1. Effects of large-scale nudging on fine-scale variability in a regional climate model
Leo Separovic, Ramón de Elía, René Laprise and Adelina Alexandru
CRCMD Network Workshop 2008, Estérel, QC

2. Is RCM a “magnifying glass”?
Internal variability (IV)
- nudging of large scales in RCM ensemble simulations helps to reduce inter-member variance. But, how much this variance is reduced in the range of fine scales that are not resolved by the driving fields?
Generation of fine scales
IV is a fundamental property of the atmosphere. It has been suggested that IV in RCMs might be necessary for a proper generation of fine scale details.

3. Definition of reproducibility ratio
(i) Decompose members xm in ensemble average <x> and ensemble deviations xm*.
(ii) Compute transient-eddy variances 2 of
-ensemble average <x>
-members’ deviations xm*.
Then transient-eddy variance can be decomposed as:
REPRODUCIBLE
PART
IRREPRODUCIBLE
AVERAGE
TRANSIENT-EDDY
VARIANCE
Reproducibility ratio is defined as reproducible part of the left-hand side in %,
(it quantifies internal variability)

4. Reproducibility of fine scales’ transient-eddy variance
Large scales (resolved by NCEP driving fields) are filtered out from model variables
Here a spectral filter based on DCT is employed.
Example - vorticity at 925 hPa
without SN
SN850

5. Scale analysis of reproducibility
Analogous decomposition can be performed on spectral variances (power spectra).
time and ensemble average of the spectral power for vorticity at 850 hPa for the simulation without LSN on 120x120-domain
spectrum computed on 80x80-control domain;
NCEP time-averaged power also shown:

6. Scale analysis of reproducibility
Analogous decomposition can be performed on spectral variances (power spectra).
time and ensemble average of the spectral power for vorticity at 850 hPa for the simulation without LSN on 120x120-domain
spectrum computed on 80x80-control domain;
NCEP time-averaged power also shown:

7. Set-up
Alexandru et al. (2008)

8. Reproducibility ratio of transient eddies as function of scale, domain size and nudging intensity
RVORT 850 hPa
Spectral reproducibility ratio computed for various configurations on a common domain of 80x80 points.
Even with completely prescribed large scales (full SN) internal variability still present below 600km!

9. Impact of different SN configurations on power spectra
spectral power of various configurations normalized by the “control” which appears as a black solid horizontal line at 100.
Control: without SN on the 120x120-domain.

10. 6-hourly precipitation histograms
frequencies gathered in each of two areas of low reproducibility with 20x20=400 sampling grid points, 369 time steps, x15 members of ensemble:
Continent
Ocean
weak i.var.
strong i.var.
RVORT 850hPa

11. 6-hourly precipitation histograms
120x120 Domain: SN-free vs. SN-850
400 grid points
25 grid points
25 grid points

12. Summary
LSN appears to influence tails of 6h precipitation frequency distributions. The prevailing feature is shorter and weaker tails when LSN is strong.
Longer time series needed.
Long wavelengths appear to have on average overestimated amplitudes at lower levels in CRCM simulations, and LSN reduces this overestimation.
The configuration with 850 hPa-SN shows a decrease in spectral variance in all wavelengths except in the range from 200 to 400 km where it is comparable with the configuration without SN.
When full-SN is applied, a very important decrease in spectral variance affects all wavelengths.

13. 6-hourly precipitation frequency distributions: CONTINENT