High Mountain Asia (HMA) has experienced rapid warming and increased climate extremes, yet limited instrumental records constrain understanding of whether recent changes exceed long-term natural variability. Paleoclimate data assimilation offers opportunities to integrate sparse proxy observations with climate model priors, generating spatiotemporally complete reconstructions. We reconstructed gridded temperature and precipitation fields (1501–2000 CE) and identified extreme climate events across HMA by applying three Ensemble Kalman Filter methods to a baseline Pages2k dataset (201 records) and an expanded Combined dataset (297 records). Cross-validation demonstrates skillful temperature reconstruction and modest precipitation skill. The three methods show high consistency, while expanding the baseline dataset with additional proxies enhances extreme event detection by 39% for cold years and 21% for warm years. Systematic extreme event identification reveals that cold/warm years account for 11.0% and 8.6% of the 500-year record. Three major events are identified: the 1641–1644 cold event (80–100% coverage, -0.68 K), the 1817–1820 compound cold-dry extreme (-0.64 K, -0.13 mm/day), and the 1994–2000 warm-wet episode (+ 0.83 K, + 0.14 mm/day) as the longest sustained warming in the 500-year record. Our 500-year climate fields provide a quantitative baseline for contextualizing recent HMA changes within pre-industrial variability.
Zhou et al. (Sat,) studied this question.