Estimating Convective Atmospheric Boundary Layer Depth from Microwave Radar Imagery of the Sea Surface

Sikora, Todd D.; Young, George S.; Shirer, Hampton N.; Chapman, R.D.

doi:10.1175/1520-0450(1997)036<0833:ecabld>2.0.co;2

Cited by 27 publications

(15 citation statements)

References 38 publications

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“…Scientific literature about SAR images over the ocean has shown a variety of geophysical phenomena detectable by SAR (Alpers & Brümmer, 1994;Kravtsov et al, 1999;Mitnik et al, 1996;Mityagina et al, 1998;Mourad, 1996;Sikora et al, 1997;Zecchetto et al, 1998), including the multiscale structure in the atmospheric turbulence under high winds and the structure of the convective turbulence under low wind. More recently, some effort has been devoted to evaluate the wind direction, using the backscatter signatures produced by the atmospheric wind rolls or those occurring at the lee side of islands (Vachon & Dobson, 2000) as effect of wind shielding, by computing the local gradient of the image backscatter (Horstmann et al, 2002;Koch, 2004) or by using the two dimensional Continuous Wavelet Transform (CWT2) (Zecchetto & De Biasio, 2002;Zecchetto & De Biasio, 2008).…”

Section: Small-scale Structure Of the Mabl From Sar Imagesmentioning

confidence: 99%

“…13, where two directions are evidenced: that of the maximum energy, occurring at a peak wavelength of 8350 m and an aliased direction of propagation of 296 • , and a secondary one, due to the presence of different atmospheric gravity wave trains in the image, with a peak wavelength of 16.7 km and a direction of 63 • . These information may be used, as in Sikora et al (1997), to estimate the vertical thickness of the MABL. …”

Section: A Case Studymentioning

confidence: 99%

See 1 more Smart Citation

Ocean Wind Fields from Satellite Active Microwave Sensors

Zecchetto¹

2010

Geoscience and Remote Sensing New Achievements

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Section: Small-scale Structure Of the Mabl From Sar Imagesmentioning

confidence: 99%

Section: A Case Studymentioning

confidence: 99%

Ocean Wind Fields from Satellite Active Microwave Sensors

Zecchetto¹

2010

Geoscience and Remote Sensing New Achievements

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“…The depth of a convective MABL was estimated by using spectral peaks along the mean wind direction to discern a typical wavelength for the mottled features [Sikora et al, 1997]. Young et al [2000] attempted to calculate turbulence and stability statistics from SAR via similarity theories in MABL.…”

Section: Introductionmentioning

confidence: 99%

On polarimetric characteristics in SAR images of mesoscale cellular convection in the marine atmospheric boundary layer

Perrie

Guo

et al. 2011

J. Geophys. Res.

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Convection is an important phenomenon in the marine atmospheric boundary layer (MABL). Previous spaceborne radar studies of such have been limited to single polarization data, and therefore their focus was on the variation in intensity of the radar return, which was constrained by the existence of a single polarization image pattern, representing different atmospheric and oceanic phenomena. In this paper, we study the polarimetric characteristics of mesoscale cellular convection (MCC) in the MABL using high‐resolution data from fully polarimetric (HH, VV, HV, and VH) RADARSAT‐2 (RS‐2) synthetic aperture radar (SAR) images, in conjunction with closely collocated mesoscale atmospheric model simulations, to identify the MCC signatures. To compare the polarimetric characteristics of MCC with those of the ocean surface, our analysis also includes 641 open ocean surface quad‐polarization RS‐2 SAR images collocated with 52 National Data Buoy Center buoys. The open ocean surface SAR images exhibit different polarimetric characteristics from those of MCC. Thus, we differentiate MCC from other open ocean phenomena, based on identifiable polarimetric SAR characteristics.

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“…This variance (q), combined with the SAR-derived MABL depth estimate (z,) (via the technique presented in [5]) and the SAR-derived friction velocity (U,) (via the wind imagery), is used to calculate an Obukhov…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, this SAR's imagery has the potential to be employed as a tool to help study the MABL because of its potential to sense the sea surface footprints of convection. References [3], [4], and [5] (among others) provide evidence of this promise. References [3] and [5] show that a typical field of three-dimensional convection will result in a mottled appearance on the SAR imagery.…”

Section: Njxoductionmentioning

confidence: 99%

On the extraction of atmospheric structure from synthetic aperture radar imagery

Sikora

Bleidorn²,

Thompson³

IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293)

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NJXODUCTIONWhen the marine atmospheric boundary layer (MABL) is statically unstable, momentum flux towards the sea surface is largely accomplished within convective downdrafts while momentum flux upwards is largely accomplished within convective updrafts ([l], [2]). In addition, [2] has shown that within individual updraft and downdraft events, the momentum flux is asymmetric along the axis of the mean wind. Larger positive (negative) momentum flux is found along the down-mean-wind edge of downdrafts (updrafts). This asymmetry in momentum flux across an updraft/ downdraft couplet can result in asymmetry in the generation of cm-scale gravity waves beneath the bases of updraft/ downdraft couplets.C-band synthetic aperture radar (SAR), such as that aboard the Canadian Space Agency satellite RADARSAT, is sensitive to cm-scale sea surface roughening. Therefore, this SAR's imagery has the potential to be employed as a tool to help study the MABL because of its potential to sense the sea surface footprints of convection. References [3], [4], and [5] (among others) provide evidence of this promise. References [3] and [5] show that a typical field of three-dimensional convection will result in a mottled appearance on the SAR imagery.Reference [4] shows that two-dimensional convection will result in linear patterns on the SAR imagery. The current study concentrates on the former type of convection.The aforementioned SAR imagery can be converted to 10 m neutral wind imagery using a transfer function as demonstrated in [6] and [7]. If one is to employ SAR 10 m neutral wind imagery in the study of MABL processes such as convection, a logical next step given that presented in [3], [4], and [5], the resolution of the imagery needs to be on order 100 m. This is because the scale of the dominant MABL convection is often on order 100 m. Reference [8] and the current study attempts to employ order 100 m S A R 10 m neutral wind imagery for just such a purpose. Reference [8] presents an algorithm based on Monin-Obukhov and mixed-layer similarity theory which attempts to correct the above-mentioned 10 m neutral wind imagery in the presence of statically unstable MABLs and to calculate several MABL statistics. Monin-Obukhov similarity theory relates a wide variety of atmospheric surface layer turbulence statistics to the static stability of the surface layer. Mixed layer similarity theory plays the same role in the remainder of the atmospheric boundary layer. Turbulence-scale horizontal variability of wind speed is related to surface layer static stability through a combination of these two theories [9]. Thus, application of these standard similarity theories to SAR-derived wind speed statistics yields a static stability estimate that can be used to correct the wind speed statistics.Reference [8]'s data set was limited to low wind speed and small air-sea temperature difference environments. The current study extends the work of [8] to a wider range of wind speeds and air-sea temperature differences. No in situ turbulence data were conc...

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Estimating Convective Atmospheric Boundary Layer Depth from Microwave Radar Imagery of the Sea Surface

Cited by 27 publications

References 38 publications

Ocean Wind Fields from Satellite Active Microwave Sensors

Ocean Wind Fields from Satellite Active Microwave Sensors

On polarimetric characteristics in SAR images of mesoscale cellular convection in the marine atmospheric boundary layer

On the extraction of atmospheric structure from synthetic aperture radar imagery

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