2nd Data Assimilation Workshop
JAMSTEC Yokohama Institute for Earth Sciences, January 13, 2012

Development of CFES–LETKF Ensemble DataAssimilation System
Nobu Komori,1 T. Enomoto,1,2 T. Miyoshi,3 B. Taguchi 1and Team OREDA
1 Earth Simulator Center (ESC), JAMSTEC, Yokohama, Japan
2 Disaster Prevention Research Institute, Kyoto University, Uji, Kyoto, Japan
3 Department of Atmospheric and Oceanic Science, University of Maryland, CollegePark, Maryland, U.S.A.
 E-mail: komori@jamstec.go.jp

Outline of Talk
• AFES-LETKF ensemble DA system• Atmospheric reanalysis: ALERA & ALERA2• CFES-LETKF ensemble DA system• Preliminary results of CLERA-A• SummaryLETKF: local transform
ensemble Kalman filter

Kalman filter for a scalar����
aat 2p ≡E x −x
: analysis error (co)variance����
fft 2p ≡E x −x
: forecast error (co)variance
���
�
ot 2
: observation error (co)variancer ≡E x −x

faxn = M xn−1
pfn = M 2 pan−1 + qn−1

M: modelq: system noise��xan = xfn + wn xon − xfn
pan = (1 − wn ) pfnwn =pfn

fpn + rn

Kalman gain

Kalman filter for a scalar
wn =pfnfpn + rn=�−1(rn )fpn

�−1−1+ (rn )� f �−1−1pn(rn )afoxn + � �−1xn
xn = � �−1−1−1ffpn+ (rn )pn+ (rn )��
−1−1a
f −1+ (rn )(pn ) = pnlocal ensemble KF (LEKF)[Ott et al. 2004]

local ensemble transform KF (LETKF)[Hunt et al. 2007]

ensemble KF (EnKF)[Evensen 1994]

ensemble transform KF (ETKF)[Bishop et al. 2001]

Kalman filter (KF)
[Kalman 1960]

Ensemble Kalman filter
Approximation by ensemble

1P ≈δXδXm−1fEnsemble updateaf
δXi = δXi T

ETKF (Bishop et al. 2001)

ALERAALERA
AFES-LETKF experimental reanalysis• first application of LETKF to full AGCM
• provides analysis ensemble spread as errorestimates• a product of collaboration among JMA, JAMSTEC
and CISALERA: specifications• Observations used in NWP at JMA• AFES T159L48M40• from 18UTC 1 May 2005 to 12UTC 11 Jan 2007
• u, v,T,T–Td, z, slp• available from the Earth Simulator Center
http://www.jamstec.go.jp/esc/afes/alera/

Hunt et al. 2007; Miyoshi and Yamane 2007; Miyoshi et al. 2007a

ALEDAS: AFES-LETKF Ensemble
Data Assimilation SystemAFES

observation
LETKF

analysisanalysisforecast

t=t0

t=t1

LETKF: Hunt et al. 2007; Miyoshi and Yamane 2007; Miyoshi et al. 2007
AFES: Numaguti et al. 1997; Ohfuchi et al. 2004; Enomoto et al. 2008

Miyoshi et al. 2007a SOLA

850 (u,v) and standardized U850 spreadmeanspread
Enomoto et al. 2010 GRL

Lag correlation between
mean and spread
0.6

0.52

0.4
0.2
0-0.2-10 -8-6

spread leads-4-202days
Enomoto et al. 2010 GRL

46810spread lags

Effects of buoy observation
ALL the TRITON buoys (blue ∆)observe surface pressure

ONLY the TAO buoys on the equator(red ∆) observe surface pressure

Q. Moteki Pers. Comm.

Influence of sondes inMatsuno-Gill pattern
ALERA (w/o MISMO sondes)

MISMO Oct–Dec 2006
in the Indian Ocean

Influence ontyphoon genesis
with MISMO sondes

ALERA – with MISMOMoteki et al. 2011 QJRMS

Impact of Arctic buoys
accuracy in the region w/Arctic buoys (●) is as high as
in the mid-latitudes

error becomeslarger over theentire Arctic

Inoue et al. 2009 GRL

ALERA2

ALERA2 features• Larger ensemble size (from 40 to 63)• Improved model physics (cloud and land surface etc)
• Covariance localization by distance• High-res SST and ice (NOAA daily 1/4° OI SST)
• Publicly obtainable observations (prepbufr)• Forecast values (precip, radiative and surface fluxes)

Low cloud fraction

Kuwano-Yoshida et al. 2010 QJRMS

Cloud water

Kuwano-Yoshida et al. 2010 QJRMS

FT=120 Z500 RMSD
against JMA analysis, August 2004

m56
55

55.4

54

53.8

53

53.1

52

ALERA
52.1
51.6

51

51.2

51.3

50
49
48+MATSIRO+PDF cloud
49.5
48.9

1.22

2.0

2.1

2.2

T159L48

2.3

2.4

2.7

2.7m

3.6

T119L48

Error covariance localization
by distance
ALERA

ALERA2

Noise due tolocal patches

Miyoshi et al. 2007b SOLASondes

Aircraft

Surface

Ships & buoys

AMV

QuikScatGPCP

ALERA2

JRA25

ALERA2 spread

ALERA2 streams
2003 2004 2005 2006 2007 2008 2009 2010 2011

ALERA
PALAU 2005
MISMO

stream 2008
PALAU 2008
Mirai Arctic Ocean Cruise
T-PARC
Winter T-PARC

ALERA2stream 2010

Mirai Arctic Ocean Cruise
VPREX 2010
CINDY 2011

CFES-LETKF

Motivations• Remove underestimation

Lag Correlation of Prec. and SST over Western Pacific (winter)

Obs
CFSR
R1
R2of ensemble spreadnear the sea surface• Improve SST–precipitation
correlation➡ Replace AFES with CFESSST lead Prec

Lag days

Prec lead SST

Saha et al. 2010 BAMSCFES mini
冬季ストームトラック活動度storm-track
activity in winter• AFES T119L48, mstrn-X,contour:
mean,color:std. deviation
コンター:
平均場,
陰影:標準偏差Emanuel, MATSIRO• OFES 0.5°x0.5° 54 lev., Sea
ice, Noh-Kim mixed layer

CFES中解像度阪mini
CFES• 177 years: interannual todecadal variability• Richter et al. 2010 GRL,

Taguchi et al. 2012 JC, ...
NCEP/NCAR再解析
NCEP/NCAR Reanalysis

B. Taguchi Pers. Comm.

Precipitation (DJF)
CMAP

AFES (T239)

CFES

CFES miniPrecipitation (JJA)
CMAP

AFES (T239)

CFES

CFES miniCLERA-A• Initial conditions from 41-year OFES spin-up with
CORE.v2 Corrected Interannual Forcing• 39 members + control• 4 CFES per node
• Atmospheric DA only to study influence of thesurface boundary uncertainties• Starting from 1 August 2008
• Preliminary result on 10 September 2008

MPI implementation
EnCFES
EnAFES

MPI_COMM_WORLD

MPI_COMM_WORLD
MPIA_...

MPIA_... ... MPIA_...

MPI_COMM_COUPLEMPI_COMM_COUPLE ...... MPI_COMM_COUPLEMPIA_...

MPIA_...

MPIO_...

...

MPIO_...

...... MPIA_...

MPIO_...

......

CFES
AFES

MPI_COMM_WORLD = MPI_COMM_COUPLEMPI_COMM_WORLD= MPIA_COMM_WORLD...

MPIA_COMM_WORLD...

MPIO_COMM_WORLD...

Forecast–Analysis Cycle
AFES-LETKF Ensemble DA Systemmerge

6h window

forecast
ICAFESBC

restart

split

t-3
t-2
t-1
tt+1t+2t+3

analysis

anal

LETKF
gues

obs

Forecast–Analysis Cycle
CFES-LETKF Ensemble DA Systemmerge

6h window

forecast
ICIC

AFES

OFES

restartrestart

split

t-3
t-2
t-1
tt+1t+2t+3

analysis

anal

LETKF
gues

obs

ALERA2

mean

CLERA-Amean

Surface temperature

spread 2008080500

spreadALERA2

mean

CLERA-Amean

Surface temperature

spread 2008091000

spreadALERA2mean

CLERA-Amean

Latent heat flux

spread 2008091000

spreadDifference in zonal mean spread
CLERA-A − ALERA2
Temperature

2008091000

Specific humidity

700

850

1000

SPEqNPSPEqNP

Summary• The CFES-LETKF ensemble DA system has been
constructed.

• Ocean ensemble creates perturbed surface BC.
• Needs to handle oceanic biases and drift for alonger run.

Thank You!