In the realm of solar energy, precision is paramount. A recent study led by Chenxi Kong from the College of Urban and Environmental Sciences at Hubei Normal University, China, has shed new light on the critical role of accurate solar spectral irradiance (SSI) data in modelling climate systems and assessing surface solar energy. The findings, published in Energies, underscore the significance of high-resolution spaceborne solar spectrum observations in enhancing the accuracy of solar power estimations and climate modelling.
Traditionally, climate models have relied on solar model calculations supplemented by limited observations to estimate solar spectral irradiance. However, recent advancements in spaceborne high-resolution solar spectrum observations, such as those from NASA’s Total and Spectral Solar Irradiance Sensor (TSIS), have provided more precise and reliable SSI data. Kong’s research compares the observed SSI data from TSIS-1 with the model-based SSI data used by the China Meteorological Administration (CMA), revealing significant discrepancies that could impact solar power estimations and climate modelling.
The study found that the CMA’s standard solar spectrum (CMA_STD) yields 4.45 Wm−2 less energy than the observed TSIS-1 Hybrid Solar Reference Spectrum (TSIS-1_HSRS). This discrepancy results in an annual regional mean downward surface shortwave radiation (DSSR) underestimation of approximately 0.44 Wm−2, with localized underestimations exceeding 2 Wm−2 for specific months. These findings highlight the importance of accurate SSI data in climate modelling and solar power applications.
“These discrepancies in the band-wise energy distribution have important implications for climate systems and various applications, given that different surfaces have unique reflecting/absorbing properties for visible and near-infrared wavelengths,” Kong explained. This means that the differences in SSI data can significantly affect how solar energy is absorbed and reflected by various surfaces, impacting climate models and solar power estimations.
The study also examined the impact of these SSI discrepancies on photovoltaic (PV) power production. For a PV plant with a power productivity of 10 MWp, the annual power production difference maximizes in high-altitude regions and the northern part of China, reaching up to 65,771.41 kWh for fixed-angle panels and 118,986 kWh for solar-tracking panels. These differences account for about 0.25~0.32% and 0.36~0.52% of the local total power production for fixed-angle and solar-tracking panels, respectively.
The implications of this research are far-reaching. As the world increasingly relies on solar energy to mitigate climate change, accurate SSI data becomes crucial for optimizing solar power generation and improving climate models. The findings suggest that long-term and high-resolution spaceborne SSI observations are essential for enhancing surface climate modelling, particularly on local scales. This could lead to more accurate predictions of solar energy potential and better-informed decisions in the renewable energy sector.
As the energy sector continues to evolve, the integration of high-resolution spaceborne SSI observations into climate models and solar power applications could revolutionize how we harness solar energy. This research by Kong and his team paves the way for future developments in the field, emphasizing the need for continuous advancements in solar spectrum observations to support the growing demand for renewable energy and climate change mitigation efforts.
