 |
| Titel |
Heavy precipitation events in the Mediterranean: sensitivity to cloud physics parameterisation uncertainties |
| VerfasserIn |
S. Fresnay, A. Hally, C. Garnaud, E. Richard, D. Lambert |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1561-8633
|
| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 12, no. 8 ; Nr. 12, no. 8 (2012-08-24), S.2671-2688 |
| Datensatznummer |
250011057
|
| Publikation (Nr.) |
 copernicus.org/nhess-12-2671-2012.pdf |
|
|
|
|
|
| Zusammenfassung |
| In autumn, southeastern France is often affected by heavy precipitation
events which may result in damaging flash-floods. The 20 October and
1 November 2008 are two archetypes of the meteorological situations under
which these events occur: an upper-level trough directing a warm and moist
flow from the Mediterranean towards the Cévennes ridge or a quasi
stationary meso-scale convective complex developing over the Rhone valley.
These two types of events exhibit a contrasting level of predictability; the
former being usually better forecast than the latter. Control experiments
performed with the Meso-NH model run with a 2.5 km resolution confirm these
predictability issues. The deterministic forecast of the November case
(Cévennes ridge) is found to be much more skilful than the one for the
October case (Rhone valley). These two contrasting situations are used to
investigate the sensitivity of the model for cloud physics parameterisation
uncertainties. Three 9-member ensembles are constructed. In the first one,
the rain distribution intercept parameter is varied within its range of
allowed values. In the second one, random perturbations are applied to the
rain evaporation rate, whereas in the third one, random perturbations are
simultaneously applied to the cloud autoconversion, rain accretion, and rain
evaporation rates. Results are assessed by comparing the time and space
distribution of the observed and forecasted precipitation. For the Rhone
valley case, it is shown that not one of the ensembles is able to drastically
improve the skill of the forecast. Taylor diagrams indicate that the
microphysical perturbations are more efficient in modulating the rainfall
intensities than in altering their localization. Among the three ensembles,
the multi-process perturbation ensemble is found to yield the largest spread
for most parameters. In contrast, the results of the Cévennes case exhibit
almost no sensitivity to the microphysical perturbations. These
results clearly show that the usefulness of an ensemble prediction system
based upon microphysical perturbations is case dependent. Additional
experiments indicate a greater potential for the multi-process ensemble when
the model resolution is increased to 500 m. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|