Chronological uncertainty limits the use of marine sediment cores for resolving the timing and coherence of late-Holocene ocean variability around Greenland. In this study, we apply two optimization methods to improve the chronological uncertainty of four sediment cores from Qeqertarsuup Tunua (Disko Bugt), West Greenland. Using the GISP2 temperature reconstruction as a reference series, we generate alignment-consistent age-model realizations with (i) Nelder-Mead optimization (NMO), which maximizes a resampled Pearson correlation coefficient (RPCC) and (ii) Dynamic Time Warping (DTW), which aligns sequential structure through non-linear time-axis adjustment. For individual cores, NMO generally yields higher RPCC values than DTW. However, when the adjusted records are merged into a Qeqertarsuup Tunua composite, DTW produces a substantially more coherent regional signal and a higher RPCC with GISP2 (0.77) than the NMO-based composite (0.36). To assess whether these improvements reflect genuine climate co-variability, we apply a phase-randomisation permutation test using 500 spectrally matched surrogate GISP2 series. Results are heterogeneous: DTW alignment is statistically significant for one core (Sullorsuaq, p=0.006), and NMO alignment is significant for another (Aasiaat1, p=0.034), while neither method reaches significance for the other two cores. Restricting the composite to these two significant core and method combinations yields an RPCC of 0.83 with GISP2, outperforming both other composites. Applying both methods to a synthetic reference series also increases RPCC values, demonstrating that correlation gains can arise from alignment flexibility alone and underscoring the need for independent chronological constraints when interpreting tuned chronologies. Mean age offsets relative to the original models range from -99 to 41 yr for NMO and from -346 to 190 yr for DTW. We conclude that NMO can be useful for site-specific alignment and that the significance-filtered composite provides the most defensible regional reconstruction of Atlantic Water variability over the past 2000 years.