## 1 Introduction
### Quantifying the Surface Solar Irradiance Spectra  
The quantity of solar energy received per unit area per unit time at the Earth's surface is termed the surface solar irradiance (SSI). The intensity of solar radiation incident at the Earth's surface is influenced by variations in the Sun-Earth distance and the solar zenith angle. It is also strongly dependent on wavelength, as well as on the vertical profiles of atmospheric composition and temperature. These factors govern radiative extinction through absorption and scattering processes, along with contributions from thermal emission. Accurately modeling surface irradiance requires accounting for all of light absorption, multiple scattering, and surface reflection (Figure 1). Measurements of SSI have a significant bearing in solar energy applications [10]. The global deployment of photovoltaic power systems has expanded rapidly over the past decade and is projected to continue increasing [11; 12]. In this context, both the variability of irradiance and the magnitude of its temporal fluctuations over defined intervals are of particular interest [11; 13]. Of equal significance, given its role as a primary driver of atmospheric phenomena and its direct influence on atmospheric composition and chemical processes, the accurate and high-resolution quantification of SSI is essential for addressing the increasing risk of poor air quality [14]. Since SSI is modulated by the scattering and absorption of aerosols and atmospheric gases, it has fluctuated with progressing climate change [15; 16]. Under clear sky conditions, approximately 20% to 30% of incoming solar  
Figure 1: The radiation incident on any volume element of the atmosphere has four contributions: (**A**) The direct solar flux, (**B**) the diffuse (scattered) flux incident from all directions, (**C**) the ground reflection of the direct solar flux, and (**D**) the ground reflection of the diffuse flux. radiation is attenuated during its downward propagation due to scattering and absorption by atmospheric constituents [17; 18; 19]. Furthermore, SSI exhibits a non-linear variability dependent upon cloud cover [20], particularly under overcast sky conditions. SSI can occasionally exceed clear-sky or even extraterrestrial levels due to radiation scattering by broken clouds, a phenomenon known as cloud enhancement [21; 22]. Concurrently, cloud shadows generate dynamic patterns of alternating high and low irradiance, leading to steep ramp rates and spatial heterogeneity in surface heat fluxes. SSI thus exhibits spatiotemporal variability spanning several orders of magnitude. To fully capture and model this variability, spatial and temporal resolutions as fine as tens of meters and seconds are required [23]. SSI is traditionally measured using ground-based radiometers, such as pyranometers and spectroradiometers, which provide high-accuracy, high-temporal-resolution data under local atmospheric conditions. However, dense networks with spatial coverage of the scope required to represent local neighborhood scales are made impractical due to cost and maintenance constraints. To address this limitation, satellite-based remote sensing offers an alternative by estimating SSI over large geographic areas [24; 25; 26; 27]. These estimates are not direct measurements of irradiance, but are derived using computational models that integrate satellite-observed parameters such as cloud cover, aerosol optical depth, and surface reflectance to infer SSI at the surface. While satellite products provide broader coverage and are invaluable for climate and energy applications, their accuracy depends heavily on the quality of input data and the assumptions within the radiative transfer models used. As previously encountered in the present discourse, the accurate modeling of radiative transfer requires accounting for all of scattering, absorption, and reflection scenarios, as well as the effect from cloud cover. Hence, their computational overhead is significantly greater, and requires a substantial number of input variables.