Climate change has contributed to recent declines in mountain snowpack and earlier runoff, which in turn have intensified hydrological droughts in western North America. Climate model projections suggest that continued and severe snowpack reductions are expected over the 21st century, with profound consequences for ecosystems and human welfare. Yet the current understanding of trends and variability in mountain snowpack is limited by the relatively short and strongly temperature forced observational record. Motivated by the urgent need to better understand snowpack dynamics in a long-term, spatially coherent framework, here we examine snow-growth relationships in western North American tree-ring chronologies. We present an extensive network of snow-sensitive proxy data to support high space/time resolution paleosnow reconstruction, quantify and interpret the type and spatial density of snow related signals in tree-ring records, and examine the potential for regional bias in the tree-ring based reconstruction of different snow drought types (dry versus warm). Our results indicate three distinct snow-growth relationships in tree-ring chronologies: moisture-limited snow proxies that include a spring temperature signal, moisture-limited snow proxies lacking a spring temperature signal, and energy-limited snow proxies. Each proxy type is based on distinct physiological tree-growth mechanisms related to topographic and climatic site conditions, and provides unique information on mountain snowpack dynamics that can be capitalized upon within a statistical reconstruction framework. This work provides a platform and foundational background required for the accelerated production of high-quality annually resolved snowpack reconstructions from regional to high (12 km) spatial scales in western North America and, by extension, will support an improved understanding of the vulnerability of snowmelt-derived water resources to natural variability and future climate warming.

气候变化导致了最近山区积雪的减少和更早的径流，反过来又加剧了北美西部的水文干旱。气候模型预测表明，预计21世纪将继续减少积雪，并将对生态系统和人类福祉产生深远影响。然而，目前对高山积雪趋势和变化的理解受到相对较短且温度强烈强迫的观测记录的限制。由于迫切需要在长期的，空间连贯的框架中更好地了解积雪动力学，因此在此我们考察了北美西部树木年轮年代学中的积雪增长关系。我们提供了一个广泛的对雪敏感的代理数据网络，以支持高时空分辨率的古雪重建，量化和解释树木年轮记录中与雪有关的信号的类型和空间密度，并在基于树木年轮的不同雪旱类型（干旱与温暖）的重建中检查区域偏见的可能性。我们的结果表明，在树年轮年代中三个明显的雪增长关系：水分受限的雪代理（包括春天温度信号），水分受限的雪代理（没有春天温度信号）和能量受限的雪代理。每种代理类型都基于与地形和气候工地条件有关的独特生理树生长机制，并提供有关山区积雪动力学的独特信息，可以在统计重建框架内加以利用。北美西部12 km）的空间尺度，并由此扩展，将有助于人们更好地理解融雪水资源对自然变异性和未来气候变暖的脆弱性。