## 1 Introduction  
Land surface temperature (LST) is a key variable used in a wide range of applications, such as in the monitoring of the surface radiation budget, climate change, the hydrological cycle and ecosystems [1, 2, 3, 4]. In spite of the recognized importance of LST, _in situ_ measurements of LST over continents are not yet adequate for resolving diurnal cycles or for analyzing synoptic, seasonal and interannual variability, because of strong spatiotemporal variations in the data and difficulties in accurate measurements. Remote sensing instruments onboard satellites working in the thermal infrared channels are the only available operational systems capable of collecting cost-effective LST data at spatial and temporal resolutions that are appropriate for various applications [5, 6, 7, 8, 9]. After it was proven that the LST data could theoretically be retrieved using a split-window (SW) method, many attempts were made to compute LST from satellite data, especially for data collected by polar orbiting satellites (e.g., National Oceanic and Atmospheric Administration (NOAA) / Advanced Very High Resolution Radiometer (AVHRR), Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat / Thematic Mapper (TM)) [1, 2, 10, 11, 12]. Similar to the retrieval of sea-surface temperature (SST), LST estimations from satellite remote sensing data are typically obtained from one or more thermal infrared channels located in the atmospheric window region of 8-13 \(\upmu\)m. Among the various types of LST retrieval methods available, the SW technique is one of the most widely used methods for retrieving LST from both polar orbiting and geostationary satellite data [1, 2, 3, 6, 10]. This method is based on the assumption that the surface emissivities of SW channels are known _a priori_[6, 13]. However, the lack of high-quality surface emissivity data with sufficient spatiotemporal resolution is a major obstacle for retrieving LST from the satellite data [14, 15, 16, 17, 18, 19]. Recently, two databases containing surface emissivity information were developed by the University of California, Santa Barbara [20], and Johns Hopkins University (JHU) [21]. In addition, various background data (land cover, vegetation index, _etc._) and methods for estimating surface emissivity have been significantly improved [14, 22, 23, 24]. As a result, LST data with global coverage, which includes LST data from polar orbiting satellites (e.g., Terra/MODIS [25]) and geostationary satellites (e.g., Meteosat Second Generation (MSG)/Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) [26]) can now be operationally retrieved and serviced to different users [6, 27, 28, 29, 30]. Given that the Asian continent is not only the largest continent in the world, but is also a strong modulator of the East Asian monsoon system, it is true that relatively few work for the LST retrieval has been done on this region compared to the European and American regions [2, 6, 18, 30]. [PERSON] _et al_. [31] developed an SW-type LST algorithm using Multi-functional Transport Satellite-1 Replacement (MTSAT-1R) data and investigated the sensitivity of the LST algorithm to various impacting factors, such as the difference between LST and air temperature, emissivity values, satellite zenith angles (SZAs) and brightness temperature differences (BTDs). Furthermore, [PERSON] _et al_. [32] retrieved LST data using a generalized SW algorithm from China's geostationary meteorological satellite (Feng Yun-2C (FY-2C)) data. The Korea Meteorological Administration (KMA) successfully launched the first Korean multipurpose geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS) on 27 June 2010. COMS is located above the Equator at longitude 128\({}^{\circ}\)E and is equipped with a meteorological imager comprising one visible channel (1 km) and four infrared channels (4 km). A detailed description for the COMS meteorological imager is given in Table 1. After an intensiveoperational test of COMS, full operation of COMS began on 1 April 2011.