Improvement of Korea Meteorological Administration insolation Information by Applying Detailed Terrain Data

  As the proportion of renewable energy continues to rise, solar energy reaching the Earth's surface holds a significant share compared to other sources such as wind power. Efficient utilization of solar energy necessitates accurate data on surface insolation. Consequently, both domestically and internationally, there's active research into developing insolation mapping using various numerical models based on solar meteorological resources.
The Korea Meteorological Administration's KMAP (Korea-Meteorological Administration Post-processing), hereafter KM, provides insolation data. However, its limitation lies in the inability to realistically account for complex terrains like mountains due to the 1.5 km resolution of the Meteorological Administration's LDAPS (Local Data Assimilation and Prediction System), an operational local forecast model.
 This study analyzes the impact and characteristics of different resolutions of Digital Elevation Models (DEMs) on the accuracy of surface insolation calculations performed by KMAP-Solar, the solar energy mapping system of the Korea Meteorological Administration (1.5 km and 100 m). Comparison and verification against insolation data from 42 Korea Meteorological Administration Automated Synoptic Observation Systems (ASOS) stations reveal that the introduction of high-resolution DEM reduces land-averaged solar radiation biases by up to 32 Wm⁻² at all observation points, particularly accentuating its effect in regions with complex terrains.
The enhanced accuracy due to high-resolution DEMs is attributed to their ability to alleviate errors caused by differences in Sky View Factors (SVF) between high and low-resolution DEMs. Both DEM resolutions exhibit correlations between insolation and terrain elevation (SVF). However, high-resolution DEMs significantly underestimate these relationships compared to low-resolution DEMs, primarily in areas with high elevations where low-resolution DEMs inadequately represent steep terrains and/or small SVFs.
This study demonstrates that high-resolution DEMs provide a more realistic distribution of insolation by integrating a broader range of crucial terrain parameters, thus proving their significance in accurate insolation calculations compared to low-resolution DEMs. It is anticipated that this research will play a crucial role in supporting future solar energy studies, real-time prediction, and management within solar power plant installations and the power grid.