The knowledge of past tropical cyclone (TC) activity is vital to understanding patterns of current and future TCs and how they will impact society, infrastructure, and the natural system. Various historical, biological, and geological proxies are commonly used to reconstruct TC behavior; however, these records vary significantly in their temporal resolution. Tree rings are known to provide high-resolution data and have been proven as a valuable proxy record of past TC activity. Here we aim to produce a TC reconstruction based on tree-ring width data of longleaf pine (Pinus palustris Mill.) located in Lake Louise near Valdosta, Georgia. Results of growth-climate analysis showed that all climate and oscillation variables influence the tree growth, and removing this climate influence may be necessary to unmask the TC signal. For this purpose, we used stepwise linear regression to iteratively model tree growth with monthly climate factors (precipitation, temperature, drought) and monthly oscillation indices (ENSO, AMO, NAO, PDO) to obtain residual chronologies. Tree-ring chronologies were compared to TC data from the National Hurricane Center's North Atlantic Hurricane Database (HURDAT2) for a 150-km buffer zone around Lake Louise between 1894 and 1999. Of the storms that entered the buffer, 13 of the 17 ≤−0.3 growth rings and 8 of the 10 ≤−0.4 growth rings occurred in the year directly after a TC event. Our results revealed the strong climate and oscillation influence in the raw chronology and no significant TC signal. However, the removal of temperature and precipitation influence from raw chronology unmasked the TC signal (p < 0.05). The TC signal was even more pronounced if influence of oscillation indices on growth had been also removed. The most pronounced TC signal was identified between most intense TCs (≥ 33 ms⁻¹) and the climate and oscillation signal-free chronology. We emphasize that future research is needed for validation and elimination of the influence of other external growth drivers, as well as replication studies at multiple sites using similar statistical applications.

过去热带气旋（TC）活动的知识对于了解当前和未来TC的模式及其对社会，基础设施和自然系统的影响至关重要。通常使用各种历史，生物和地质代理来重建TC行为。但是，这些记录的时间分辨率差异很大。众所周知，年轮可提供高分辨率数据，并已被证明是过去TC活动的有价值的代理记录。在这里，我们的目标是基于长叶松（Pinus palustris）的年轮宽度数据进行TC重建。磨坊。）位于佐治亚州瓦尔多斯塔附近的路易斯湖。生长气候分析的结果表明，所有气候和振荡变量都会影响树木的生长，因此可能有必要消除这种气候影响以隐蔽TC信号。为此，我们使用逐步线性回归以月度气候因子（降水，温度，干旱）和月度振荡指数（ENSO，AMO，NAO，PDO）迭代地模拟树木生长，以获得剩余的时间序列。在1894年至1999年之间，将路易丝湖周围150公里缓冲区的树木年轮年代与来自国家飓风中心北大西洋飓风数据库（HURDAT2）的TC数据进行了比较。在进入缓冲区的风暴中，有17 ≤−13的风暴0.3个年轮和10个≤-0.4年轮中的8个年轮发生在TC事件发生后的第一年。我们的结果表明，气候和振荡对原始年代的影响很大，并且没有明显的TC信号。但是，从原始时间顺序中去除温度和降水影响后，TC信号无法掩盖（p＜0.05）。如果还消除了振荡指数对生长的影响，则TC信号将更加明显。在最强的TCs（≥33 ms ^-1）与无气候和无振荡信号的年代之间确定了最明显的TC信号。我们强调，需要进一步的研究来验证和消除其他外部增长驱动因素的影响，以及使用相似的统计应用程序在多个站点进行的复制研究。