Meteorological satellites play a crucial role in observing and monitoring weather phenomena, providing data that is indispensable for weather forecasting, numerical weather prediction (NWP), and climate research. Satellite remote sensing, which enables continuous observation of the Earth’s atmosphere and surface, has become one of the most important tools for understanding and predicting atmospheric processes, as well as for assessing the impacts of climate change. In Korea, the utilization of meteorological satellite data began in the 1970s when the Korea Meteorological Administration (KMA) first received polar-orbit satellite images from the United States (Korea Meteorological Administration, 2011). These kinds of satellite images have primarily been used for weather forecasting and monitoring hazardous weather events such as typhoons, heavy rainfall, and Asian dust.

Throughout the 1980s and 1990s, Korea relied heavily on foreign satellite data, including imagery from Japan, the United States, and Europe. This data was used to gradually expand the scope of meteorological applications, including improving disaster monitoring and supporting numerical weather prediction models. However, Korea’s independent development of meteorological satellite technology began in earnest with the launch of its first geostationary meteorological satellite, the Communication, Ocean, and Meteorological Satellite (COMS), in June 2010. The COMS satellite marked a significant milestone in the nation’s satellite operations, as it allowed Korea to produce its own meteorological products and move towards technological self-sufficiency (Ahn et al., 2023).

The COMS satellite not only provided the basis for real-time weather monitoring but also facilitated extensive research activities related to satellite data processing and algorithm development (Korea Meteorological Administration, 2004). Over the past decade, Korea has made substantial progress in satellite-based research, including the development of advanced data assimilation techniques, real-time data processing systems, and the production of high-resolution satellite products. These advancements have enabled more accurate monitoring of atmospheric conditions and have contributed significantly to weather forecasting, environmental monitoring, and climate studies.

In 2018, Korea further expanded its capabilities with the launch of the Geo-KOMPSAT 2A (GK2A) satellite (Fig. 1), which featured an Advanced Meteorological Imager (AMI) with enhanced spatial, temporal, and spectral resolution. The GK2A satellite brought new opportunities for high-precision weather forecasting and environmental monitoring while increasing the number and quality of satellite products. The development of the GK2A satellite also led to the creation of more sophisticated data processing systems and algorithms, which were designed to handle the increased complexity and volume of satellite data (Korea Meteorological Administration, 2019).

Figure 1. The Korean geostationary meteorological satellites: COMS and GK2A.

As Korea continues to develop its satellite technology, the KMA is also exploring the feasibility of launching additional geostationary (GEO) and low earth orbit (LEO) satellites. These future missions aim to improve the monitoring of greenhouse gases and other atmospheric components, contributing to global efforts to address climate change. Additionally, advancements in artificial intelligence and cloud computing are expected to further enhance the efficiency and accuracy of satellite data processing.

This paper provides a comprehensive review of the history, status, and future prospects of meteorological satellite remote sensing in Korea. It highlights the key milestones in the development of Korea’s meteorological satellite systems, the evolution of data processing and application technologies, and the growing role of satellite data in meteorology, numerical weather prediction, and climate science. Through this review, we aim to showcase the advancements that have been made in meteorological satellite technology and outline the challenges and opportunities for future developments in this rapidly evolving field.

Technical and engineering research related to the meteorological satellite system has focused on very limited topics, especially the meteorological payloads of COMS and GK2A satellites because the area of satellite development will be reviewed as an independent theme in this special issue. In this area, only a few papers have been published from the mid-2000s such as the design of interface unit with spacecraft (Chae, 2006), the performance evaluation of the payload regarding the radiometric calibration (Jin et al., 2013), and the best detector selection (Jin et al., 2021).

Regarding the LEO meteorological satellite, a few studies on the technical criteria for the development (Eun, 2012) and the payload requirements (Eun, 2013) as prior research for the feasibility study of the Korean LEO meteorological satellite project were performed.

Additionally, in order to sustain and expand meteorological satellites, we have not only studied to make policies (Park et al., 1998; Ahn, 2012, 2014) but also assessed the socio-economic benefits and values obtained from geostationary meteorological satellite operation (Kim and Jang, 2018; Kim et al., 2021b).

Currently, KMA is about to start the third GEO meteorological satellite development project, named Geo-KOMPSAT 5 (GK5) which is scheduled to launch in 2031. Also, we are now studying the feasibility of the small-size LEO satellite for monitoring greenhouse gases and the core technology of meteorological payload for the preparation of meteorological satellite system expansion. Therefore, we expect to publish more papers related to meteorological satellite system technology in the future.

Information obtained from meteorological satellites is utilized in various fields, including nowcasting, numerical weather prediction, and climate studies. The core technologies required for these applications involve techniques for generating value-added information from raw observational data and methods for utilizing the produced information. In Korea, the development of these technologies can be broadly divided based on the launch of the nation’s first geostationary multipurpose satellite, the COMS, in the early 2000s. Prior to the COMS, the focus was primarily on receiving and utilizing processed foreign satellite data, with an emphasis on adopting and learning from foreign technologies. However, with the development of the COMS, there was a rapid advancement in satellite data processing technologies for information production. Additionally, as the scope of satellite data applications expanded, the initial focus, which was primarily on phenomenon detection and interpretation, gradually shifted towards more advanced applications, such as utilization in numerical models. Recently, this expansion has further progressed into predictive fields involving artificial intelligence and deep learning. In this section, we summarize the advancements in data processing technologies for information production and the major developments across various application fields.

3.1 Data Processing Technology

The development of data processing technologies for producing value-added products from raw satellite data began in earnest with the launch of the COMS Meteorological Data Processing System (CMDPS) project, aimed at developing an independent system to process COMS data using domestic technology. This project marked a significant leap in technology, as it not only involved developing algorithms to generate 16 different satellite products but also the development of an operational real-time data processing system. This enabled the National Meteorological Satellite Center (NMSC) to establish the fundamental capabilities required for satellite operation. Following this, with the development of the GK2A, which featured significantly improved performance, additional projects were launched to develop and improve new algorithms. Building upon the experience gained from the first satellite, efforts were made to enhance the completeness of algorithms developed solely with domestic technology, while also receiving periodic consultation from foreign experts. These efforts contributed to elevating the technological standards in the field of data processing systems. Through the domestically led development of the data processing systems for both satellites, the sector is considered to have achieved technical independence.

3.1.1. COMS Meteorological Data Processing System (CMDPS)

With the development of COMS, which was dedicated to weather observation, efforts to establish various technologies and infrastructures for its operation and utilization began. One of these initiatives was the development of a system to produce value-added products from the raw data observed by the satellite. The CMDPS development project was led by the National Institute of Meteorological Sciences (NIMS), with participation from not only the KMA, which operates the satellite, but also domestic university researchers responsible for algorithm development, and local software companies tasked with standardizing, formalizing, and creating operational software from the developed algorithms (Korea Meteorological Administration, 2004).

The CMDPS, designed to generate 16 types of satellite products, was developed entirely with domestic expertise over an eight-year project period (Chung et al., 2006; Choi et al., 2007). It was utilized not only in operational settings during the COMS’s lifespan but also as a prototype for data processing systems used in foreign aid programs that supported international use of the COMS data. The product chains in CMDPS are aligned mainly according to the priority of product sequences, the time limit for operation, and the interaction between the 16 baseline products. In the CMDPS milestone, the conceptual design has been prepared in the first project year, which is based on the algorithm development strategy, annual progress, integration/optimization strategy, implementation of CMDPS in the COMS operation system, and preparation for operation. During the third project year of 2005–2006, the prototype S/W modules for the 16-baseline products were completed with the interface design concept between the modules. The CMDPS will be brought to completion after standardization and optimization of the modules, performance test by a specially produced data set for assessment, interfacing into the COMS ground system, and setting for real-time operation.

3.1.2. GK2A Data Processing System

AMI onboard the GK2A, which succeeded in the mission of the MI onboard the COMS, has made significant advancements in terms of temporal, spatial, and spectral resolution. As a result, the number of value-added products increased to 52, and the interconnectivity between these products, as well as the complexity of the data processing flow, demanded the development of a far more sophisticated and intricate system than CMDPS. To meet these requirements, a new technology development project was initiated under the supervision of NMSC, led by the Electronics and Telecommunications Research Institute (ETRI) with participation from several domestic universities’ research teams. Additionally, to ensure the effective application of new technologies, regular consultations with leading international expert groups were facilitated, resulting in a highly refined system. As shown in Fig. 2, the products generated by the system can be broadly classified into four groups, including those related to the scene and surface sector, atmospheric and aviation sector, cloud and precipitation sector, and radiation and aerosol sector (Chung et al., 2020). Over the six-year development period, independent data processing capabilities were secured, and the system’s completeness was significantly enhanced.

Figure 2. GK2A meteorological products.

3.2. Data Utilization Technology

The first domestic research paper on the utilization of meteorological satellite data analyzed the characteristics of the Karman vortex, which occurs south of Jeju Island (Lee, 1983). This study attempted to generate quantitative information about the Karman vortex using the size and shape of clouds observed in geostationary meteorological satellite imagery. Since then, research on the utilization of foreign meteorological satellite data, the development and improvement of independent algorithms, and the application of these technologies in fields outside of meteorology have been conducted intermittently. However, with the development of COMS in the early 2000s, there was a rapid advancement in both data processing technologies and data utilization techniques. In this section, we briefly summarize the technological advancements in nowcasting, numerical weather prediction, and climate and environmental applications.

3.2.1. Nowcasting and Short-Term Forecasting

One of the key application areas of satellite data, which has been consistently studied throughout the years, is its use in nowcasting and short-term forecasting. Technologies supporting this field include the automatic detection of special phenomena, the production of quantitative information on important weather events, and atmospheric motion analysis. Key phenomena detection technologies include cloud detection, fog (Kim et al., 2019), yellow sand/aerosols (Jee et al., 2020), and wildfire detection. Quantitative information products include surface temperature information, tropical cyclone intensity, cloud parameters, rainfall rate, aerosol optical thickness, and atmospheric motion vectors. In terms of atmospheric analysis, synoptic analysis techniques using imagery data are widely used.

The most fundamental aspect of phenomenon detection is the algorithm for detecting the presence or absence of clouds. Continuous advancements have been made, and relatively high accuracy has now been achieved using various channels and methods. Fog detection has also seen continuous improvement and the development of new technologies due to its necessity and importance. However, challenges remain, such as the discontinuity of detection performance during twilight periods and difficulties in detecting fog when mid- to upper-level clouds are present. For yellow sand and aerosol detection, continuous 24-hour monitoring using infrared imagery is mainly utilized in operational systems, and during the daytime, visible imagery is also used to improve accuracy. Furthermore, technologies for objectively detecting rapidly developing severe convection in summer, based on both physical and artificial intelligence approaches, have been continuously developed and applied to nowcasting (Park et al., 2021). For wildfire detection, which utilizes imagery with high-temperature sensitivity near 3.7 μm, the accuracy of detection has been limited by the spatial resolution of sensors. However, the future use of sensors with improved spatial resolution is expected to significantly enhance detection accuracy.

In addition to qualitative phenomenon detection, various quantitative information is also produced. One representative product is surface temperature information, particularly sea surface temperature (SST), which relies entirely on satellite-derived data (Park et al., 2020a). However, the accuracy of land surface temperature remains limited due to its large spatiotemporal variability. Quantitative information about tropical cyclones, which spend most of their lifecycle over the ocean, also heavily depends on satellite observations. Key products include technologies for accurately locating tropical cyclones and producing information on their intensity and radius of strong winds (Lee and Kwon, 2015). These technologies serve as crucial data for tropical cyclone analysis and forecasting operations. Moreover, satellite-based total cloud amount estimation, which replaces subjective observer-based measurements, and technologies for cloud top height, cloud base height, and cloud optical thickness are also developed and provided as critical quantitative data products.

3.2.2. Numerical Weather Prediction (NWP)

The use of satellite data in NWP became fully operational in the early 2000s with the development of direct radiance data assimilation techniques, establishing satellite data as a key observational input for improving the accuracy of numerical models (Joo and Lee, 2007). In South Korea, numerous studies have been conducted since the early 2000s to enhance the initial conditions of numerical models. These efforts include technologies for utilizing temperature and humidity data from microwave sensors, surface, and atmospheric information from optical sensors, sea surface winds from scatterometer sensors, and wind field data from satellite-based active lidar sensors. Additionally, various preprocessing techniques for optimizing the assimilation of satellite data into numerical models and the development of methods to select optimal channels from hyperspectral sensors have been actively pursued.

As the use of satellite data in NWP has expanded, research to improve the accuracy of satellite-derived products using numerical models has also intensified. One example is solving the inverse problem to quantitatively produce the 3D distribution of atmospheric variables (temperature, humidity, wind, etc.) by generating vertical profiles of temperature and humidity from satellite data, a technique that has been independently developed in Korea for processing GK2A data (Kim et al., 2020a). Recent studies have also focused on utilizing GPS data for traditional infrared data assimilation (Ha and Park, 2009) and developing all-sky retrieval techniques using microwave radiometers.

3.2.3. Climate and Environmental Applications

The long-term datasets obtained from meteorological satellites, which have been operational since the launch of the first weather satellite in 1960, are critical for understanding climate issues. A representative example of their use is the analysis showing that temperatures are rising in the troposphere and falling in the stratosphere (Yoo et al., 2001; 2011), demonstrating that the increase in greenhouse gases is indeed altering the thermal structure of Earth’s atmosphere. Satellite data has also been used extensively for analyzing and understanding vegetation changes due to human activities and their seasonal and interannual climate variability (Suh and Nam, 2003; Han et al., 2015), as well as for studying changes in the water cycle (Seo et al., 2012). Moreover, satellite-based analyses of changes in Earth’s emitted radiation due to shifts in clouds and surface conditions contribute to a more accurate understanding of climate change processes (Lee et al., 2018; Jung et al., 2020).

In addition, technologies have been developed to monitor variations in trace gas concentrations over short periods, such as ozone depletion and related trace gases (Choi and Lim, 2010), ozone and nitrogen dioxide retrievals (Moon et al., 2002), and the real-time and long-term monitoring of aerosols (Baek and Kim, 2010). To support carbon neutrality initiatives, there has been active development of technologies to produce greenhouse gas data, including carbon dioxide and methane, using both satellite and ground-based remote sensing methods.

The raw data observed by COMS and GK2A are radiometrically and geometrically corrected by the pre-processing system to produce Level 1B (L1B) data, and L1B data are processed to produce meteorological products and used in various fields. Accuracy information including calibration for L1B data is an increasingly important area of research as Meteorological satellite technology improves and the need to improve the accuracy of meteorological products. As more than 30 years of datasets around the Korean Peninsula will be available from the observation of COMS, GK2A and the start of development of GK5, instrument calibration and data continuity between different satellites are important for climate change research. In addition, the increased spatial resolution of the GK2A, up to 500 meters, has increased the importance of geometric correction, which determines the exact latitude and longitude of an observed position in the Earth’s coordinate system. This section summarises the development research of L1B calibration techniques and geometric correction as the fundamental dataset for the production of meteorological products.

4.1. Radiometric Calibration

The COMS operation and data provision have led the researchers to monitor the accuracy of satellite sensors and to provide users with information on the reliability of its datasets, i.e., the degree of degradation over the operating period. The quantitative assessment of the L1B data stems from the need to provide confidence in the COMS data disseminated globally and the need to expand the use of meteorological satellite information for climate change research with the launch of the next-generation satellites in the 2010s.

Through participation in the international joint program of the Global Space-based Inter-Calibration System (GSICS; Hewison et al., 2013), which is composed of global meteorological satellite operating agencies, a study on infrared channel accuracy using the intercomparison method with LEO hyperspectral infrared sounders whose accuracy is well known was conducted in Korea (Kim et al., 2015), led by the KMA. By intercomparing the same LEO data as a reference, it is possible to provide accurate information between meteorological satellites (Hewison et al., 2013).

For the visible channel, since there was no on-board calibration for the COMS, vicarious calibration was conducted using radiative transfer model calculations of the theoretical radiation reflected by various targets on Earth (e.g., ocean, Australian desert, deep convective clouds, etc.) (Chun and Sohn, 2014; Ham and Sohn, 2010). Despite the periodic updating of the visible channel calibration coefficients by the GK2A on-board calibration system different from COMS, the long-term monitoring of the GK2A visible channel calibration has been assessed by vicarious calibration. A GK2A visible channel calibration study is also underway, using observations of the Moon, a target whose brightness does not change with time and is independent of the effects of the Earth’s atmosphere (Kim et al., 2021a). The calibration information of 16 channels through intercomparison and vicarious calibration of GK2A is processed in near-real time included in the L1B header information and provided directly to users. In particular, research on producing Fundamental Climate Data Record (FCDR) of COMS and GK2A which is well-characterized, long-term data with re-calibration sufficient to support climate applications around Korea in the future.

4.2. Image Geometric Correction

The Image geometric correction ensures that the observed image is located at the correct point, and its performance is determined by image positioning, where each pixel of the observed image is determined by the correct latitude and longitude on the earth, and image position maintenance, where the position of the pixel is consistent among the 16 channels of images. Errors in this image positioning can affect the location of major weather events depending on the spatial resolution of the pixels.

The geometric correction of COMS was developed based on landmarks, and that of GK2A was developed by observing stars with known positions and brightnesses rather than landmarks (Huh et al., 2019; Huh and Yong, 2020). The GK2A geometric correction was based on observations of the best stars around the Earth (Huh et al., 2015), rather than observations of specific regions of the Earth, such as the Australian coast for landmark observations during the operational timeline of GK2A, but using landmarks separately for validation of the post-geometric correction.

Geometry correction research is applied to satellite operations rather than academic achievements, so it is mainly conducted by participating research institutes and companies rather than universities. While the conceptual design of the COMS was developed by a foreign company and only the software was developed by a domestic company (Jin et al., 2011), the GK2A was designed by a domestic research institute, and the software developed by a domestic company (Yong et al., 2013). The geometric correction of the GK2A was developed based on Korea’s own technology, and thus the system is steadily improving through continuous research, benefiting from the acquisition of proprietary geometric correction technology.

Meteorological satellite data have significant utility in various domains, including weather forecasting, input for numerical weather prediction models, and climate change monitoring. In this context, a review was conducted on studies published in domestic and international journals that explore the operational application of Korea’s geostationary meteorological satellites, COMS and GK2A, in these fields.

5.1. Applications in the Weather Forecasting

In the field of weather forecasting, the most frequently used meteorological satellite data are the analyzed images that allow forecasters to intuitively assess weather phenomena such as clouds, fog, and dust storms by utilizing the observed images and characteristics of each wavelength. Examples of studies utilizing GK2A satellite imagery for applications in the weather forecasting field are as follows: a study aimed at improving RGB images reported by correcting the differences in atmospheric path length caused by the satellite’s observation viewing angle (Kim et al., 2021c). Additionally, the development of fog information for road weather services based on GK2A fog detection data (Lim et al., 2024) and the development of techniques for deriving fog probability information using artificial intelligence to distinguish between low clouds and fog (Lee et al., 2021) have been reported.

Geostationary meteorological satellites, with their high temporal resolution, are effective for monitoring the movement, development, and dissipation of clouds. Utilizing this characteristic, studies have been conducted to detect Convective Initiation (CI), which can lead to severe weather (Park et al., 2021), and to derive cloud-top temperature using observation viewing angle differences between two geostationary satellites (Lee et al., 2020a). Further research to support weather forecasting has been reported on deriving sea surface temperature (Park et al., 2020a) and ocean current information (Kim et al., 2020b) using geostationary satellite data.

The high spatiotemporal resolution of the GK2A satellite also makes it suitable for monitoring dust storms that affect the Korean Peninsula in the spring. Research has been conducted on improving dust detection algorithms to monitor the occurrence and movement of dust storms (Shin et al., 2021; Jang et al., 2021a), analyzing the optical properties of aerosols (Ahn et al., 2021a), and detecting volcanic ash for volcanic eruption monitoring (Ahn et al., 2021b).

In the field of typhoon monitoring using satellite imagery, the Dvorak technique is widely recognized. However, recent studies have introduced artificial intelligence techniques to estimate typhoon intensity (Lee et al., 2020b; Jung et al., 2024) and to improve precipitation forecasts for typhoons (Kim et al., 2023a).

5.2. Applications in Numerical Modeling

Various studies in the field of numerical modeling using satellite data have been reported by Ahn et al. (2023). Subsequent studies focused on improving the utilization of satellite data in numerical weather prediction models include research on enhancing radiative models to correct for the satellite’s zenith angle (Lee and Ahn, 2023). Studies evaluating the impact of satellite data on numerical weather prediction models include the utilization of wind fields from the GK2A satellite (Lee et al., 2022), the impact of SAPPHIRE satellite data (Lee and Lee, 2018), quality control and bias correction of Advanced Microwave Sounding Unit-A (AMSU-A) data in the Korean Integrated Model (KIM) (Jeong et al., 2019), diagnostic of observation errors of satellite radiance data in KIM for data assimilation system (Kim et al., 2021a), and new bias correction approach for utilizing microwave satellite data in sea ice regions of the polar areas (Kim et al., 2023b).

Additionally, studies have been conducted on the data assimilation effects of new satellite observation data such as radio occultation data (Jo et al., 2015; Park et al., 2017). Other studies include bias characteristics analysis of satellite clear-sky radiance data using KMA NWP models (Kim et al., 2018), and the impact of assimilating GK2A all-sky radiance assimilation with new observation error for summer precipitation forecasting (Hastuti and Min, 2023).

5.3. Applications in Climate and Environmental Monitoring

Since the 1970s, satellite observation data have been invaluable for monitoring global climate change and the environment. Although research on the production of Essential Climate Variables (ECVs) using COMS and GK2A satellites has not yet been extensively conducted, several studies have been reported. These include the quality assessment of surface albedo (Woo et al., 2021) and efforts to ensure data consistency with AI technique for COMS and GK2A (Woo et al., 2023a), as well as quality assessments of land surface temperature from the GK2A (Baik et al., 2022).

With growing interest in hydrometeorological monitoring due to climate change, research has increasingly focused on the retrieval and application of hydrometeorological variables using GK2A satellites. For instance, studies have been conducted on agricultural drought assessments using indices produced from satellite data (Yoon et al., 2020), very short-term forecasts using satellite-based drought indices (Park et al., 2020b), and the development of evapotranspiration estimation techniques utilizing artificial intelligence (Kim et al., 2020c; Jang et al., 2021b). Additionally, vegetation index analysis for meteorological drought index calculation (Jung et al., 2023) and soil moisture estimation techniques combining satellite data with artificial intelligence (Lee et al., 2019; 2023) have been reported.

Other studies using COMS and GK2A data include the detection of marine heatwave events in Northeast Asia (Woo et al., 2023b) and an analysis of the characteristics of the East Asian summer monsoon using GK2A data (Wie et al., 2024). Furthermore, research has been conducted on the use of satellite data in the renewable energy sector in response to climate change. Examples include hourly surface solar radiation estimation using GK2A data (Jang et al., 2022), the estimation of solar and wind energy resources in North Korea using COMS (Yeom et al., 2020), and the calculation of radiative energy balance in East Asia using GK2A (Zo et al., 2023).

Research is also being conducted to monitor vegetation changes due to climate change, such as the development of techniques to estimate solar-induced chlorophyll fluorescence using GK2A and Orbiting Carbon Observatory-3 (OCO-3) (Jeong et al., 2024) and the calculation of aerosol radiative forcing resulting from unprecedented wildfires in South Korea (Seong et al., 2024).

It is anticipated that research on the development of techniques to derive essential climate variables using satellite data and the application of satellite data in the renewable energy sector will continue to grow actively in the future.

The GK2A has not only an advanced meteorological payload but also a new space weather payload, Korea Space wEather Monitor (KSEM) that was not in the previous COMS satellite (Oh et al., 2018). Geostationary orbit lies between the Earth’s magnetopause and plasmapause, and depending on the conditions, these boundaries may approach or even cross the geostationary orbit. This makes the geostationary orbit a physically dynamic space, and understanding its various physical properties is key to interpreting diverse space weather phenomena.

To improve the usability and quality of KSEM data and promote various research utilizing it, KMA has tried to release its performances and research findings including comparisons with foreign satellites (Oh et al., 2024). Currently, NOAA is conducting a study to investigate high-energy particle influx phenomena in geostationary orbit using data from GK2A/KSEM and Magnetospheric Particle Sensor-High (MPS-HI) on GOES-16. Additionally, studies analyzing the G5-level geomagnetic disturbance in May 2024 using particle detector and magnetometer data from both the GOES satellites and the GK2A have also been presented (Kwak et al., 2024).

Recently, in order to utilize the climatological geostationary space weather data, KMA has participated in international collaboration such as cross-calibration activities under the GSICS of the Coordination Group for Meteorological Satellites (CGMS). Also, we have a plan to develop the KSEM-II which will be equipped on the GK2A follow-on satellite, GK5. Through these activities, we expect to contribute to data utilization and service to not only the research community but also the governmental operation group for securing the national space properties.

The development and application of meteorological satellite technology in Korea have made remarkable progress over the past few decades. From the early reliance on foreign satellite data to the independent operation of the nation’s geostationary meteorological satellites, such as COMS and GK2A, Korea has significantly advanced its capabilities in satellite data processing and utilization. The development of the CMDPS laid the foundation for Korea’s ability to generate value-added satellite products domestically. The subsequent advancements with the GK2A satellite, which included improvements in sensor technology and data processing systems, have expanded the range and accuracy of meteorological products available for operational use.

The use of satellite data has evolved from basic phenomenon detection to more sophisticated applications, such as numerical weather prediction and climate monitoring, thanks to advancements in data assimilation techniques and artificial intelligence. Furthermore, satellite data is now being applied in new areas such as environmental monitoring, renewable energy assessments, and the study of space weather.

Looking ahead, the KMA is poised to continue expanding its satellite capabilities with the planned development of the GK5 satellite and the exploration of small LEO satellites for greenhouse gas monitoring. These efforts, combined with the integration of artificial intelligence and cloud computing technologies, are expected to enhance the accuracy and efficiency of satellite data processing and utilization. The cooperation between the KMA, the Korean remote sensing and meteorological societies, research institutions, and international partners will further strengthen Korea’s position as a leader in meteorological satellite research and operations. This paper highlights the significant progress made and provides insights into the future direction of satellite-based remote sensing in Korea.

None.

No potential conflict of interest relevant to this article was reported.