A Global 5-km Multi-Temporal Mean Land and Sea Surface Temperature Dataset (2001–2024)

Land Surface Temperature (LST) and Sea Surface Temperature (SST) are key variables in Earth system processes, playing crucial roles in ecological, environmental, and climate-related studies. Compared to instantaneous temperature observations, mean temperature values can smooth short-term fluctuations and offer a more stable and representative measure of surface thermal dynamics. To support global-scale analyses, this dataset provides daily, monthly, and annual mean LST and SST at a spatial resolution of 5 km. The dataset is derived from the instantaneous MODIS LST products (i.e., MOD11C1 and MYD11C1) and SST products (i.e., MODIS-Terra and MODIS-Aqua SST Level-3 Binned). Daily mean LST/SST is calculated using the multi-temporal weighted averaging method proposed by Xing et al. (2021, https://doi.org/10.1016/j.isprsjprs.2021.05.017). Monthly means are further generated using the approach developed by Liu et al. (2023, https://doi.org/10.1109/TGRS.2023.3247428), which incorporates clear-sky fraction adjustments, multi-temporal weighting, and a hybrid aggregation strategy to ensure both accuracy and spatial completeness. Annual means are subsequently derived from the monthly averages. This dataset supports global studies on surface energy balance, climate change, and land–ocean interactions, offering valuable input for climate modeling, environmental monitoring, and ecosystem assessment. For users requiring finer spatial detail, a 1-km version of the dataset is also available (https://zenodo.org/records/6618442#.YqB1UoRByUl).