Long-term gridded climate datasets are essential for for investigating the spatiotemporal variability and trends of regional climate. Developing reliable gridded reconstructions for the past few centuries requires preserving the spatial co-variability of climate variables while maintaining reconstruction efficiency. This study develops a gridded temperature dataset for East Asia (EA) spanning 1400–2000 CE, reconstructed using an improved Analogue Method (AM) based on climate proxy records and model simulations, at annual temporal resolution and 1°×1° spatial resolution. During the overlapping period of 1901–2000, the reconstructed mean temperature series is strongly correlated with instrumental observations (<em>r=0.74, p<0.0</em><em>1</em>). In addition, the leading empirical orthogonal function (EOF1) mode of the reconstruction is highly consistent with that derived from instrumental observations, indicating that the reconstruction captures the dominant mode of temperature variation over EA. The reconstruction further shows that thetemperature variations over the past 600 years can be divided into three phases: a cooling phase (1400–1510), a fluctuating cold phase (1511–1844), and a warming phase (1845–2000). The most rapid centennial-scale cooling and warming occurred during 1400–1500 (-0.31 °C/100 a) and 1900–2000 (0.58 °C/100 a), respectively. Spatially, temperature variability is strongest in the core region of the Siberian High. This dataset a valuable basis for understanding historical temperature variability and associated heat and cold extremes in EA, and for further examining long-term regional climate change. The dataset can open access on <a href="https://doi.org/10.5281/zenodo.18477496" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.18477496</a> (Yan et al, 2026).