High-resolution modelling in mountainous areas: MAP results

1
High-resolution modelling in mountainous
areasMAP results

• Evelyne Richard
• Laboratoire dAérologie
• CNRS / Univ. Paul Sabatier
• Toulouse, France

2
What are the skills of high-resolution models to
forecast orographically influenced
precipitation? Does explicit (versus
parameterized) convection lead to a gain in
predictability?
IOP 2a 17 September 1999 A short, intense,
isolated, convective event 70 mm within 12 hours
Sensitivity experiments performed with Meso-NH
3
MAP IOP 2a IR Meteosat
4
MAP target area
5
MAP IOP 2A
Composite radar reflectivity _at_ z 2km
1800 UT
1900 UT
2000 UT
250 km
2200 UT
2300 UT
2100 UT
6
Observation
Simulation (?x 2km)
Toce Ticino watershed
2000 UT
2300 UT
Reflectivity _at_ 2000m
7
RADAR
SIMULATION
12 hour accumulated precipitation
8
Composite radar reflectivity _at_ z 2km
1700 UT
1800 UT
250 km
1900 UT
2000 UT
9
Radar Retrieval (S-Pol)
Simulation (Meso-NH)
1800 UT
12 km
1900 UT
2000 UT
(x) hail graupel
graupel
hail
(o) hail
rain
rain
100 km
10
Great ! My model is doing a good job
11
MAP - IOP2A Intense Convection Strong
sensitivity to initial state Low
predictability
12
IOP 2a
ANA. OP. 1999
REANA E9MI
850hPa water vapor mixing ratio 17 September
1999 12UTC
13
IOP 2a
850hPa water vapor mixing ratio 17 September
1999 12UTC
14
Lascaux et al., 2004
MAP IOP 2a
Streamlines at 1000 m, 17/09/99 12 UTC
ECMWF ANALYSIS
MAP ECMWF REANALYSIS
Low-level convergence between the Ligurian and
Adriatic flows
Increase in the model resolution -gt higher
mountains -gt the Ligurian flow is blocked
15
Prectitability ? Still a long way to go !
16
How do the models compare with each other ?
IOP2b 20/21 September 1999 Orographic
enhancement of a frontal system 200 mm within
30h Model intercomparison MC2, MM5,
MOLOCH, Meso-NH
17
19 Sept. 1999 1200
20 Sept. 1999 1200
METEOSAT infrared
18
Sensitivity to the analysis
ECMWF Op. Analysis MAP Reanalysis
Max 512 mm Max 482 mm Mean 78 mm Mean
87 mm
19
The different models

• MESO-NH 10 KM 2.5 KM
• MOLOCH 10 KM 2 KM
• MM5-RE 27 KM 9 KM 3 KM
• MM5-E1 18 KM 6 KM 2 KM
• MC2 40 KM 10 KM 2 KM

Initial and boundary conditions from ECMWF
operational analyses From 19 Sep. 12 UTC to 20
Sep. 18 UTC (30 hours)
20
Toce-Ticino watershed
MAP - IOP2B - 19-20 Sep. 1999 Intercomparison
exercise 4 non-hydrostatic models with horizontal
resolution of 2 to 3 km Initialization based upon
ECMWF operational analysis Accumulated
precipitation from the 19th 15 UTC to the 20th
18UTC
21
(No Transcript)
22
Time evolution of the mean hourly precipitation
rate
Rain gauges
Radar
23
Time evolution of the correlation coeffecient
(wrt rain gauges)
24
Heidke skill scores as a function of precip. class
1h precip.
27h precip.
25
Comparison with rain gauge measurements (121
points)
26
Hydrological response
Toce watershed 1532 km2
27
Grossi et al., 2004
28
Grossi et al., 2004
29
How does the flow over complex terrain modify the
growth mechanisms of precipitation particles?

• Three Doppler radars
• Monte Lema Ronsard S Pol
• Dual Doppler analysis
• 3D wind fields rerievals
• Microphysical retrievals

Monte Lema
S Pol
Ronsard
30
Blocked and stable case
dry snow
U/Nh lt 1
wet snow
light rain
Unblocked and unstable case
graupel
riming
U/Nh gt 1
coalescence
heavy rain
Medina and Houze, 2003
31
To what extend the models able to reproduce this
contrasted behaviour in the microphysics ?
32
Mean vertical distribution of the hydrometeors
33
Dominant microphysical processes
IOP2a
IOP8
MELTING-CONVERSION of the snow (into graupel)
ACCRETION of cloud droplets by raindrops
Growth of graupel by RIMING
DEPOSITION on ice (and sublimation)
AUTOCONVERSION of pristine ice
Depletion of graupel by WET GROWTH of hail
34

• Conclusion
• IOP 2A (Predictability)
• The use of non-hydrostatic high-resolution models
  will improve the precipitation forecast but only
  to some extend.
• Further improvement is tied to the improvement of
  the model initial state
• Adding mesoscale data in a global assimilation
  system is insufficient
• Mesoscale data assimilation system
• Limited area ensemble forecast
• (MAP D-PHASE)

35

• IOP 2b (Model Intercomparison)
• Very good consistency of the accumulated
  precipitation pattern
• Model results over/under estimate the total
  precipitation by a factor ranging from 30 to
  -30
• The accuracy of the model precipitation is rather
  weak for the hourly rainfall but fairly
  reasonable for the precipitation accumulated over
  the 30h time period of the event
• However model results are not yet accurate enough
  to be used for hydrological forecast on small
  watersheds

36

• Explicit microphysical schemes do provide fairly
  realistic results
• The contrasted microphysical behaviour between
  different IOPs is reasonably reproduced
• Convective flow over ----gt
• Strong riming and coalescence
• Stratiform blocked flow ----gt
• Melting of snow

37
http//www.aero.obs-mip.fr/map/MAP_wgnum
N. Asencio (2), R. Benoit (3), A. Buzzi (4), R.
Ferretti (5), F. Lascaux (1), P. Malguzzi (4),
S. Serafin (6), G. Zängl (7), J-F. Georgis (1),
R. Ranzi (8), G. Grossi (8), N. Kouwen (9)
(1) LA CNRS/UPS, Toulouse, France (2) CNRM,
Météo-France, Toulouse, France (3) RPN, Montréal,
Canada (4) ISAC, CNR, Bologna, Italy (5)
University of L Aquila, Italy (6) University of
Milano, Italy (7) University of Munich,
Germany (8) University of Brescia, Italy (9)
University of Waterloo, Canada