COSMO Priority Project ’Tackle deficiencies in quantitative precipitation forecasts’

1. COSMO Priority Project ’Tackle deficiencies in quantitative precipitation forecasts’ S. Dierer1, M. Arpagaus1, U. Damrath2, A. Seifert2, J. Achimowicz8, E. Avgoustoglou7, M. Baldauf2, R. Dumitrache9, V. Fragkouli7, F. Grazzini3, P. Louka7, P. Mercogliano6, P. Mezzasalma3,M. Milelli4, D. Mironov2, A. Morgillo3, E. Oberto4, A. Parodi5, I.V. Pescaru9, U. Pflüger2, A. Sanna4, F. Schubiger1, K. Starosta8, M. S. Tesini3 1MeteoSwiss (CH), 2DWD (D), 3ARPA-ER (IT), 4ARPA-P (IT), 5Uni Genova (IT), 6CIRA-CMCC (IT), 7HNMS (GR), 8IMGW (PO), 9NMA (RO) 29th EWGLAM Meeting, 9 October 2007, Dubrovnic

2. Aim of PP QPF Good quantitative precipitation forecast is a challenging task – also for the COSMO model: • The aim of PP QPF is improved knowledge about • most suitable namelist settings or • parts of the model that need to be reformulated • to obtain a better QPF at 7 km horizontal grid size The project has a focus on model deficiencies – not on errors from e.g. initial and large scale conditions

3. Overview of PP QPF • Task 1: Selection of test cases representative for „typical“ QPF deficiencies of COSMO model • Task 2: Definition of sensitivity studies • Task 3: Run sensitivity studies and draw conclusions

4. List of test cases from all countries

5. Forecast errors • 10 cases of stratiform overestimation (8 from D, CH and PO) • 4 cases of stratiform underestimation • 3 cases of convective overestimation • 7 cases of convective underestimation (6 from I and GR)

6. Sensitivity studies • 1. Changes of initial conditions • 2. Changes of numerical methods • 3.1 Changes of microphysics • 3.2 Changes of convection schemes • 3.3 Changes of PBL schemes

7. Sensitivity studies: initial conditions • Soil moisture increased/decreased by 20% • Initial humidity increased/decreased by 10%

8. Sensitivity studies: numerical methods • Halved time step • Leapfrog, tri-cubic semi-Lagrange advection of QR and QS • Runge-Kutta, tri-cubic semi-Lagrange advection of QV, QC, QI, QR and QS • Runge-Kutta, flux-form advection of QV, QC, QI, QR and QS • Runge-Kutta, flux form advection and T’-p’ dynamics • increased orography filtering

9. Sensitivity studies: physics 1 - microphysics • New warm rain scheme (Seifert and Beheng; 2001) • Strong changes of ice microphysics and new warm rain scheme • Moderate changes of ice microphysics and new warm rain scheme

10. Sensitivity studies: physics 2 –convection • Modified Tiedtke scheme • Kain-Fritsch/Bechtold scheme • No parameterization of deep convection

11. Sensitivity studies: physics 3 – PBL • Decreased/increased scaling factor of height of laminar boundary layer for heat • Decreased/increased stomatal resistance • Decreased/increased laminar scaling factor for heat over sea

12. Relative change of 24h area average precipitation, first forecast day (06 – 30) Convection scheme Snow microphysics Runge-Kutta Δrel = (rrexp–rrref)/rrref Initial humidity Cases Vertical heat/moisture exchange Romanian { Polish{ Greek { Ital.(EuroLM){ Ital. (LAMI){ Swiss{ Δrr > +30% +10% < Δrr <+30% 0% < Δrr < +10% Δrr = 0% 0% > Δrr > -10% -10% > Δrr > -30% Δrr < -30% German{ rlam01 sto50 sea01 ws80 dt20 RKsl RKtp micro1 micro2 qv90 conmod ws120 qv110 RKbott micro3 conoff rlam50 sto250 sea40 LFsl oro kfb

13. Relative change of 24h area average precipitation RK RLAM QV0 MP CON Δrel = (rrexp–rrref)/rrref  Δrel  | Δrel |

14. Change of bias between simulated and measured area average precipitation overestimation underestimation stratiform bias > 200% 100% < bias <200% bias = 100% 100% > bias > 50% bias < 50% convective convection Initial humidity Runge-Kutta snow microphysics

15. Conclusions until now … • Strongest effect (5-40%) on area average precipitation by: • Initial humidity • Runge-Kutta • microphysics • convection scheme • Strong effect for Roman and Greek cases • Vertical heat/moisture exchange (extreme change of RLAM) • Runge-Kutta • reduces mean precipitation in most of the cases • and has an overall positive effect on the results • None of the studies completely solves a QPF problem, but some give a significant improvement for single cases like • changes of snow microphysics for a case with overestimation of stratiform precipitation • Kain-Fritsch/Bechtold for underestimated convective precipitation

16. Cross experiments

17. Relative change of area average precipitation in cross experiments compared to control simulation Δrr > +30% +10% < Δrr <+30% 0% < Δrr < +10% Δrr = 0% 0% > Δrr > -10% -10% > Δrr > -30% Δrr < -30%

18. Bias of reference run and cross experiments M-Swiss Italy HNMS IMGW NMA DWD

19. Relative bias of cross experiments M-Swiss Italy HNMS IMGW NMA DWD

20. Improvement of area average precipitation in numbers… • 17 cases improved by one of the studies: COSMO4.0+ • KFB: 5 cases (3C- / 2S+) • QV90+RK+Tiedtkemod : 3 cases • QV90+RK+KFB : 3 cases • -/Tiedtkemod/RK+QV90: 2 cases • 7 cases hardly affected or worse (5C-) } 8S+/3S-

21. Conclusions • COSMO4.0+ • reduced initial humidity • modified convection • Runge-Kutta • has a positive impact on stratiform overestimation • little or negative impact on convective underestimation • Few cases are “solved” • COSMO Version 4.0 is a step forward! • Further improvements expected from Runge-Kutta. • We should have a closer look at the (initial) humidity fields. – Any improvements in data assimilation expected? • Convection schemes are the next thing to look at. • Draft of a final report has been written and will be revised based on the discussion of PP QPF sessions in Athens and will be available in the next weeks • publication of results planned until end of the year