Pixel-Level Uncertainty Quantification for Land Surface Temperature Retrieved from MODIS Thermal Infrared Data (2003–2023)

Land surface temperature (LST) is a core physical parameter that characterizes land surface processes and surface-atmosphere energy exchange. As the demand for high-accuracy LST products intensifies across diverse research domains—including climate science, hydrology, and ecosystem modeling—the systematic quantification of pixel-level retrieval uncertainties has become essential for generating long-term, consistent Climate Data Records (CDRs). However, existing studies predominantly emphasize algorithmic development or localized validation, with limited attention to systematic cross-site and long-term uncertainty assessments. This gap impedes a comprehensive understanding of the compositional structure and spatiotemporal variability of LST retrieval uncertainties under heterogeneous surface and atmospheric conditions. In this study, based on the improved generalized split-window (GSW) algorithm and error propagation theory, the total uncertainty (Utotal) and its four primary components—algorithm uncertainty (Ua), land surface emissivity uncertainty (Ue), noise equivalent delta temperature uncertainty (Un), and atmospheric water vapor uncertainty (Uw)—at the pixel level over long time series and across multiple sites are quantified. Our analysis spans a 21-year period (2003–2023) and encompasses multiple geographically distributed sites, utilizing high-quality Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared data—specifically MYD11_L2 and MOD11_L2 products—collocated at the locations of 15 globally distributed ground-based reference sites. These sites are used to represent diverse climatic regimes and land-cover conditions, rather than to provide point-scale “true” LST values for residual-based validation. Results show that the interquartile range (IQR) of Utotal is consistently concentrated between 1.0 and 1.2 K, demonstrating long-term stability. Systematic differences in Utotal are identified across sensor platforms and diurnal cycles: Utotal for Aqua/MYD data (1.13–1.25 K) is marginally higher than that for Terra/MOD data (1.05–1.17 K); similarly, daytime Utotal (1.08–1.23 K) is generally slightly elevated relative to nighttime Utotal (1.05–1.18 K). The contributions of individual uncertainty components to Utotal exhibit substantial variation, with mean relative contributions of 81.97%, 11.32%, 4.46%, and 2.25% for Ue, Ua, Un, and Uw, respectively. The dominant drivers of Utotal differ markedly across climatic regions: in arid regions, Utotal is predominantly governed by Ue, termed “emissivity-dominated,” accounting for over 85% of the total; conversely, humid tropical regions exhibit a “surface-atmosphere co-influenced” regime, characterized by a reduced contribution from Ue and correspondingly enhanced contributions from Ua and Uw. Furthermore, Utotal decreases with increasing total column water vapor (TCWV) (Pearson correlation coefficient r = −0.498; linear slope k = −0.0425 K/(g/cm2)), and increases with increasing viewing zenith angle (VZA) (r = 0.208; k = 0.0022 K/degree). While Ua, Un, and Uw all increase with TCWV, Ue decreases.