12 September 2007 ESRIN/ESA Reanalysis and climate monitoring Lennart Bengtsson Reanalysis and...

12 September 2007ESRIN/ESA

Reanalysis and climate monitoringLennart Bengtsson

Reanalysis and climate monitoring

Lennart Bengtsson

Environmental System Science Centre

University of Reading, UK

Thanks to ECMWF

Uppala and Simmons



Reanalysis and climate monitoring

• Achievements

• Challenges

• Vision



Reanalysis

• Why reanalysis?

• Background

• What has been achieved

• Limitations



Why reanalysis?

• It is required to integrate different kind of observations in a consistent way making it possible to project the observation on suitable scales of motion.

• Such an approach is needed for a systematic control of observational quality.

• Many studies require access to data in gridded form.• This include diagnostic and predictive studies needed

for an integrated assessment of observational data.



Examples of re-analyses

• FGGE-1 ( ECMWF and GFDL) 1979

• ERA-15 (ECMWF) 1990

• ERA-40 (ECMWF) 2001

• NCAR/NCEP- ( US Org.) 1988

• JMA - 25 ( Japan Met Agency) 2005



How can we measure the value (operational and otherwise) of new observing systems?

• To use observations on its own is not feasible.

• Observational information must be assimilated by a model as information will have to be combined by other observations in time and space.

• Information content carried by the model based on previous data is as large or larger than the actual observations on its own.

• Observations must be controlled and filtered against an estimate, best provided by a dynamical projection of an ensemble of other data.



Re-analyses applications

• Assessing the value of observing systems

• Numerical weather prediction

• Detection of climate change

• Understanding the climate system










Conventional•Surface•Upperair•Aircraft•Satellite products

TOVS radiances

SSMI radiances

AIRS radiances

O3 data

Bia

s m

odul

es

NWP systemNWP system

Observations and observation equivalents

from the model and analysis

in database

Quality anddeparture

information

Input observations How the observations were used in the analysis

(feedback)

Conventional feedback•Surface•Upperair•Aircraft•Satellite products

TOVS feedback

SSMI feedback

AIRS feedback

O3 feedback

(Input and feedback observations in BUFR code)



Comparison of reanalysis and land-station values

Surface air temperature anomaly (oC) with respect to 1987-2001

EuropeERA-40 – CRUTEM2v

Inadequate SYNOP coverage in ERA-40

Erroneous CLIMAT data in CRUTEM2v, corrected in

HadCRUT3 (Brohan et al., 2006)



METEOSAT Reprocessed Winds










The principle of error reduction in data assimilation



Evolution of 1-Day Forecast Error, Lorenz Error

Growth, and Forecast Skill for ECMWF Model (500 hPa NH Winter)

1982 1987 1992 1997 2002

“Initial error” (1-dayforecast error) (m) 20 15 14 14 8

Doubling time (days) 1.9 1.6 1.5 1.5 1.2

Forecast skill (day 5 ACC) 0.65 0.72 0.75 0.78 0.84

2007

8

1.2*

0.91



Improvements in NWP from Miyakoda (1972) to 2002. Courtesy ECMWF

How long to get to D+10 in winter?



The impact of observations on forecast skillExperiments with different observing systems

DJF 1990/91 using ERA40 observations

• The control system (using all observations)

• A terrestrial based system ( radio-sondes and aircraft obs.)

• A satellite based system ( satellites and surface pressure)

• A surface based system ( surface observations)



Global forecasts DJF 90/91

• 7- day forecasts, every 6hr.• Later ECMWF model T159/L60

• Extra-tropics 20-90N and 20-90S• 500 hPa Z, normalized SD for the period

• Tropics 20N-20S

• Wind vector field 850 and 250hPa



Observing systems and predictive skillNorthern Hemisphere extra-tropics

Bengtsson and Hodges, 2004



Observing systems and predictive skillSouthern Hemisphere extra-tropics




Observing systems and predictive skillTropics V 250 hPa




Ops 1980Ops 1980

ERA 2001

Ops 2001

Northern Hemisphere

%

Anomaly correlations of 500hPa height forecasts

Ops 2001Ops 1980

ERA 2001

Ops 2003

Northern Hemisphere

%



Anomaly correlations of 500hPa height forecasts

Ops 1980

Ops 2003

Ops 2001

ERA 2001

%

Australia/New Zealand

%










Based on monthly CLIMAT station data (CRUTEM2v; Jones and Moberg, 2003)

Based on ERA-40 reanalysis of SYNOP data

(Simmons et al., 2004)

Linear trend in two-metre temperature (1979-2001)

Mean over land: 0.30OC/decade Mean over land: 0.32OC/decade



Based on monthly CLIMAT station data (CRUTEM2v; Jones and Moberg, 2003)

Based on ERA-40 reanalysis of SYNOP data, sub-sampled

to match CRUTEM2V

Linear trend in two-metre temperature (1979-2001)

0.27OC/decade 0.32OC/decade Mean over land: 0.30OC/decade



500hPa temperature fits for two Antarctic stations

ERA-40 Radiosonde



Trend and variability in two-metre temperature

CRUTEM2v (Jones and Moberg, 2003)

ERA-40

Linear trend (1979-2001): CRUTEM2v 0.31OC/decade

ERA-40 0.28OC/decade

NCEP 0.19OC/decade



Trend and variability in lower stratospheric temperature

Linear trend: MSU-4 - 0.39OC/decade

ERA-40 - 0.30OC/decade

NCEP - 0.82OC/decade

MSU-4 data analyzed by Mears et al. (2003)ERA-40 equivalent from Ben Santer



Tropical water-vapour content










Global wave climatology atlasS. Caires, A. Sterl, G. Komen and V. Swail

http://www.knmi.nl/onderzk/oceano/waves/era40/atlas.html

1971 - 2000 90th percentile of significant wave height February

m



Hurricane Katrina August 2005ECMWF operational analyses, 850 hPa vorticity



Prediction of Atlantic hurricanes are influenced by ENSOResults from a general circulation model integrated over

30 years comparing active seasons from less active

ECHAM5/OM ERA-40

Temperature difference

Measure of divergence

Vertical wind shear

prediction verification



Challenges

• Trends in the free atmosphere

• The water cycle

• Surface fluxes between the surface and the atmosphere

• Extending the re-analyses back in time before upper air observations



0.01

0.02

0.03

0.050.07

0.1

0.2

0.3

0.50.7

1

2

3

5

7

10

20

30

50

70

100

200

300

500

700

1000

Pressure (hPa)

60 levels 91 levels

1

2

3

4

5

6

7

8

9

10

12

14

16

18

20

25

30

35

40455055606570

91

Level number

ERA-40/ L60 ERA-Interim/ L91

65 km

81 km



• Data-assimilation system

T159L60 T255L91

New humidity analysis and improved model physics

3D-Var FGAT 12 hour 4D-Var • Satellite level-1c radiances

Better RTTOV and improved use of radiances especially IR

Assimilation of rain affected radiances from SSM/I

Adaptive bias correction• Improved use of radiosondes

Bias correction and homogenization based on ERA-40• Correction of SHIP/ SYNOP surface pressure biases• Use of reprocessed Meteosat winds• New set of Altimeter wave height data 1991

ERA-40 1957-2002

ERA-Interim 1989 to continue as CDAS



Much improved 500hPa height

forecasts

Day

Southern hemisphere

Anomaly correlation of 500hPa height, averaged for 12UTC forecasts from 1 January to 31 December 1989

ERA-new

ERA-40

Operations

Northern hemisphere



Much improved tropical 850hPa wind forecasts

Day

vs radiosondes

RMS error of vector wind, averaged for 12UTC forecasts from 1 January to 31 December 1989

vs analyses

ERA-new

ERA-40

Operations



Global precipitation-evaporation 1989 (+12h forecast)

ERA-Interim (test) = 0.01ERA-40 = 0.23ERA-40 23 year Climate = 0.32



• Reanalysis does have a role to play in the study of recent climate trends

• It can help in the detection and correction of problems in the instrumental record

• ERA-40 represents a clear step forward for the depiction of trends

• Insights into deficiencies are provided by analysis and background fits to observations, analysis increments and comparisons with simulations and other reanalyses

• There is considerable potential for improvement of reanalysis – more so than for improvement of the database of past observations?

In summary



Visions

• Extending the re-analyses to incorporate the full 20th century. How feasible is this?

• Extending re-analyses to the fully coupled climate system.

• To incorporate bio-geochemical processes

• Applying re-analyses ideas on other planetary atmospheres ( e.g Venus, Mars)



500mb Height Analyses for 0Z 20 Dec 2001

5500 m contour is thickened

Full NCEP Climate DataAssimilationSystem (CDAS)(120,000+ obs)

Kalman / Ensemble Filter(EnsFilt) 1895(308 surfacepressure obs)RMS = 49 m

ClimatologicalEnsemble Filter(EnsClim) 1895(308 surfacepressure obs)RMS = 96 m

CDAS-SFC obsonly 1895(308 surfacepressure obs)RMS = 96 m



ca.60%

2002-06

4.9 PgC

annually

Emission now 8PgC



• Could start in 2010 depending on resources

• ~ 1940 • Important components

Recovery of observations

Variational technique aimed for reanalysis

Comprehensive adaptive bias handling

Handling of model bias

Improved SST & ICE dataset

ERA-Interim

ERA-70?



Some comments to climate monitoring

• Climate monitoring should be undertaken in an integrated mode applying the conceptual ideas from the re-analyses

• Major efforts are needed to determine biases so overlapping of satellite sensors is needed as well as the use of complementary instruments ( e.g. GPS occultation versus temperature retrievals)

• Operational time of particular instruments should ideally cover representative climate periods ( several decades)



END

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