Experiences with SMHI local ALARO DA suite
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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

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Experiences with smhi local alaro da suite

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
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
PRE-OPERATIONAL HARMONIE DOMAINS2011

AEMETDMIFMIKNMIMet Eirannmet.noSMHIVeðurstofa


Harmonie domains
HARMONIE DOMAINS

AEMETDMIFMIKNMIMet Eirannmet.noSMHIVeðurstofa

3dvar/can/oim


Nwp models at smhi

Operational

NWP models at SMHI

HIRLAM C22/C11 (4D-VAR)

HIRLAM E11 (3D-VAR)

HIRLAM G05 (3D-VAR)

Pre-Operational

E05 (3D-VAR)

ALARO (3D-VAR)

Daily

AROME (Downscaling)


Experiences with smhi local alaro da suite

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


Experiences with smhi local alaro da suite

SMHI ALARO is run under

mini-SMS

system


Experiences with smhi local alaro da suite

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))


Experiences with smhi local alaro da suite

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)


Experiences with smhi local alaro da suite

Surface data assimilation

(SYNOP T2m H2m observations over land)

ECMWF SST, temperature over sea ice from surface temperature in boundary field, LST from FA file surface temperature climatology

Spatialisation of screen level data (CANARI OI)

Surface data assimilation

OImain


Scores for verification against observations april 2011
Scores for verification against observationsApril 2011

RMS/BIAS as function of forecast range

ALARO E11E05 E05(7.3)

Surface Pressure (hPa)

T2m (K)

10 m Wind speed (m/s)


Scores for verification against observations april 20111
Scores for verification against observationsApril 2011

T2m BIAS (K) averaged over forecast lengths

ALARO E05 E05(7.3)

00 UTC

12 UTC


Scores for verification against observations april 20112
Scores for verification against observationsApril 2011

T (K)

RMS/BIAS averaged over forecasts length as function of vertical level

Wind speed (m/s)

ALARO E11E05 E05(7.3)

RH (%)


Scores for verification against observations february 2011
Scores for verification against observationsFebruary 2011

RMS/BIAS as function of forecast range

ALARO E11E05 E05(7.3)

Surface Pressure (hPa)

T2m (K)

10 m Wind speed (m/s)


Scores for verification against observations february 20111
Scores for verification against observationsFebruary 2011

T2m BIAS (K) averaged over forecast lengths

ALARO E05 E05(7.3)

00 UTC

00 UTC

12 UTC

12 UTC


Scores for verification against observations february 20112
Scores for verification against observationsFebruary 2011

T (K)

RMS/BIAS averaged over forecasts length as function of vertical level

Wind speed (m/s)

ALARO E11E05 E05(7.3)

RH (%)



Experiences with smhi local alaro da suite

00 UTC

06 UTC

12 UTC

coverage

24 h update

06 h update


Experiences with smhi local alaro da suite
A comparison of two off-line soil analysis schemes for assimilation of screen level observations (Mahfof et al., 2009)

OI-equations

1/(2π)

1/(2)

(ztiner in cactus.F90)

Table of coefficients

Conclusions


Scores for verification against observations i month parallel exp january 2010
Scores for verification against observations assimilation of screen level observations (Mahfof et al., 2009)I month parallel exp, January 2010

RMS/BIAS T2M (K)

as function o

forecast range

ALARO (1/2π)

ALARO 1/2

T2m BIAS/RMS (K) averaged over forecast lengths

ALARO (1/2π)

ALARO 1/2


Experiences with smhi local alaro da suite

Experimental set-up assimilation of screen level observations (Mahfof et al., 2009)

Two parallel exp. for July & August 2009 and January & Febr. 2010:

  • 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

Observation time window:

  • HH +/- 3 h for 6 h itermittent DA cycle

  • HH +/- 1.5 h for 3 h intermittent DA cycle

(no modifications of error statistics or IDFI settings applied when modifying from 6 h to 3 h cycle)

At 00 and 12 UTC 30 h forecasts were launched


Experiences with smhi local alaro da suite

20 Aug 2009 12 UTC assimilation of screen level observations (Mahfof et al., 2009)sum6h mslpfc (black, hPa)sum6h-sum3h psdiff (red, conint 1 hPa)

+6 h

+12 h

+18 h


Experiences with smhi local alaro da suite

20 August 2009 09 UTC (RUC 3h) assimilation of screen level observations (Mahfof et al., 2009)sum3h mslpfc(black,hPa) 3h analysis incr.(red,conint 0.1hPa)


Scores for verification against observations january 2010 first 14 days
Scores for verification against observations assimilation of screen level observations (Mahfof et al., 2009)January, 2010, first 14 days

4D-Var 3D-Var

(experiment for January and July ongoing)

14 Day RMS/BIAS time series

500 Temperature (K)

500 hPa Wind Speed (m/s)

Timings 96 processor on SMHI Linux Clustre

3D-Var:~925 s

4D-Var: ~5500 s

30 h forecast: ~5200 s


Experiences with smhi local alaro da suite

RADAR radial wind DA experiments assimilation of screen level observations (Mahfof et al., 2009)


Recent harmonie data assimilation developments
Recent HARMONIE data assimilation developments assimilation of screen level observations (Mahfof et al., 2009)

  • 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
Conclusions and Future Plans assimilation of screen level observations (Mahfof et al., 2009)

  • 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
Proposed domains for operational SMHI-met.no system in 2014 assimilation of screen level observations (Mahfof et al., 2009)

~5.5 km hor res (1212*1360 gp), ~65 vert levels

~2.5 km hor res (1134*1720 gp), ~65-90 vert levels