Slide 1 ESA-ECMWF bilateral meeting March 2011 PB ECMWF – ESA Liaison Meeting 3 March 2011 ESA-funded projects

Slide 1

ESA-ECMWF bilateral meeting March 2011 PB

ECMWF – ESA Liaison Meeting

3 March 2011

ESA-funded projects

Slide 2


ESA Support

Support of ERS/Envisat/Cryosat-2: Data monitoring and assimilation

• Wind speed, wave height• Temperature, trace gases

Support of EarthCARE: Potential of radar/lidar forNWP

• Clouds, precipitation, aerosols

Support of SMOS: Data monitoring/assimilation• Soil moisture

Support of ADM: Level-2 processing/assimilation• Wind

Support of Galileo: Optimal radio-occultation constellation

• Temperature, moisture, pressure

Slide 3


ESA Support









Slide 4


0

10

20

30

40

50

60

70

80

90

100

-3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Da

ta R

ec

ep

tio

n

(%)

Time, in hours, from the major synoptic time

Average Received during a 6-hour Time Window, 1 Jan. - 31 Dec. 2010

Envisat

Jason-2

Jason-1

6-hour time window

DC

ED

~ 68%

~ 81%

Operational altimeter data reception at ECMWF

Envisat - Altimeter

Slide 5


Global comparison between altimeter and ECMWF wave model (WAM) first-guess SWH values

(From 02 February 2010 to 01 February 2011)

Jason-1Jason-2Envisat

0 2 4 6 8 10 12 14WAM Wave Heights (m)

0

2

4

6

8

10

12

14

EN

VIS

AT

W

ave

H

eig

hts

(m

)

SYMMETRIC SLOPE

CORRELATION

SCATTER INDEX

STANDARD DEVIATION

BIAS (ENVISAT - WAM)

MEAN ENVISAT

MEAN WAM

ENTRIES

STATISTICS

REGR. CONSTANT

REGR. COEFFICIENT

1 . 0026

0 . 9786

0 . 1051

0 . 2733

- 0 . 0163

2 . 5851

2 . 6014

1 125908

- 0 . 0587

1 . 0163

1510501005001000500010000100000

0 .9983

0 .9791

0 .1044

0 .2826

-0 .0032

2 .7041

2 .7073

142 5055

0 .0637

0 .9753

1. 0 397

0. 9 738

0. 1 200

0. 3 232

0. 1 140

2. 8 078

2. 6 939

138 2997

0. 1 072

1. 0 025

Envisat - Altimeter

Slide 6


• Triple Collocation (1 August 2009 – 31 July 2010) 3 data sets:• Model, Envisat, Buoys• Model, Jason-2, Buoys• Model, Jason-1, Buoys

• Model:• For SWH: Wave model hindcast (i.e. a stand-alone

wave model run without data assimilation, forced by consistent wind fields).

• For wind speed: NWP model day-1 forecast.

• Errors are assumed to be linear and independent from each other.

• Note: Jason-1 suffered from several periods of instability during 2009 especially between March and May 2009.

Envisat - Altimeter

Slide 7


Monthly Significant Wave Height (SWH) Errors (3-month running averages)

08-20

09

09-20

09

10-20

09

11-

20

09

12-20

09

01-20

10

02-20

10

03-20

10

04-20

10

05-20

10

06-20

10

07-20

100.04

0.06

0.08

0.10

0.12

Rela

tive S

WH

E

rror

Jason-2EnvisatJason-1Model HindcastBuoys

Envisat - Altimeter

Slide 9


Operability of Envisat products to ECMWF in 2010

GO

MO

SS

CIA

MA

CH

Y

SCIAM. GOMOS

2006 89.0% 96.1%

2007 83.1% 94.7%

2008 80.7% 96.4%

2009 81% 97.1%

2010 83% 96.3%

2006 -6% +0.2%

2009 +2% -0.8%

Percentage of data received on time to be included in DCDA

Envisat – GOMOS/SCIAMACHY

Slide 10


1JAN

4 7 10 13 16 19 22 25 28 31 3FEB

6 9 12 15 18 21 24 27 2MAR

5 8 11 14 17 20 23 26 29 1APR

4 7 10 13 16 19 22 25 28 1MAY

4 7 10 13 16 19 22 25 28 31 3JUN

6 9 12 15 18 21 24 27 30

-85-75-65-55-45-35-25-15

-55

1525354555657585

Latit

ude

-85-75-65-55-45-35-25-15-551525354555657585

1JUL

4 7 10 13 16 19 22 25 28 31 3AUG

6 9 12 15 18 21 24 27 30 2SEP

5 8 11 14 17 20 23 26 29 2OCT

5 8 11 14 17 20 23 26 29 1NOV

4 7 10 13 16 19 22 25 28 1DEC

4 7 10 13 16 19 22 25 28 31

-85-75-65-55-45-35-25-15

-55

1525354555657585

Latit

ude

-85-75-65-55-45-35-25-15-551525354555657585

1JAN

4 7 10 13 16 19 22 25 28 31 3FEB

6 9 12 15 18 21 24 27 2MAR

5 8 11 14 17 20 23 26 29 1APR

4 7 10 13 16 19 22 25 28 1MAY

4 7 10 13 16 19 22 25 28 31 3JUN

6 9 12 15 18 21 24 27 30

-85-75-65-55-45-35-25-15

-55

1525354555657585

Latit

ude

-85-75-65-55-45-35-25-15-551525354555657585

1JUL

4 7 10 13 16 19 22 25 28 31 3AUG

6 9 12 15 18 21 24 27 30 2SEP

5 8 11 14 17 20 23 26 29 2OCT

5 8 11 14 17 20 23 26 29 1NOV

4 7 10 13 16 19 22 25 28 1DEC

4 7 10 13 16 19 22 25 28 31

-85-75-65-55-45-35-25-15-55

1525354555657585

Latit

ude

-85-75-65-55-45-35-25-15-551525354555657585

SCIAMACHY – GOME-2

SCIAMACHY – OMI

Envisat – SCIAMACHY

Slide 12


• GOMOS data was available in 2010, except in November after an orbit change.

• The quality was stable, in particular:

• Temperature: Good agreement in the Stratosphere (+/- 1%), but larger biases found in the Mesosphere where the T profiles are relaxed to a climatology.

• Ozone: first-guess and analysis departures are within -5 and +20% in the Stratosphere, but larger in the Mesosphere (>50% in places). The standard deviations of the departures are >15% at all levels.

• Water vapour: still show a poor level of agreement with the ECMWF analyses, one to four orders of magnitude difference between obs and fg/an.

• Impact of the ENVISAT orbit change: negligible on average, but the O3

data seem to have a larger noise in December 2010 than they had until October 2010 to be confirmed during 2011.

-90 -80 -70 -60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60 70 80 90Latitude [ deg ]

-100-90-80-70-60-50-40-30-20-10

0102030405060708090

100

OBS

-FG

[ D

U ]

All DataEXP = 0001 ; Period = 2010060100 to 2010063018GOMOS on ENVISAT, Ozone, Layer 11 (20-40 hPa)

Scatterplot of FG Departures versus Latitude

1

2

5

10

20

50

75

100

200

500

750

1000

2000

5000

7500

10000

y mean = -2.02 y stdev = 12.76

Latitude min = -74.41 max = 12.30FG min = 38.80 max = 99.93OBS min = 0.00 max = 137.75

Maximum number per bin = 43Total number = 1274

-90 -80 -70 -60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60 70 80 90Latitude [ deg ]

-100-90-80-70-60-50-40-30-20-10

0102030405060708090

100

OBS

-FG

[ D

U ]

All DataEXP = 0001 ; Period = 2010120100 to 2010123118GOMOS on ENVISAT, Ozone, Layer 11 (20-40 hPa)

Scatterplot of FG Departures versus Latitude

1

2

5

10

20

50

75

100

200

500

750

1000

2000

5000

7500

10000

y mean = -6.53 y stdev = 15.85

Latitude min = -49.95 max = 56.92FG min = 52.77 max = 97.59OBS min = 27.13 max = 178.85

Maximum number per bin = 42Total number = 2704

Dec 2010Jun 2010

Envisat – GOMOS

Slide 15


MIPAS L1(5.02) radiances: O3(MLS(v2.2))-O3(An)

Res

idu

als

Exp-CTRL Exp-MIPAS

-2

-1

0

1

2

mg/k

g

-90 -60 -30 0 30 60 90Latitude

100.00

10.00

1.00

0.10

0.01

Pre

ssure

, hP

a

-2

-1

0

1

2

mg/k

g

-90 -60 -30 0 30 60 90Latitude

100.00

10.00

1.00

0.10

0.01

Pre

ssure

, hP

a

0.0

0.5

1.0

1.5

2.0

mg/k

g

-90 -60 -30 0 30 60 90Latitude

100.00

10.00

1.00

0.10

0.01

Pre

ssure

, hP

a

0.0

0.5

1.0

1.5

2.0

mg/k

g

-90 -60 -30 0 30 60 90Latitude

100.00

10.00

1.00

0.10

0.01

Pre

ssure

, hP

a

Std

dev

Envisat – MIPAS L1

Slide 18


• CryoSat-2 mission will be generating an ocean product called “Fast Delivery Ocean Level 2 (FDM)” while operating in Low Resolution Mode (LRM) on a “best-effort” basis ⇒ FDM not released yet.

• CNES is developing a prototype processor (for Sentinel-3) which they used to generate an independent experimental ocean product.

• CNES product was verified: very high quality!

• FDM as a fully supported operational product would be highly appreciated!

Cryosat-2

0 2 4 6 8 10 12Buoy Sig. Wave Height (m)

0

2

4

6

8

10

12

Cry

oS

at

Sig

. W

ave

H

eig

ht

(m)

SYMMETRIC SLOPE

CORRELATION

SCATTER INDEX

STANDARD DEVIATION

BIAS (CRYOSAT - BUOY)

MEAN CRYOSAT

MEAN BUOY

ENTRIES

STATISTICS

REGR. CONSTANT

REGR. COEFFICIENT

0.94920.96060.1530

0.4189

-0.1661

2.5718

2.7379

3427

-0.0095

0.9428

15

153050

100300500

100030000

0 2 4 6 8 10 12 14WAM Model Sig. Wave Height (m)

0

2

4

6

8

10

12

14

Cry

oS

at

Sig

. W

ave

H

eig

ht

(m)

SYMMETRIC SLOPECORRELATION

SCATTER INDEX

STANDARD DEVIATIONBIAS (CRYOSAT - WAM)

MEAN CRYOSAT

MEAN WAMENTRIES

STATISTICS

REGR. CONSTANTREGR. COEFFICIENT

0.94490.9768

0.1031

0.2594-0.1761

2.3415

2.5176157237

-0.13680.9844

15

1050

100500

10005000

10000100000

Cryosat vs WAM Cryosat vs Buoys

Slide 19


Global comparison between altimeter and ECMWF wave model (WAM) first-guess SWH values

28

O

ct

04

N

ov

11

N

ov

18

N

ov

25

N

ov

02

D

ec

09

D

ec

16

D

ec

23

D

ec

30

D

ec

06

Ja

n

13

Ja

n

2 0 1 0

-0.3

-0.2

-0.1

0.0

0.1

0.2

0.3

0.4

SD

D

(m

)

ENVISATCryoSat

SDD

Bias

2 0 1 1

Alt

.-Mo

del B

ias

Cryosat-2

Slide 21


ESA Support









Slide 22


EarthCARE

Project: Quantitative Assessment of the Operational Value of Space-Borne Radar and Lidar Measurements of Cloud and Aerosol Profiles (QuARL)

1st Project (concluded) 2nd Project (under review) FutureGeneral Studies Support To Science Element EarthCARE?

Model validation - clouds - aerosols

Radar : Radar+Lidar : Radar+LidarSimulator SimulatorMonitoring demonstrator Experimental monitoring Operational monitoringExperimental assimilation Experimental assimilation Operational assimilationAssimilation strategies

based on Cloudsat/Calipso data based on Cloudsat/Calipso data based on EarthCARE dataMain conclusions:• Model validation with profiling cloud/aerosol lidar/radar is fundamental for future

parameterization developments with significant impact on cloud-aerosol-radiation interaction

• Unique verification source of already assimilated data affected by clouds/aerosols• Assimilation experiments show beneficial impact – but localized

Slide 23


REF_AT

62 N 60 N 58 N 56 N 54 N 52 N 50 N 48 N 46 N 44 N 42 N 40 N 38 N 36 N 34 N 32 N 30 NLat

100W 99 W 98 W 97 W 96 W 95 W 94W 93 W 92 W 91 W 90 W 89W 88W 87 WLon

1.1

1.9

3.0

4.3

5.9

7.6

9.3

10.9

12.5

Hei

gh

t (k

m)

-24 - -21 -21 - -18 -18 - -15 -15 - -12 -12 - -9 -9 - -6 -6 - -3 -3 - 0 0 - 3 3 - 6 6 - 9 9 - 12 12 - 15 15 - 18Observation

REF_AT



1.1

1.9

3.0

4.3

5.9

7.6

9.3

10.9

12.5

Hei

gh

t (k

m)

-24 - -21 -21 - -18 -18 - -15 -15 - -12 -12 - -9 -9 - -6 -6 - -3 -3 - 0 0 - 3 3 - 6 6 - 9 9 - 12 12 - 15 15 - 18

REF_AT



1.1

1.9

3.0

4.3

5.9

7.6

9.3

10.9

12.5

Hei

gh

t (k

m)

-24 - -21 -21 - -18 -18 - -15 -15 - -12 -12 - -9 -9 - -6 -6 - -3 -3 - 0 0 - 3 3 - 6 6 - 9 9 - 12 12 - 15 15 - 18

15 – 18

REF_AT

62N

60N

58N

56N

54N

52N

50N

48N

46N

44N

42N

40N

38N

36N

34N

32N

30N

Lat100

W99

W98

W97

W96

W95

W94

W93

W92

W91

W90

W89

W88

W87

WLon

1.1

1.9

3.0

4.3

5.9

7.6

9.3

10.9

12.5Height (km)

-24 - -21-21 - -18

-18 - -15-15 - -12

-12 - -9-9 - -6

-6 - -3-3 - 0

0 - 33 - 6

6 - 99 - 12

12 - 1515 - 18

-24 – -21

-21 – -18

-18 – -16

-16 – -12

-12 – -9

-9 – -6

-6 – -3

-3 – 0

0 – 3

3 – 6

6 – 9

9 – 12

12 – 15

Model First-Guess

Analysis

1D-Var Assimilation of Cloudsat Radar Reflectivities (dBZ)

EarthCARE

Slide 24


EarthCARE1D-Var Assimilation of Calipso lidar Backscatter Coefficients (km-1 sr-1)

Observation

Model First-Guess

Analysis

Slide 25


EarthCARE

1D+4D-Var Assimilation of Cloudsat Radar Reflectivities (dBZ)

GOES-12 EXP-CTRL

IR-Imagery GOES-12

IR-Imagery

NEXRAD EXP-CTRL

Radar rainfall Radar rainfall

Slide 26


ESA Support









Slide 27


L1C-NRT BUFR product

Convert to L1C-NRT ECMWF BUFR product

Pre-process data:• Consistency checks

• Parallel data thinning per angular bins

ESAC

MARS ECFS

Store in ECMWF archives

Computations in model space (gp_model)

Get SMOS data in grid point• call smos_process

Forward model (CMEM) physics interface routines

call callpar

Back to observation space call smos_update

BUFR files

Mapping and load data to ODB tables

ODB data

passivemonitoring ofNRT TB overland & sea call smos_screen

CMEM interface

call mwave_screen RTTOV interface

Tatm

ε

Distribution per processor and grid point

Acquisition, quality control, thinning, etc.

Collocation, screening, forward modelling, first-guess departures, etc.

SMOS - Monitoring

Slide 29


TBxx:

Std of obs

1-7 Oct 2010

80°S80°S

70°S 70°S

60°S60°S

50°S 50°S

40°S40°S

30°S 30°S

20°S20°S

10°S 10°S

0°0°

10°N 10°N

20°N20°N

30°N 30°N

40°N40°N

50°N 50°N

60°N60°N

70°N 70°N

80°N80°N

160°W

160°W 140°W

140°W 120°W

120°W 100°W

100°W 80°W

80°W 60°W

60°W 40°W

40°W 20°W

20°W 0°

0° 20°E

20°E 40°E

40°E 60°E

60°E 80°E

80°E 100°E

100°E 120°E

120°E 140°E

140°E 160°E

160°E

Fg_departure0 - 5 5 - 10 10 - 15 15 - 20 20 - 25

25 - 30 30 - 35 35 - 40 40 - 200

SMOS - Monitoring

Standard deviation of Observations 1-7 October 2010

Slide 30


3 months of data (28 Nov 2010-28 Feb 2011)

Radiances at

10˚ incidence angle

Stability test (calibration event) 6 days

Thermal instability science data is degraded

12 January Hardware problem is solved (thermal control is restored, BUT, calibration of algorithm

parameters need re-calibration.

18 February NRT processor working again normal.

SMOS - Monitoring

Slide 32


Data assimilation Data processing

Assimilation expt

Thinning

Noise filtering

Bias correction

T2m, RH2m

SMOS data

T2m, RH2m, SMOS

Maintenance, testing, reports, etc.

SMOS - Next

Slide 33


ESA Support









Slide 34


ADM-AeolusThe L2B implementations HLOS wind retrieval for use in NWP

Core PDS

Stand-alone version for late- and re-processing

(ESRIN)

NWP Centres

Subroutine version for integration in data-

assimilation systems

ECMWF/IFS

For operational generation of ESA’s L2B and L2C products

To complete/refine 2011/12

Portable L2B software and documentation to ESA and NWP-SAF standards

Two releases planned for 2011“Final burst mode” + “First continuous mode”

Slide 35


ADM-Aeolus: ECMWF implementationOperational acquisition of inputs from ESA

ECMWF polls the ESA ftp site every 10 minutes

Additional transfers prepared for GSOV Part 2

2012

Slide 36


ADM-Aeolus: ECMWF implementationProcessing from Level-1B to Level-2B/2C

L2B/L2C/AuxMet data generated & stored in ECMWF’s Observation

DataBase (ODB)

Data from ODB written in ESA’s Earth Explorer

format for dissemination to PDS

Monitoring statistics on data quality are

compiled/plotted routinely

Already passed GSOV Part 1 2009, internal enhancements ongoing

Slide 37


• The measuring capability of the Aeolus lidar instrument has been simulated

• Real scattering measurements obtained from the LITE instrument

• ESA’s software (E2S) is used to simulate what ADM would ‘see’

• The L1B software retrieves scattering ratio on the ADM measurement resolution

ADM-Aeolus: Example

Slide 38


ADM Aeolus: Ongoing activities

• Adapting to continuous mode laser

• Preparing for GSOV Part 2, 2012

• Participating in cal/val expert panel

• Preparing for commissioning phase

• Scientific validation of the processing chain (especially upstream calibration) and assimilation impact of real DWL data (airborne demonstrator flown by DLR)

• Finalize the download website and license agreement for other users of the software

• Supporting other users for integration/implementation within their own NWP systems

• On standby in case EUMETSAT seeks a QRT L2B service for other users (cf KNMI option)

• Exploring greater use of Aeolus aerosol products

Slide 39


ESA Support









Slide 40


Support of Galileo GNSS: Observing System Simulation Experiments (OSSE) to estimate the optimal radio occultation constellation number for NWP and climate research (submitted)

Galileo

Background:• GNSS radio occultation observations provide fundamental

(complementary) contribution to radiance data: NWP and Climate• Currently experienced decline in GNSS radio occultation observation

numbers hopefully compensated by COSMIC-2 (2014) and, multiple transmitter capability (GPS, Galileo) in the future.

• WMO Vision for GOS requires estimation of optimal constellation configuration

• ECMWF proposal employs ensemble-based Observing System Simulation Experiments (OSSE) for this task ensuring consistency with recently performed Observing System Experiments (OSE) using real data.

Slide 41


OSE with all (!) available GPSRO data to test saturation limit for

NWP impact

Galileo

Future constellation impact will be evaluated with Ensemble-

OSSEs (proposed to ESA under Galileo science programme)

Documents

Slide 1 ESA-ECMWF bilateral meeting March 2011 PB ECMWF – ESA Liaison Meeting 3 March 2011 ESA-funded projects