Validation of Satellite Scatterometer Sea-Surface Wind Vectors (MetOp-A/B ASCAT) in the Korean Coastal Region

2021 ◽  
Vol 42 (5) ◽  
pp. 536-555
Author(s):  
Byeong-Dae Kwak ◽  
◽  
Kyung-Ae Park ◽  
Hye-Jin Woo ◽  
Hee-Young Kim ◽  
...  
2012 ◽  
Vol 500 ◽  
pp. 550-555
Author(s):  
Feng Feng Chen ◽  
Wei Gen Huang ◽  
Jing Song Yang

Synthetic aperture radar (SAR) on aboard Chinese Huan Jing (HJ)-1C satellite has been planed to be launched in 2010. The satellite will fly in a sun-synchronous polar orbit of about 500-km altitude. SAR will operate in S band with HH polarization. Its image mode has the incidence angles 25°and 47°at the near and far sides of the swath respectively. SAR image has a spatial resolution of 20 m with a swath of 100 km. Here, the sea surface wind mapping capability of the SAR in the Chinese Coastal Region has been examined using M4S radar imaging model developed by Romeiser et al. The model is based on Bragg scattering theory in a composite surface model expansion. It accounts for contributions of the full ocean wave spectrum to the radar backscatter from ocean surface. The model reproduces absolute normalized radar cross section (NRCS) values for wide ranges of wind speeds. The model results of HJ-1C SAR have been compared with the model results of Envisat and Radarsat SAR signals. It shows that HJ-1C SAR is as good as both Envisat ASAR and Radarsat SAR at sea surface wind mapping Capability.


2012 ◽  
Vol 50 (7) ◽  
pp. 2901-2909 ◽  
Author(s):  
Alexis A. Mouche ◽  
Fabrice Collard ◽  
Bertrand Chapron ◽  
Knut-Frode Dagestad ◽  
Gilles Guitton ◽  
...  

2019 ◽  
Vol 11 (9) ◽  
pp. 1112
Author(s):  
Guoqing Han ◽  
Changming Dong ◽  
Junde Li ◽  
Jingsong Yang ◽  
Qingyue Wang ◽  
...  

Based on both satellite remote sensing sea surface temperature (SST) data and numerical model results, SST warming differences in the Mozambique Channel (MC) west of the Madagascar Island (MI) were found with respect to the SST east of the MI along the same latitude. The mean SST west of the MI is up to about 3.0 °C warmer than that east of the MI. The SST differences exist all year round and the maximum value appears in October. The area of the highest SST is located in the northern part of the MC. Potential factors causing the SST anomalies could be sea surface wind, heat flux and oceanic flow advection. The presence of the MI results in weakening wind in the MC and in turn causes weakening of the mixing in the upper oceans, thus the surface mixed layer depth becomes shallower. There is more precipitation on the east of the MI than that inside the MC because of the orographic effects. Different precipitation patterns and types of clouds result in different solar radiant heat fluxes across both sides of the MI. Warm water advected from the equatorial area also contribute to the SST warm anomalies.


2004 ◽  
Vol 1 (6) ◽  
pp. 137-143 ◽  
Author(s):  
Alexey Nekrasov ◽  
Jacco J.M. de Wit ◽  
Peter Hoogeboom

2002 ◽  
Vol 124 (3) ◽  
pp. 169-172 ◽  
Author(s):  
Dag Myrhaug ◽  
Olav H. Slaattelid

The paper considers the effects of sea roughness and atmospheric stability on the sea surface wind stress over waves, which are in local equilibrium with the wind, by using the logarithmic boundary layer profile including a stability function, as well as adopting some commonly used sea surface roughness formulations. The engineering relevance of the results is also discussed.


2011 ◽  
Vol 29 (2) ◽  
pp. 393-399
Author(s):  
T. I. Tarkhova ◽  
M. S. Permyakov ◽  
E. Yu. Potalova ◽  
V. I. Semykin

Abstract. Sea surface wind perturbations over sea surface temperature (SST) cold anomalies over the Kashevarov Bank (KB) of the Okhotsk Sea are analyzed using satellite (AMSR-E and QuikSCAT) data during the summer-autumn period of 2006–2009. It is shown, that frequency of cases of wind speed decreasing over a cold spot in August–September reaches up to 67%. In the cold spot center SST cold anomalies reached 10.5 °C and wind speed lowered down to ~7 m s−1 relative its value on the periphery. The wind difference between a periphery and a centre of the cold spot is proportional to SST difference with the correlations 0.5 for daily satellite passes data, 0.66 for 3-day mean data and 0.9 for monthly ones. For all types of data the coefficient of proportionality consists of ~0.3 m s−1 on 1 °C.


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