Progress and Prospects of Diurnal Temperature Cycle Models: From Isotropic to Anisotropic

Land surface temperature (LST) and its diurnal variation are critical for understanding the surface energy balance and water cycle processes. Traditional diurnal temperature cycle (DTC) models are widely used to reconstruct continuous temperature sequences from sparse satellite observations. However, these models rely on the idealized assumption of an isotropic surface and ignore the thermal radiation directionality caused by viewing geometry, which introduces substantial errors over heterogeneous surfaces. Thus, incorporating angular effects into DTC modeling has become an effective approach to improving LST simulation accuracy. This review traces the progress of DTC models from isotropic to anisotropic representations. First, we summarize the development and inherent limitations of conventional isotropic DTC models. Then, we synthesize representative angular-coupled models, ranging from early simple component-based models to recent kernel-driven coupling methods, and compare their physical assumptions, data requirements, parameter complexity, and applicable scenarios. Although these coupled models can significantly improve fitting accuracy over heterogeneous surfaces, they still face challenges. These include strict data requirements, limited all-weather applicability, a lack of nighttime angular correction, and incomplete validation systems. Future research can advance through multi-source data fusion, hybrid modeling strategies, and robust validation systems. These are key to generating high-precision, spatiotemporally consistent LST data.