Recently, the CARE team member Prof. Husi Letu and Prof. Shi Chong in collaboration with scientists from the National Satellite Meteorological Center, the National Space Science Center of the Chinese Academy of Sciences, the Institute of Atmospheric Physics of the Chinese Academy of Sciences, Tokai University, the University of Tokyo, Chiba University, the University of Lille, and the UK Met Office, has achieved a groundbreaking milestone published in the prestigious international journal The Innovation (Impact Factor: 33.2). They have pioneered the development of a geostationary satellite network observation (GSNO) system based on the latest generation of international geostationary satellites. By establishing a remote sensing model for multi-source heterogeneous satellite observations, the team has realized the highest spatial and temporal resolution for near-global surface solar radiation detection while simultaneously enhancing measurement precision. This accomplishment has been widely reported by media outlets such as CCTV News, Xinhua News Agency, China News Service, and Beijing Daily under the headline "Chinese Scientists Lead the Successful Development of a Near-Global High-Precision Surface Solar Radiation Monitoring System."

This technological advancement is like equipping the Earth's surface with a "sunlight scanner," enabling precise monitoring of surface solar radiation variations. It provides accurate data support for applications such as clean energy utilization, agricultural yield estimation, climate change mitigation, and human health.

Surface solar radiation refers to the aggregate of solar radiation components received at the Earth's surface, encompassing electromagnetic radiation across various wavelengths, including ultraviolet, visible, and infrared light. It serves as the fundamental energy source for terrestrial life activities and a critical factor influencing climate change, agricultural production, and solar energy utilization. Satellite remote sensing technology, characterized by its robust data continuity and extensive coverage, stands as one of the most effective tools for monitoring changes in surface solar radiation.

Building upon a near-real-time surface solar radiation remote sensing system developed in 2023, the research team has overcome challenges in multi-satellite collaboration, such as spectral disparities and differences in observational geometry. This has enabled the integrated application of advanced geostationary satellites, including China's Fengyun-4, Japan's Himawari-8, Europe's Meteosat Second Generation (MSG), and the United States' Geostationary Operational Environmental Satellites (GOES). The system has successfully achieved continuous and seamless monitoring of surface solar radiation across Asia, Europe, North America, South America, Oceania, and Africa, addressing the shortcomings of low observation frequency in polar-orbiting satellites and the limited coverage of individual geostationary satellites. Husi Letu, the initiator of the CARE project, stated: "Through years of dedicated effort, this system has accomplished a leap from regional to near-global observation via multi-satellite networking. It enables simultaneous analysis of near-global solar shortwave radiation (0.3–3 microns), photosynthetically active radiation (0.4–0.7 microns), ultraviolet A/B radiation, and their direct and diffuse components."

Clouds represent the primary source of uncertainty affecting surface solar radiation and pose a significant challenge to its monitoring. Leveraging an intelligent cloud detection system and a scattering model for irregular ice cloud particles, combined with the spectral characteristics of various satellites, the study has developed tailored high-precision cloud remote sensing algorithms for each satellite. Additionally, accounting for the effects of atmospheric aerosols, gases, and surface reflectance, the team devised a rapid radiative transfer simulator integrating artificial intelligence and radiative transfer models. This innovation has accelerated radiative transfer calculations by a factor of 90,000, with an error margin of less than 0.3%. Shi Chong remarked: "By consolidating these core technologies, we have constructed a surface solar radiation remote sensing algorithm for the GSNO system. Through innovative algorithms, we have resolved issues related to cloud interference and rapid radiative transfer computation for each satellite."

Currently, the GSNO system delivers near-global surface solar radiation monitoring data with a spatial resolution of 5 kilometers and an observation frequency of once per hour, markedly surpassing established products such as the U.S. CERES (100 kilometers, 1 hour) and Europe's ERA5 (25 kilometers, 1 hour). This represents an order-of-magnitude improvement in spatial resolution, allowing for detailed capture of localized radiation changes, such as those along typhoon paths and over the Tibetan Plateau. Validated against global ground-based measurements, the GSNO system's surface solar radiation data exhibits a daily mean error of 27.48 W/m², outperforming CERES (daily mean error of 29.59 W/m²) and ERA5 (daily mean error of 35.36 W/m²). This precision supports refined applications, including local meteorological disaster monitoring, photovoltaic power station site selection, and data-driven high-spatiotemporal-resolution Earth system models.

This achievement, titled "Near-Global Monitoring of Surface Solar Radiation through the Construction of a Geostationary Satellite Network Observation System," has been published in the esteemed journal The Innovation. Husi Letu noted that the GSNO system will facilitate global solar resource assessment, support clean energy planning under China's "dual carbon" goals, provide a novel basis for grain yield estimation and ecological carbon sink calculations through its photosynthetically active radiation data, and offer potential applications in public health via its ultraviolet data module.

Surface solar radiation remote sensing data products derived from the GSNO system are now available and shared on the CARE website (http://www.slrss.cn/care_zh/). CARE is dedicated to cloud remote sensing, atmospheric radiation, and renewable energy, striving to develop associated radiative transfer models and satellite remote sensing data to enhance clean energy utilization and climate change research.

Construction of the GSNO system and its application in surface solar radiation retrieval

Article link: https://www.cell.com/the-innovation/fulltext/S2666-6758(25)00079-7

Near-global monitoring of surface solar radiation through the construction of a geostationary satellite network observation system