with warm and moist low-level southerly flow ahead of it. Over the target area, a convective system appeared in the early morning peaking at 08UTC in the presence of strong low-level flow. The passing of the front brought a second rainfall peak at 17UTC. Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties Z + T 500hPa (18UTC)θ and winds at 950hPa (18UTC)

10. Results – IOP6 – ICBC Ensemble Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties All simulations displace convective line to the north over the Cévennes. AR the only simulation to simulate rain in the Gard department AR WM WFAP

11. Results – IOP6 – ICBC Ensemble Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties AR most correctly simulates the intensity of the peak. AR also gives the highest spatial correlation and correct standard deviation with the OBS All simulations display a time delay of 3 h with the OBS.

12. Results – IOP6 – Physical Process Ensembles Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties MT6 WC6 WA6 WARM COLD TURBULENCE WARM COLD WARM

13. Results – IOP6 – Physical Process Ensembles Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties MT6 WARM COLD TURBULENCE WC6 WARM COLD WARM WA6

14. Results – IOP7a – ICBC Ensemble Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties Convective Frontal Passage AR WM WFAP All simulations succeed in capturing both convective line and frontal rainfall. WM simulation pushes convective line to the east of observed area. WF simulation over-estimates intensity of convective peak.

15. Results – IOP7a – ICBC Ensemble Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties Both peaks seen by all simulations. AR and WF give highest spatial correlations with the OBS. AR gives most accurate frontal peak. No time delay with the OBS as in IOP6.

16. Results – IOP7a – Physical Process Ensembles Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties MT7a WC7a WA7a WARM COLD TURBULENCE WARM COLD WARM

17. Results – IOP7a – Physical Process Ensembles Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties MT7a WARM COLD TURBULENCE WC7a WARM COLD WARM WA7a

18. Sensitivity to the Different Perturbations Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties WARM COLD TURBULENCE INITIAL AND BOUNDARY CONDITIONS IOP6 IOP7a

19. Conclusions & Perspectives IOP6 (low model skill and moderate to weak low- level flow) more sensitive to physical perturbations than IOP7a (high model skill and strong low-level flow) Dispersion introduced in surface rainfall of ICBC and physical perturbation ensembles comparable when model skill and low-level flow are weak (IOP6) but not when both are high (IOP7a) Results published in NHESS : Hally et al (2014) Perform a similar analysis for less synoptically forced cases Ensemble study of IOP6 and IOP7a: Sensitivity to physical and IC/BC uncertainties

20. Thank You