Scatterometer_impppt.pdf

Active Techniques for Wind and Wave Observations: Scatterometer, Altimeter (& SAR)

Giovanna De Chiara & Saleh Abdalla ECMWF

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 1

Outline Scatterometer Winds     

The importance of scatterometer wind observations Physical mechanism and wind inversion Data usage at ECMWF and their impact How we can improve the use and impact Concluding remarks

Altimeter Wind and Waves       

Introduction Verification and Monitoring Wave Data Assimilation Assessment of Model Performance (inc. Model Effective Resolution) Error Estimation Long Term Studies Concluding Remarks

Synthetic Aperture Radar (SAR)

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 2

Why is Scatterometer important? The scatterometer measures the ocean surface winds (ocean wind vector).

Ocean surface winds:  affect the full range of ocean movement (from individual surface waves to complete current systems)  modulate air-sea exchanges of heat, momentum, gases, and particulates

Wind observations below 850 hPa FSO values relative quantities (in %)

Wide daily coverage of ocean surface winds Ex: 1 day of ASCAT-A data

[Horanyi et al, 2013] ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 3

What is a Scatterometer?  A Scatterometer is an active microwave instrument (radar)  Day and night acquisition  Not affected by clouds  The return signal, backscatter (σ0 sigma-nought), which is sensitive to:  Surface wind (ocean)  Soil moisture (land)  Ice age (ice)

[ASCAT-A from http://www.eumetsat.int]

Scatterometer was originally designed to measure ocean winds:  Measurements sensitive to the ocean-surface roughness due to capillary gravity waves generated by local wind conditions (surface stress)  Observations from different look angles: wind direction

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 4

Dependency of the backscatter on... Wind speed

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 5

Dependency of the backscatter on... Wind direction Backscatter response depends on the relative angle between the pulse and capillary wave direction (wind direction) Mid Fore Beam

Mid Beam Wind direction wrt Mid Beam Fore Aft Beam

C-band SCAT geometry

Wind direction wrt Mid Beam Aft

Wind direction wrt Mid Beam ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 6

How can we relate backscatter to wind speed and direction?  The relationship is determined empirically  Ideally collocate with surface stress observations  In practice collocation between buoy winds and 10m model winds

𝜎0 = 𝐺𝑀𝐹(𝑈10𝑁 , 𝜙, 𝜃, 𝑝, 𝜆) U10N: equivalent neutral wind speed : wind direction w.r.t. beam pointing : incidence angle p : radar beam polarization : microwave wavelength

 Geophysical model functions (GMF) families  C-band: CMOD  Ku-band: NSCAT, QSCAT

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 7

How can we relate backscatter to wind speed and direction? For the C-band observations, σ0 triplets lies on a double conical surface

z_mid

σ0 triplets with the same wind speed 0°

CMOD5

180°

270° 90°

[Stoffelen]

 Wind inversion: search for minimum distances between the σ0 triplets and all the solutions on the GMF surface.  Noise in the observations can change the position wrt the cone: wind ambiguities ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 8

C- band scatterometers Used on European platforms (1991 onwards):  SCAT on ERS-1, ERS-2 by ESA  ASCAT on Metop-A, Metop-B by EUMETSAT  f~5.3 GHz (λ~5.7 cm)  VV polarization  Three antennae

Pros and cons:    

Hardly affected by rain High quality wind direction (especially ASCAT) Two nearly opposite wind solutions Rather narrow swath:  ERS-1/2: 500km  ASCAT-A/B: 2x500km

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 9

Ku-band scatterometers Used on US and Japanese platforms, later also India, China  NSCAT, QuikSCAT, SeaWinds by NASA (and Japan)  Oceansat by ISRO  Haiyang-2A by China  f~13 GHz (λ ~ 2.2 cm)  VV and HH polarization:  Two rotating pencil-beams (4 look angles)

Pros and cons:  Up to four wind solutions (rank-1 most often correct one)  Broad swath (1,800km)  Affected by rain  Problems regarding wind direction:  azimuth diversity not good in centre of swath  outer 200km only sensed by one beam.

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 10

OSCAT daily coverage

Operational usage of Scatterometer winds at ECMWF 95

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01

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ERS-1 ERS-2 (Regional Mission Scenario)

ERS-2

QuikSCAT

METOP-A ASCAT

METOP-B ASCAT Oceansat-2 (OSCAT)

C-Band

Ku Band

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 11

14

ASCAT-A & ASCAT-B assimilation strategy ASCAT (25km) from EUMETSAT  Wind inversion is performed in-house:  Sigma nought bias correction  Inversion using CMOD5.N  Wind speed bias correction  Quality control, thinning:  Screening: sea ice check based on SST and sea ice data  Thinning: 100 km  Threshold: 35 m/s  In the 4D-Var 2 solutions provided: best one chosen dynamically during the minimization ASCAT-A vs ECMWF FG Wind Speed  Assimilated as 10m equivalent neutral winds  Observation error: 1.5 m/s

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 12

OCEANSAT-2 assimilation strategy OCEANSAT-2 (50km)  Use of Level-2 wind products from OSI-SAF (KNMI)  Wind speed bias correction (wind-speed dependent)  Quality control:  Screening: sea ice check on SST and sea ice model  Rain flag  No thinning; weight in the assimilation 0.25  Threshold: 25 m/s  Assimilated as 10m equivalent neutral winds  Observation error: 2 m/s OSCAT vs ECMWF FG Wind Speed

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 13

Impact of scatterometer winds Contribution to the reduction of the 24h Forecast Error (total dry energy norm) [Cardinali, 2009, Q.J.R.Met.Soc. 135]

Global statistics with respect to the total observing network Dec 2012 / Feb 2013

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 14

Impact of scatterometer winds …on Tropical Cyclone FC  For each storm the min SLP have been detected from the ECMWF model fields  SLP have been compared to observation values (from NHC and JMA)

Statistics based only on cases where ASCAT-A, ASCAT-B and OSCAT passes were available Dec 2012/ Feb 2013 ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 15

Impact of scatterometer winds

…on the ocean parameters

Temperature difference Scatt – NoScatt November 2013

Verified against conventional temperature observations Tropical Atlantic

Tropical Indian

Tropical East Pacific

[P. Laloyaux] ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 16

Is the model able to propagate the information? Single Observation Experiment (1 ASCAT-A)

ML

PL(hPa)

137 ~ 1013 114 ~ 850 96 ~ 500 79 ~ 250 60 ~ 100

analysis increments (U)

analysis increments (V)

50

Model Levels

50

100

100

S 137

N

S 137

ECMWF Seminar 2014 - Active techniques for wind and wave observations

N Slide 17

How can we improve usage and impact?  Include dependency from other geophysical quantities such as ocean currents  Stress is related to relative wind  The observation operator should act on relative wind  Accurate ocean current input are needed  Improve QC mostly for extreme events  Because of thinning and QC the strongest winds can be rejected  Test on the observation error, thinning and use of high resolution products

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 18

Concluding remarks Scatterometer observations widely used in NWP Typhoon Haiyan 20131107 ASCAT-A

ASCAT-B

OSCAT

   

Ocean wind vectors Positive impact on analysis and the forecast Global scale and extreme events Available continuously from 1991 onwards

ECMWF has a long experience with scatterometry  Assimilation since 1995  ERS1/2, QuikSCAT, ASCAT-A/B, Oceansat-2  Future missions: ASCAT-C, Oceansat-3,…  GMF development  Monitoring, validation, assimilation, re-calibration

On-going efforts to improve usage and impact  Improve QC for tropical cyclones (Huber norm)  Adapt observation errors, thinning, super-obbing  Include dependency from other geophysical quantities

Use in the Reanalysis  ERS1/2 and QuikSCAT in ERA-Interim  ASCAT-A reprocessed products will be used in ERA5 ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 19

Altimeter Wind & Waves

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 20

Outline Scatterometer Winds     

The importance of scatterometer wind observations Scatterometer principle Data usage at ECMWF and their impact How we can improve the use and impact Concluding remarks

Altimeter Wind and Waves       

Introduction Verification and Monitoring Wave Data Assimilation Assessment of Model Performance (inc. Model Effective Resolution) Error Estimation Long Term Studies Concluding Remarks

Synthetic Aperture Radar (SAR)

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 21

Introduction

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 22

Radar Altimeters

ENVISAT

● Radar altimeter is a nadir looking instrument.

● Specular reflection.

Radar Altimeter-2

● Electromagnetic wave bands used in altimeters: Primary:

Ku-band (~ 2.5 cm) – ERS-1/2, Envisat, Jason-1/2/3, Sentinel-3. Ka-band (~ 0.8 cm) – SARAL/AltiKa (only example).

Secondary: C-band (~ 5.5 cm) – Jason-1/2/3, Topex, Sentinel-3. S-band (~ 9.0 cm) – Envisat.

● Main parameters measured by an altimeter: 1. 2. 3. 4.

Sentinel-3

Sea Surface Height (ocean) Significant wave height Wind speed Ice/land/lakes characteristics,…

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Radar Altimeter (SRAL) Slide 23

How Radar Altimeter Works:

Height=∆t/2  c

a t m o s p h e r e

radar signal

ocean surface surface

illuminated area

emitted signal

returned signal

flat surface

power

Power of illumination

rough surface

time time ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 24

Information extracted from a radar echo reflected from ocean surface (after averaging ~100 waveforms) slope of leading edge  significant wave height

power

waveform amplitude of the signal  wind speed

epoch at mid-height  sea surface height

time

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 25

Impact of the atmosphere on Altimeter signal: ● Delay  sea surface height – Water vapour impact: ~ 10’s cm. – Dry air impact: ~ 2.0 m.

● Attenuation  wind speed

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 26

Typical Daily Coverage of: Envisat/SARAL

Jason-1/2

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 27

Verification & Monitoring of Altimeter Surface Wind Speed

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 28

Altimeter surface wind speed:

power

waveform

emitted signal

amplitude of returned signal  wind speed

backscatter

time

● backscatter is related to water surface mean square slope (mss). ● mss can be related to wind speed. ● Stronger wind  higher mss  smaller backscatter. ● Errors are mainly due to algorithm assumptions, waveform retracking (algorithm), unaccounted-for attenuation & backscatter. ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 29

Relation between wind speed and altimeter backscatter

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 30

Comparison between ENVISAT NRT wind speed and ECMWF model AN (top) and in-situ measurements (bottom) for all data;

100000 10000 5000 1000 500 100 50 10 5 1

(m/s)

25

ENVISAT Wind Speed

20

15

STATISTICS

10

ENTRIES 1128826 MEAN ECMWF 7.7799 MEAN ENVISAT 8.0723 BIAS (ENVISAT - ECMWF) 0.2924 STANDARD DEVIATION 1.1181 SCATTER INDEX 0.1437 CORRELATION 0.9461 SYMMETRIC SLOPE 1.0339 REGR. COEFFICIENT 0.9595 REGR. CONSTANT 0.6076

5

0

0

5

10

15

ECMWF Wind Speed

20

25

(m/s)

1 Jan. 2011 – 31 Dec. 2011

50000 1000 500 300 100 50 30 15 5 1

120°W

80°W

40°W

0°

40°E

80°E

120°E

160°E

60°N

60°N

40°N

40°N

20°N

20°N

0°

0°

20°S

20°S

40°S

40°S

60°S

60°S

ENVISAT Wind Speed

160°W

(m/s)

25

20

15

STATISTICS ENTRIES MEAN BUOY MEAN ENVISAT BIAS (ENVISAT - BUOY) STANDARD DEVIATION SCATTER INDEX CORRELATION SYMMETRIC SLOPE REGR. COEFFICIENT REGR. CONSTANT

10

5

160°W

120°W

80°W

40°W

0°

40°E

80°E

120°E

160°E

Typical locations of in-situ measurements

0

0

ECMWF Seminar 2014 - Active techniques for wind and wave observations

5

10

15

Buoy Wind Speed

Slide 31

20

(m/s)

25

14597 8 . 4282 8 . 3144 - 0 . 1138 1 . 4560 0 . 1728 0 . 9008 0 . 9884 0 . 9019 0 . 7128

Comparison between Jason2 NRT wind speed and ECMWF model AN (top) and in-situ measurements (bottom) for all data; 1 May 2013 – 30 April 2014 160°W

120°W

80°W

40°W

0°

40°E

80°E

120°E

160°E

60°N

60°N

40°N

40°N

20°N

20°N

0°

0°

20°S

20°S

40°S

40°S

60°S

60°S

160°W

120°W

80°W

40°W

0°

40°E

80°E

120°E

160°E

Typical locations of in-situ measurements ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 32

Verification & Monitoring of Altimeter Significant Wave Height

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 33

Altimeter Significant Wave Height (SWH) slope of leading edge  SWH

power

waveform

time  SWH is the mean height of highest 1/3 of the surface ocean waves.  Higher SWH  smaller slope of waveform leading edge.  Errors are mainly due to waveform retracking (algorithm) and

instrument characterisation. ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 34

Global comparison between Altimeter and ECMWF wave model (WAM) first-guess SWH values (From 02 February 2010 to 01 February 2011) 14

100000 10000 5000 1000 500 100 50 10 5 1

(m)

12

ENVISAT Wave Heights

10

8

Envisat Jason-2 Jason-1

STATISTICS 6

1 125908 2 . 6014

142 50 55

138 299 7

2 .7 073

2 . 6 939

2 . 5851

2 .7 041

2 . 8 078

- 0 . 0163 STANDARD DEVIATION 0 . 2733

- 0 .0 032

0 . 1 140

0 .2 826

0 . 3 232

ENTRIES MEAN WAM MEAN ENVISAT

4

BIAS (ENVISAT - WAM)

2

0

0

2

4

6

8

WAM Wave Heights

10

12

14

SCATTER INDEX

0 . 1051

0 .1 044

0 . 1 200

CORRELATION

0 . 9786

0 .9 791

0 . 9 738

SYMMETRIC SLOPE

1 . 0026

0 .9 983

1 . 0 397

REGR. COEFFICIENT

1 . 0163

0 .9 753

1 . 0 025

- 0 . 0587

0 .0 637

0 . 1 072

REGR. CONSTANT

(m)

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 35

Comparison between Cryosat-2 NRT SWH and ECMWF model FG (top) and in-situ measurements (bottom) for all data; 1 April 2013 – 17 June 2014 160°W

120°W

80°W

40°W

0°

40°E

80°E

120°E

160°E

60°N

60°N

40°N

40°N

20°N

20°N

0°

0°

20°S

20°S

40°S

40°S

60°S

60°S

160°W

120°W

80°W

40°W

0°

40°E

80°E

120°E

160°E

Typical locations of in-situ measurements ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 36

Comparison between SARAL (Ka) NRT SWH and ECMWF model FG (top) and in-situ measurements (bottom) for all data; 1 May 2013 – 30 April 2014

160°W

120°W

80°W

40°W

0°

40°E

80°E

120°E

160°E

60°N

60°N

40°N

40°N

20°N

20°N

0°

0°

20°S

20°S

40°S

40°S

60°S

60°S

160°W

120°W

80°W

40°W

0°

40°E

80°E

120°E

160°E

Typical locations of in-situ measurements ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 37

Assimilation of Altimeter Significant Wave Height

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 38

Data Assimilation Method

● Assimilation Method for Altimeter data: – Data are subjected to a quality control process (inc. super-obbing). – Bias correction is applied. – Simple optimum interpolation (OI) scheme on SWH. – The SWH analysis increments  wave spectrum adjustments... (several assumptions)

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 39

Operational Assimilation of SWH NRT Altimeter SWH operational assimilation at ECMWF: - ERS-1 URA, 15 Aug. 1993 – 1 May 1996; - ERS-2 URA, 1 May 1996 – 23 Jun. 2003; - ENVISAT RA-2 FDMAR, 22 Oct. 2003 – 7 Apr. 2012; - Jason-1 OSDR, 1 Feb. 2006 – 1 Apr. 2010; - Jason-2 OGDR, 10 Mar. 2009 – on-going; - Cryosat-2 FDM, Coming model change (~Q4, 2014); - SARAL OGDR, Coming model change (~Q4, 2014). ERS-1 ERS-2

15 Aug. 1993

1 May 1996

Envisat

22 Oct. 2003

Jason-1 Envisat

1 Feb. 2006

Jason-2 Envisat

10 Mar. 2009

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Jason-1 Jason-2 Jason-2 Envisat Envisat

8 Jun. 2009 Slide 40

1 Apr. 2010

Jason-2

7 Apr. 2012

Mean impact of assimilating Cryosat-2 SWH (with BC) on SWH analysis [CS & J2] - [J2 only]

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 41

Impact of assimilating altimeter data on SWH random error as verified against Extra-tropical in-situ data, Feb. – April 2014

4

160°W

120°W

80°W

40°W

0°

40°E

80°E

120°E

160°E

60°N

60°N

40°N

40°N

20°N

20°N

0°

0°

20°S

20°S

40°S

40°S

60°S

60°S

160°W

120°W

80°W

40°W

0°

40°E

80°E

120°E

160°E

Typical locations of in-situ measurements

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 42

Impact of assimilating altimeter data on SWH random error as verified against Tropical in-situ data, Feb. – April 2014

160°W

120°W

80°W

40°W

0°

40°E

80°E

120°E

160°E

60°N

60°N

40°N

40°N

20°N

20°N

0°

0°

20°S

20°S

40°S

40°S

60°S

60°S

160°W

120°W

80°W

40°W

0°

40°E

80°E

120°E

160°E

Typical locations of in-situ measurements

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 43

Impact of assimilating SARAL data on SWH error as verified against Cryosat -2 SWH, Feb. – March 2014

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 44

Mean Impact of using SARAL (with BC) SWH on Geopotential anomaly correlation (bars @ 95% level) Northern Hemisphere

Southern Hemisphere

1000 hPa

500 hPa ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 45

Assessment of model changes & Monitoring of model performance

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 46

Change Assessment: Change of SDD between ENVISAT RA-2 and ECMWF Model Wind Speed

Model C35R2

Model C32R2

IPF 5.02 1.3

1.2

1.1

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 47

Jan-2012

Jan-2011

Jan-2010

Model change Jan-2009

Model change Jan-2008

Jan-2006

Jan-2005

1.0

Jan-2004

Alt. algorithm change

Jan-2007

U10 Std. Dev. of Difference

-1

(m s )

1.4

Performance Monitoring: Change of SDD between Envisat RA-2 and ECMWF Operational SWH

Change of alt. algorithm 0.35

0.30

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 48

Jan-2012

Jan-2011

Jan-2010

Jan-2009

Jan-2008

Jan-2007

Jan-2006

0.20

Jan-2005

0.25

Jan-2004

SWH Std. Dev. of Difference

(m)

IPF 6.02L04

0.40

Effective Model Resolution

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 49

6

|

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k -2.5

1024 (~7,100 km) -5/3

k -2.5 k -2.5

6

10

sampling at 7 km 685 seq. 1 year Envisat

k 10

20 km

|

50 km

20 km

|

100 km

50 km

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200 km

100 km

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500 km

200 km

|

1000 km

500 km

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2000 km

1000 km

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5000 km

2000 km

|

Effective Resolution = ~125 km

10

5000 km

Surface wind speed spectra

5

10

4

Spectral Density

Spectral Density

3 -2

(m s )

(m3 s-2)

5

~400km -5/3

k

10

10

3

4

10

Envisat RA-2

3

10

ECMWF Model 10

2

Envisat RA-2

k -5/3 2

10

Env. RA-2, 685sp, 1024x7km T1279, 592sp, 2011, 512x16km

-6

10

-5

10 wavenumber

-4

10 -1 (m )

ECMWF Seminar 2014 - Active techniques for wind and wave observations

-6

10

-5

10

wavenumber

Slide 50

-4

10

(m-1)

2000 km

1000 km

500 km

200 km

100 km

50 km

20 km

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Spectral Density

(m3 s-2)

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10

600

3

10

Envisat RA-2 Model (T1279) -6

10

-5

10

wavenumber

-4

10

(m-1)

T255

500

400

300 T511

T799

200

100

2

10

Full Resolution 50% Reduction 8x D 4x D

(km)

10

700

Shortest Resolved Scale

6

50% Resolution ~65 km

Effective Resolution ~125 km

5000 km

Effective Model Resolution

T639

T2047 T1279 T3999

0 0

10

20

30 40 Grid Resolution, D ,

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 51

50 (km)

60

70

80

Error estimation

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 52

Random Error Estimation of Wind Speed & SWH using triple collocation technique

1.2 Model FC Buoy Jason-1 Jason-2 ENVISAT

(m)

3

Model FC Buoy Jason-1 Jason-2 ENVISAT

1.0

Sig. Wave Height Error

10-m Wind Speed Error

(m.s-1 )

4

2

1

0.8

0.6

0.4

0.2

0

0

1

2

3

4

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0.0 0

1

2

3

Forecast Days

ECMWF Seminar 2014 - Active techniques for wind and wave observations

4

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Forecast Days

Slide 53

7

8

9

10

Long Term Studies

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 54

Trend of “zonal” winds between 1992 and 2010 according to: Scatterometer &

Altimeter

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 55

Mean “zonal” winds in Tropical Pacific basin according to: Scatterometer & Altimeter

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 56

Concluding Remarks

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 57

Model – Satellite Data: 2-Way Benefit ● Model wind and wave data are used for:

- Monitoring quality of satellite data. - Assessing changes in processing of satellite data. - Detecting anomalies in the data. - Cal/Val of new instruments/products. ● Satellite wind and wave data are used for:

- Data assimilation. - Monitoring of model performance (inc. model resolution). - Assessment of model changes. - Use in reanalyses (assimilation and validation). ● Error estimation. ● Long term assessments & climate studies. ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 58

Synthetic Aperture Radar (SAR)

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 59

Outline Scatterometer Winds     

The importance of scatterometer wind observations Scatterometer principle Data usage at ECMWF and their impact How we can improve the use and impact Concluding remarks

Altimeter Wind and Waves       

Introduction Verification and Monitoring Wave Data Assimilation Assessment of Model Performance (inc. Model Effective Resolution) Error Estimation Long Term Studies Concluding Remarks

Synthetic Aperture Radar (SAR)

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 60

Synthetic Aperture Concept

● A radar system with a “synthetic” aperture simulates a “virtually” long antenna in order to increase azimuth resolution without increasing the actual antenna.

● The green target remains within the radar beam for the distance travelled by the satellite. The length of the synthesized antenna is equivalent to this distance. Synthetic Aperture Radar allows for a resolution of ~30 meters. Azimuth (flight) direction

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 61

Synthetic Aperture Radar (SAR) ● SAR is a side-pointing radar that provides 2D spectra of ocean surface waves (wavelength and direction of wave systems).

● Measures distances in the “slant range”  distortions.

● Water motion introduces further (nonlinear) distortions.

● 5 km x 6 (or 10) km images  SAR image spectra.

● SAR inversion: ocean wave spectrum is retrieved from SAR spectrum using nonlinear mapping. ECMWF Seminar 2014 - Active techniques for wind and wave observations

https://earth.esa.int/

Slide 62

ENVISAT Advanced Synthetic Aperture Radar (ASAR)

https://earth.esa.int/

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 63

SAR Wave Mode Image & SAR Image CrossSpectrum (Level 1b)

https://earth.esa.int/

● Almost full Resolution in the range direction (30 m ~ 1000 m). ● Limited resolution in the azimuth direction (>~200 m). ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 64

Global comparison between ASAR and WAM model (2011) Inverted L1b (full spectrum)

6

ENTRIES

4

2

0

(m)

STATISTICS

0

2

4

6

8

WAM Sig. Wave Height

10

12

776756

MEAN WAM

2. 6720

MEAN ASAR

2. 5195

7 6

OK

5

STATISTICS

4

ENTRIES

453973

MEAN WAM

1. 1044

100’s

3

MEAN WVW

0. 8514

BIAS (ENVISAT - WAM)

- 0. 2530

STANDARD DEVIATION

0. 3903

SCATTER INDEX

0. 3534

CORRELATION

0. 7884

0. 9565

SYMMETRIC SLOPE

0. 7303

0. 9722

REGR. COEFFICIENT

0. 4499

REGR. CONSTANT

0. 3545

BIAS (ENVISAT - WAM)

- 0. 1525

STANDARD DEVIATION

0. 3690

SCATTER INDEX

0. 1381

CORRELATION

0. 9591

SYMMETRIC SLOPE REGR. COEFFICIENT

REGR. CONSTANT

100000 10000 5000 1000 500 100 50 10 5 1

10’s

8

WVW Swell Wave Height

(m) ASAR Sig. Wave Height

8

9

50000 1000 500 300 100 50 30 15 5 1

12

10

L2 (within azim. cut-off)

- 0. 0781

2 1

0

0

(m)

ECMWF Seminar 2014 - Active techniques for wind and wave observations

1

2

3

4

5

6

WAM Swell Wave Height

Slide 65

7

(m)

8

9

Assimilation of SAR Wave Data - Method

● Assimilation Method: – L1b SAR spectra are inverted to ocean wave spectra. – Ocean spectra are partitioned into wave systems which then paired with the corresponding systems in the model. – Simple OI scheme on integrated parameters of the systems. – Each partition is adjusted based on its analysis increment.

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 66

Assimilation of Wave Data

● NRT Altimeter (Ku) SWH operational assimilation at ECMWF: - ERS-1 URA, - ERS-2 URA, - ENVISAT RA-2 FDMAR, - Jason-1 OSDR, - Jason-2 OGDR,

15 August 1993 – 1 May 1996; 1 May 1996 – 23 June 2003; 22 October 2003 – 7 April 2012; 1 February 2006 – 1 April 2010; 10 March 2009 – on-going

● NRT SAR spectra operational assimilation at ECMWF: - ERS-2 SAR UWA, - ENVISAT ASAR WVS, 13 Jan. 2003

ERS-1 ERS-2

15 Aug. 1993

1 May 1996

21 Oct. 2010

1 Feb. 2006

ERS-2 SAR

SAR Alt.

13 January 2003 – 31 January 2006; 1 February 2006 – 21 October 2010. ENVISAT ASAR

Jason-1 Jason-1 Jason-2 Jason-2 Jason-2 Envisat Jason-2 Envisat Envisat Envisat Envisat

22 Oct. 2003

10 Mar. 2009

ECMWF Seminar 2014 - Active techniques for wind and wave observations

8 Jun. 2009 Slide 67

1 Apr. 2010

7 Apr. 2012

Impact of assimilating WM data on SWH bias and SDD in the Tropics Verified against Envisat and Jason-1 altimeter SWH data. Bias = Mod.-Alt. (m)

L2 (QC)

L1b

No data

-0.08 -0.10 -0.12 -0.14 -0.16 0

1

2

3

4

5

St. Dev. of Error (m)

0.30

0.25

0.20

01 Aug. – 04 Sep. 2008

0.15

0.10

0

1

2

FORECAST DAYS ECMWF Seminar 2014 - Active techniques for wind and wave observations

3

4

(0 = AN) Slide 68

5

SWH Error reduction Due to Assimilating WM (& RA-2 SWH) Products Verified against in-situ measurements in Tropics

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 69

Conclusions (SAR) • Fast delivery ENVISAT ASAR Wave Mode products: - L1b  inverted in-house  operationally assimilated. - L2  already inverted  difficulties in assimilation.

● Assimilation of ASAR WM L1b product leads to positive impact on the model forecasts (up to 4% error reduction and last for 2-5 days).

● Assimilation of ASAR WM L2 leads to rather limited impact (<2% error reduction).

● Similar work will be carried out for Sentinel-1. ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 70

Definition of Difference Measures ● Systematic error (Bias) is:

Bias  N

1

N

 (x T )  x  T i

i 1

● Root mean square difference (RMSE):

● Standard deviation of the difference (SDD):

i

N

N 1  ( xi  Ti ) 2

RMSE 

i 1

SDD 

N

1

N

2 ( x  T  Bias )  i i i 1

SDD 

N

1

N

2 2 ( x  T )  Bias  i i i 1

● Scatter index (SI):

SI  SDD / T

● x = altimeter data set,

T = reference data set (e.g. in-situ), N = total number of collocations

ECMWF Seminar 2014 - Active techniques for wind and wave observations

Slide 71