scholarly journals Influence of the Temporal Resolution of Sea Surface Temperature on Winter Precipitation over the Coastal Area of the Sea of Japan

SOLA ◽  
2019 ◽  
Vol 15 (0) ◽  
pp. 107-112 ◽  
Author(s):  
Masaya Nosaka ◽  
Hiroaki Kawase ◽  
Hidetaka Sasaki ◽  
Akihiko Murata
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Of Japan ◽  
Temporal Resolution ◽  
Coastal Area ◽  
Winter Precipitation ◽  
Sea Surface ◽  
The Sea Of Japan

scholarly journals Contrastive Influence of ENSO and PNA on Variability and Predictability of North American Winter Precipitation

2019 ◽  
Vol 32 (19) ◽  
pp. 6271-6284 ◽  
Author(s):  
Xiaofan Li ◽  
Zeng-Zhen Hu ◽  
Ping Liang ◽  
Jieshun Zhu
Keyword(s):  
North America ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North American ◽  
North Pacific ◽  
Winter Precipitation ◽  
Sea Surface ◽  
The North ◽  
Remote Forcing ◽  
The North Pacific

Abstract In this work, the roles of El Niño–Southern Oscillation (ENSO) in the variability and predictability of the Pacific–North American (PNA) pattern and precipitation in North America in winter are examined. It is noted that statistically about 29% of the variance of PNA is linearly linked to ENSO, while the remaining 71% of the variance of PNA might be explained by other processes, including atmospheric internal dynamics and sea surface temperature variations in the North Pacific. The ENSO impact is mainly meridional from the tropics to the mid–high latitudes, while a major fraction of the non-ENSO variability associated with PNA is confined in the zonal direction from the North Pacific to the North American continent. Such interferential connection on PNA as well as on North American climate variability may reflect a competition between local internal dynamical processes (unpredictable fraction) and remote forcing (predictable fraction). Model responses to observed sea surface temperature and model forecasts confirm that the remote forcing is mainly associated with ENSO and it is the major source of predictability of PNA and winter precipitation in North America.

scholarly journals Change in the Recent Warming Trend of Sea Surface Temperature in the East Sea (Sea of Japan) over Decades (1982–2018)

2019 ◽  
Vol 11 (22) ◽  
pp. 2613 ◽  
Author(s):  
Eun-Young Lee ◽  
Kyung-Ae Park
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Of Japan ◽  
Warming Trend ◽  
Frequent Occurrence ◽  
Sea Surface ◽  
East Sea ◽  
The Arctic ◽  
Arctic Oscillation Index ◽  
Sst Cooling

Long-term trends of sea surface temperature (SST) of the East Sea (Sea of Japan, EJS) were estimated by using 37-year-long satellite data, for the observation period from 1982 to 2018. Overall, the SST tended to increase with time, for all analyzed regions. However, the warming trend was steeper in the earlier decades since the 1980s and slowed down during the recent two decades. Based on the analysis of the occurrence of events with extreme SST (high in the summertime and low in the wintertime), a shift toward the more frequent occurrence of events with extremely high SST and the less frequent occurrence of events with extremely low SST has been observed. This supports the observations of the consistent warming of the EJS. However, seasonal trends revealed continuous SST warming in the summertime, but frequent extreme SST cooling in the wintertime, in recent decades. The observed reduction in the warming rates occurred more frequently in specific regions of the EJS, where the occurrence frequency of events with extremely low SST was unusually high in the recent decade. The recent tendency toward the SST cooling was distinctively connected with variations in the Arctic Oscillation index. This suggests that changes in the Arctic Ocean environment likely affect the recently observed SST changes in the EJS, as one of the marginal seas in the mid-latitude region far from the polar region.

scholarly journals Sea surface temperature trend analysis by Mann-Kendall test and sen’s slope estimator: a study of the Hai Phong coastal area (Vietnam) for the period 1995-2020

2022 ◽  
Author(s):  
Vinh Vu Duy ◽  
Sylvain Ouillon ◽  
Hai Nguyen Minh
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Coastal Area ◽  
Kendall Test ◽  
Sea Surface ◽  
Intrinsic Mode Functions ◽  
Sen’S Slope ◽  
Enso Events ◽  
Mann Kendall Test ◽  
The Impact

Based on the Mann-Kendall test and Sen’s slope method, this study investigates the monthly, seasonal, and annual sea surface temperature (SST) trends in the coastal area of Hai Phong (West of Tonkin Gulf) based on the measurements at Hon Dau Station from 1995 to 2020. The results show a sea surface warming trend of 0.02°C/year for the period 1995-2020 (significant level α = 0.1) and of 0.093°C/year for the period 2008-2020 (significant level α = 0.05). The monthly SSTs in June and September increased by 0.027°C/year and 0.036°C/year, respectively, for the period 1995-2020, and by 0.080°C/year and 0.047°C/year, respectively, for the period 2008-2020. SST trends in winter, summer, and other months were either different for the two periods or not significant enough. This may be due to the impact of ENSO, which caused interannual SST variability in the Hai Phong coastal with two intrinsic mode functions (IMF) signals a period of ~2 (IMF3) and ~5.2 years cycle (IMF4). A combination of these signals had a maximum correlation of 0.22 with ONI (Oceanic Niño Index) delayed by 8 months. ENSO events took ~8 months to affect SST at Hai Phong coastal area for 1995-2020 and caused a variation of SST within 1.2°C.

scholarly journals MONITORING CHLOROPHYLL-A AND SEA SURFACE TEMPERATURE WITH SATELLITE DATA DERIVED FROM MULTIPLE SENSORS

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 515-520
Author(s):  
A. Tuzcu Kokal ◽  
N. Musaoğlu
Keyword(s):  
Water Quality ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Temporal Resolution ◽  
Satellite Data ◽  
Sea Surface ◽  
High Temporal Resolution ◽  
Landsat Images ◽  
Combined Data

Abstract. Water is an essential natural source for human being and environment. To conserve water sources, monitoring them by using remote sensing data and technologies is an efficient way. In this study, water quality of the Sea of Marmara (Turkey), which has lots of currents, was examined. The main aim of the study was developing a common model to monitor chlorophyll-a concentration in time by using satellite data. After, the coefficients of the OC2 (ocean chlorophyll 2) model were detected by curve fitting, it was applied to Landsat images. The bias and RMSE (Root Mean Square Error) were found as 0.73 µg/l and 5.80 µg/l, respectively. The high RMSE was stemmed from dynamic structure of the sea. Thus, the temporal resolution has a profound impact on the accuracy of estimations. The developed model was applied to the HLS (Harmonized Landsat Sentinel-2) data, which has high temporal resolution. The results of the HLS and Landsat images were compared, and HLS is found as proper to monitor the water quality. The combined data (SST (Sea Surface Temperature) daily data from 1981 to present derived from satellite observations Level-4 product) was used for the secondary aim of the study which was monitoring SST. The bias and RMSE of the data, which was acquired on 19.07.2017, were found as 0.33 °C and 1.12 °C, respectively. The bias and RMSE of the data, which was acquired on 18.07.2018, were found as −0.02 °C and 1.03 °C, respectively. The combined data is found appropriate to monitor the SST.

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