Recent Trends of Abnormal Sea Surface Temperature Occurrence Analyzed from Buoy and Satellite Data in Waters around Korean Peninsula

Abstract

In this study a tendency of abnormal sea surface temperature (SST) occurrence in the seas around South Korea is analyzed from daily SST data from satellite and 14 buoys from August 2020 to July 2021. As thresholds 28℃ and 4℃ are used to determine marine heatwaves(MHWs) and abnormal low water temperature (ALWT), respectively, because those values are adopted by the National Institute of Fisheries Science for the breaking news of abnormal temperature. In order to calculate frequency of abnormal SST occurrence spatially by using satellite SST, research area was divided into six areas of coast and three open seas. ALWT dominantly appeared over a wide area (7,745 km²) in Gyeonggi Bay for total 94 days and it was also confirmed from buoy temperature showing an occurrence number of 47 days. MHWs tended to be high in frequency in the coastal areas of Chungcheongdo and Jeollabukdo and the south coastal areas while in case of buoy temperature Jupo was the place of high frequency (32 days). This difference was supposed to be due to the low accuracy of satellite SST at the coasts. MHWs are also dominant in offshore waters around Korean Peninsula. Although detecting abnormal SST by using satellite SST has advantage of understanding occurrence from a spatial point of view, we also need to perform detection using buoys to increase detection accuracy along the coast.

1. Introduction

Sea surface temperature (SST) is an important factor in understanding the global climate system. Its distribution and characteristics have important impacts on marine ecosystems. Aquatic animals are poikilothermic and thus have to fully rely on the water temperature rather than controlling their own body temperature. Thus, their growth and reproduction depend on the water temperature, and a slight change may cause a long-term effect like disruption in growth and reproduction. Decrease in SST results in decrease in gas (including dissolve oxygen) holding capacity of water. On the contrary, the oxygen requirement of fish in general increases as the water temperature increases (Oh and Noh, 2006). For instance, the metabolic rate in general increases by 10% at each degree rises in water temperature. Moreover, fish need more food in higher temperature. These happen when slight to moderate changes in SST occurs. In extreme cases abrupt changes in SST may cause mass mortality of aquatic organisms. To cite an instance, abnormal SST is found to be the main cause of 57.5% damage to farmed fish in the southern coast of Korean Peninsula (Lee et al., 2018).

The abnormal SST is caused by the influence of atmosphere, ocean currents, and natural variability, etc. The Northwest Pacific Ocean is affected mainly by the Kuroshio Current moving northward from the Pacific Ocean. Long-term marine phenomena such as El Niño, La Niño, etc. change the intensity and flow of Kuroshio Current (Nan et al., 2015). In addition, abnormal SST can be caused by various external forces such as atmospheric heat and cold waves, and high temperature and diluted water from the Yangtze River that flow into the Yellow Sea. The National Institute of Fisheries Science (NIFS) conducts marine environmental survey to monitor SST in real-time and make it public through the marine environment fishery information system (https://www.nifs.go.kr/risa/main.risa). In addition, NIFS provides forecasts and breaking news on abnormal sea temperature conditions, cold water zone, and oxygen-poor water mass for each sea areas of Korea (https://nifs.go.kr/bbs?id=seastate). NIFS defines abnormal SST of Korea as marine heat waves (MHWs) and abnormal low water temperature (ALWT) as ≥28°C and ≤4°C (KMA, 2019). However, in spite of the accuracy of data measured by buoys or ships its usages are still limited due to some spatial constraints. In order to overcome those limitations, it is necessary to develop an abnormal SST detection technique such as numerical modelling or remote sensing based detection of MHWs and ALWT (Kim and Yang, 2019; Oh and Yang, 2011).

With the development of satellite remote sensing technology, global SST data collection from satellite data has been possible since 1980s (Casey et al., 2010; Hosoda, 2010). In general, SST can be obtained through different types of sensors for microwave and infrared bands mounted on satellites (Park et al., 2008a, 2008b; Kim and Park, 2018). Currently many research institutes are operating satellites for obtaining high quality SST data by using various techniques (Martin et al., 2012). In Korea, the Korea Institute of Ocean Science and Technology (KIOST) produces daily average multi-satellite SST of 1 km resolution (Yang et al., 2015; Yang and Kim, 2016).

Many research teams have studied abnormal SST in the Korean Peninsula. Kim et al. (2019) calculated SST anomaly from multi-satellite SST by the KIOST and Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) data by the Meteorological office, and used for MHWs detection. In addition, Jung et al. (2020) predicted SST (1–7 days period) in the South Sea area of Korea using Long Short-Term Memory (LSTM) and Convolution Long Short-Term Memory (ConvLSTM) deep learning techniques, and analyzed MHWs cases. However, these studies were biased toward MHWs, and except these there are not much works on the tendency of abnormal SST around the South Korea. Therefore, this study will analyze the frequency trends of abnormal SST around South Korea from August 1, 2020 to July 31, 2021.

2. Data

1) Buoy temperature data

Buoys are capable of continuously recording data which are thus used for obtaining long-term data. Therefore, for marine weather observation purposes buoys are moored at specific locations in the sea around Korean (Kim and Kim, 2014). However, observations can be affected due to foreign substances on sea surface. In order to identify and remove such errors in this study data quality control (QC) is conducted through the method suggested by the Korea Meteorological Administration Observation Infrastructure Bureau (Lee et al., 2019). The QC was accomplished in four stages: (1) Physical limit check - removing the outliers outside the range of upper and lower limits of usual water temperature, (2) Standard deviation check –using the mean and standard deviation for 2 days for removing numerical changes that cannot be physically observed as natural phenomena, (3) Spike check –removing the maximum temperature difference from the mean for 2 hours before and after, and (4) Durability check – removing data with no change in water temperature for 12 hours. In this study, water temperature data were obtained from 14 buoys located at Jangbong Island, Pung Island, Dangjin Port, Chang-ri, Eoui, Jupo, Gapa Island, Sinsan, Balpo, Sinwol, Gangjin, Gigang, Pohang, and Samcheock (Table 1, Fig. 1).

Table 1. Locations for 14 buoys used for abnormal SST detection

Fig. 1. Mean SST map of the study area for August 2020 to July 2021. The buoy locations are indicated by triangles.

2) Satellite SST

Korea Institute of Ocean Science and Technology (KIOST) developed an integrated operational marine system that can predict several oceanic physical parameters’ information in real time for the Korean Peninsula through development of the Korea Operational Oceanographic System (KOOS) project through the support of the Ministry of Oceans and Fisheries (Park et al., 2015). KIOST uses the optimal interpolation algorithm on multi-satellite data to generate daily average synthetic SST at 1 km resolution in semi-real time mode (RT) and delayed mode (DM) with an average accuracy of 0.71°C which is termed as KOOS SST (Guan and Kawamura, 2004; Yang et al., 2015; Yang and Kim, 2016). This KOOS SST is generated by using four infrared satellite datasets acquired by the Moderate Resolution Imaging Spectroradiometer, Advanced Very High Resolution Radiometer,

Meteorological Imager, and Visible Infrared Imaging Radiometer Suite, and two microwave satellite datasets acquired by the Advanced Microwave Scanning Radiometer-2, and WindSAT (Guan and Kawamura, 2004; Park et al., 2015; Yang et al., 2015). However, due to some unwanted and unavoidable events such as the shutdown of the satellite, Meteorological Imager and WindSAT were replaced by the Advanced Meteorological Imager and the Global Precipitation Measurement Microwave Imager, respectively.

3. Study area and methods

1) Study area and its subdivisions

The coastal regions under this study around South Korea were divided into six regions, namely the Gyeonggi Bay, coasts of Chungcheongdo, and Jeollabukdo, Jeollanamdo, Jeju, south coast of Korea, and east coast of Korea. In addition, in order to confirm the distribution of abnormal SST the open sea was divided into three areas like the Yellow Sea, the East Sea, and waters between Jeju and Japan. Notably, according to MHWs breaking news of the NIFS in 2018, the number of warnings issued in the west coast of the Korean Peninsula has increased significantly compared to those in previous years (Kim and Yang, 2019). In addition, MHWs in the breaking news is found to be occurred in large areas of the west coast of Korea. For these reasons, the west coast was divided into three areas to identify the trends of abnormal SST in the subdivided regions (Fig. 2).

Fig. 2. Six subdivisions of coastal area (gray): (a) the Gyeonggi Bay, (b) coast of Chungcheongdo and Jeollabukdo, (c) coast of Jeollanamdo, (d) south coast of Korea, (e) east coast of Korea, (f) Jeju, and three subdivisions of open sea area (light blue), (g) the Yellow Sea, (h) the East Sea, and (i) waters between Jeju and Japan.

2) Method

Fig. 3 shows the flowchart of research methodology to analyze the tendency of ALWT and MHWs around South Korea. The NIFS defines MHWs as 28°C or higher, and ALWT as 4°C or lower temperature which are also used in this study for abnormal SST detection. The spatial frequency represents the total times whether the abnormal SST occurs for each pixel during the study period. The study results show the representative frequency and distribution of each area (subdivisions shown in Fig. 1). The representative frequency indicates the number of days when abnormal SST occurred in the area. For this purpose, the abnormal SST occurrence of the area is considered if occurred to any of the pixels included in each subdivision. The hourly collected buoy data were calculated to daily average after four QC processes. This study used data from 14 buoys, and thus the frequency of abnormal SST for 14 locations (points) was analyzed.

Fig. 3. Flowchart of the study method in order to analyze ALWT and MHWs trends.

4. Results

1) Spatial frequency using satellite SST

Fig. 4 shows the spatial frequency of detecting ALWT (a) and MHWs (b) from daily KOOS SST from August 1, 2020 to July 31, 2021. It can be observed that ALWT generally occurred on the west coast region of Korea. It frequently occurred in the northern part of the Gyeonggi Bay, and the area had a characteristic that the frequency was evenly distributed over a wide area (7,745 km2). On the other hand, ALWT occurred in smaller areas at the coasts of Chungcheongdo and Jeollabukdo compared to that of the Gyeonggi Bay. MHWs was detected both at coastal areas and in the open sea. The frequency increased along the open sea far from the Korean coasts in the cases of the Gyeonggi Bay, the coast of Chungcheongdo and Jeollabukdo and the south coast.

Fig. 4. Spatial frequency of ALWT (a) and MHWs (b) using KOOS SST during the study period.

Table 2 shows the frequencies of detection per month of ALWT and MHWs by 9 regions and Fig. 5 indicate the detection results by date. The ALWT occurred intensively in January and February in the order of the west and south coasts of Korea and Jeju. In the Gyeonggi Bay alone, ALWT occurred for the longest period from the mid of December to the end of March. The frequency of ALWT in Gyeonggi Bay was 94 days which was almost 1.4 times compared to those of the coasts of Chungcheongdo and Jeollabukdo. On the other hand, ALWTs were detected in the south coast of Korea and Jeju for 11 days and 5 days, respectively. However, ALWT was not detected at the east coast of Korea. In the case of the open sea, it occurred in the order of waters between Jeju and Japan, and the Yellow Sea. ALWT of waters between Jeju and Japan was detected for 7 days near the northern part of Jeju and in the Yellow Sea, and occurred for 5 days near the Gyeonggi Bay, and did not occur at the East Sea during the period of study. In the case of MHWs, it was the most frequent in Jeju coast (39 days), followed by the south coast (30 days) and the coast of Chungcheongdo and Jeollabukdo (25 days). In the case of waters between Jeju and Japan, it occurred the most (47 days) followed by the East Sea (39 days) and the Yellow Sea (13 days). Usually MHWs occurs from July to September. However, due to limitation of data period (August to next year July) we had to analyze MHWs where August 2020 was considered as ending point and July 2021 is considered as starting (without considering the year) for the purpose of comparison with the common MHWs data. In August 2020 MHWs occurred in all nine subdivisions of the study area, and specially the coasts of Chungcheongdo and Jeollabukdo, the south coast of Korea, the East Sea, and waters between Jeju and Japan continued to occur MHWs until September. When looking at the start of 2021, MHWs occurred only twice at the south coast, on June 9 and 19. Except for the south coast, MHWs occurred in the rest of the seas from mid-July.

Fig. 5. KOOS SST based chronological occurrence of ALWT and MHWs in the study areas.

Table 2. Frequencies of ALWT/MHWs in the study areas during the study period

2) Frequency at buoy location

Fig. 6 shows the frequency of abnormal SST detected from 14 buoys, and Fig. 7 shows their date-wise occurrences. ALWT intensively occurred in January and February, 2021. In particular, buoys of Jangbong Island, Pung Island, and Dangjin Port located in Gyeonggi Bay generated ALWT on an average for 47 days, and were characterized by continuing until early March. At Jupo (located on the coast of Jeollanamdo) ALWT occurred twice at the end of February, and at Sinwol and Gangjin (located on the south coast) ALWT occurred twice in mid-January. Notably, ALWT didn’t occurred at Gapa Island and Sinsan located on Jeju and Gijang, Pohang, and Samcheok located on the east coast. MHWs occurred only buoys located on the west coast, south coast, and Jeju. MHWs in Jupo occurred for in total 32 days which is exactly 4 times to that of Sinsan located at Jeju. In addition, Jupo was the only place where occurred MHWs in both 2020 and 2021. MHWs was occurred in 2020 only in Gapa Island and Sinsan, and occurred in 2021 only in Chang-ri, Sinwol, and Gangjin, and the numbers of detection were 2, 3, and 2 days, respectively.

Fig. 6. Frequency of ALWT and MHWs for each of the 14 buoys during the study period.

Fig. 7. Buoys (14) based occurrence of ALWT and MHWs in the study areas.

5. Conclusions

SST is an important environmental parameter for understanding the ocean, and the detection of abnormal SST is directly related to aquatic biota. The NIFS uses the marine environment fishery information system to provide forecasts and breaking news on ALWT and MHWs. However, the NIFS sets the location of buoy as a specific sea area. Therefore, this study is an attempt to grasp the trends around South Korea using satellite and buoy SST. Detection results using KOOS SST and buoy SST showed similar tendencies. The ALWT occurred more frequently along the west coast of Korea than the east coast of Korea, and ALWT occurrences were more in the coasts than the open sea. Gyeonggi Bay is detected as the most vulnerable area where ALWT occurred over the widest area for the longest period, starting from the earliest day (December). The MHWs was detected at both coast and open sea compared to ALWT. In the case of the coast of Chungcheongdo and Jeollabukdo and the south coast of Korea, the frequency of MHWs tended to increase in the direction of onshore.

Satellite SST is known to be difficult to reflect water temperature variability on the coast due to proximity to land and shallow water depths. In addition, microwave measurements are known to increase errors in vigorous tidal mixing waters. The detection of abnormal SST should be performed using KOOS SST, which can solve spatial constraints, and the accuracy of the coast should be improved by using buoy water temperature data observed in the field. Though the tendency of ALWT and MHWs was suggested, it is not suitable to analyze the tendency with one-year data. Thus, research works are needed with data of several years, and the accuracy of detection need to be improved if abnormal SST thresholds suitable for regional water temperature characteristics are set and additional factors that cause abnormal SST occurrence are applied to detection conditions. This study will be the basis for the monitoring system of ALWT and MHWs around the Korean Peninsula.