Campaign data for parameterization tests: Examples from MAP‘99VERTIKATOR’02, AWIATOR‘03
Hans Volkert, Thorsten Fehr, Christoph Kiemle,
Oliver Reitebuch, Arnold Tafferner and Martin Weißmann
DLR Oberpfaffenhofen, DInstitut für Physik der Atmosphäre
Evelyne RichardLaboratoire d‘Aérologie, CNRS & Université Paul Sabatier Toulouse, F
“Whenever possible, parameterizations should … be quantitatively validated against observations“ (Peixoto & Oort 1991)
Textbook knowledge:
High resolution …… simulation models need special data,
e.g from dedicated field campaigns
here: wind,boundary layer, precipitation microphysics
Which variables and processes?
The campaigns MAP-SOP 1999 Mesoscale Alpine Programme
Special Observing Period„Weather and Alps“ 7 Sept. – 15 Nov 1999
cf. Bougeault et al. 2001, BAMS 82, 433–462
wind QJ, Jan. 2003 B (No. 588), 129, 341-895 VERTIKATOR-02 Vertikaler Austausch, Trans- port und Orographie„Alpine Pumping“ July 2002, north of the Alps wind & precipitation AWIATOR-03 Wake Vortices at airports„Wake Vortex“ Aug. 2003, north of Pyrénées wind
MAP-SOP 1999
IOP-15 8 Nov.
north Föhn with waves
•
•
•
Rhone
Aosta
(model) orography (x=1 km)
1.67–2.00
km
aircraft triptych: B-A-C-D , 8 Nov. 1999
L
North Föhn
8 Nov. 1999
ARPEGE ana. 12 UT
500 hPa: flow (max. 30 m/s) geopot. (=40 gpm)
model: Meso-NH with four nests (32, 8, 2, 0.5 km)
Drop-sounding: uniform wind direction
ff
dd
T
rh
dry
moist
Three drop-sondes in 2mins.: reproducibility
130355
130455
130555
vertical velocity: trans-Alpine sections
Rhone
Aosta
Rhone
Valtellina
ob
s
obs+
sim(--)
F C E
+2
-2
18
legs
4 legs
10
legs
vertical velocity: 2 & 1/2 km simulation
2 km
½ km
Rhone
Valtellina
Rhone
Aosta
F C E
+2
-2
water vapour triptych: lidar-obs. vs. simulation
100
350
100
350
w(C130)
mean diff. < 10% --> backs retrieval (s.p.=0.7)
sim.
obs.
100 ppmv 200
VERTIKATOR 2002
8, 9, 19 July
Alpine pumping &generation of
thunderstorms
10 µm-System WINDDLR/CNRS/CNES/Meteo-Francevert. res. 250 mhor. res. 3 - 15 kmaccuracy 0.5 - 2 m/s
2 µm-SystemDLR/CTI-MAG1100 m3 - 10 km0.2 - 2 m/s
Airborne Doppler Lidar at DLR
Flight Track Falcon 8 July 2002
13:05 - 15:34 LT
Data processing with averaging 3 scanner revolutions: 10 - 11 km
12.0
0.0
1.5
3.0
4.5
6.0
7.5
9.0
10.5
6.0
0.0
1.0
2.0
3.0
4.0
5.0
altitude [km ASL] wind speed [m/s]
360
0
45
90
180
270
315
6.0
0.0
1.0
2.0
3.0
4.0
5.0
2000 20 40 60 80 100 120 140 160 180
altitude [km ASL] wind direction [deg]
distance [km]
east-westgradient in speed(> 4 km)
southwest
northerly winds along the Alps up to 2.3 km
WIND July 8, 2002, 14:10 - 14:27 LTTrack Bodensee Chiemsee
wind speed below 4 m/s(< 2.5 km)
MM5 by L. Gantner,Uni München
12
0
2
4567
910
6.0
0.0
1.0
2.0
3.0
4.0
5.0
2000 25 50 75 100 125 150 175
altitude [km ASL] wind speed [m/s]
360
0
45
90120
180
220
270300330
6.0
0.0
1.0
2.0
3.0
4.0
5.0
2000 25 50 75 100 125 150 175
altitude [km ASL] wind direction [deg]
distance [km]distance [km]
WIND and MM5 on July 8, 2002 Track Bodensee ChiemseeWIND: top, 14:10 - 14:27 LT; MM5: bottom, 14:00 LT
19 July: 2µm Lidar and vertical velocity
shallow
medium
steep
40 km
9 July:Bistatic
Doppler andpolarimetric
radar
steep
shallow
medium 12 min
later ...
shallow
medium
steep
12:30 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
13:00 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
13:30 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
14:00 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
14:30 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
15:00 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
15:30 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
16:00 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
16:30 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
17:00 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
17:30 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
18:00 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
18:30 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
19:00 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
19:30 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
20:00 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
20:30 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
21:00 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
21:30 UT
Meso-NH 2 km res.
surf. wind,all hydromet.,accum. precip.
storm gene-ration @ Alps
AWIATOR 2003
27 August
Diurnal cycle of surface profiles
RASS vs. LM & MM5
Tarbes Airport
Airport
Tarbes
Pau
The Pyrenees
LM forecast domain (DWD) MM5 forecast domain
0 2 4 6 8 10 12 14 16 18 m/s
2000
1800
1600
1400
1200
1000
800
600
400
LM
MM5WakePredictor
P2P
MM5 vertical grid
Modelling chain: LM–MM5–P2P
00 UT
virt. temperature
wind speed
01 UT
virt. temperature
wind speed
02 UT
virt. temperature
wind speed
03 UT
virt. temperature
wind speed
04 UT
virt. temperature
wind speed
05 UT
virt. temperature
wind speed
06 UT
virt. temperature
wind speed
07 UT
virt. temperature
wind speed
08 UT
virt. temperature
wind speed
09 UT
virt. temperature
wind speed
10 UT
virt. temperature
wind speed
11 UT
virt. temperature
wind speed
12 UT
virt. temperature
wind speed
13 UT
virt. temperature
wind speed
14 UT
virt. temperature
wind speed
15 UT
virt. temperature
wind speed
16 UT
virt. temperature
wind speed
17 UT
virt. temperature
wind speed
18 UT
virt. temperature
wind speed
19 UT
virt. temperature
wind speed
20 UT
virt. temperature
wind speed
21 UT
virt. temperature
wind speed
22 UT
virt. temperature
wind speed
23 UT
virt. temperature
wind speed
24 UT
virt. temperature
wind speed
Concluding messages
Potentially useful, non-standard data are available for parameterization test ofhigh-resolution models;here: remotely sensed wind and precipitationA suitable number of case-studies may bemore revealing than standard statistics
Modelling and measuring camps have tocome closer together
DANKE for listening to me !!!