Ongoing global warming due to anthropogenic climate change has long been recognized, yet uncertainties regarding how seasonal extremes will change in the future persist. Paleoseasonal proxy data from intervals when global climate differed from today can help constrain how and why the annual temperature cycle has varied through space and time. Records of past seasonal variation in marine temperatures are available in the oxygen isotope values of serially sampled accretionary organisms. The most useful data sets come from carefully designed and computationally robust studies that enable characterization of paleoseasonal parameters and seamless integration with mean annual temperature data sets and climate models. Seasonal data sharpen interpretations of—and quantify overlooked or unconstrained seasonal biases in—the more voluminous mean temperature data and aid in the evaluation of climate model performance. Methodologies to rigorously analyze seasonal data are now available, and the promise of paleoseasonal proxy data for the next generation of paleoclimate research is significant.

由于人为气候变化导致的持续全球变暖早已得到认可，但关于未来季节性极端事件将如何变化的不确定性仍然存在。来自全球气候与今天不同的时间间隔的古季节性代理数据可以帮助限制年度温度循环如何以及为什么随着空间和时间而变化。在连续采样的增生生物的氧同位素值中可以获得过去海洋温度季节性变化的记录。最有用的数据集来自精心设计和计算稳健的研究，这些研究能够表征古季节性参数并与年平均温度数据集和气候模型无缝集成。季节性数据加强了对海量平均温度数据的解释——并量化了被忽视或不受约束的季节性偏差，并有助于评估气候模型的性能。现在可以使用严格分析季节性数据的方法，并且古季节性代理数据对下一代古气候研究的前景意义重大。