Surface Solar Radiation Resource Evaluation of Xizang Region Based on Station Observation and High-Resolution Satellite Dataset

Abstract

Xizang boasts a vast and geographically complex landscape with an average elevation surpassing 4000 m. Understanding the spatiotemporal distribution of surface solar radiation is indispensable for simulating surface processes, studying climate change, and designing photovoltaic power generation and solar heating systems. A multi-dimensional, long-term, spatial, and temporal investigation of solar radiation in Xizang was conducted using three unique datasets, including the difference in surface solar radiation (SSR) between high-resolution satellite and ground station data, the annual and monthly distribution of SSR, and the interannual–monthly–daily variation and the coefficient of hourly variability. Combined with high-resolution elevation data, a strong linear correlation was shown between the radiation and the elevation below 4000 m. Furthermore, analysis reveals greater differences in data between east and west compared to the center, as well as between summer and winter seasons. SSR levels vary in steps, reaching the highest from Ngari to Shigatse and the lowest in a U-shaped area formed by southeastern Shannan and southern Nyingchi. In June, high monthly SSR coverage was the highest of the year. Since 1960, the annual mean SSR has generally exhibited a declining trend, displaying distinctive trends across various seasons and datasets. Owing to intricate meteorological factors, some regions exhibited double peaks in monthly SSR. Finally, we have introduced a solar resource assessment standard, along with a multidimensional evaluation of the resources, and categorized all townships. We offer a thorough analysis of Xizang’s solar radiation to provide a comprehensive understanding, which will help to prioritize recommendations for PV construction in Xizang.

Keywords

• surface solar radiation
• differential analysis
• elevation variation
• spatiotemporal characteristics
• township scale classification