Upload
aderyn
View
50
Download
0
Tags:
Embed Size (px)
DESCRIPTION
Experiences with SMHI local ALARO DA suite. LACE Data Assimilation Working Days, Budapest, 14-16 June, 2011 Magnus Lindskog, Ulf Andrae, Lisa Bengtsson, Lars Meuller, Karl-Ivar Ivarsson, Martin Ridal. Outline. Introduction SMHI local ALARO data assimilation set-up - PowerPoint PPT Presentation
Citation preview
Experiences with SMHI local ALARO DA suite
LACE Data Assimilation Working Days, Budapest,
14-16 June, 2011
Magnus Lindskog, Ulf Andrae, Lisa Bengtsson, Lars Meuller, Karl-Ivar Ivarsson, Martin Ridal
Outline
• Introduction• SMHI local ALARO data assimilation set-up• Results from pre-operational system• SMHI data assimilation impact studies • Some recent general HARMONIE data
assimilation developments • Conclusions and future plans for SMHI ALARO
data assimilation
PRE-OPERATIONAL HARMONIE DOMAINS
2011
AEMETDMIFMI
KNMIMet Eirann
met.noSMHI
Veðurstofa
HARMONIE DOMAINS
AEMETDMIFMI
KNMIMet Eirann
met.noSMHI
Veðurstofa
3dvar/can/oim
NWP models at SMHI HIRLAM C22/C11 (4D-VAR)HIRLAM C22/C11 (4D-VAR)
HIRLAM E11 (3D-VAR)HIRLAM E11 (3D-VAR) HIRLAM G05 (3D-VAR)HIRLAM G05 (3D-VAR)
Operational
Pre-Operational
ALARO (3D-VAR)ALARO (3D-VAR) E05 (3D-VAR)E05 (3D-VAR)
AROME (Downscaling)AROME (Downscaling) Daily
SMHI Pre-operational ALARO system
General System Design
SMHI HARMONIE 2010:• 35h1.3• 5.5 km horisontal resolution• 60 vertical levels (HIRLAM definitions)• 3 hourly LBC from ECMWF fc• Forecast length: 0-36 h• ALARO with 2-L ISBA (not SURFEX)• Hydrostatic forecast model• Surface analysis and 3DVAR• IDFI
SMHI HARMONIE 2011:• 36h1.3• ALARO-0 physics with surfex scheme
General System Design
SMHI HARMONIE 2010:• 35h1.3• 5.5 km horisontal resolution• 60 vertical levels (HIRLAM definitions)• 3 hourly LBC from ECMWF fc• Forecast length: 0-36 h• ALARO with 2-L ISBA (not SURFEX)• Hydrostatic forecast model• Surface analysis and 3DVAR• IDFI
SMHI HARMONIE 2011:• 36h1.3• ALARO-0 physics with surfex scheme
SMHI ALARO is run under mini-SMS
system
Background error statistics • Background error statistics from ensemble of downscaled ECMWF 6h forecasts (20060920-2061031, 00UTC)• REDNMC=0.6• REDZONE=250 km• Background error statistics also derived also utilising ensemble DA (not used)• (Shiyu at DMI has derived background error statistics based on downscaling for different seasons and time of day (201001-201012))
• Background error statistics from ensemble of downscaled ECMWF 6h forecasts (20060920-2061031, 00UTC)• REDNMC=0.6• REDZONE=250 km• Background error statistics also derived also utilising ensemble DA (not used)• (Shiyu at DMI has derived background error statistics based on downscaling for different seasons and time of day (201001-201012))
Observation usage
• SYNOP/SHIP (Z)
• DRIBU (Z)
• AIREP/AMDAR (u,v,T)
• TEMP (u,v,T,q)
• PILOT (u,v)
• ATOVS AMSU-A (NOAA 18 and METOP) (Tb ch 6-10 and VarBC)
Spatialisation of screen level data (CANARI OI)
Surface data assimilation(SYNOP T2m H2m observations over land)
)()( 1 bTTba HxyRHBHBHxx
Surface data assimilation
11,wT
22 ,wT
OImain
mH
mT HTw 21211
mH
mT HTw 22222
mTT 21
22
2mTT
ECMWF SST, temperature over sea ice from surface temperature in boundary field, LST from FA file surface temperature climatology
Scores for verification against observations
April 2011
RMS/BIAS as function of forecast range
ALARO E11 E05 E05(7.3)Surface Pressure (hPa) T2m (K) 10 m Wind speed (m/s)
Scores for verification against observations
April 2011
T2m BIAS (K) averaged over forecast lengths
ALARO E05 E05(7.3)
00 UTC
12 UTC
Scores for verification
against observations
April 2011
ALARO E11 E05 E05(7.3)
RH (%)
Wind speed (m/s)
T (K)
RMS/BIAS averaged over forecasts length as function
of vertical level
Scores for verification against observations
February 2011
RMS/BIAS as function of forecast range
ALARO E11 E05 E05(7.3)Surface Pressure (hPa) T2m (K) 10 m Wind speed (m/s)
Scores for verification against observations
February 2011
T2m BIAS (K) averaged over forecast lengths
ALARO E05 E05(7.3)
00 UTC
12 UTC
00 UTC
12 UTC
Scores for verification
against observations
February 2011
ALARO E11 E05 E05(7.3)
RH (%)
Wind speed (m/s)
T (K)
RMS/BIAS averaged over forecasts length as function
of vertical level
Monitoring of satellite data
and VarBC
00 UTC 06 UTC 12 UTCco
vera
ge24
h u
pdat
e06
h u
pdat
e
A comparison of two off-line soil analysis schemes for
assimilation of screen level observations (Mahfof et al., 2009)
OI-equations
Table of coefficients
Conclusions
1/(2π)
1/(2) (ztiner in cactus.F90)
T2m BIAS/RMS (K) averaged over forecast lengths
ALARO 1/2
ALARO (1/2π)
RMS/BIAS T2M (K) as function o
forecast range
Scores for verification against observations
I month parallel exp, January 2010
ALARO (1/2π) ALARO 1/2
Experimental set-up
• 6 h intermittent data assimilation cycle
• 3 h intermittent data assimilation cycle
Lateral boundary conditions from 6 to 9 h old ECMWF forecasts and observations from ECMWF MARS archive
Two parallel exp. for July & August 2009 and January & Febr. 2010:
At 00 and 12 UTC 30 h forecasts were launched
• HH +/- 3 h for 6 h itermittent DA cycle
• HH +/- 1.5 h for 3 h intermittent DA cycle
Observation time window:
(no modifications of error statistics or IDFI settings
applied when modifying from 6 h to 3 h cycle)
20 Aug 2009 12 UTC sum6h mslpfc (black, hPa)
sum6h-sum3h psdiff (red, conint 1 hPa)
+6 h +12 h +18 h
20 August 2009 09 UTC (RUC 3h)sum3h mslpfc(black,hPa)
3h analysis incr.(red,conint 0.1hPa)
Scores for verification against observations
January, 2010, first 14 days
14 Day RMS/BIAS time series
4D-Var 3D-Var
500 Temperature (K) 500 hPa Wind Speed (m/s)
Timings 96 processor on SMHI Linux Clustre3D-Var:~925 s4D-Var: ~5500 s
30 h forecast: ~5200 s
(experiment for January and July ongoing)
RADAR radial wind DA experiments
Recent HARMONIE data assimilation developments
• Technical problems with initialisation of snow in SURFEX solved (Trygve Aspelien).
• Technical problems with syncronisation of snow between FA file and LFI file solved (Trygve Aspelien).
• Data assimilation of with empty pools in ODB is enabled (Sami Saarinen) arp/obs_preprocs/readoba.F90 &
odb/cma2odb/shuffle_odb.F90, export BASETIME=YYYYMMHHDD.
• Spectral mixing of large scale information from first lateral boundary file enabled through LSMIXBC option (first step towards Jk-large scale constraint) (Ole Vignes). (xmix(m,n,l)=wbcxbc(m,n,l)+(1-wbc)xown(m,n,l))
Conclusions and Future Plans
• Verification scores indicate that the qualiy of SMHI ALARO upper air forecasts are at least as good as the quality of SMHI HIRLAM upper air forecasts.
• SMHI ALARO 10 m wind speeds too low and winter time 2m-temperatures too warm.
• SMHI system will be updated to next HARMONIE version (36h1.4) with recent developments for handling ODB empty pools, improved handling of snow and option for LSBCMIX (to be tested in SMHI system).
• Further experiments with modified surface data assimilation in OImain to be carried out, utilising updated version.
• AMSU-B, radar radial winds and later on ground based GPS to be introduced and evaluated (follow work by others on IASI brightness temperatures and radar reflectivities).
• Sensitivity studies to VarBC settings and wide extension zone.• Potential application of EKF for surface data assimilation, Flake lake
model, RUC and 4D-Var are in the longer term plans. Follow DMI work on varying structure functions.
• Close co-operation with met.no towards common operational HARMONIE system in 2014.
Proposed domains for operational SMHI-met.no system in 2014
~5.5 km hor res (1212*1360 gp), ~65 vert levels ~2.5 km hor res (1134*1720 gp), ~65-90 vert levels