spaceborne synthetic aperture radar (sar) applications in marine meteorology xiaofeng li noaa/nesdis...

Spaceborne synthetic aperture radar (SAR) applications in marine meteorology

Xiaofeng Li

NOAA/NESDIS

AcknowledgmentZheng Weizhong and William Pichel, NOAA/NESDISXiaofeng Yang, Institute of Remote Sensing Application, CAS

NOAA Gilmore Creek Ground Station, Alaska

Outline

Motivation

SAR Observation and WRF model simulation of Marine Atmospheric Boundary Layer (MABL) phenomena

1) Atmospheric Gravity Waves

2) Atmospheric Vortex Streets

3) Katabatic Winds

4) Storm pattern

Summary

Motivation

SAR Provides high resolution (tens to hundreds m) all day/night synoptic observation of ocean surface.

Community weather model now provides time series of sub-km actual atmospheric circulation fields.

Synergy of the two to understand the actual atmospheric conditions that leadTo the generation and evolution of these phenomena in the MABL.

SAR applications in Marine meteorology

atmospheric lee waves atmospheric disturbances atmospheric boundary layer rolls atmospheric fronts katabatic winds, gap winds Hurricanes island wakes cold air outbreaks Storms atmospheric vortex streets Land breeze Cloud line …

1. Atmospheric Gravity Wave Observations

Upstream Waves: Waves propagates against the mean flow

Lee wave has two types of wave patterns:

1. the transverse wave type where the wave crests are nearly perpendicular to the wind direction

2. (2) the diverging wave type where the wave crests are orientated outwards from the center of the wake.

Upstream waves


Upstream waves (2)

Wind variations are between 8 (wave trough)and 16 m/s (wave crest).


Upstream waves 3

06/06/2001@COPYRIGHT CSA


The number of wave crests increases from 3 to 8 in 4.5 hrs.

Upstream AGW can be understood by solving the FeKdV Model with Froude number f=1.1 Li, et al. 2004, JGR


A RADARSAT ScanSAR wide B SAR Western AlaskaImage center (60N, 145W) 03:10:05 GMT, June 12, 2001.

(© Canadian Space Agency, 2001)

Win

d Dire

ction

Lee Wave (transverse waves)


RADARSAT ScanSAR wide image shows the island lee wave pattern in the Gulf of Alaska.

• Image center: (55N, 154W) • Time16:29:42 UTC, June 27,

1997. (© CSA, 1997)

Wind Direction

Lee Wave (Diverging waves)


Lee Wave (diverging waves, Example 2)W

ind

Dire

ctio

n

Constant lee wave phase linesChunchuzov, Vachon, and Li, Remote Sensing of Environment, 74, 343-361, 2000.



Lee Wave 3

Lee wave simulation with WRFWeather Research and ForecastingNCAR Community modelTwo-way nested domains:D1: 9km 280 x 251D2: 3km 310 x 301D3: 1km 271 x 262Vertical levels: 27

Model parameterization: • Rapid Radiative Transfer Model (RRTM) longwave

radiation • Dudhia shortwave radiation• Yonsei University (YSU) planetary boundary layer

scheme• WRF Single Moment 3‐Class (WSM)

cloudmicrophysics, • Kain‐Fritsch (new Eta) convective

parameterization employed only in coarse and medium domains,

• Monin‐Obukhov surface‐layer scheme• Noah land‐surface model.

Boundary conditions are specified by linearly interpolating the NCEP 6 hourly final analyses (FNL) at a resolution of 1° × 1° degree.

The digital elevation of 30 s USGS topography data.



WRF Simulation results at the imaging time

Vertical velocity

Horizontal velocity


Standing WavesMODIS true color image acquired about 8.5 h prior to the Envisat ASAR pass in Google Earth.

Lee Wave 3


Lee Wave 4

Not trapped in the MABL


Lee Wave 4

Comparison of WRF simulated surface wind speed with the independent SAR measurements

AGW Summary

AGM patterns can be identified on SAR image.

Most of the waves generated by flow over bump observed by SAR are on the lee side of the bump, and has two types of wave patterns.

The terrain-forced stmospheric lee waves can be simulated using the WRF model. Model reveals evolution of the AGW.

Upstream waves happen when Froude number is close to 1. They are elevation waves. They are explained well with FeKDV model.


2. Atmospheric Vortex Streets (AVS)

Atmospheric vortex-street patterns on the lee side of a flow obstacle double row of counter rotating vortex pairs shedding alternately near the

edge of the obstacle No observation in the atmosphere prior to the satellite age due to AVS

scale (100-400 km): too small to be delineated by a synoptic observation network and too large to be observed by a single station

h/a is the basic property of an atmospheric vortex streets Uo is the wind speed, Ue is the vortex shedding velocity

NASA space shuttle picture cloud pattern (1)

NASA space shuttle picture cloud pattern (2)


Landsat-7 (Defelice et al. Vol. 81,No.5, 1047-1048, BAMS, 2000)-cloud

pattern

Aircraft photo (Ferrier et al. Vol. 17,

No. 1, 1-8, International J. of Remote

Sensing, 1996)- sediment pattern

SAR Wind Pattern. IEEE/TGARSSFeb. 2004


ATMOSPHERIC VORTEX STREETS OBSERVED ON

REMOTE SENSING IMAGES (3)

RADARSAT synthetic aperture radar (SAR) image (© CSA, 1999)

RADARSAT synthetic aperture radar (SAR) image (© CSA, 1999)

Li, et al. 2002, GRL

SAR observation of AVS

Li, et al. 2008, Sensors


WRF Simulation of AVS

Li, et al. 2008, Sensors


WRF Simulation of AVS

• Vortex shedding rate and propagation velocity

•Reynolds Number (50-250)

•Frude Number (0.15-0.4)

•Vorticity and energy dissipation


3. Katabatic Wind

katabatic wind is a gravitational air flow that descends from a high-elevation mountain down slope to lower elevation.

Happens night and early morning hours in the winter season when the air mass over the mountain top becomes colder and heavier due to fast radiation cooling and when the land-sea temperature gradient is large.

3. Katabatic Wind

hourly coastal horizontal wind speed

3. Katabatic Wind

The black solid line is the topography; the red dash line represents the horizontal wind speed simulated by the model, the blue line represents the sea surface wind derived from SAR measurements, and the green dash line represents the near surface descending wind speed

3. Katabatic Wind

• Summary:

• The wind associated with the katabatic wind varies between 5 and 8 m/s

• The katabatic wind finger extends up to 20 km offshore.

• The 3-layer nested weather model simulation captures the finger-like katabatic wind pattern

observed in the SAR image.

• Katabatic wind is the strongest at 14:00 UTC when the land-sea temperature gradient is the

largest.

• The low-level model wind speed is very close to that derived from the SAR image.

• The SAR image shows a more detailed finger-like katabatic wind structure than that shown in the

• model simulation.

4 Storm and Precipitation

4 Storm and Precipitation

Storm Summary:

WRF can capture wind and rain pattern in the storm

Heavy rain in the hurricanes damps NRCS.

Moderate rain has less effect in C-band NRCS than wind does in the regular storm case

5 Summary

We have set up WRF model to simulate SAR observed MABL phenomena

WRF model captures the basic characteristics AGV, AVS, Katabatic and Storm

The 1-km resolution WRF model gives detailed structures of the phenomena

This leads to the understanding of generation and evolution of these phenomena

Synergy of SAR and WFR provides great opportunity for detailed study of MABLPhenomena

spaceborne synthetic aperture radar (sar) applications in marine meteorology xiaofeng li noaa/nesdis...

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