The Japanese 55-year Reanalysis“JRA-55”
Kazutoshi Onogi
大野木 和敏Japan Meteorological Agency
気象庁
2013/11/25 GEOSS AAWCS

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~ Introduction ~What is reanalysis?

2Required dataset for climate research• For several decades• Consistent and high quality for any time and any region• Many meteorological variables– Pressure, temperature, wind, humidity, …
• They can be observed.
• But these are not sufficient for climate research.

– Variables at the top of atmosphere (i.e. radiation),surface fluxes, vertically accumulated variables(i.e. precipitable water), …
• They are difficult to observe.

3Approach for producing climate data
1. From observational data only– Example) GSN, GUAN managed by GCOS
– High quality climate dataset can be generated at theobservation station and surrounding region, but the regions
and variables are limited.

2. Numerical data assimilation using observational data
– Uniformly distributed grid point values are generated basedon consistent dynamics and physics.
– Advanced NWP model with high performance supercomputer.
– Many kind of variables are produced at every grid point.
– Numerical data assimilation cycle is performed for severaldecades.  Long-term Reanalysis
4Reanalysis

BoundarySST, sea ice

Satelliteozone
Assimilate past observational data

Surface, Upper

Data assimilation cycle
Consistent quality Reanalysis Product

Ship, aircraft

Observation- Provide Initial Condition and Verification datafor seasonal forecast- Climate Monitoring- Research on climate system and water circulation etc.

5The JRA-55 reanalysis

6Japanese Global Atmospheric Reanalysis
1st JRA-25
By JMA and CRIEPI (1979~2004)(Central Research Institute for Electric Power Industry)

2nd JRA-55 ( JRA Go! Go! )By JMA (1958~2012)
JRA-55 is the first reanalysis
which covers more than 50 years since 1958
with 4D-var data assimilation system.
JMA operates JRA-55 continuously
in real time basis after 2013.

7JRA-55 Reanalysis system
JRA-25JRA-55

Reanalysis years

1979-2004 (26 years)

1958-2012 (55 years)

Equivalent
operational NWPsystem

As of Mar. 2004

As of Dec. 2009

Resolution

T106L40 (~110km)(top layer at 0.4 hPa)

TL319L60 (~55km)(top layer at 0.1 hPa)

Time integration

Eularian

Semi-LagrangianAssimilation
scheme3D-Var

4D-Var(with T106 inner model)

Bias correction(satelliteradiance)

Adaptive method(Sakamoto et al. 2009)

Variational Bias Correction(Dee et al. 2009)

GHG
concentrations

Constant at 375 ppmv (CO2)Annual mean data areinterpolated to daily data
(CO2,CH4,N2O)

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Observational Data available for JRA-55

GNSS: Global Navigation Satellite System

9Number of observations assimilated（Global））

logarithmic scale

Lower coverage in TOVSMETEOSAT

FGGE

ATOVS

METEOSAT(Indian Ocean)10Quality of JRA
Forecast [FT=48] Scores
RMSE of Z500 for N.H. and S.H. [gpm]N.H.

JRA-55JRA-25

Year

S.H.

Operation

Lower spatial coverage in TOVSYearVTPR TOVS

ATOVS

11Time-Height Cross Sections of global mean
Temperature [K] anomalies in JRA and ERA reanalyses
JRA-55JRA-25(hPa)(hPa)(Year)(Year)

ERA-40ERA-Interim
(hPa)

(hPa)

(Year)(Year)

Anomalies from the mean temperature at each pressure level for years 1980 to 2001 of eachreanalysis, JRA-55, ERA-40, JRA-25 and ERA-Interim , respectively.

Temporal consistency of temperature analysis(Part 2)
JRA-55(hPa)Time series of global mean
temperature anomalies

MERRA(NASA GMAO)CFSR(NOAA NCEP)

NCEP/NCAR
Anomalies are calculated withrespect to their own averages
for the years from 1980 to2001.

(Year)13

JRA-55 data available
JMA http://jra.kishou.go.jp/DIAS http://dias-dss.tkl.iis.u-tokyo.ac.jp/acc/storages/filelist/dataset:204

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Summary• Observational Data for JRA-55– Improvement in both quality and quantity from JRA-25• Many reprocessed Satellite Data
• Newly available data

• Validation of JRA-55– JRA-55 has much better quality than JRA-25.
– Unnatural gaps have been significantly reduced.

• References– Ebita et al. (2011)

SOLA, 2011, 7, 149-152• The Japanese 55-year Reanalysis “JRA-55”: An Interim Report• Interim report as of 2011

– Comprehensive reports are under preparation.
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Red leaves of Japanese maple in autumn
at Heirinji temple in Niiza city on 23 Nov. 200916