Comparison of Sea Surface Temperature from Oceanic Buoys and Satellite Microwave Measurements in the Western Coastal Region of Korean Peninsula

2018 ◽  
Vol 39 (6) ◽  
pp. 555-567 ◽  
Author(s):  
Hee-Young Kim ◽  
◽  
Kyung-Ae Park
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Korean Peninsula ◽  
Coastal Region ◽  
Sea Surface ◽  
Microwave Measurements ◽  
Satellite Microwave ◽  
Satellite Microwave Measurements

scholarly journals The Effect of Variable Sea Surface Temperature on Forecasting Sea Fog and Sea Breezes: A Case Study

2012 ◽  
Vol 51 (5) ◽  
pp. 986-990 ◽  
Author(s):  
Yongming Tang
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Coastal Region ◽  
Weather Forecast ◽  
Sea Breeze ◽  
Forecast Model ◽  
Sea Surface ◽  
Sea Breezes ◽  
Shelf Sea ◽  
Numerical Weather Forecast

AbstractA preliminary study of the effect of sea surface temperature (SST) temporal and spatial variability on regional coastal weather forecasts is described. A high-resolution numerical weather forecast model from the Met Office is run for the U.K. region with hourly updates of SST data obtained from a shelf sea model. When compared with a control run in which SST is maintained with Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) data, it is found that there are significant differences in the coastal-region forecasts for sea breezes and fog formation. The control run underestimates surface temperature and the strength of the sea breeze when compared with the run with hourly SST updates.

Construction of a climate data record of sea surface temperature from passive microwave measurements

2020 ◽  
Vol 236 ◽  
pp. 111485 ◽  
Author(s):  
Emy Alerskans ◽  
Jacob L. Høyer ◽  
Chelle L. Gentemann ◽  
Leif Toudal Pedersen ◽  
Pia Nielsen-Englyst ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Passive Microwave ◽  
Sea Surface ◽  
Microwave Measurements ◽  
Climate Data ◽  
Data Record ◽  
Climate Data Record

Remote Control of Sea Surface Temperature on the Variability of Tropical Cyclone Activity Affecting Vietnam’s Coastline

2021 ◽  
Author(s):  
Duong Hoang Trinh ◽  
Hoang Duc Cuong ◽  
Duong Van Kham ◽  
Chanh Kieu
Keyword(s):  
Tropical Cyclone ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Large Scale ◽  
Coastal Region ◽  
Principal Component ◽  
Strong Relationship ◽  
Sea Surface ◽  
Philippine Sea ◽  
Principal Component Analyses

AbstractThis study examines the teleconnection between sea surface temperature (SST) in different ocean regions and tropical cyclone (TC) activity affecting Vietnam’s coastal region. Using spatial correlation and principal component analyses, it is found that the variability of TCs affecting Vietnam during 1982-2018 is remotely connected with SST in the Indian Ocean, the southwestern Pacific Ocean, and the northern Philippine Sea. Among the three regions, SST in the northern Philippine Sea displays the most significant inverse relationship with TC activity in the South China Sea (SCS), with lower June-November TC accumulated energy (ACE) for warmer northern Philippine Sea SST. Further analyses of large-scale atmospheric circulations show that this teleconnection between the northern Philippine Sea SST and TC activity in the SCS is linked to the East Asian subtropical jet (EASJ). Principal component analyses of the 200-hPa zonal wind associated with EASJ capture indeed a strong relationship between the second principal component, which characterizes the EASJ intensity, and ACE. Specifically, higher EASJ intensity corresponding to colder northern Philippine Sea SST would enhance large-scale ascending motion and low-level cyclonic anomalies in the SCS, which are favorable for TC formation and result in an overall increased ACE. Examination of correlation between this second principal component and the northern Philippine Sea SST confirms that this correlation is statistically significant at a 95% confidence level. In this regard, these results support the Pacific-Japan teleconnection between the northern Philippine Sea SST and TC activity in the SCS.

scholarly journals Increasing Trends in Air and Sea Surface Temperature in the Central Adriatic Sea (Croatia)

2021 ◽  
Vol 9 (4) ◽  
pp. 358
Author(s):  
Ognjen Bonacci ◽  
Duje Bonacci ◽  
Matko Patekar ◽  
Marco Pola
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Air Temperature ◽  
Adriatic Sea ◽  
Coastal Region ◽  
Sea Surface ◽  
The Mean ◽  
Increasing Trends

The Adriatic Sea and its coastal region have experienced significant environmental changes in recent decades, aggravated by climate change. The most prominent effects of climate change (namely, an increase in sea surface and air temperature together with changes in the precipitation regime) could have an adverse effect on social and environmental processes. In this study, we analyzed the time series of sea surface temperature and air temperature measured at three meteorological stations in the Croatian part of the Adriatic Sea. To assess the trends and variations in the time series of sea surface and air temperature, different statistical methods were employed, i.e., linear and quadratic regressions, Mann–Kendall test, Rescaled Adjusted Partial Sums method, and autocorrelation. The results evidenced increasing trends in the mean annual sea surface temperature and air temperature; furthermore, sudden variations in values were observed in 1998 and 1992, respectively. Increasing trends in the mean monthly sea surface temperature and air temperature occurred in the warmer parts of the year (from March to August). The results of this study could provide a foundation for stakeholders, decision–makers, and other scientists for developing effective measures to mitigate the negative effects of climate change in the scattered environment of the Adriatic islands and coastal region.

scholarly journals Relationship between Monthly Rainfall in NW Peru and Tropical Sea Surface Temperature

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Juan Bazo ◽  
María de las Nieves Lorenzo ◽  
Rosmeri Porfirio da Rocha
Keyword(s):  
Surface Temperature ◽  
Regression Model ◽  
Sea Surface Temperature ◽  
Southern Oscillation ◽  
Coastal Region ◽  
Monthly Rainfall ◽  
Sea Surface ◽  
Equatorial Atlantic ◽  
The Indian Ocean ◽  
Tropical Sea

This study assesses the relationship between global sea surface temperature (SST) and a regional index of rainfall (NWPR) in Piura-Tumbes, a coastal region in northwestern Peru, over the period 1965–2008 by means of the Pearson product-moment correlation. The results show that this area is strongly influenced by three indices: El Niño-Southern Oscillation (ENSO) Niño3.4 region, the Indian Ocean Dipole (IOD), and the equatorial Atlantic Oscillation (ATL3). In particular, a positive correlation has been found with the two first indices (Niño3.4 and IOD) and a negative one with ATL3 with several months of delay. This allows developing a forecast regression model for monthly rainfall in NW Peru with months in advance. The results show that linear regression model is not enough to provide satisfactory results; however, a nonlinear regression model improves considerably the prediction of rainfall anomalies in NW Peru.

scholarly journals High-Resolution Sea Surface Temperature Retrieval from Landsat 8 OLI/TIRS Data at Coastal Regions

2019 ◽  
Vol 11 (22) ◽  
pp. 2687 ◽  
Author(s):  
Jae-Cheol Jang ◽  
Kyung-Ae Park
Keyword(s):  
High Resolution ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Korean Peninsula ◽  
Sea Surface ◽  
Global Ocean ◽  
Small Scale ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Coastal Regions

High-resolution sea surface temperature (SST) images are essential to study the highly variable small-scale oceanic phenomena in a coastal region. Most previous SST algorithms are focused on the low or medium resolution SST from the near polar orbiting or geostationary satellites. The Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIRS) makes it possible to obtain high-resolution SST images of coastal regions. This study performed a matchup procedure between 276 Landsat 8 images and in-situ temperature measurements of buoys off the coast of the Korean Peninsula from April 2013 to August 2017. Using the matchup database, we investigated SST errors for each formulation of the Multi-Channel SST (MCSST) and the Non-Linear SST (NLSST) by considering the satellite zenith angle (SZA) and the first-guess SST. The retrieved SST equations showed a root-mean-square error (RMSE) from 0.59 to 0.72 °C. The smallest errors were found for the NLSST equation that considers the SZA and uses the first-guess SST, compared with the MCSST equations. The SST errors showed characteristic dependences on the atmospheric water vapor, the SZA, and the wind speed. In spite of the narrow swath width of the Landsat 8, the effect of the SZA on the errors was estimated to be significant and considerable for all the formations. Although the coefficients were calculated in the coastal regions around the Korean Peninsula, these coefficients are expected to be feasible for SST retrieval applied to any other parts of the global ocean. This study also addressed the need for high-resolution coastal SST, by emphasizing the usefulness of the high-resolution Landsat 8 OLI/TIRS data for monitoring the small-scale oceanic phenomena in coastal regions.

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