Simulating daily precipitation variability. Is there any benefit from increased resolution ?

1. Simulating daily precipitation variability. Is there any benefit from increased resolution ? Colin Jones1, Samuel Girard1 and Katja Winger1,2 1CRCMD/UQAM 2Environment Canada Email : jones.colin@uqam.ca

2. There is a common held view that the number of wet days will decrease in future climate conditions, while the number or intensity of extreme precipitation events will increase. These contentions arise mainly from precipitation changes simulated by Coupled GCMs and RCMs for the future climate. Although observations suggest this trend can be somewhat seen for the recent past decades. An obvious question is whether a given Climate Model can simulate present-day observed (daily) precipitation variability (Number of wet-days, No. & intensity of extreme wet-days Does increased resolution improve a models ability to simulate high time frequency precipitation variability ?

3. Run a Limited-Area version of GEM over North America forced by ‘’perfect’’ analysed boundary conditions and ask how well it simulates observed daily mean precipitation variability. • Compare 0.45 simulations for the period 1964-1998 to NCEP • gauge based 0.25ºdaily precipitation accumulations for USA

4. Higher resolution may improve simulated precipitation variability Improved topographic forcing ? Better resolution of convection-dynamical interaction/organisation ? 2.Analyse 3 GEM-LAM runs at 0.45º, 0.33º & 0.15º for the period 1993 and 1994 (all runs identical with Kain-Fritsch convection scheme)

6. Mean Annual Cycle (1964-1998) GEM,Observed & Corrected-Observed NW CNTR SE Corrections for wind effects & evaporation losses due to Ungersbock et al. 2003. NW winter season accurate NW Summer season dry bias

7. Mean Annual Cycle (1964-1998) GEM,Observed & Corrected-Observed NW CNTR SE CNTR winter ppt accurate CNTR LARGE summer season dry bias: 50% underestimate of mean JAS precipitation

8. Mean Annual Cycle (1964-1998) GEM,Observed & Corrected-Observed NW CNTR SE SE winter season dry bias SE summer season accurate

9. How is the monthly/seasonal mean precipitation distributed in terms of the underlying daily mean intensities ? Can GEM-LAM simulate this distribution ?

10. Fraction of total number of days in a given season for 1964-1998 mean that experience precipitation in a given daily accumulation bin e.g. SE USA Fraction of events per intensity band DJF 1964-1998 mean Observations and GEM-LAM 0.45º X10 0 0.25 1 2 5 10 20 50 100 mm/day

11. Fraction of total precipitation over a given region coming from each daily intensity bin, average for 1964-1998. SE USA DJF fraction of total precipitation from a given intensity band Observations and GEM-LAM 0.45º 0 0.25 1 2 5 10 20 50 100 mm/day

12. Absolute amount of precipitation (in mm/day) averaged over a given region coming from each daily intensity bin, mean for 1964-1998. e.g. SE USA absolute amount of precipitation from a given intensity band Observations and GEM-LAM 0.45º 0 0.25 1 2 5 10 20 50 100 mm/day

13. Cumulative intensity curves of total precipitation as a function of intensity class for a given region averaged over 1964-1998. e.g. SE USA DJF : Observations and GEM-LAM 0.45º

14. Cumulative intensity curves of total precipitation as a function of intensity class for a given region averaged over 1964-1998. e.g. SE USA DJF : Observations and GEM-LAM 0.45º

15. X10 NW JJA (0.45º 1964-1998 mean) Fraction of events per intensity band: Too many dry days. Too few wet days.

16. X10 NW JJA (0.45º 1964-1998 mean) Fraction of total precipitation from each intensity band: Distribution quite accurate

17. X10 NW JJA (0.45 1964-1998 mean) Absolute amount of precipitation from each intensity band: Significant underestimate for all bands due to underestimate of occurrence.

18. Central USA (CNTR) JJA 0.45º 1964-1998 mean Same occurrence underestimate across all classes Underestimate of precipitation in all intensity bands in CNTR X10 0 0.25 1 2 5 10 20 50 100 mm/day 0 0.25 1 2 5 10 20 50 100 mm/day

19. Central USA (CNTR) JJA 0.45º 1964-1998 mean Same occurrence underestimate across all classes Underestimate of precipitation in all intensity bands in CNTR X10 0 0.25 1 2 5 10 20 50 100 mm/day Problems in triggering convection and maintenance of intense and organised convection are prime candidates causing these errors Do things improve at higher resolution? 0 0.25 1 2 5 10 20 50 100 mm/day

20. NW JJA Some modest improvement with increasing resolution in the NW (mountainous) region. Improved topographic forcing ? 11% 25% The number of intense days (>20mm/day) increases too much with increasing resolution

21. Central USA (CNTR) JJA Some very modest improvement at 0.33º resolution, largely Lost again at 0.15º resolution. Convection in CNTR region is not topographically forced. Even at higher resolution all precipitation classes are underestimated in CNTR JJA except very intense classes which are overestimated.

22. DJF cumulative precipitation distributions by resolution (93-94) NW CNTR SE

23. JJA cumulative precipitation distributions by resolution (93-94) CNTR NW SE

24. JJA cumulative precipitation distributions by resolution (93-94) CNTR NW SE

25. Summary Winter season precipitation variability is fairly well simulated by GEM at 0.45º. This remains true at higher resolutions. Summer precipitation is less accurate with an underestimate of occurrence across all intensity classes, especially higher intensity days Resolution helps a little in regions of topographic forcing: NW Resolution does not help in regions where convection is not topographically forced (Central North America). A more fundamental (convection) parameterisation problem. Very intense precipitation events (≥50 mm/day) become too frequent as resolution is increased.

26. Summary Winter season precipitation variability is fairly well simulated by GEM at 0.45º. This remains true at higher resolutions. Summer precipitation is less accurate with an underestimate of occurrence across all intensity classes, especially higher intensity days Resolution helps a little in regions of topographic forcing: NW Resolution does not help in regions where convection is not topographically forced (Central North America). A more fundamental (convection) parameterisation problem. Very intense precipitation events (≥50 mm/day) become too frequent as resolution is increased. Can we simulate summer daily precipitation variability at resolutions that require convective parameterisations ??? What can we do to make progress ??

27. Look at other models in a variety of summer season precipitation regimes. Is the problem universal? Can we find pointers in other models how to improve summer season convection in GEM ? This is why we perform model intercomparisons e.g. ICTS-CEOP

28. Run multi-nested models, with the interior model convection-resolving. compare convection-parameterising and convection-resolving domains to try to get pointers for improving the lower resolution simulations

29. NW JJA 1993-1994 mean Some modest improvement with increasing resolution in the NW (mountainous) region. Improved topographic forcing ? 0 0.25 1 2 5 10 20 50 100 mm/day But the number of intense days (>20mm/day) increases too much with increasing resolution

30. Central USA (CNTR) JJA 1993-1994 mean Some very modest improvement at 0.33º, which is lost at 0.15º Convection in CNTR region is not topographically forced. 0 0.25 1 2 5 10 20 50 100 mm/day Even at higher resolution all precipitation classes are underestimated in CNTR JJA except very intense classes which are overestimated.