In situ angular measurements of thermal infrared sea surface emissivity—Validation of models

2005 ◽  
Vol 94 (1) ◽  
pp. 83-93 ◽  
Author(s):  
Raquel Niclòs ◽  
Enric Valor ◽  
Vicente Caselles ◽  
César Coll ◽  
Juan Manuel Sánchez
Keyword(s):  
Thermal Infrared ◽  
Sea Surface ◽  
Surface Emissivity ◽  
Validation Of Models ◽  
Angular Measurements

Temperature and salinity dependence of sea surface emissivity in the thermal infrared

2005 ◽  
Vol 131 (610) ◽  
pp. 2539-2557 ◽  
Author(s):  
S. M. Newman ◽  
J. A. Smith ◽  
M. D. Glew ◽  
S. M. Rogers ◽  
J. P. Taylor
Keyword(s):  
Thermal Infrared ◽  
Sea Surface ◽  
Surface Emissivity

Sea surface emissivity angular measurements: comparison with theoretical models

2004 ◽  
Author(s):  
Raquel R. Niclos ◽  
Enric Valor ◽  
Vicente Caselles ◽  
Cesar Coll
Keyword(s):  
Theoretical Models ◽  
Sea Surface ◽  
Surface Emissivity ◽  
Angular Measurements

scholarly journals Autonomous Measurements of Sea Surface Temperature Using In Situ Thermal Infrared Data

2004 ◽  
Vol 21 (4) ◽  
pp. 683-692 ◽  
Author(s):  
Raquel Niclòs ◽  
Vicente Caselles ◽  
César Coll ◽  
Enric Valor ◽  
Eva Rubio
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Thermal Infrared ◽  
Sea Surface ◽  
Infrared Data

Evaluation of reanalysis and satellite-based sea surface winds using in situ measurements from Chinese Antarctic Expeditions

2013 ◽  
Vol 24 (3) ◽  
pp. 147
Author(s):  
Ming LI ◽  
Qinghua YANG ◽  
Jiechen ZHAO ◽  
Lin ZHANG ◽  
Chunhua LI ◽  
...  
Keyword(s):  
In Situ Measurements ◽  
Sea Surface ◽  
Surface Winds ◽  
Sea Surface Winds

scholarly journals Influence of Oceanic Parameters on Aquarius L-Band Sea Surface Emissivity

2021 ◽  
Vol 1961 (1) ◽  
pp. 012065
Author(s):  
Yanyan Li ◽  
Zhenzhan Wang ◽  
Yiqiang Hu ◽  
Xiaolin Tong
Keyword(s):  
Sea Surface ◽  
Surface Emissivity ◽  
L Band

scholarly journals Intercomparison of Global Sea Surface Salinity from Multiple Datasets over 2011–2018

2021 ◽  
Vol 13 (4) ◽  
pp. 811
Author(s):  
Hao Liu ◽  
Zexun Wei
Keyword(s):  
Time Scales ◽  
Correlation Coefficients ◽  
Dominant Mode ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Ocean Data Assimilation ◽  
Multiple Datasets ◽  
Different Time Scales

The variability in sea surface salinity (SSS) on different time scales plays an important role in associated oceanic or climate processes. In this study, we compare the SSS on sub-annual, annual, and interannual time scales among ten datasets, including in situ-based and satellite-based SSS products over 2011–2018. Furthermore, the dominant mode on different time scales is compared using the empirical orthogonal function (EOF). Our results show that the largest spread of ten products occurs on the sub-annual time scale. High correlation coefficients (0.6~0.95) are found in the global mean annual and interannual SSSs between individual products and the ensemble mean. Furthermore, this study shows good agreement among the ten datasets in representing the dominant mode of SSS on the annual and interannual time scales. This analysis provides information on the consistency and discrepancy of datasets to guide future use, such as improvements to ocean data assimilation and the quality of satellite-based data.

Low Wave Number Radar Image Energy Influence on Determining Current

2012 ◽  
Vol 433-440 ◽  
pp. 6054-6059
Author(s):  
Gan Nan Yuan ◽  
Rui Cai Jia ◽  
Yun Tao Dai ◽  
Ying Li
Keyword(s):  
Wave Spectrum ◽  
Surface Current ◽  
Sea Surface ◽  
Radar Image ◽  
Wave Number ◽  
Sea State ◽  
Low Frequencies ◽  
In Situ Data ◽  
Main Effects

In the radar imaging mechanism different phenomena are present, as a result the radar image is not a direct representation of the sea state. In analyzing radar image spectra, it can be realized that all of these phenomena produce distortions in the wave spectrum. The main effects are more energy for very low frequencies. This work investigates the structure of the sea clutter spectrum, and analysis the low wave number energy influence on determining sea surface current. Then the radar measure current is validated by experiments. By comparing with the in situ data, we know that the radar results reversed by image spectrum without low wave number spectrum have high precision. The low wave number energy influent determining current seriously.

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