Abstract: Objective: Snow depth on sea ice is a critical parameter for retrieving sea ice thickness using satellite altimetry techniques. This study utilizes coordinated observations from ICESat-2 and CryoSat-2 altimetry satellites (IS2CS) to compare and evaluate two spatiotemporal matching methods (along-track search method and gridded search method) for satellite altimetry snow depth estimation, and analyzes the spatiotemporal distribution characteristics of snow depth in the Arctic sea ice growth season (October to April) from 2018 to 2024.Methods: Based on the penetration characteristics of Ku-band into snow cover on sea ice surface and considering the propagation delay of radar waves in the snow layer, snow depth is derived from the difference between CryoSat-2 observed radar freeboard and ICESat-2 laser altimeter observed total sea ice freeboard. The along-track method identifies near-simultaneous IS2 and CS2 measurements through strict spatiotemporal constraints (within 24 hours and within radar footprint range), but with limited spatial coverage. The gridded method aggregates measurements into 25-kilometer spatial grids, adopting relaxed temporal constraints (±15 days).Results: The along-track method shows high correlation with Operation IceBridge (OIB) field measurements (R=0.613, mean bias -2.6 cm, RMSE 4.0 cm), better characterizing fine-scale variations in snow depth profiles despite limited spatial coverage. The gridded method is more suitable for representing large-scale spatial distribution and seasonal evolution patterns of snow depth, with accuracy comparable to GSFC snow depth products in OIB validation, and performing better in Sea Ice Mass Balance Array (SIMBA) data validation (RMSE 4.0 cm versus 4.5 cm). Compared to IS2CS snow depth estimates, MW99/AMSR2 snow depth products show relatively greater thickness (mean bias 7.5 cm compared to OIB measurements) and exhibit weaker seasonal variations during sea ice growth (monthly growth rate 0.53 cm/month, compared to 1.52 cm/month for our gridded method). IS2CS gridded snow depth shows that snow cover on multi-year ice (average 21.9 cm) is consistently thicker than on first-year ice (average 13.9 cm), with snow depth displaying a distinct seasonal pattern characterized by gradual accumulation from autumn to maximum values in spring.Conclusion: During the 2018-2024 period, Arctic sea ice snow depth shows an overall thinning trend, with multi-year ice regions thinning faster than first-year ice regions. The multi-year ice region in the Beaufort Sea shows the most significant thinning trend, consistent with the continued decline of Arctic multi-year ice. These findings provide valuable scientific basis for enhancing satellite altimetry snow depth products and refining sea ice thickness retrieval algorithms, with important implications for improving Arctic sea ice monitoring in a changing climate.