Implementation of KENDA at ARPA-SIMC and first experiences
with an OSSEChiara Marsigli
Tiziana Paccagnella
ARPA Emilia-Romagna, SIMC
Outline
• Implementation of KENDA at ECMWF (sms system)• Set-up of the OSSE suite• First results• Discussion items
KENDA suite at ECMWF
MARS retrieval of conventional observation
creation of the directoriesand set-up of the runs
(ARPA) bufr2netcdf
get Boundary Conditions from ECMWF ENS (and Ics for the cold start)
int2lmget analysis from previous KENDA cycle
COSMO run
KENDA analysis step
processing of output
output archiving
currently 20 members
3-hourly cycles
OSSE set-up
NATURE RUNoptimal configuration, generates the pseudo-observations (fof files)
FOF FOF FOF FOF FOF FOF FOF
00 03 06 09 12 15 18 21 24
CONTROL RUN“dried” run, qv reduced by half in the Initial Condition
10 IC original qv
10 IC halved qv
KENDA CYCLE
KENDA OSSE suite at ECMWFget fof from nature run (psuedo-observations)
modification of the IC (like in the control run)only for members 1-10
Execution of:• Nature run• Control run• KENDA OSSEis driven by the specification in the .def file (file for the definition of the sms suite)
Set-up of the experiments
• KENDA cycle: – 3-hourly cycles, 24 hours– 20 members– BCs from ECMWF ENS (also ICs for cold start)– no model perturbations– observations: TEMP SYNOP AIREP
qv lev 40-41 +3h
NATURE RUN
CONTROL RUN
qv lev 40-41 +6h
NATURE RUN
CONTROL RUN
qv lev 40-41 +12h
NATURE RUN
CONTROL RUN
KENDA cycle - qv lev 40-41 +3hBACKGROUND (lff) ANALYSIS (laf)
MEAN
SPREAD
KENDA cycle - qv lev 40-41 +6h
MEAN
SPREAD
BACKGROUND (lff) ANALYSIS (laf)
qv lev 40-41 +6hNATURE RUN
CONTROL RUN
KENDA ANALYSIS
KENDA cycle - qv lev 40-41 +9hBACKGROUND (lff) ANALYSIS (laf)
MEAN
SPREAD
KENDA cycle - qv lev 40-41 +12hBACKGROUND (lff) ANALYSIS (laf)
MEAN
SPREAD
qv lev 40-41 +12hNATURE RUN
CONTROL RUN
KENDA ANALYSIS
Issues under investigation• “sufficient” spread is needed in the OSSE ensemble• after the KENDA step:
– the ensemble mean is correctly driven towards the pseudo-observations
– the ensemble spread is greatly reduced
• pseudo-observation rejected if the spread is too small• techincal issues to be solved related to quality control checks
(pseudo-observations rejected if they are too different from the background, which may be needed for an OSSE)
• further testing: localisation, multi-step analysis
• suggestions for this OSSE are welcome!
Thank you!
Heght of the levels
Level Height (m) Pressure (hPa)
50 10 1000
40 800 900
30 3000 670
20 7000 400
10 13500 150
1 21500 35
Test cases (Hymex SOP)
I.T. ensemble run Area of the main meteorological phenomenon KENDA cycle
2012092512 Alps 20120924002012092512
2012092612 Liguria Tuscany 20120925002012092612
2012101100 Corse Central Italy 20121010002012101100
2012101112 Corse Central Italy 20121010002012101112
2012102512 Northern Italy (IOP16) 20121024002012102512
