scholarly journals In situ validation of sea surface temperatures from the GCOM-W1 AMSR2 RSS calibrated brightness temperatures

2015 ◽  
Vol 120 (5) ◽  
pp. 3567-3585 ◽  
Author(s):  
Chelle L. Gentemann ◽  
Kyle A. Hilburn
Keyword(s):  
Sea Surface ◽  
Sea Surface Temperatures ◽  
Brightness Temperatures ◽  
Surface Temperatures

Long-term comparison of satellite and in-situ sea surface temperatures around the Korean Peninsula

2015 ◽  
Vol 50 (1) ◽  
pp. 109-117 ◽  
Author(s):  
Myeong-Taek Kwak ◽  
Gwang-Ho Seo ◽  
Yang-Ki Cho ◽  
Bong-Guk Kim ◽  
Sung Hyup You ◽  
...  
Keyword(s):  
Korean Peninsula ◽  
Sea Surface ◽  
Sea Surface Temperatures ◽  
Surface Temperatures

Cloud Detection with MODIS. Part I: Improvements in the MODIS Cloud Mask for Collection 5

2008 ◽  
Vol 25 (7) ◽  
pp. 1057-1072 ◽  
Author(s):  
Richard A. Frey ◽  
Steven A. Ackerman ◽  
Yinghui Liu ◽  
Kathleen I. Strabala ◽  
Hong Zhang ◽  
...  
Keyword(s):  
Near Infrared ◽  
Sea Surface ◽  
Sea Surface Temperatures ◽  
Cloud Detection ◽  
Stream Data ◽  
Water Vapor Absorption ◽  
Brightness Temperatures ◽  
Surface Temperatures ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Mask

Abstract Significant improvements have been made to the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask (MOD35 and MYD35) for Collection 5 reprocessing and forward stream data production. Most of the modifications are realized for nighttime scenes where polar and oceanic regions will see marked improvement. For polar night scenes, two new spectral tests using the 7.2-μm water vapor absorption band have been added as well as updates to the 3.9–12- and 11–12-μm cloud tests. More non-MODIS ancillary input data have been added. Land and sea surface temperature maps provide crucial information for mid- and low-level cloud detection and lessen dependence on ocean brightness temperature variability tests. Sun-glint areas are also improved by use of sea surface temperatures to aid in resolving observations with conflicting cloud versus clear-sky signals, where visible and near-infrared (NIR) reflectances are high, but infrared brightness temperatures are relatively warm. Day and night Arctic cloud frequency results are compared to those created by the Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder-Extended (APP-X) algorithm. Day versus night sea surface temperatures derived from MODIS radiances and using only the MODIS cloud mask for cloud screening are contrasted. Frequencies of cloud from sun-glint regions are shown as a function of sun-glint angle to gain a sense of cloud mask quality in those regions. Continuing validation activities are described in Part II of this paper.

scholarly journals Influence of Upwelling in the Southern Waters of Java on CO2 Concentration in Kototabang, Agam District West

2020 ◽  
Vol 5 (1) ◽  
pp. 8
Author(s):  
Martono Martono ◽  
Fanny Aditya Putri
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Descriptive Analysis ◽  
Co2 Concentration ◽  
Sea Surface ◽  
Sea Surface Temperatures ◽  
Chlorophyll A Concentration ◽  
Surface Temperatures

<p>Absorption of atmospheric CO<sub>2</sub> by the sea through two processes, namely solubility pumps and biological pumps. This study aims to determine the effect of upwelling in the southern waters of Java on atmospheric CO<sub>2</sub> concentrations in Kototabang. The data used are in situ CO<sub>2</sub> concentration, sea surface temperature and chlorophyll-a concentration from 2004-2016. The method used was descriptive analysis. The results showed that upwelling that occurred during JJA-SON caused a decrease in sea surface temperature to 26.8 °C and 27.1 °C respectively, as well as an increase chlorophyll-a concentration to 2.03 mg/m<sup>3</sup> and 2.19 mg/m<sup>3</sup>. In both seasons CO<sub>2</sub> concentration in Kototabang dropped to 385.8 ppm and 385.4 ppm. Meanwhile, when there was no upwelling during DJF-MAM, sea surface temperatures rose to 28.8 °C and 29.0 °C, and chlorophyll-a concentration dropped to 0.32 mg/m<sup>3</sup> and 0.54 mg/m<sup>3</sup>. CO<sub>2</sub> concentration in DJF and MAM increased to 386.3 ppm and 386.5 ppm. Based on these results it is known that when upwelling occurs, CO<sub>2</sub> concentration decrease and vice versa.</p>

scholarly journals High-Resolution Sea Surface Temperatures Derived from Landsat 8: A Study of Submesoscale Frontal Structures on the Pacific Shelf off the Hokkaido Coast, Japan

2020 ◽  
Vol 12 (20) ◽  
pp. 3326
Author(s):  
Hiroshi Kuroda ◽  
Yuko Toya
Keyword(s):  
Spatial Distribution ◽  
Ocean Model ◽  
Sea Surface ◽  
Basic Question ◽  
Landsat 8 ◽  
Sea Surface Temperatures ◽  
Surface Temperatures ◽  
The Pacific ◽  
The Difference

Coastal and offshore waters are generally separated by a barrier or “ocean front” on the continental shelf. A basic question arises as to what the representative spatial scale across the front may be. To answer this question, we simply corrected skin sea surface temperatures (SSTs) estimated from Landsat 8 imagery with a resolution of 100 m using skin SSTs estimated from geostationary meteorological satellite Himawari 8 with a resolution of 2 km. We analyzed snapshot images of skin SSTs on 13 October 2016, when we performed a simultaneous ship survey. We focused in particular on submesoscale thermal fronts on the Pacific shelf off the southeastern coast of Hokkaido, Japan. The overall spatial distribution of skin SSTs was consistent between Landsat 8 and Himawari 8; however, the spatial distribution of horizontal gradients of skin SSTs differed greatly between the two datasets. Some parts of strong fronts on the order of 1 °C km−1 were underestimated with Himawari 8, mainly because of low resolution, whereas weak fronts on the order of 0.1 °C km−1 were obscured in the Landsat 8 imagery because the signal-to-noise ratios were low. The widths of the strong fronts were estimated to be 114–461 m via Landsat 8 imagery and 539–1050 m via in situ ship survey. The difference was probably attributable to the difference in measurement depth of the SST, i.e., about 10-μm skin layer by satellite and a few dozen centimeters below the sea surface by the in situ survey. Our results indicated that an ocean model with a grid size of no more than ≤100–200 m is essential for realistic simulation of the frontal structure on the shelf.

scholarly journals The timescale and extent of thermal expansion of the global ocean due to climate change

Ocean Science ◽  
2010 ◽  
Vol 6 (1) ◽  
pp. 179-184 ◽  
Author(s):  
S. Marčelja
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Temperature Variation ◽  
Sea Level ◽  
Heat Content ◽  
Sea Surface ◽  
Sea Surface Temperatures ◽  
The Past ◽  
Surface Temperatures

Abstract. With recently improved instrumental accuracy, the change in the heat content of the oceans and the corresponding contribution to the change of the sea level can be determined from in situ measurements of temperature variation with depth. Nevertheless, it would be favourable if the same changes could be evaluated from just the sea surface temperatures because the past record could then be reconstructed and future scenarios explored. Using a single column model we show that the average change in the heat content of the oceans and the corresponding contribution to a global change in the sea level can be evaluated from the past sea surface temperatures. The calculation is based on the time-dependent diffusion equation with the known fixed average upwelling velocity and eddy diffusivity, as determined from the steady-state limit. In this limit, the model reduces to the 1966 Munk profile of the potential temperature variation as a function of depth. There are no adjustable parameters in the calculation and the results are in good agreement with the estimates obtained from the in situ data. The method allows us to obtain relevant timescales and average temperature profiles. The evaluation of the thermosteric sea level change is extended back to the beginning of accurate sea surface temperature records. The changes in sea surface temperature from 1880 until the present time are estimated to have produced a thermosteric sea level rise of 35 mm. Application to future IPCC scenarios gives results similar to the average prediction of more complex climate models.

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