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

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

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

8. GEM, Observed & Corrected-Observed
Mean Annual Cycle ( )
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. X10 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 mean
Observations and GEM-LAM 0.45º
X10
mm/day

11. Fraction of total precipitation over a given region coming from each
daily intensity bin, average for
SE USA DJF fraction of total precipitation from a given intensity band Observations and GEM-LAM 0.45º
mm/day

12. Absolute amount of precipitation (in mm/day) averaged over a given region coming from each daily intensity bin, mean for
e.g. SE USA absolute amount of precipitation from a given intensity band Observations and GEM-LAM 0.45º
mm/day

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

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

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

17. X10
NW JJA ( 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
mm/day
mm/day

19. Central USA (CNTR) JJA 0.45º 1964-1998 mean Do things improve at
Same occurrence underestimate
across all classes
Underestimate of precipitation
in all intensity bands in CNTR
X10
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?
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)NW
CNTR SE

24. JJA cumulative precipitation distributions by resolution (93-94)NW
CNTR 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 mean
Some modest improvement with increasing resolution in the NW (mountainous) region. Improved topographic forcing ?
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.
mm/day
Even at higher resolution all precipitation classes are underestimated in CNTR JJA except very intense classes which are overestimated.