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SAR-derived Sea Surface Winds

in the Seas around Korea and

Air-Sea Interaction

Kyung-Ae Park and Tae-Sung Kim

Department of Earth Science Education / Research Institute of Oceanography, Seoul National University, KOREA

SEOUL(Satellite Earth/Ocean Sciences & EdUcation Lab.)

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Air-Sea-Land interaction by sea surface windOcean surface circulationModification of vertical thermal structure, MLD variabilityAir-sea gas exchange through sea surfaceKey environmental factor of Ocean EcosystemGlobal/Local Climate Change

For operational UseWeather forecastingSevere weather disastersHuman-related activities …

Role of Sea Surface Wind

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Obtained easilyRelatively low spatial resolution : 25km × 25kmUnable to observe winds in the near-shore regionLimitation of understanding coastal phenomena

Scatterometer Winds

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Importance of Coastal Wind Observation

Complicated coastline of Korean PeninsulaInsufficient in-situ wind measurements (5 ocean buoys)Need for monitoring sea surface winds at the Korean coastUnderstanding of coastal wind variability Korean Coastal regions :

Unpredictable Natural Disasters

(severe fog, heavy rainfall, swell, …)

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Objectives

Retrieval of sea surface wind field along the Korean coast from SAR data

Comparison of the high-resolution SAR-derived wind vectors with wind measurements and other satellite winds to assess the accuracy

Attempted to eliminate noise problems in ALOS PALSAR data

Understanding air-sea interactions through wind field modification over a variety of complex oceanographic phenomena, frequently apparent along the Korean coast.

Understanding of the air-sea-land interactions by relationship between cold-air outbreak and along-coast wind field off Russian coast in the East/Japan Sea

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Wind Estimation for Scientific Applications

• By Satellite• …σ0

• CMOD Se-ries

• L-band HH GMF

• …

Model

• Accuracy / Error

• Causes• Limitation

Wind

• Understanding Oceanographic Phe-nomena

• Air-Sea Interaction, …

Monitoring & Science Prediction

ARIRANG 5(Korea)

2011 X-band, multi-mode Operationally Used ?

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L-band SAR-derived

Sea Surface Wind Retrieval

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Estimation of Wind Direction

Wind Speed

Algorithms

L-band HH GMF

Incidence An-gle

Wind Di-rection

Normalized Radar Cross Section(σ0)

Wind measurement data (in situ, other

satellite sensor data, reanalysis data, etc)

ECMWF Interim Reanalysis Winds

Interpolation

Distribution of interpolated near surface wind vectors from ECMWF reanalysis

data on 18 Jul 2007

1 3 2

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Wind Field from ALOS PALSAR

• High wind speed in the offsea region• Low values near the shore

In spite of the noises, low winds are found along the western coast.

What Happened ?

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Wind Field from ALOS PALSAR

Images of (a) NRCS and (b) retrieved wind field off the east coast of Korea from ALOS PALSAR image (2007/08/11 02:56:56 (UTC))

Observing Direction

Low Inci-dence An-

gle

• Noises were small but extended over the land.• Reasonable wind speed field, but still contained the erros

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Wind Field from ALOS PALSAR

• Relatively Low Wind Speed near the shore• What mechanisms and processes are related on this?

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Backscattering Cross Section

Problems in PALSAR Images

Causes & Solutions

How to eliminate noises ?

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Backscattering Coefficient (σ0)

Also found on Land !

(a) DN (b) σ0

Animation of DN and NRCS valuesAll images reveal the same issues

Dark and BrightStripe- and Band-like FeaturesIrregularity

Yellow Sea

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Maps of (a) NRCS(σ0) and (b) Gradient values ofALOS PALSAR ScanSAR (2007. 07. 18 02:15:15 (UTC))

(a) σ0 (b) ▽σ0

Problems of ScanSAR Image

• Land affected by stripes• Careful landuses are needed

Gradient of NRCS

Yellow Sea

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Wind Field from ALOS PALSAR

Images of (a) NRCS and (b) retrieved wind field off the east coast of Korea from ALOS PALSAR image (2007/08/11 02:56:56 (UTC))

Observing Direction

Low Inci-dence An-

gle

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Problems of ScanSAR Image

Examples (PALSAR) in other regions

• Not too much noises• The noises are not limited in the Yellow

Sea• Non-local, but universal problem

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Problems on Other ScanSAR Images

Examples (other SARs)

RADARSAT-1(Southeast Alaska coast)

COSMO-SkyMed(from Geo-Alliance)

RADARSAT-1(Western Lake Superior)

Discontinuity

• Also apparent in other SAR data• Non-local, but Universal problem• The different noise patterns seems to depend on

regional characteristics

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Error Characteristics of

SAR-derived Sea Surface Wind

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Assessment of Accuracy with QuikSCAT

Scenes RMSE (m/s)

2007.07.18 5.20

2007.08.04 5.69

2007.08.16 7.17

2008.07.03 3.56

2009.07.23 7.77

2009.08.21 6.32

• Comparison of PALSAR wind with QuikSCAT wind

• Large RMS errors (3~7m/s)• Interference problems from land

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Assessment of Accuracy

Comparison of wind speeds from ALOS PALSAR and QuikSCAT

Overestimation !

vPALSAR - vQuikSCAT

RMSE of wind speed 3.45 m/s (QuikSCAT) 3.74 m/s (ASCAT) Large errors along the edge

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Assessment of Accuracy

Comparison of wind speeds from PALSAR and QuikSCAT• General patterns of spatial distribution of wind speed showed good agreement

with each other• No noises

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Assessment of Accuracy with QuikSCAT

• Wind Field from QuikSCAT • Wind Field from PALSAR

Scenes RMSE (m/s)

2008.01.29 2.20

Wind speed Mean (m/s)

QSCAT 6.50

PALSAR 6.26

• Subsampled PALSAR winds at QuikSCAT WVC

• Similar wind speed range (~6m/s)

• Not too high rms errors

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Wind Field from SIR-C/X SAR Image

(a) Location of SIR-C SAR image on the SST map and (b) distribution of wind field off the east coast of Korea from SIR-C SAR data by using CMOD4 algorithm (m/s).

(a) (b) • No noises• Fairly good rms errors

(<2m/s)• Detailed patial struc-

ture of wind speeds

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Error characteristics by wind directions

e.g. V > 10m/s, Maximum of wind speed er-ror induced by wind direc-tion : 6.09 m/s

• Strong dependence of wind speeds on the wind direction as input data

• Difference of wind direction between coastal and outsea regions

• MBL stability change-induced deflection of the wind direction

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How to eliminate the noises

on SAR Images ?

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DN Values

DN values ofALOS PALSAR ScanSAR2007. 07. 18 02:15:15 (UTC)(Center : 125.21ºE, 35.49ºN)

• Dark and Bright• Stripe- and Band-like Features• Irregularity

• Apparent on land

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Noise Removal

Investigation of their characteristics- Random, Irregular, Band-like Stripes

- Similarity along the range direction

Assumption :

- Normalized Radar Cross Section (σ0) val-

ues corresponding to the noises are almost

constant along the range direction

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Noise Reduction

Subsampling FFT analysis Band-pass Filtering

Retrieve the imageSpectrum from SAR im-age without any noises

Spectrum from SAR image with noises

Clear image after noise reduction

• Try & error process• Determination of the fre-

quency for band-pass fil-tering

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(a) Subimage with band-like noises, (b) the mean image of extracted noises from the spectrum, and (c) the filtered ScanSAR subimage

Noise ReductionOriginal Noise (a) - (b)

• Successful fil-tering of band-like noises

• Ships and Small scale oceanic fea-tures still re-mained

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Noise Reduction

Band-like noises in the original image almost removed However, discontinuity between the scans were still apparent. Further researches for more accurate field

Original Noise Filtered

Scenes RMSE (m/s)

Original 5.20

Scenes RMSE (m/s)

Noise Filtered 3.92

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Hypothesis High-resolution SAR wind field Might provide us with Low Wind

near the western coast of Korea in summer

Particularly at 3 dominant places

MBL Dynamics associated with stability changes

Sea surface Temperature Change

Tidal Currents and Mixing

Strong thermal stratification

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Coastal Wind Field

ERROR!

Real Feature ?

Nevertheless,Still Meaningful !

• The hypothesis seems to be correct

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Wind Field from ALOS PALSAR

Asiana Air OZ733July 26, 1993Gimpo to Mokpo Air-port68 /100 died

• induced by heavy sea fog• Seafog: SST difference ,strong tidal current, Tidal mixing

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Wind Field from ALOS PALSAR

Oil Spill by ENVISATDec 14, 2007

• Such a disastrous oil spill event occurred near Taean

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Effects of Tidal Front

(a) Wind field from ALOS PALSAR (2007. 07. 18 02:15:15 (UTC)) and (b) Contours of log(H/U3) in the spring tide

(a)(b)

• Low resolution

High-resolution under development

Expectation of detail structure co-incident with wind field

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Land-Air-Sea Interactions

from Scatterometer and SAR

Intensification of Winds through Land Orography

Characteristic Ekman Pumping Structure

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Schematic of air flow over coastal ranges

cold-air outbreak in winter

The mountain ranges along the North Korean and Russian

coasts reach heights of 1000m or higher, and are separated by

an orographic gap at Vladivostok

The wintertime synoptic weather pattern is dominated by the

Siberian high, which forces northerly or northwesterly

winds(cold-air outbreak) from the Asian continent over the JES

Beardsley et al.(2000),

Role of Wind Field has been paid no attention

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Ekman Pumping Variability

Fig. (a) Land topography,and (b) mean of Ekman pumping. Contour overlaid in (a) is mean of EKP. Contours with

zero EKP corresponds to the enter of strong winds along the wind direction, which seem to be affected by inten-

sified winds through shallow trough of land orography.

Miniature of Global OceanThe East/Japan Sea• Zero line of EKP coincides

with maximum wind speed.• Characteristic EKP structure• Hypothesis on air-sea-land in-

teraction

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VladivostokGap

Evidence of Orography-Induced Ekman Pumping Structure

Fig. Land topography, wind speed, and EKP along the Russian and North Korean coast. Zero value of EKP corresponds to the center of strong winds along the wind direction, which is produced by intensified winds through a shallow trough of land orography.

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Effects of Topography on SAR Image

Wind vectors from ECMWF reanalysis data off Primorye coast

Strong wind blows to the offshore in winter. SAR wind field : detailed spatial structure and elongated wind speed field.

Wind field from ALOS PALSAR (2008. 01. 29 01:26:07 (UTC))

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Wind field from PALSAR

Wind field from PALSAR / QuikSCAT

Wind field from QuikSCAT

• PALSAR winds : Small-scale, detail features • QuikSCAT winds : Similar to SAR Wind, low resolution No observation along the coast.

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Influence of Land Orography on Winds

Relationship along-coast wind speed and land elevation (< 50 km)

• Subset : along-coast topography, mean of wind speeds along offshore direction• Negative Relationship• As land elevations are lower, so the wind speeds tend to increase• Confirmed the potential impact of land orography on the EKP structure.

R = -0.7395

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Summary & Conclusion

In this study, we retrieved the high-resolution wind fields along the coast of Korea

from SAR images and assessed the accuracy of wind vectors.

We found some noisy signals, but still PALSAR ScanSAR images provide us

some meaningful ocean signal.

Winds at the coastal region were significantly low relative to those in the outsea.

This supports our hypothesis on winds, SSTs, tides, and MBL dynamics.

We could find an evidence on Land-Air-Sea Interactions through the relationship

between land orography and characteristic EKP structure by the intensification of

wind speed change through the orographic gaps.

In order to use SAR wind field for diverse purposes, the wind errors and causes

should be beforehand specified and understood regionally and globally.

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