Radar backscatter across the Gulf Stream sea surface temperature front

2000 ◽  
Vol 38 (2) ◽  
pp. 926-941 ◽  
Author(s):  
S.V. Nghiem ◽  
F.K. Li ◽  
E.J. Walsh ◽  
Shu-Hsiang Lou
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Gulf Stream ◽  
Sea Surface ◽  
Radar Backscatter ◽  
Temperature Front

Low-Level Cloud Response to the Gulf Stream Front in Winter Using CALIPSO*

2014 ◽  
Vol 27 (12) ◽  
pp. 4421-4432 ◽  
Author(s):  
Jing-Wu Liu ◽  
Shang-Ping Xie ◽  
Joel R. Norris ◽  
Su-Ping Zhang
Keyword(s):  
Boundary Layer ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Gulf Stream ◽  
Satellite Observations ◽  
Sea Surface ◽  
Warm Water ◽  
Low Level ◽  
Temperature Front ◽  
The Cross

Abstract A sharp sea surface temperature front develops between the warm water of the Gulf Stream and cold continental shelf water in boreal winter. This front has a substantial impact on the marine boundary layer. The present study analyzes and synthesizes satellite observations and reanalysis data to examine how the sea surface temperature front influences the three-dimensional structure of low-level clouds. The Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite captures a sharp low-level cloud transition across the Gulf Stream front, a structure frequently observed under the northerly condition. Low-level cloud top (<4 km) increases by about 500 m from the cold to the warm flank of the front. The sea surface temperature front induces a secondary low-level circulation through sea level pressure adjustment with ascending motion over the warm water and descending motion over cold water. The secondary circulation further contributes to the cross-frontal transition of low-level clouds. Composite analysis shows that surface meridional advection over the front plays an important role in the development of the marine atmospheric boundary layer and low-level clouds. Under cold northerly advection over the Gulf Stream front, strong near-surface instability leads to a well-mixed boundary layer over the Gulf Stream, causing southward deepening of low-level clouds across the sea surface temperature front. Moreover, the front affects the freezing level by transferring heat to the atmosphere and therefore influences the cross-frontal variation of the cloud phase.

scholarly journals Impact of a Narrow Coastal Bay of Bengal Sea Surface Temperature Front on an Indian Summer Monsoon Simulation

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Dhrubajyoti Samanta ◽  
Saji N. Hameed ◽  
Dachao Jin ◽  
Vishnu Thilakan ◽  
Malay Ganai ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Bay Of Bengal ◽  
Sea Surface ◽  
Temperature Front ◽  
Coastal Bay

Air-sea fluxes and surface layer turbulence around a sea surface temperature front

1991 ◽  
Vol 96 (C5) ◽  
pp. 8593 ◽  
Author(s):  
C. A. Friehe ◽  
W. J. Shaw ◽  
D. P. Rogers ◽  
K. L. Davidson ◽  
W. G. Large ◽  
...  
Keyword(s):  
Surface Layer ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Temperature Front

scholarly journals Comparison of Satellite-Derived Sea Surface Temperature and Sea Surface Salinity Gradients Using the Saildrone California/Baja and North Atlantic Gulf Stream Deployments

2020 ◽  
Vol 12 (11) ◽  
pp. 1839 ◽  
Author(s):  
Jorge Vazquez-Cuervo ◽  
Jose Gomez-Valdes ◽  
Marouan Bouali
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Atlantic ◽  
Gulf Stream ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Temporal Sampling ◽  
The North

Validation of satellite-based retrieval of ocean parameters like Sea Surface Temperature (SST) and Sea Surface Salinity (SSS) is commonly done via statistical comparison with in situ measurements. Because in situ observations derived from coastal/tropical moored buoys and Argo floats are only representatives of one specific geographical point, they cannot be used to measure spatial gradients of ocean parameters (i.e., two-dimensional vectors). In this study, we exploit the high temporal sampling of the unmanned surface vehicle (USV) Saildrone (i.e., one measurement per minute) and describe a methodology to compare the magnitude of SST and SSS gradients derived from satellite-based products with those captured by Saildrone. Using two Saildrone campaigns conducted in the California/Baja region in 2018 and in the North Atlantic Gulf Stream in 2019, we compare the magnitude of gradients derived from six different GHRSST Level 4 SST (MUR, OSTIA, CMC, K10, REMSS, and DMI) and two SSS (JPLSMAP, RSS40km) datasets. While results indicate strong consistency between Saildrone- and satellite-based observations of SST and SSS, this is not the case for derived gradients with correlations lower than 0.4 for SST and 0.1 for SSS products.

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