Development of an Ensemble-Based Data Assimilation System with a - - PowerPoint PPT Presentation

Development of an Ensemble-Based Data Assimilation System with a Coupled Atmosphere– Ocean GCM

6th WMO Symposium on Data Assimilation College Park, Maryland, U.S.A., October 10, 2013

Nobu Komori,1 T. Enomoto,1,2 T. Miyoshi,1,3,4 A. Yamazaki,1 and B. Taguchi 1

1 Earth Simulator Center (ESC), JAMSTEC, Yokohama, Japan 2 Disaster Prevention Research Institute, Kyoto University, Uji, Kyoto, Japan 3 RIKEN Advanced Institute for Computational Science, Kobe, Japan 4 Department of Atmospheric and Oceanic Science, University of Maryland, College Park, Maryland, U.S.A.  E-mail: komori@jamstec.go.jp

Outline of Talk

• ALERA & ALERA2 (atmospheric reanalysis)
• CFES–LETKF ensemble DA system
• Motivations
• Experimental settings
• Preliminary results of CLERA-A
• Comparison with ALERA2
• Comparison with EnOFES (ensemble ocean simulation)
• Summary

ALERA

AFES–LETKF experimental ensemble reanalysis (Miyoshi &

Yamane, 2007, MWR; Miyoshi et al., 2007, SOLA)

• first (or second) application of LETKF to full AGCM
• provides analysis ensemble spread as error estimates
• a product of collaboration among JMA, JAMSTEC and CIS
• available from http://www.jamstec.go.jp/esc/research/oreda/

products/

ALERA and ALERA2 compared

ALERA ALERA2 AFES version Resolution Ensemble size

Boundary conditions

Covariance localization

Spread inflation

Obs compiled by

2.2 3.6 T159 L48 T119 L48 40 63+1

NOAA OISST weekly 1° NOAA OISST daily 1/4°

21x21x13 400 km/0.4 lnp 0.1 0.1 JMA NCEP

Enomoto et al. (2013)

ALERA and ALERA2 streams

2005 2006 2007 2008 2009 2010 2011 2012 2013 stream 2010

PALAU 2008 Mirai Arctic Ocean Cruise Mirai Arctic Ocean Cruise VPREX 2010 T

• PARC

Winter T

• PARC

PALAU 2005 MISMO CINDY 2011

ALERA stream 2008 ALERA2

Poster Session A-p08 by T. Enomoto A-p35 by A. Yamazaki

CFES–LETKF Ensemble DA System

Motivations

• Remove underestimation
• f ensemble spread

near the sea surface

• Improve SST–precipitation

correlation

• Evaluate observations

including ocean buoys ➡ Replace AFES with CFES

• Atmospheric DA only

Kunii & Miyoshi (2012, Wea. Forecasting) Forecast of Typhoon Sinlaku (2008)

Motivations

• Remove underestimation
• f ensemble spread

near the sea surface

• Improve SST–precipitation

correlation

• Evaluate observations

including ocean buoys ➡ Replace AFES with CFES

• Atmospheric DA only

Saha et al. (2010, BAMS) Obs CFSR R1 R2

SST lead Prec Prec lead SST Lag days

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

Motivations

• Remove underestimation
• f ensemble spread

near the sea surface

• Improve SST–precipitation

correlation

• Evaluate observations

including ocean buoys ➡ Replace AFES with CFES

• Atmospheric DA only

Enomoto et al. (2013) Effects of Ocean Buoy Observation

CFES

• Coupled GCM for the ES
• AFES + OFES
• Komori et al. (2008)
• CFES mini
• AFES: T119 L48
• OFES: 0.5°x0.5° 54 levels
• Coupling: every hour
• Richter et al. (2010, GRL),

Taguchi et al. (2012, JC), Bajish et al. (2013, SOLA), Nagura et al. (2013, JGR), Sasaki et al. (2013, JC)

Different treatment of sea ice

AFES CFES Concentration Thickness External forcing Prognostic variable 0 or 1 Fractional 0.5 m at the maximum No upper limit

Forecast–Analysis Cycle

AFES–LETKF ensemble DA system

Hunt et al. (2007, Phisica D); Miyoshi & Yamane (2007, MWR)

AFES restart restart restart restart IC IC IC IC t-3 t-2 t-1 t t+1 t+2 t+3 t-3 t-2 t-1 t t+1 t+2 t+3 t-3 t-2 t-1 t t+1 t+2 t+3 t-3 t-2 t-1 t t+1 t+2 t+3 merge split anal anal anal anal gues gues gues gues BC

• bs

LETKF

forecast 6h window analysis

Forecast–Analysis Cycle

CFES–LETKF ensemble DA system forecast 6h window analysis

restart restart restart restart IC IC IC IC t-3 t-2 t-1 t t+1 t+2 t+3 t-3 t-2 t-1 t t+1 t+2 t+3 t-3 t-2 t-1 t t+1 t+2 t+3 t-3 t-2 t-1 t t+1 t+2 t+3 merge split anal anal anal anal gues gues gues gues IC IC IC IC restart restart restart restart

• bs

gues gues gues BC AFES OFES LETKF

CFES

Experimental settings

• Ensemble size: 63 members + control
• Atmospheric observation (PREPBUFR) only
• Integration from 1 August to 30 September 2008
• Atmospheric ICs from ALERA2
• Oceanic ICs from ensemble simulation with OFES (EnOFES)
• Single spin-up run: CORE v2 (1948–2007), ALERA2 (2008–)
• Ensemble run: each member of ALERA2 (2 June 2008–)

Ensemble spread of oceanic ICs (1 Aug)

0.34ºC

Sea-ice concentration SST

Comparison with ALERA2

ALERA2 (BC) CLERA-A

SST (mean, 2-month ave.)

+3.6 K –3.6

Precipitation (mean, 2-month ave.)

ALERA2 CLERA-A

+4.5 mm/day –4.5

Surface temperature (spread, 2-month ave.)

ALERA2 CLERA-A

+0.36 K –0.36 1.7 K

• Diff. in surface variables (2-month ave.)

mean spread mean spread

T2 [K] Q2 [g/kg]

+3.6 –3.6 +1.2 –1.2 +0.18 –0.18 +0.12 –0.12

• Diff. in zonal-mean analysis (2-month ave.)

Air T emperature [K] Specific Humidity [g/kg]

~700 hPa Surface 90ºS 90ºN mean spread mean spread –1.8 +1.8 –0.09 +0.09 –0.3 +0.3 –0.06 +0.06

Comparison with EnOFES

Ensemble spread of SST (1 Aug & 30 Sep)

EnOFES CLERA-A

0.34ºC 1 Aug 30 Sep 30 Sep

Zonal-mean ensemble spread

EnOFES CLERA-A

90ºS 90ºN 1 Aug 30 Sep SST Shortwave Flux SST Shortwave Flux 0.17ºC 85 W/m2

Ensemble spread of ocean temp.

EnOFES CLERA-A

150ºW Eq. 90ºS 90ºN 30ºE 30ºE 800 m 0 m

Summary

• The CFES–LETKF ensemble DA system has been constructed.
• Ocean ensemble creates perturbed surface BC.
• Ensemble spread in the lower troposphere is successfully

increased.

• Ensemble spread of SST is mainly induced by ensemble spread
• f shortwave flux.
• Ensemble spread of ocean surface is slightly increased by

atmosphere–ocean coupling.

• Additional assimilation of oceanic observation is necessary to

reduce model biases.

Thank You!